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Personal Traits that Influence Resilience in Women Who Completed Chemotherapy for Breast Cancer

DOI: 10.31038/CST.20251012

Abstract

Background: In Ghana, chemotherapy is the primary treatment for breast cancer, often leading to significant physical and emotional challenges due to drug side effects. While global literature highlights improved breast cancer survival rates, there is limited research on the personal traits influencing resilience in Ghanaian women who undergo chemotherapy for breast cancer, despite their remarkable ability to navigate treatment challenges and its aftermath.

Methods: This exploratory descriptive qualitative study investigated the perspectives of 14 breast cancer survivors in Accra who endured chemotherapy- related distress. Participants were recruited purposively, meeting specific criteria, and interviewed in English using a semi-structured guide. Data collection and analysis were conducted concurrently. Data were analyzed inductively to uncover themes without predefined frameworks. Trustworthiness was ensured through strategies like member checking, triangulation, and reflexivity. Ethical approval was obtained from Noguchi Memorial Institute for Medical Research (NMIMR), and participants provided informed consent before being audio-recorded. Interviews lasted 45–60 minutes, achieving saturation by the 12th interview, with two additional sessions confirming findings. Identified codes were grouped into sub-themes and themes with findings highlighting survivors’ lived experiences and the care they received.

Results: Four (4) themes; hope, optimism, self-esteem, and confidence and 13 sub-themes emerged from the data.

Conclusions: In the absence of structured support systems, resilience in surviving breast cancer treatment is primarily shaped by individual personality traits such as hope, optimism, self-esteem, and confidence and emotional responses to the illness. A more structured support system aimed at fostering resilience and boosting personal traits among women receiving chemotherapy for breast cancer is highly recommended.

Keywords

Personal traits, Resilience, Women, Breast cancer, Chemotherapy

Background to the Study

Breast cancer remains one of the most prevalent cancers affecting women globally. According to the [1], breast cancer accounts for 12.5% of all new cancer cases worldwide, making it a significant public health challenge. Advances in treatment, including surgery, radiation therapy, and systemic therapies such as chemotherapy, have significantly improved survival rates over the past decades. Despite these advancements, chemotherapy—a cornerstone in breast cancer treatment—is often associated with severe physical and psychological burdens, including fatigue, nausea, emotional distress, and disruption of daily life [2]. For women undergoing chemotherapy, these challenges can impact their overall quality of life and mental health.

In low- and middle-income countries (LMICs), including sub- Saharan Africa, the burden of breast cancer is compounded by late- stage diagnoses, limited access to healthcare resources, and cultural stigmas surrounding cancer [3]. In Ghana, breast cancer is the leading malignancy among women, with an estimated incidence rate of 20.4 per 100,000 women [4]. The increasing survival rates call for a shift in focus from merely treating the disease to addressing the psychosocial and emotional needs of survivors [5].

Women who complete chemotherapy for breast cancer often exhibit remarkable resilience, enabling them to navigate the challenges posed by the treatment and its aftermath. Resilience, defined as the ability to recover from or adapt to adversity, is a multidimensional construct influenced by personal, social, and environmental factors [6]. However, while there is an expanding body of literature on resilience in cancer survivors, the specific personal traits that influence resilience in women who have completed chemotherapy for breast cancer remain underexplored. Existing research highlights the importance of psychological factors such as optimism, emotional regulation, and self-efficacy, as well as the role of social support and lifestyle choices in fostering resilience [7,8].

In the Ghanaian context, breast cancer survivors often face unique cultural and socioeconomic challenges, including limited access to psychosocial support services and societal expectations of stoicism [9]. The lack of context-specific studies addressing the personal traits that contribute to resilience in this population limits the ability of healthcare providers to develop effective, tailored interventions. Understanding these traits is crucial for designing psychosocial programs that enhance the well-being and survivorship experiences of women who have undergone chemotherapy for breast cancer.

Aim of the Study

This study aims to explore the personal traits that influence resilience in women who have completed chemotherapy for breast cancer.

Methods

Research Design

The study utilized an exploratory descriptive qualitative research design, deemed suitable for providing detailed insights into the perspectives of women who survived breast cancer and endured chemotherapy-related distress, supported by the care they received [10,11].

Participants and Setting

The research was conducted in Accra, targeting women aged 18 and older diagnosed with breast cancer and residing within the Accra Metropolis. Participants met specific inclusion criteria: a breast cancer diagnosis, completion of chemotherapy, and fluency in English. Exclusion criteria included newly diagnosed breast cancer patients, those with altered mental status, and individuals who were acutely ill or in pain. A total of 14 participants were recruited using purposive sampling.

Data Collection Method

Individual qualitative interviews were conducted with the 14 participants. Permission was obtained from the Teaching Hospital where the study took place. Eligible participants were recruited and provided with information sheets explained in simple terms. Interview sessions were arranged through phone calls. A semi- structured interview guide ensured the focus of the study. Face-to-face interviews, conducted in English at participants’ convenience, were audio-recorded with their consent and lasted between 45 minutes and an hour. Saturation was achieved after interviewing 12 participants, with two additional interviews conducted to confirm saturation.

Data Analysis

Data were analyzed using inductive content analysis [12]. This method involves deriving categories, subthemes, and themes directly from the data without relying on pre-existing frameworks, allowing for the emergence of new insights. Data analysis was conducted concurrently with data collection [12,13]. Transcriptions were performed verbatim and reviewed multiple times by the first author to extract meaning. Codes representing similar concepts were grouped into subthemes, and related subthemes were organized into overarching themes. To ensure objectivity, the second and third authors reviewed the process to eliminate potential biases.

Trustworthiness and Reflexivity

To ensure rigor, trustworthiness, and reflexivity, various strategies were employed [14-16]. Member checking involved seeking participant clarification on unclear responses and confirming their statements during interviews. Data triangulation compared field notes with transcripts to accurately represent participants’ experiences. Dependability was reinforced by involving impartial reviewers—the second and third authors, who supervised the first author’s process. Reflexivity was maintained through bracketing, separating the researchers’ personal experiences from the study to minimize biases. Confirmability was achieved by meticulously reviewing transcripts before interpretation, while an audit trail documented raw data, analysis notes, field diaries, and recordings.

Ethical Considerations

The study received ethical approval from the Noguchi Memorial Institute for Medical Research in Ghana (NMIMR), under reference number NMIMR-IRB CPN 111/15-16. Participants were provided with detailed information about the study’s objectives, procedures, risks, and benefits. Informed consent was obtained through signed or thumb-printed forms, ensuring inclusivity for participants of varying literacy levels.

Results

Demographic Characteristics of Participants

The study involved 14 women aged 38 to 78 years. Specifically, 3 participants were in their late 30s, 5 in their early 40s, 3 in their early 50s, 1 in their early 60s, and 2 in their late 70s. The mean age was approximately 49.5 years, with a standard deviation of 13.6 years. Educational backgrounds varied, with 4 participants having secondary education, 2 with vocational training, and 8 with tertiary education. Regarding religious affiliations, 10 participants were Christians, 3 Muslims, and 1 Traditionalist.

The majority of participants (79%) were married, with marriage durations ranging from 1 to 38 years; 1 participant was single, and 2 were widows. The number of children ranged from 1 to 5. Participants’ occupations included teachers, nurses, fashion designers, bankers, and businesswomen. Breast cancer diagnoses were made between 2013 and 2016, with treatments completed between 2014 and 2017. The participants represented various tribes, including Ga, Akan, Adangbe, Ewe, Hausa, and Dagaare. For more details, refer to Table 1.

Table 1: Demographic characteristics of participants.

Synonyms

Age Level of education Religion Marital status No. of children Occupation Date of diagnosis Date of completing treatment

Tribe

P1

44

Tertiary Christian Married

3

Teacher

2015

2016

Ga

P2

77

Secondary Traditional Widow

5

Trader

2014

2015

Ga

P3

50

Tertiary Christian Married

4

Nursing

2013

2014

Ga

P4

38

Vocational Christian Married

1

Fashion designer

2016

2017

Adangbe

P5

61

Secondary Christian Married

2

Pensioner

2013

2014

Ewe

P6

38

Tertiary Christian Married

2

Fashion designer

2016

2017

Ga

P7

44

Secondary Muslim Married

2

Textile telephones

2014

2015

Dagaare

P8

50

Tertiary Christian Married

3

Teacher

2016

2015

Aka

P9

44

Tertiary Muslim Married

4

Teacher

2013

2014

Hausa

P10

43

Tertiary Christian Married

2

Banker

2015

2016

Akan

p11

43

Vocational Muslim Married

5

Fashion designer

2013

2014

Hausa

P12

39

Tertiary Christian Married

2

Teacher

2016

2017

Akan

P13

78

Tertiary Christian Widow

3

Pensioner

2015

2016

Ewe

P14

51

Secondary Christian Single

2

Business women

2014

2015

Akan

To answer the research question, what are the personal traits that influence resilience among breast cancer women who received chemotherapy for breast cancer, four (4) themes and fourteen sub- themes emerged from the data. The themes are: hope, optimism, self- esteem, and confidence. See Table 2 for details.

Table 2: Themes and Sub-themes.

Themes

Sub-themes

 

 

1.         Hope

•    Hope in nurses

•    Hope in doctors

•    Hope in patients themselves

•    Breast cancer survivors

•    Hope in God

 

2.         Optimism

•    Focus on positive mindset

•    Avoidance coping

•    Acceptance coping

3.         Self-esteem •    Strong inner voice/Self-motivation,

•    Setting of new goals

 

4.         Confidence

•    Self-reliance

•    Preparedness

•    Confidence in health care practitioners

Theme One: Hope

After the analysis of data, the personal trait that influenced resilience in women who completed chemotherapy for breast cancer were; hope in nurses, hope in doctors, hope in patients, themselves, hope in breast cancer survivors and hope in God.

Hope in Doctors

The participants expressed hope and expectations in the doctors that took care of them during chemotherapy. They expressed that they were hopeful that doctors were going to help them to recover because they were under their cared.

“I put my trust in the doctors because I wanted recovery and they were those to care for me and so they became my only hope”. P1

“…so, when I came to the hospital and then the treatment started, I trusted and also had expectation that the doctors were going to help me through my chemotherapy”. P14

Hope in Nurses

Participants narrated that prior to their chemotherapy they were scared based on the unknown outcome of their treatment. However, they reported that their experiences with nurses on the first day at the hospital changed their believe as they received warm reception from nurses. To the participants, that gave them hope that their treatment journey will be smooth and probably end well

“my experience with the first nurse on my first day gave me hope and this expectation kept repeating itself till I finished my treatment”. P10

“…. formerly I perceived nurses as unintelligent workers who don’t care about patients but my chemo provided me with an opportunity to really know them. They offered me hope throughout my days during hospitalization. I can say from day one at the OPD what the nurse there counselled me on gave me hope athat my cancer journey was going to smooth”. P2

“For me, I was hopeful and this was placed within the context of finding meaning in my suffering, the pain and sadness I experienced every day during my chemo was too much but I didn’t give-up. I knew I was going to get hope due to the good relationship the nurses were offering to us, that was quiet assuring”. P4

Hope in Participants Themselves

Majority of the participants also placed their hope in themselves for recovery, as they believed that they are winners and can persevere throughout the treatment.

…so, all days I kept hoping for the best. I didn’t look down upon myself no, no way. I kept telling myself you are a conqueror; you are more than a conqueror”. P2

“I am one person who hardly quit. I persevere. Within me is full of hope”. P8

“I took it easy and I have to, because all I have at that time was hope. Personally, I take everything in my life easy although I was anxious initially, I later told myself that if I am worried, I can’t change anything and so, I have to just hope for the better.”. P6

Hopes in Breast Cancer Survivors

Other participants placed their hopes in breast cancer survivors who reassured them and wished them a speedy recovery. The personal testimonies of the survivors were sources of hope, which took away participants fears.

“There was this organisation called Breast Cancer Survivors Association, whose members came to give me and my family hope by offering us more information about breast cancer and how I can contribute to my survival, after all, they were living testimonies for us”. P9

“…so, I was not afraid, after all some patient had recovered from same condition and others from similar diagnosis and they were all there to offer us any information we wanted. That gave many of us hope because here are people who suffered what I am suffering and if they recovered from it that is assuring”. P12.

Hope in God

Other participants were hopeful that God will see them through their chemotherapy. They believed and trusted in the blood of Jesus.

There were instances when I used to sing this song, “my hope is built on nothing less than Jesus blood and righteousness” (long laugh) oh yeah and you feel God’s presence around you. So, I was hopeful God will do something”. P13

“ Hope is belief and beliefs are found in God. So, all I needed at that time was hope in God so that even if i die as they say it can lead to, i will go to heaven and that if I live I live for Him. So, my hope was only on Christ and Christ alone (laughter)”. P8

Theme Two: Optimism

The second theme that emerged from the data was optimism with the sub-themes; focus on positive mindset, avoidance coping and acceptance coping.

Focus on Positive Mindset

Participants indicated that they looked at the positive side of their conditions. They reported that by focusing on what they could do to keep healthy rather than on the negative circumstances of life kept them moving on with life.

I was inclined to look on the more positive side of my condition and to expect the greatest result from treatment since many women who came to the hospital had recovered, so I tuned my mind that surely I can recover”. P8

“…. believing in myself with much focus enables me to look more on what I could do to help myself. So, I kept saying I can overcome”. P7

Avoidance Coping

Participants narrated that they adopted avoided coping mechanism during their chemotherapy journey because of some misconceptions about breast cancer and it causes.

“…In fact, I was stable in mind that am going to get well. I tried as much not to let my church people know about it except my pastor and even at my work place only my brother-in-law knew about it because I trusted him. People gossip a lot and some of them don’t even think cancer can be cured and I never wanted any bad advice so I kept it to myself because I believed I was going to be healed”. P10.

“…. you know the misconceptions of Ghanaians about cancer. Most of them believed it is gotten through fornication and adultery, and others it is a curse and all that, but with my background as a health worker I was quite certain about the future that I will be well after all, we have discharged many with complete recovery from breast cancer”. P5.

Acceptance Coping

Some participants also narrated that they were able to cope with cancer and treatment duress by acceptance their present condition as a natural phenomenon, a circumstance they have no control of.

“…you know!! a condition like cancer, if you are not a person that is willing to accept that it is a condition you have no control of, it will be difficult to adjust to its treatments…I initially had a similar challenge till my second cycle of thermotherapy when I came to terms with the fact that I need to accept my present situation (cancer diagnosis) and move on. That really did the trick for me”. P14

Without first accepting to the fact that hey, this is the impact of cancer and chemotherapy…my brother, you will run away from the chemo, the drugs are many and come with a lot of side effects and for me to think I can take all these medications and get well, then I needed to be optimistic and accept all the effects knowing that its but for a while”. P12

Self-Esteem

Participants narrated that they were able to cope with cancer and its treatment through a feeling of strong inner voice/self-motivation and setting of new goals.

Strong Inner Voice/Self-Motivation

Participants indicated that their ability to even stretch their hands and switch on their phones was enough motivation for them to trust that their treatment journey will be successful. Other participants revealed that there was a strong inner voice encouraging them to keep going

“To the extent that I find it’s helpful to spend time to switch on my phone and take a selfie and forward it to my loved ones like before was enough for me, actually I had a strong feeling that I am fine and anything from someone to me is the person’s opinion”. P3

“I’m a person with deep feelings; I could hear an inner voice saying to me, this is nothing, God will help you out. It is that voice that kept encouraging me, so I had a positive feeling that I will get well, yeah”. P13

Setting of New Goals

Participants narrated that they never bordered to compare themselves to those who could not successfully recover from breast cancer. According to these participants, they set new goals and tune their minds on happy moments in order to overcome the effects of the chemotherapy and the disease burden.

“Hmmm, I did so many things to help me, like …. I never compare myself to any one…. I mean those who couldn’t make it through treatment, no. I know people died from breast cancer so I set new goals and thought for myself with the feeling, I am born to win. I tell you with that opinion I could move mountains”. P2.

“You see many people focus on the problem and cry and complain meanwhile those you complain to can’t help you out. As for me, the secret has been that this breast cancer is just one of many problems in life so just this specific situation can’t stop me from going on with life, so I set new goals for myself”. P1

Confidence

Confidence is another positive factor that influenced resilience among women with breast cancer who received chemotherapy. Participants revealed that they were self-reliant, prepared and had Confidence in health care practitioners

Self-reliant

participants expressed confidence in themselves and that contributed to their recovery. They said that self-confidence is needed to manage the effect of chemotherapy treatment.

“I needed confidence my-self, because to take chemo for a whole year (long laugh) my son, you need confidence, yes, else you can’t finish the chemo, you will stop because of its effects”. P3

“…to take chemo for almost one year it’s very important to be confident else I couldn’t have been able to finish my treatment. When you are not confident you will say is ok, I won’t take the treatment again because the side effects are a lot”. P5

Confidence is what got me here. I needed confidence to enable me stay and complete my treatment. When you are on chemo, and you are not confident in yourself you can’t stay to complete the chemo the side effects are just too many”. P7.

Preparedness

Participants narrated that they used past experiences from their mensural pains to cope with chemotherapy effects.

“…my mensural cycle pains have not been different from my cancer experiences…so for me I have learn how to cope with pain and life struggles since I started menstruating”. P4

“My past experience on menstrual pains has been a blessing in disguise. It has taught me how to cope with pain, so, I see this cancer experiences as similar to my monthly cycle pains and that helping me adjust to treatment”. P6

Confidence in Health Care Practitioners

Others expressed the opinion that they survived due to the confidence they had in doctors and nurses during the chemotherapy. They were of the conviction that the competence of the health team will help them, most importantly after their first chemotherapy dose.

“I was of the conviction that I needed confidence from the health care team to be able to stay through after receiving my first dose of chemo. My whole system changed and I could feel am no more the same and at this point all I need was to be sure the nurses and doctors knew what they were about’’. P9.

“…So, all I needed was to see them (nurses and doctors) confident in their procedures to assure me I will be fine because of the drug’s effects I was experiencing; and when I saw the confidence level the nurses showed (xxxx name mentioned) to me during my chemo I became ok throughout in my mind and that helped”. P1

Discussion

The findings of this study revealed four themes that encapsulate the personal traits influencing resilience among women who received chemotherapy for breast cancer: hope, optimism, self-esteem, and confidence. These themes are further enriched by fourteen sub- themes that provide deeper insights into the various ways these traits manifest. This discussion examines these findings in the context of existing literature, emphasizing their alignment with prior studies while acknowledging areas of divergence.

Hope

Hope emerged as a pivotal trait, with participants expressing reliance on sources such as nurses, doctors, themselves, breast cancer survivors, and God. This aligns with studies that highlight hope as a critical component of psychological resilience in cancer patients [17]. Hope in healthcare providers, particularly doctors and nurses, was tied to trust in their expertise and care quality. Similar findings are reported by [18], who found that positive patient-provider interactions bolster hope and treatment adherence. Hope derived from breast cancer survivors further supports prior research, such as [19,20], which underscores the impact of peer support on emotional well-being and resilience.

However, the centrality of hope in God reflects cultural and spiritual dimensions unique to the participants. Studies like those of Nyarko and colleagues affirm the significant role of spirituality in the resilience of African cancer patients [21,22], underscoring the interplay between cultural beliefs and coping mechanisms. Conversely, research in predominantly secular contexts [23] places less emphasis on spiritual hope, highlighting a cultural variance.

Optimism

Optimism, expressed through positive mindsets, avoidance coping, and acceptance coping, was another prominent trait. Participants’ ability to focus on the positives aligns with [24] conceptualization of optimism as a vital trait fostering resilience. Avoidance coping, despite its occasional association with negative outcomes, was viewed positively here by participants as a means of reducing exposure to stigma and misconceptions-a finding supported by [25,26] in the context of Ghanaian cancer patients. While participants viewed avoidance as protective, broader literature often critiques avoidance as counterproductive in resilience [27]. This suggests that the efficacy of avoidance coping may be context-dependent, influenced by cultural factors and individual perceptions of stigma and support.

Acceptance coping, where participants embraced their condition as a natural phenomenon, echoes findings of [28,29], who emphasize the role of acceptance in mitigating emotional distress during cancer treatment. However, some literature, such as that of [30], highlights that excessive avoidance can hinder emotional processing and long- term resilience, suggesting a potential area for further exploration.

Self-esteem

Self-esteem emerged as a cornerstone for resilience, with participants citing strong inner voices and goal-setting as pivotal. These findings resonate with studies by Campbell-Sills and colleagues [31]], which emphasize the role of self-motivation and personal agency in building resilience. The emphasis on setting new goals as a way to maintain focus and motivation is supported by the goal-setting theory of resilience [32].

While the study highlights self-esteem as a positive force, it contrasts with findings by Lim colleagues [33], who observed that individuals with lower self-esteem were more likely to experience prolonged emotional distress post-treatment. This divergence underscores the importance of understanding individual differences in resilience pathways.

Confidence

Confidence, encompassing self-reliance, preparedness, and trust in healthcare practitioners, was also crucial. Participants’ self-reliance aligns with [34] self-efficacy theory, which identifies belief in one’s abilities as essential for overcoming adversity. Preparedness, as shaped by prior experiences such as menstrual pain, highlights the role of experiential learning in resilience building, corroborating findings of [35] on post-traumatic growth.

Confidence in healthcare practitioners was tied to perceived competence and empathy, echoing findings of [36,37], which emphasize the significance of trust in healthcare teams. However, this study’s emphasis on cultural variance, such as reliance on healthcare practitioners’ confidence, offers a fresh perspective that is less emphasized in Western-centric studies.

Conclusion

In the absence of structured support systems, resilience in surviving breast cancer treatment is primarily shaped by individual personality traits such as hope, optimism, self-esteem, and confidence and emotional responses to the illness. While most findings resonate with prior studies, the positive framing of avoidance coping introduces a valuable area for further exploration, particularly in culturally diverse populations.

Declarations

Ethics Approval and Consent to Participate

The Noguchi Memorial Institute for Medical Research Institutional Review Board at the University of Ghana (NMIMR-IRB CPN017/17- 18) granted ethical approval for this study. All participants provided informed consent, and the research adhered to the relevant guidelines and regulations by Helsinki Declaration.

Consent for Publication

Not applicable.

Availability of Data and Materials

The datasets utilized and analyzed during this study can be obtained from the corresponding author upon reasonable request.

Conflict of Interest

The authors declare no conflicts of interest.

Funding

This study was not supported by any specific funding or grants from commercial or public entities.

Authors’ Contributions

All authors contributed to the conceptualization of the study. SG was responsible for data collection, and all authors participated in data analysis. SG drafted the manuscript, while LAO, and provided critical revisions. All authors reviewed and approved the final version of the manuscript.

Acknowledgments

The authors extend their heartfelt gratitude to the women who participated in this study.

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Core Shell Quantum Dot Solar Cells: Recent Advances and Future Perspectives

DOI: 10.31038/NAMS.2025811

Abstract

Core-shell quantum dot solar cells (CSQDSCs) have emerged as a promising technology in the field of photovoltaics, offering unique advantages such as tunable bandgaps, enhanced charge carrier dynamics, and improved stability. The core-shell structure mitigates surface defects, passivates dangling bonds, and reduces non-radiative recombination, thereby significantly improving efficiency. Recent advancements in material synthesis, device fabrication, and tandem architectures have demonstrated the potential of CSQDSCs to achieve higher power conversion efficiencies and address the limitations of traditional quantum dot solar cells. However, challenges such as material toxicity, scalability, and long-term stability remain barriers to their commercialization. This mini review highlights the recent progress in CSQDSC research, explores challenges like environmental concerns and cost-effectiveness, and discusses future prospects, including the development of lead-free materials, advanced passivation strategies, and scalable manufacturing techniques. With continued interdisciplinary efforts, CSQDSCs hold great promise for driving sustainable and efficient solar energy solutions.

Keywords

Quantum dot; Core-shell; Solar cell; Nanomaterials

Introduction

Solar energy has unbridled potential to veer the energy sector from pollution causing non-renewable energy sources to the unending renewable source, the sun causing lesser environmental pollution. This transformation of energy requires the materials which can control the flow of current under different circumstances and the research shows that the semiconductors have innate ability to do this. It was in 1954 when Daryl Chaplin, his physicist friend Gerald Pearson and chemist friend Calvin Fuller made the first significantly efficient silicon solar cell [1]. As per a report of April 26, 1954 issue, the Times, it was the beginning of a new era which would eventually lead to the mankind’s most cherished dream of harnessing unlimited power of sun [2]. Fast forward through 68 years of continuous efforts and today we see four generations of solar cells under the light. After exploring the first and second generation solar cells for decades and achieving a saturation of efficiency, the third generation solar cells came into the picture. Every newer generation comes with the hopes of high efficiency, low cost and more environment friendly. The latest generations with the introduction of nanotechnology in the field has given it a new horizon. It has provided us an unparalleled sea of opportunities for synthesizing novel materials which are stable, economical, non-toxic and suitable for absorbing large spectrum of solar radiations. The third generation includes a variety of solar cells made up of materials besides silicon, including dyes, organic materials, perovskite materials and quantum dots. Tremendous research is under the progress to increase the efficiency of these solar cells with low cost. It was not long ago when dye sensitized solar cells (DSSCs) came into the picture as a promising candidate for low-cost efficient solar cells. Here dye acts as a light absorbing material which has the tendency to replace traditional expensive silicon solar cells. In the last decade, DSSCs are largely explored while the research of other solar cells has just begun.

Among all, quantum dot solar cells draw much attention due to unprecedented properties of quantum dots like size dependent tunable band gap, Multiple Exciton Generation (MEG), Hot Electron Extraction (HEE) and wide range of absorption from visible to infrared region. These factors are of much importance as they are helpful in increasing the short circuit current, depicting the possibility of solar cell of 44.7% efficiency (theoretically reported) [3]. The maximum reported efficiency as of yet for QDSCs is 18.1% [4]. Moreover, quantum dots can be used to fabricate low-cost multiple junction solar cells as the different layers can be made up of same material of different band gaps. However, there are some disadvantages associated with quantum dot solar cells. The major problem associated with quantum dots is non-radiative recombination centres or traps causing recombination. Due to these traps, the interfacial charge transportation suffers which decreases the current and thus, efficiency of solar cells. To overcome this problem associated with quantum dots, an idea of covering it with another material was proposed and tested. The covering of quantum dot by another material called shell overcome this problem and the efficiency of solar cells can be increased. Thus, exploring the properties of core shell materials by varying different parameters like concentration of materials, temperature, pH, etc. is an open area of research and the solar cell fabricated using these materials are expected to have good efficiency.

The emergence of core shell nanomaterials and their successful synthesis has taken the research of efficient electronic devices to a new horizon. One material with some properties enveloped by another material having different properties to form a hybrid structure showing enhanced properties has amazed scientists for a long time. The study of the unique properties of core shell nanomaterials, their applications in different fields and their synthesis methods are still at its infant stage and the researchers have a long way to go. Numerous arguments can be given in the favour of the need of core shell materials. These include the enhancement of quantum efficiency, photoluminescence efficiency, fluorescence, thermal stability and chemical stability. The list continues with the reduced toxicity, tuned band gap and passivated dangling bonds [5]. The surface passivation by reduction in the dangling bonds by shell covering is an important reason of the emerging research in this field. The surface traps decrease the free flow of electrons and thus the current. The shell reduces the traps enabling the free flow of electrons and thus opportunity to increase the efficiency of solar cells [6]. This review paper is an attempt to throw light on the recent advances and future perspectives of core shell quantum dot solar cells.

Increased efficiency of Core Shell QD Solar Cells

Many papers have reported the increased efficiency and open circuit voltage of core shell solar cells in comparison to only core. The reason can be successfully attributed to the surface passivation by shell. Quantum dots are generally capped by a ligand viz. oleylamine, oleic acid, etc to be in stable state. However, these ligands create a barrier for charge carriers. Thus, to reduce the barrier, the QD film is exposed to a shorter ligand viz. mercaptopropionic acid, halide anions, etc. Though ligand exchange process reduces the band gap, it introduces several surface defects, vacancies and dangling bonds producing non radiative recombination centres on the surface. These recombination centres trap the charge carriers and reduces the carrier mobility, thus reducing the open circuit voltage and current. One of the proposed ways of eliminating these traps is to envelop the quantum dots by shell [7].

Speirs et. al. [8] have demonstrated solar cells made from PbS@CdS CSQDs and have shown a 147 mV increase in VOC as compared to only core. They have investigated the physical reason behind this enhancement and found the same as the improved passivation of core by the shell and thus lower electron trap density. To demonstrate this, they have fabricated PbS and PbS@CdS Schottky solar cells using layer by layer deposition as reported [9,10]. The current density versus voltage responses of these devices is obtained as shown in Figure 1. It can be seen that though short circuit current is higher for core only i.e. PbS, open circuit voltage is higher for core shell device.

Figure 1: Current density versus voltage curve of PbS and PbS@CdS devices. Reproduced from ref. [8] with permission from Royal Society of Chemistry.

Neo et. al. [11] have shown the effect of surface passivation on PbS@CdS core shell colloidal quantum dot solar cells. The CSQDs have been synthesized using cation-exchange process and used as an active layer in solar cell. The whole process of layer deposition is done using spin coating technique on ITO substrate as reported. Using CSQDs, an improvement in open circuit voltage from 0.42 V (while used pristine core) to 0.66 V has been observed and the power conversion efficiencies of 5.6 ± 0.4 % have been achieved. Figure 2 shows the current density versus voltage curves of PbS and different PbS@CdS devices from different ligand exchange process. Here, we have seen that although short circuit current is lower in PbS@CdS device, open circuit voltage is higher.

The efficiency of a solar cell is not only dependent of formation of shell around the core but also the thickness of the shell. Dana et. al. have shown the relation between excitonic and efficiency of solar cell.

Figure 2: Current density versus voltage curve of PbS@CdS device from different ligand exchange treatments. Reproduced with permission from ref. [12] Copyright © 2014 American Chemical Society.

Challenges and Future Prospects

Despite the promising advantages of CSQDSCs, several challenges need to be addressed to advance their real-world application. A significant hurdle lies in the toxicity of materials used, particularly in lead-based quantum dots such as PbS and PbSe, which raise environmental and safety concerns. Efforts to synthesize lead-free or environmentally benign alternatives, such as tin-based or copper-based quantum dots, have shown potential, but these materials often suffer from lower efficiency and stability, necessitating further research [13]. Another challenge is the long-term stability of core-shell quantum dots. While the shell improves passivation and reduces non-radiative recombination, the overall durability of devices remains a concern under real-world conditions, such as exposure to moisture, oxygen, and ultraviolet (UV) light. Encapsulation techniques and the development of more robust shell materials are critical to overcoming these issues. Additionally, shell thickness plays a crucial role in determining device performance. A very thin shell might fail to effectively passivate the core, while an overly thick shell could hinder charge transport, leading to reduced efficiency. Achieving the optimal shell design requires precise control during synthesis, which can be challenging on a large scale [14].

The scalability of CSQDSCs for commercial production presents another barrier. Current fabrication techniques, such as spin-coating and layer-by-layer deposition, are not easily scalable for mass production. Developing cost-effective and scalable methods, such as roll-to-roll printing or inkjet printing, will be essential for translating laboratory advancements into commercial viability. Furthermore, ligand exchange processes used to improve charge transport often introduce surface defects, which compromise the performance of the solar cells [15]. Alternative methods that maintain surface integrity while enhancing carrier mobility need to be explored. Finally, economic competitiveness remains a challenge for CSQDSCs. While they promise lower costs compared to silicon-based solar cells, the high price of certain precursor materials and the complexity of fabrication processes limit their market potential. The integration of these solar cells into existing energy systems will require further cost reductions and infrastructure adaptation.

The future of core-shell quantum dot solar cells lies in addressing these challenges through innovative materials, advanced fabrication techniques, and enhanced device architectures. Research into lead-free and cadmium-free quantum dots is expected to accelerate, with materials such as perovskite quantum dots, carbon-based quantum dots, and other non-toxic alternatives gaining traction [16]. These materials, coupled with optimized core-shell designs, could lead to highly efficient and environmentally sustainable devices. Machine learning and artificial intelligence (AI) are emerging as valuable tools in the optimization of quantum dot materials and device performance. By analyzing large datasets from experimental and simulation studies, AI can identify patterns and predict optimal material compositions, synthesis parameters, and device configurations, significantly accelerating the development process. Another promising direction is the integration of CSQDSCs with tandem solar cell technologies. Combining core-shell quantum dot layers with perovskite or silicon-based layers can leverage the broad spectral absorption of quantum dots while benefiting from the higher efficiencies of other materials, potentially surpassing the efficiency limits of standalone quantum dot solar cells [17].

Additionally, research into advanced passivation strategies and robust encapsulation materials will play a vital role in improving the stability of these devices. Techniques such as atomic layer deposition (ALD) for ultra-thin and conformal coatings can enhance both stability and efficiency. On the industrial front, efforts to scale up production through automated and high-throughput fabrication techniques are expected to lower manufacturing costs and improve commercial feasibility [18]. Governments and private industries could play a crucial role in driving this transition by investing in pilot projects and providing incentives for renewable energy technologies based on CSQDSCs. While challenges persist, the unique properties of core-shell quantum dots position them as a promising candidate for the next generation of solar cells. Continued multidisciplinary research and collaboration between academia, industry, and policymakers will be essential to unlock the full potential of this technology, ensuring its contribution to a sustainable energy future.

Conclusion

Core-shell quantum dot solar cells offer a promising solution for next-generation photovoltaics by enhancing efficiency and stability through surface passivation and improved charge dynamics. Despite challenges like material toxicity, stability, and scalability, advancements in lead-free materials, synthesis techniques, and tandem architectures provide pathways for improvement. Their potential for high efficiency, cost-effectiveness, and environmental sustainability positions them as a key technology for renewable energy. Collaborative efforts across research, industry, and policy will be crucial to unlocking their full potential for a sustainable energy future.

Acknowledgement

The authors acknowledge the support and guidance of Prof. Anand Srivastava, Vice Chancellor, Netaji Subhas University of Technology and Prof. Ranjana Aggarwal, Director, CSIR-NIScPR.

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Association of the Extent of Exposure to Environmental Tobacco Smoke with Exhaled Nitric Oxide and Eosinophils: a Cross-Sectional Study Based on the NHANES 2007–2012 Database

DOI: 10.31038/GEMS.2025714

Abstract

Background: Previous studies have demonstrated that exposure to environmental tobacco smoke is associated with a reduction in fractional exhaled nitric oxide (FeNO) levels, elevation in eosinophil (EOS) counts and alterations in airway inflammation patterns, influencing the efficacy of glucocorticoid therapy for TH2 inflammation. No previous study has investigated the association of the extent of exposure to environmental tobacco smoke with FeNO levels. This study aimed to investigate the association of the extent of exposure to environmental tobacco smoke with FeNO level and EOS count.

Methods: In this retrospective cohort study, we included 12766 individuals from the National Health and Nutrition Examination Survey 2007–2012. The extent of exposure to environmental tobacco smoke was assessed by measuring serum cotinine levels. Participants were categorised into quintiles based on their cotinine levels. Logistic regression models were developed to evaluate the association of serum cotinine levels with FeNO levels and EOS count.

Findings: In the unadjusted and adjusted models, the highest quintile of serum cotinine levels (>105 ng/ml) was significantly negatively associated with FeNO levels. However, low-to-moderate quintiles of serum cotinine levels were not significantly associated with FeNO levels. Based on sensitivity analyses, the negative associations between the highest quintile of serum cotinine levels and FeNO levels remained consistent among participants with asthma, chronic bronchitis and respiratory symptoms within 7 days. Increased serum cotinine levels were significantly associated with increased EOS counts, which in turn were significantly associated with increased FeNO levels. EOS significantly mediated 7.59% of cotinine-associated reductions in FeNO levels.

Conclusions: Our findings indicated that high levels of tobacco smoke exposure are associated with a decrease in FeNO levels and an increase in EOS count. The smoking status should be considered when evaluating type 2 airway inflammation based on FeNO levels and EOS count.

Introduction

The subtypes of airway inflammation include neutrophilic, eosinophilic, mixed and oligocytic inflammation. Airway eosinophilic inflammation is defined as a blood eosinophil (EOS) count ≥300 cells·μL−1 and/or a sputum EOS count ≥3% [1]. Airway eosinophilic inflammation is sensitive to inhaled corticosteroids (ICS) [2]. In particular, in patients with asthma and chronic obstructive pulmonary disease (COPD) exhibiting airway eosinophilic inflammation, treatment with ICS can ameliorate symptoms, reduce acute attack frequency and improve lung function [3]. Therefore, diagnosing airway eosinophilic inflammation is important. Fractional exhaled nitric oxide (FeNO) levels, along with blood EOS counts, are considered indicators of airway eosinophilic inflammation [4]. Moreover, FeNO levels are closely associated with an individual’s response to allergens, airway hyper-responsiveness and impaired lung function [5,6], thus enabling the diagnosis of airway eosinophilic inflammation. They are helpful for guiding ICS and IgE-targeted therapies for patients with COPD, asthma and chronic cough. Therefore, FeNO and eosinophils are of great significance in the management of airway diseases. Nitric oxide (NO) serves as an endogenous regulatory molecule whose production is regulated by NO synthase (NOS), which is predominantly produced by inducible NOS in bronchial epithelial cells. Exhaled NO levels can be measured by quantifying NO concentration in exhaled breath.

Smoking induces alterations in airway inflammation types, thereby affecting the efficacy of ICS therapy in patients with asthma and COPD. Consequently, investigating the influence of smoking on type 2 airway inflammation has become a focal point of research. Previous studies have grouped light and heavy smokers together, making it difficult to determine the specific extent of tobacco smoke exposure that leads to changes in airway inflammation types, thus resulting in contradictory research findings. No previous study has investigated the association of the extent of exposure to environmental tobacco smoke with FeNO levels. Furthermore, although FeNO and EOS are associated with airway eosinophilic inflammation and act through different pathways, it remains unknown whether EOS play a mediating role in reducing FeNO levels induced by tobacco smoke exposure. Cotinine is the primary metabolite of nicotine and is significantly positively correlated with the extent of tobacco smoke exposure [7]. The estimated elimination half-life of cotinine (approximately 15–20 h) is longer than that of nicotine [8]. Therefore, cotinine has been widely used as a biomarker for tobacco exposure [9-12], as explained in detail in the NHANSE database (https://wwwn.cdc.gov/Nchs/Nhanes/2011-2012/COTNAL_G.htm). In the current study, cotinine was used to determine the level of tobacco smoke exposure.

Materials and Methods

Study Design and Population

The National Health and Nutrition Examination Survey (NHANES) is a programme of studies designed to assess the health and nutritional status of adults and children in the United States (US). During each survey cycle, a sample of participants is selected from the US non-institutionalised civilian population using a complex, stratified, multistage probability cluster sampling design. We analysed data from the participants of the NHANES from 2007 to 2012. A total of 16,784 participants aged ≥18 years had available data on cotinine. The National Center for Health Statistics (NCHS) Institutional Review Board (Hyattsville, MD) approved the study protocols, and all participants provided written informed consent.

FENO

FENO was measured using Aerocrine NIOX MINO®, which features a dynamic flow restrictor that stabilises the flow rate at 50 ml/s. The NHANES protocol required two reproducible FENO measurements in accordance with the testing procedures recommended by the manufacturer and similar to those published by the American Thoracic Society and European Respiratory Society. If either or both of the first two valid FENO measurements are <30 ppb and the measurements differ by ≤2 ppb or if both measurements are >30 ppb and within 10% of each other, then the test was considered reproducible and complete. Two values below or above the limit of detection were also considered reproducible.

Cotinine

Serum samples were processed, stored and shipped to the Division of Laboratory Sciences, National Center for Environmental Health and Centers for Disease Control and Prevention for analysis. Serum cotinine level was measured via isotope dilution–high-performance liquid chromatography–atmospheric pressure chemical ionisation–tandem mass spectrometry (ID–HPLC–APCI–MS/MS). Briefly, the serum sample was spiked with methyl-D3 cotinine as an internal standard, and after an equilibration period, the sample was applied to a basified solid-phase extraction column. Cotinine was extracted from the column with methylene chloride; the organic extract was concentrated, and the residue was injected into a short C18 HPLC column. The eluant from these injections was monitored using APCI–MS/MS, and the m/z 80 daughter ion from the m/z 177 quasi-molecular ion was quantitated, along with additional ions for the internal standard, external standard and confirmation. Cotinine levels were calculated from the ratio of native to labelled cotinine in the sample based on a comparison with a standard curve.

Other Variables of Interest

Age, sex and race/ethnicity were self-reported. Body mass index (BMI) was calculated using the height and weight measured at the mobile examination centre. Race and ethnicity were categorised as non-Hispanic Black, other Hispanic, non-Hispanic white and non-Hispanic other race, based on categories provided by NHANES investigators. Self-reported data on engaging in strenuous exercise within 1 h, consumption of NO-rich vegetables within 3 h , consumption of NO-rich meat within 3 h, use of oral or inhaled steroids within 2 days and development of respiratory symptoms within 7 days were collected using a computer-assisted personal interview system. Asthma and chronic bronchitis were defined according to self-reported diagnosis by a physician. A complete blood count was performed using the Beckman Coulter MAXM instrument in MECs, and all participants underwent blood cell analysis.

Selection of the Study Population

We conducted a cross-sectional study using aggregated data from three NHANES cycles (2007/2008, 2009/2010 and 2011/2012) in which serum cotinine was tested. A total of 16,784 adults completed the serum cotinine test during this survey period (Figure 1). Among them, 3280 were excluded due to missing data on exhaled NO (3227) and EOS (53). Additionally, 738 participants were excluded due to the following missing covariate data: asthma; chronic bronchitis; engaging in strenuous exercise within 1 h; consumption of NO-rich vegetables within 3 h; consumption of NO-rich meat within 3 h; use of oral or inhaled steroids within 2 days and development of cough, cold or respiratory illness within 7 days. Finally, 12766 participants were included in the study. The participants were categorised into five groups based on cotinine levels: Q1 (first quintile), Q2 (second quintile), Q3 (third quintile), Q4 (fourth quintile) and Q5 (fifth quintile).

Figure 1: Flow diagram of the study. Abbreviations: FeNO: fractional exhaled nitric oxide; EOS: eosinophils; ICS: inhaled corticosteroids; CI: confidence interval; OR: odds ratio; SD: standard deviation.

Statistical Analysis

Continuous variables of age, BMI at enrolment and laboratory findings were expressed as median (interquartile range) or mean ± standard deviation (SD). The remaining categorical variables were expressed as n (%). The participants were categorised into quintiles based on the cotinine levels provided by NHANSE: Q1 (0.011), Q2 (0.011–0.027), Q3 (0.027–0.104), Q4 (0.104–105) and Q5 (≥105). Quintiles based on cotinine levels can effectively reflect the distribution of tobacco smoke exposure levels among the participants. Participants in the highest quintile (Q5) were considered to have high levels of tobacco smoke exposure. Logistic regression models were used to investigate the odds ratios (ORs) and 95% confidence intervals (CIs) of FeNO levels according to serum cotinine levels (quintiles). In adjusted model 1, the adjusted covariates included cotinine, age, , BMI and ethnicity. In adjusted model 2, the adjusted covariates were asthma, chronic bronchitis, EOS, engaging in strenuous exercise within 1 h, consumption of NO-rich vegetables within 3 h, consumption of NO-rich meat within 3 h, use of oral or inhaled steroids within 2 days, development of respiratory symptoms within 7 days and covariates included in model 1. A sensitivity analysis was conducted using the logistic regression model among participants with such as chronic bronchitis , asthma, and respiratory symptoms within 7 days prior to testing. After weighting the data with the sample weights (full sample 2-year interview weight) obtained from the NHANS 2007–2012 demographics file, logistic regression analysis was performed to explore the relationship between tobacco exposure and FeNO levels in the US population. Additionally, logistic regression models were utilised to explore the association between cotinine levels (quintiles) in the participants and higher EOS counts (≥0.3 × 103 cells/µl). Logistic regression models were also used to analyse the association between EOS counts in the participants and higher FeNO levels (>25 bbp). Correlation coefficients (Spearman’s rho and Kendall’s tau) were calculated to investigate the cotinine–EOS association. This study examined the proportion of mediation through EOS in the associations of cotinine levels and FeNO using the R (R4.2.1) based on the mediation method recommended by Hayes [13]. The data were analysed using R (R4.2.1) and SPSS version 21.0 (IBM Corp., Armonk, NY, USA). The statistically significant cut-off of the two-sided P-value was 0.05.

Results

Characteristics of the Participants

Table 1 describes the socio-demographic, anthropometric, race, primary disease and laboratory data of the participants. Approximately 17.5% (2446/13,945) of the participants had FeNO levels >25 bbp, and approximately 21.5% (3194/13,945) had EOS counts ≥0.3 × 103/µl. The median age of the participants was 43 (20, 60) years. In total, 2844 (20.4%) participants had cough, cold or respiratory illness within the past 7 days, 1721 (12.4%) had asthma, and 459 (4.1%) had chronic bronchitis. In order to ensure that the survey results can represent the entire US population, we weighted the data. The characteristics of the US adults were showed in the Table S4.

Table 1: Characteristics and laboratory data of the participants according to cotinine levels (n = 12766).

Association of Cotinine Levels with FeNO Levels

Table 2 presents the risk of higher FeNO levels (>25 bbp) associated with serum cotinine levels categorized into quintiles among participants. In the unadjusted models, participants with the highest quintile of serum cotinine levels (>105 ng/ml) showed decreased FeNO levels compared with those with the lowest quintile of serum cotinine levels (0.011 ng/ml) (OR, 0.24 [0.20, 0.29]). There were no significant differences in FeNO levels of participants between Q3 and the lowest quantile of cotinine levels (21.6% vs 19.5%) as well as between Q2 and the lowest quantile of cotinine levels (21.7% vs 19.5%) (Table 2). After adjusting for potential confounders, similar results were observed in models 1 and 2. In model 2, a 1 SD increase in cotinine level was associated with lower FeNO levels (OR, 0.47 [0.42, 0.517]) (Table 2). Sensitivity analyses performed among participants with asthma, recent respiratory symptoms, and chronic bronchitis yielded consistent findings (Tables S1-S3). After weighting the sample, the negative association between cotinine and FeNO levels remained consistent across the US population (Table S5).

Table 2: Adjusted ORs and 95% CIs for the association of cotinine levels with the risk of high FeNO level (n = 12766).

#P > 0.05 Abbreviations: FeNO: fractional exhaled nitric oxide; EOS: eosinophils; CI: confidence interval; OR: odds ratio; SD: standard deviation.

Logistic regression model 1 included covariates of cotinine, age, sex, BMI, race and EOS count. Logistic regression model 2 included covariates of use of oral or inhaled steroids within 2 days, development of respiratory symptoms within 7 days, consumption of NO-rich food within 3 h, engaging in strenuous exercise within 1 h, asthma, chronic bronchitis and covariates in model 1.

Association of Cotinine Levels with EOS Levels

Compared with participants with the lowest quintile of cotinine levels, those with the highest quintile of cotinine levels had higher EOS count (≥0.3 × 103 cells/µl) (OR 1.82 [1.61, 2.06]). The ORs were 1.87 (1.64, 2.13) and 2.39 (2.09, 2.74) in models 1 and 2, respectively (Table 3). However, no statistically significant difference in EOS counts was observed between Q3 and the lowest quintile of cotinine levels and between Q2 and the lowest quintile of cotinine levels. This study revealed that higher cotinine levels were positively associated with EOS count in all models (Table 3). A 1 SD increase in cotinine levels was associated with elevated EOS count (ORs of 1.14, 1.14 and 1.24 in the unadjusted model, model 1 and model 2, respectively). Correlation analyses revealed significant positive correlations between cotinine and EOS levels (Spearman’s rho: r = 0.074, P < 0.0001; Kendall’s tau: r = 0.097, P < 0.0001).

Table 3: Adjusted ORs and 95% CIs for the association of cotinine levels with EOS count (n = 12766).

#P > 0.05 Abbreviations: FeNO: fractional exhaled nitric oxide; EOS: eosinophils; ICS: inhaled corticosteroids; CI: confidence Interval; OR: odds ratio.

Logistic regression model 1 included covariates of cotinine, age, sex, BMI, race and FeNO level. Logistic regression model 2 included covariates of use of oral or inhaled steroids within 2 days, development of respiratory symptoms within 7 days, consumption of NO-rich food within 3 h, engaging in strenuous exercise within 1 h prior to testing, asthma, chronic bronchitis and covariates in model 1.

Association of EOS Count with FeNO Levels

This study revealed a positive association between EOS count and FeNO levels. The participants were categorized into quintiles based on the EOS counts (Table 4). The results showed that a 1 SD increase in EOS count was significantly associated with higher FeNO levels (>25 bbp) (OR 1.55 [1.48, 1.62], 1.53 [1.46, 1.60], 1.35 [1.29, 1.43] and 1.43 [1.15, 1.59] in the unadjusted model, model 1, model 2 and model 3, respectively).

Table 4: Adjusted ORs and 95% CIs for the association of EOS count with FeNO levels (n = 12766).

#P > 0.05 Abbreviations: FeNO: fractional exhaled nitric oxide; EOS: eosinophils; ICS: inhaled corticosteroids; CI: confidence interval; OR: odds ratio; SD: standard deviation

Multivariate linear regression model 1 included covariates of EOS, age, sex, BMI, race and cotinine level. Multivariate linear regression model 2 included covariates of use of oral or inhaled steroids within 2 days, development of respiratory symptoms within 7 days, consumption of NO-rich food within 3 h, engaging in strenuous exercise within 1 h prior to testing, asthma, chronic bronchitis and covariates in model 1.

Mediation Analyses

As shown in Table 5, significantly mediated effects by EOS were observed on the association of cotinine levels with FeNO levels. Increased EOS count significantly mediated 13% of the cotinine-associated reduction in FeNO levels. Mediation analyses were conducted using the R programming language.

Table 5: Mediated effects by EOS on the association of cotinine levels with FeNO levels (n = 12766).

Abbreviations: FeNO: fractional exhaled nitric oxide; EOS: eosinophils; CI: confidence interval; OR: odds ratio; SD: standard deviation.

Discussion

This study revealed that participants with the highest quintile of cotinine levels (≥105 ng/ml) exhibited decreased FeNO levels compared with those with the lowest quintile of cotinine levels (0.11 ng/ml, indicating no tobacco exposure). Compared with participants with the lowest quantile of cotinine levels, no significant difference was observed in FeNO levels in those with Q2, Q3 and Q4 cotinine levels (P > 0.05). Sensitivity analyses conducted among participants with asthma, recent respiratory symptoms and chronic bronchitis revealed consistent findings. Similar results were obtained across the US population after the data were weighted. A positive association between high tobacco exposure and EOS count was observed. EOS mediated the cotinine-associated decrease in FeNO levels. Chronic airway inflammation and acute airway inflammation are associated with increased FeNO levels [14-17]. Additionally, exercise [18-20] and consumption of NO-rich foods [21-22] can cause changes in FeNO levels. Therefore, in this study, we included variables such as engaging in strenuous exercise within 1 h, consumption of NO-rich foods within 3 h, asthma, chronic bronchitis and with respiratory symptoms within 7 days as covariates in the model.

Some studies have indicated that smoking can lead to a decrease in FeNO levels [23,24] and alter airway inflammation types. These studies confirm our research findings. However, another study showed no remarkable difference in FeNO levels between smokers and non-smokers [8]. Previous studies have categorised participants into smokers, former smokers and non-smokers but failed to assess the extent of tobacco exposure. Consequently, various studies may yield conflicting conclusions. Furthermore, previous studies employed small samples that lacked representativeness. In our research, we utilised a nationally representative large sample of the adult population in the US to explore the association of tobacco exposure with FeNO levels. We employed serum cotinine level as a reliable measure to evaluate the extent of exposure to environmental tobacco smoke. Participants were categorised into quintiles based on cotinine levels: Q1 (0.011–0.0185), Q2 (0.0185–0.075), Q3 (0.075–125), Q4 (125–309) and Q5 (≥309). This approach allows us to understand the distribution of tobacco exposure levels among participants across different quintiles. We can effectively understand the trend in the effect of cotinine levels on FeNO levels by investigating the regression relationship across different quantiles. Our study demonstrated that high exposure to tobacco smoke is associated with lower FeNO levels. Ashley et al. [25] used data from the NHANES 2007–2012 to investigate the association of tobacco exposure with FeNO levels in non-smoking adolescents and found that tobacco exposure was associated with lower FeNO levels, consistent with the results of the current study. The research population in their study was a specific cohort of non-smoking adolescents. Our study further explored the effects of smoking on EOS count and the mediating role of EOS, providing a reference for the mechanism by which tobacco exposure leads to lower FeNO levels.

EOS and FeNO have been utilised as indicators of type 2 airway inflammation as well as for identifying patients experiencing asthma exacerbations [26,27], guiding corticosteroid therapy during the exacerbation of COPD 28 and determining the suitability of ICS therapy regimens [29-32]. Their importance in COPD treatment is paramount [33,34]. Considering that smoking can influence airway inflammation, there has been increasing interest in exploring the association between blood EOS counts and smoking habits. Current smoking is significantly associated with EOS counts ≥210 cells·μl−1 (OR, 1.72). Colak et al. [35] reported that a history of smoking is associated with a blood EOS count ≥300 cells·μl−1; however, the association between current cumulative tobacco exposure and EOS count remains uncertain. Our study revealed that EOS counts were elevated in participants with Q4 and Q5 serum cotinine levels. In a study involving the Copenhagen general population, Pedersen et al. [36] showed that high cumulative and daily tobacco consumption in current smokers was associated with substantial increases in EOS counts in a dose-dependent manner. However, their minimum reference value was <10 g/day of tobacco consumption. The reference for our study was the absence of tobacco exposure.

Although EOS and FeNO serve as markers for type 2 airway inflammation, they represent different aspects of this condition [37-40]. FeNO level reflects airway IL‐13 activity, whereas blood EOS count reflects systemic IL‐5 activity [22]. FeNO level is correlated with increased induced sputum levels of airway type 2 cytokines, chemokines and alarmins. In contrast, blood EOS counts are only correlated with serum IL‐5 levels in the sputum [41]. Tobacco exposure may cause a decrease in FeNO levels and an increase in EOS count through different signalling pathways. The exact mechanism underlying this effect remains unclear. The mediated analysis in the current study showed that EOS counts mediated the cotinine-associated reduction in FeNO levels, But more research is needed to confirm this. First, the effect of tobacco exposure on type 2 airway inflammation was corroborated, and the range of tobacco exposure levels that influence changes in airway inflammation types was further analysed. Second, the potential mechanism underlying the alterations in EOS counts and FeNO levels induced by tobacco exposure was investigated, revealing that EOS mediated the cotinine-associated reduction in FeNO levels. This result provides valuable insights for further elucidation of related mechanisms. Third, previous studies [23-24] have employed past and current smoking as indicators for classifying tobacco exposure. Such an approach is considered overly general and overlooks second-hand smoke exposure. In contrast, our study substituted serum cotinine levels to assess tobacco exposure levels, yielding results with increased accuracy. Finally, relevant adjustments were made by incorporating potential confounders.

Inevitably, this study had certain limitations. First, the effect of long-term smoking accumulation and duration of quitting smoking on EOS count was not considered (21). Environmental pollutants are associated with FeNO levels [42-45]. Furthermore, allergic rhinitis, eosinophilic esophagitis, atopic rhinitis and food allergy are associated with elevated levels of FeNO [46-50]. However, the NHANES 2007–2012 database lacks data on environmental pollution, allergic rhinitis, eosinophilic esophagitis, atopic dermatitis and food allergies. Second, smoking induces neutrophilic inflammation. The effect of smoking-related neutrophil inflammatory factors on FeNO levels requires further investigation. Third, disease history relies on self-reporting, which is susceptible to individual subjectivity. Finally, the utilisation of retrospective data may lead to data loss, measurement errors and inaccuracies. In conclusion, this study demonstrated that tobacco exposure can cause a decrease in FeNO levels and an increase in EOS counts. The smoking status should be considered when evaluating type 2 airway inflammation using FeNO and EOS count. The reduction in FeNO levels due to tobacco exposure is partially mediated by EOS. High levels of tobacco exposure can lead to a distinct type of airway inflammation characterised by elevated EOS count but decreased FeNO levels. This airway inflammation type should be classified as a subtype separate from typical airway eosinophilic inflammation. These findings provide clinicians with a scientific basis for the diagnosis, treatment and management of patients with airway inflammation.

Conflict of Interest

The authors declare that they have no conflicts of interest.

Funding

This study was supported by Scientific Research Fund Project of Hunan Provincial Health Commission of China (No. D202303028856).

Data Availability

The data underpinning this article were obtained from the National Health and Nutrition Examination Survey (NHANES) 2007–2012. The datasets utilized and analyzed in the present study are available from the corresponding author upon reasonable request.

Authors’ Contributions

Xingfang Hou, Shufen Hou, Chenggong Hou, Xuelian Chen, and Yuling Tang conducted this study. Xingfang Hou was responsible for the conceptualization, methodology, investigation, formal analysis, preparation of the original draft, provision of resources, and visualization. Shufen Hou and Chenggong Hou contributed to data curation and investigation. Yuling Tang and Xuelian Chen provided supervision, reviewed the manuscript, and managed project administration. Xingfang Hou, Yuling Tang, and Xuelian Chen were designated as guarantors of the paper, ensuring the integrity of the work from inception to publication. All authors reviewed and approved the final manuscript.

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Extremely 13C-rich Diamond in Orthorhombic Cassiterites in the Variscan Erzgebirge, Saxony/Germany

DOI: 10.31038/GEMS.2025713

Abstract

Raman studies on a large cassiterite sample from Zinnwald, E-Erzgebirge/Germany, brought some surprising results to light. To these belong the 13C-rich diamonds and graphite, as well as other minerals, first and foremost as high-pressure and high-temperature orthorhombic cassiterite. Because there are also 12C-rich diamonds in the root zones in a crystal present, especially in a large cassiterite crystal from Ehrenfriedersdorf, we assume at least two distinct pulses with varying isotopes of carbon (12C versus 13C) in the supercritical fluids (SCGF) coming from the earth’s mantle. First came 12C-rich and later 13C-rich supercritical fluids. If so, other isotopes can also effectively be separated in supercritical fluids.

Keywords

Raman spectroscopy, 13C-rich diamond, Orthorhombic cassiterite, Variscan tin deposits, Supercritical fluids, Isotope separation

Introduction

A presentation about the 800 years of mining activity and 450 years of geological research in the Erzgebirge/Krǔsné hory region given by Breiter (2014) [1] shows, among other things, the extensive tin exploration and the origin and relationship of tin deposits with granite magmatism. According to this classic work by many scientists, there are no questions about the genesis of this type of ore deposit. It seems that all problems are solved, which is not the case. Thomas (2024a and 2024b) [2,3] has, however, shown that the origin of the Variscan tin deposits must be newly scrutinized. The first doubts came from the intensive work on the tin deposit Ehrenfriedersdorf presented in Schütze et al. (1983) [4]. However, their conclusions are not conclusive, at least speculative. The first concrete proof came from Thomas (2024a) [2]. In this publication, we will show that the proofs of mantle participation via supercritical fluids or melts up to now are no exceptions. We classify the supercritical fluids or melts according to Ni et al. (2024) [5] as supercritical geofluids (SCGF).

Sample Materials Microscopy and Raman Spectroscopy: Methodology

Sample Material

A sample from Zinnwald (Figure 1) clearly shows two parts of cassiterite composed of an opaque part (2/3 in volume) and a transparent cassiterite-brown nearby pale part (1/3 in volume). This cassiterite contains fluid inclusions that homogenized at about 386°C (see Thomas 1982) [6] in the liquid phase (with 15 equivalent % NaCl). In the black part, no fluid inclusions are present.

Figure 1: Cassiterite sample (Sn-23) from Zinnwald, E-Erzgebirge/Saxony. All black parts are orthorhombic cassiterite (about 2/3 in volume). The transparent brown zones contain tetragonal cassiterite parts.

The pale part of cassiterite contains many small black to colorless (~10 µm in diameter) spherical crystals of graphite and diamond. The black part of that cassiterite contains pyrrhotine and pyrite, as well as diamond and graphite inclusions, which are relatively stable against hydrothermal activity. The sample is from the Mining Academy Freiberg. At this place, it is essential to emphasize that graphite-like material in Variscan cassiterites is typical. A description of another cassiterite sample used in this short contribution is from Ehrenfriedersdorf (Sn-70), described in Thomas 2024a [3].

Microscopy and Raman Spectroscopy

We performed all microscopic and Raman spectroscopic studies with a petrographic polarization microscope (BX 43) with a rotating stage coupled with the EnSpectr Raman spectrometer R532 (Enhanced Spectrometry, Inc., Mountain View, CA, USA) in reflection and transmission. The Raman spectra were recorded in the spectral range of 0–4000 cm−1 using an up-to-50 mW single-mode 532 nm laser, an entrance aperture of 20 µm, a holographic grating of 1800 g/mm, and spectral resolution ranging of 4 cm−1. Generally, we used an objective lens with a magnification of 100x: the Olympus long-distance LMPLFLN100x objective (Olympus, Tokyo, Japan). The laser power on the sample is adjustable down to 0.02 mW. The Raman band positions were calibrated before and after each series of measurements using the Si band of a semiconductor-grade silicon single-crystal. The run-to- run repeatability of the line position (based on 20 measurements each) is ±0.3 cm−1 for Si (520.4 ± 0.3 cm−1) and 0.4 cm−1 for diamond (1332.7 cm−1 ± 0.4 cm−1 over the range of 80–2000 cm−1). The FWHM = 4.26 ± 0.42 cm−1. FWHM is the Full-Width at Half Maximum. We also used a water-clear natural diamond crystal (Mining Academy Freiberg: 2453/37 from Brazil) as a diamond reference (for more information, see Thomas et al. 2022 [7] and 2023 [8]).

Results

Diamond in Cassiterite

During the microscopic study of the cassiterite sample Sn-23 from Zinnwald, we found (besides fluid inclusions) many spherical mineral inclusions. Often, these inclusions were, according to Raman spectroscopy, diamond and/or graphite. Figure 2 shows such typical inclusion (insert right above in Figure 1) and the accompanying Raman spectrum. Conspicuously is the Raman doublet at 1309 and 1514 cm−1, which is characteristically for a very 13C-rich diamond (see Blank et al. 2016) [9]).

Figure 2: Raman spectrum of lonsdaleite in pale-colored cassiterite (Sn-23). The photomicrograph shows the 13C-rich diamond crystal (30 µm deep) in the cassiterite matrix as well as 13C-rich graphite (G-band at about 1514 cm-1). The Raman spectrum was taken with 5.0 mW laser power on the sample (15 minutes exposure) – see Blank et al. 2016 [9].

Because this type of diamond and graphite is currently untypical, we have performed further Raman measurements. The results on 18 different diamond inclusions and the belonging graphite are in Table 1 compiled.

  1. See Methodology
  2. According to Gutierrez et 2014 [10] and Thomas et al. (2021) [11].
  3. Gr – graphite (about 73 µm deep)

Table 1: Results on diamond and graphite in the cassiterite (Sn-23) from Zinnwald and references.

Mineral

First-order Raman line (cm-1) FWHM

(cm-1)

n

(number of crystals)

13C-rich Diamond

1313.9 ± 6.1

59.4 ± 19.1

18

12C-rich Diamond1)

1332.7 ± 0.4

4.26 ± 0.42

20

13C-rich Graphite

1521.5 ± 8.5

70.0 ± 26.0

10

13C-rich Gr needle

1518.8 ± 1.1

39.3 ± 14.7

6

12C-rich Graphite2)

1581.5

3.5

13C-rich Graphite2)

1519.0

Besides the diamonds with a marked G-band at about 1522 cm−1, there are also diamonds without such a G-band (Figure 3).

Figure 3: 13C-rich diamond in cassiterite (Sn-23) from Zinnwald without graphite band. The Raman spectrum was taken with 1.0 mW laser power on the sample (15 minutes exposure).

Figure 4 shows a Raman spectrum of 13C-rich diamond with an outlined 13C-rich graphite G band at 1527 cm−1.

Figure 4: Raman spectrum of 13C-rich diamond in cassiterite (Sn-23) from Zinnwald (30 mW on sample). The Raman band at 1527 cm-1 is the G band from the 13C-rich graphite (see Gutierrez et al. (2014) [10]).

Figure 5 shows the relationship between the laser energy on the sample and the band position of the first-order diamond band. We see clearly that the values at the low energy (0.92 mW) represent the best values for the estimation of the 13C concentration. The data in Figure 5 shows a linear correlation: Band position = 1310.53 + 0.16871 * mW. The extrapolation to the lowest value of 0.92 mW results in a value of 1310.7 cm−1. According to Anthony and Banholzer (1992), the first-order Raman peak position has a 13C content of the diamond of about 50%. For a natural diamond that is very high, and if we assume that this diamond represents the quasi-frozen state from the deep, it follows, according to Schiferl et al. (1997) [12], a minimum pressure of about 7 GPa.

Figure 5: Correlation of the Raman shifts with the laser energy used on the sample

Orthorhombic Cassiterite Bearing 13C-rich Diamond

The relatively large cassiterite crystal aggregate (Figure 1) from Zinnwald/Erzgebirge/Germany, sample Sn-23, contains large parts of different orthorhombic cassiterites. Tetragonal cassiterite is not present or only in traces in the whole sample Sn-23. It is well known that the polymorphs of cassiterite can easily be transformed into another (Balakrishnan et al., 2022) [13]. Therefore, different polymorphs can be present side by side, which makes the differentiation difficult. Figure 6 is an example of a more tetragonal cassiterite (with dominant indications of the Pbcn-type: 75.0, 124.8, 245, and 472.6 cm−1). The strong Raman band at 75.0 cm−1 is untypical for tetragonal cassiterite (see Figure 5 in Thomas 2024b) [3].

Figure 6: Raman spectrum of light cassiterite from the edge of sample (Sn-23)

Figure 7 shows the Raman spectrum of more dark cassiterite from the center of the plate (Sn-23 from Zinnwald). The strong band at 75.0 cm−1 corresponds, according to Thomas 2024b, to a pressure of about 10.5 GPa.

Figure 7: Raman spectrum of dark cassiterite from the center of the crystal plate (Sn-23 from Zinnwald)

Figure 8: Raman spectrum of diamond in orthorhombic cassiterite from Ehrenfriedersdorf – sample Sn-70 (size 4 x 2 cm). The Raman band at 1284 cm-1 corresponds to an almost isotopic pure 13C diamond, which is according to Enkovich et al. 2016 at 1283.1 cm-1. The G-band is at 1519 cm-1.

The very strong Raman band 121.4 cm−1 (122.7 ± 1.02 cm−1; n = 6) results in a pressure of 21.9 GPa (see also Helwig et al. 2003 [14] and Thomas 2024b [3]). By the mixture of different parts of high-pressure and high-temperature SnO2 polymorphs of rutile-type→CaCl2– type pyrite-type ZrO2 orthorhombic phase I cotunnite- type (Balakrishnan et al. (2022) [13] and Shieh et al. (2006) [15]) demonstrate that high-pressure phases (CaCl2– and cotunnite-type) are essential pieces of evidence for the transport of this ore mineral from mantle depths to the crust region. The presence of 13C-rich diamonds in all parts of this Zinnwald cassiterite sample (Sn-23) supports this statement. Noteworthy is also the general presence of graphite and traces of Fe, Ta, Nb, Ti, Mn, Fe, and Zr (Betechtin, 1964) [16], which make the determination of the polymorphs of cassiterite a little bit difficult by the shift of the Raman bands.

Interpretation

The clear evidence of 13C-rich diamonds in orthorhombic cassiterite from Zinnwald demonstrates clearly that a lot of cassiterite or tin comes directly from the mantle range. The old genetic thinking about the origin of the Variscan tin deposits of the Erzgebirge/Germany alone from the surrounding granite is, therefore, questionable.

Up to now, we have found mainly 12C-rich diamonds in cassiterite (Thomas 2024a, 2024b – [2,3] and Thomas and Rericha 2025) – [17] from Ehrenfriedersdorf in the Central Erzgebirge/Germany, in the cotunnite-type cassiterite from Krupka (Krušné hory Mining District/ Czech Republic, and the Slavkovský les, North Bohemia (Czech Republic). Figures 2 and 4, as well as Table 1, clearly show that the diamond in the here-discussed case is 13C-rich because the typical G band of graphite lies at significantly lower values. That is also valid for the main crystal of cassiterite Sn-70 from Ehrenfriedersdorf in the central Erzgebirge.

Table 2 shows the measured data on the 13C-rich diamond in cassiterite from Ehrenfriedersdorf, Central Erzgebirge, Germany, as well as the data for isotope pure diamond and graphite according to Enkovich et al. (2016) – [18] and Gutierrez et al. (2014) – [10].

Table 2: Raman bands of 13C- and 12C-rich diamonds and graphite, according to Gutierrez et al. (2014) [10] and Enkovich et al. (2016) [18]. The values for the diamonds in cassiterite from the Sauberg mine near Ehrenfriedersdorf (Sn-70) are based on this work (6 crystals).

 

13C-rich

diamond

12C-rich

diamond

13C-rich

graphite

12C-rich

graphite

Pure 13C phase

1283.1 cm-1

1519 cm-1

Pure 12C phase

1332.7 cm-1  

1581 cm-1

Sn-70

1286.7 ± 6.5 cm-1

1318.8 ± 0.9 cm-1 1518.1 ± 0.8 cm-1

From a first approximation, according to Enkovich et al. (2016) [18], the 12C-richer cassiterite Sn-70 has a value of 12.6C (12.5C has an isotopically mixed 1:1 composition). The finding of clear proofs for 13C-rich diamond and graphite in cassiterite from Zinnwald forces the assumption of two different pulses of supercritical fluid (SCGF): the first one is in 12C enriched, and the second one is in 13C enriched. In the Sauberg mine near Ehrenfriedersdorf, we found diamonds in a cassiterite crystal that were very rich in 13C. However, the root zone of the same crystal dominates in 12C-rich diamonds (Thomas 2024a) [2].

Discussion

The presence of orthorhombic cassiterite up to the cotunnite polytype, as well as the frequent occurrence of 12C- and 13C-rich diamonds in different minerals, here in cassiterite, forces a re- thinking of the old genetic concept of the formation of the Variscan tin deposits in the Erzgebirge/Germany and the Krušné hory Mining District/Czech Republic. Furthermore, if so, other isotopes can also effectively be separated in supercritical fluids (SCGF). Also, another point is essential: with the widespread SCGFs in the whole Variscan Erzgebirge region, an enormous amount of water comes from the mantle into the crustal region.

Acknowledgment

For the samples, I thank Professor Ludwig Baumann (1929-2008) from the Mining Academy Freiberg, who initiated my interest in the genetic aspects of the Variscan tin deposits, too. Paul Davidson (Hobart, Tasmania) and Jim D. Webster (AMNH; New York) stimulated my critical thinking regarding supercritical fluids. The nearby daily discussion with Adolf Rericha (Falkensee) forced my intense Raman work.

References

  1. Breiter K (2014) 800 years of mining activity and 450 years of geological research in the Krušné Hory/Erzgebirge Mountains, Central Bol Mus Para Emilio Goeldi. Ciências Naturais 9: 105-134.
  2. Thomas R (2024a) The CaCl2-to-rutile phase transition in SnO2 from high to low pressure in nature. Geol Earth Mar Sci 6: 1-4.
  3. Thomas R (2024b) Rhomboedric cassiterite as inclusions in tetragonal cassiterite from Slavkovský les – North Bohemia (Czech Republic). Geol Earth Mar Sci 6: 1-6.
  4. Schütze H, Stiehl G, Wetzel K, Beuge P, Haberland R, et al. (1983) Isotopen- und elementgeochemische sowie radiogeochronologische Aussagen zur Herkunft des Ehrenfriedersdorfer Granits. – Ableitung erster Modellvorstellungen. ZFI- 76: 232-254.
  5. Ni H, Xiao Y, Xiong X, Liu X, Gao C, et al. (2024) Formation and evolution of supercritical Science China Earth Sciences. 67: 1-13.
  6. Thomas R (1982) Ergebnisse der thermobarometrischen Untersuchungen an Flussigkeitseinschlussen in Mineralen der postmagmatischen Zinn-Wolfram- Mineralisation des Erzgebirges. Freiberger Forschungshefte C370, Pg: 85.
  7. Thomas R, Davidson P, Rericha A, Recknagel U (2022) Water-rich coesite in prismatine-granulite fromWaldheim/Saxony. Veröffentlichungen Naturkunde Chemnitz. 45: 67-s80.
  8. Thomas R, Davidson P, Rericha A, Recknagel U [2023] Mineral inclusions in a crustal granite: Evidence for a novel transcrustal transport mechanism. Geosciences. 13.
  9. Blank VD, Kulnitsky BA, Rerezhogin IA, Tyukalova EV, Denisov VN, et (2016) Graphite-to-diamond (13C) direct transition in a diamond anvil high-pressure cell. Int. J. Nanotechnol. 13: 604-611.
  10. Gutierrez G, Le Normand F, Aweke F, Muller D, Speisser C, et al. (2014) Mechanism of thin layers graphite formation by 13C implantation and Appl Sci. 4: 180-194.
  11. Thomas R, Rericha A, Davidson P, Beurlen H (2021) An unusual paragenesis of diamond, graphite, and calcite: A Raman spectroscopic Estudos Geológicos 31: 3-15.
  12. Schiferl D, Malcolm N, Zaug JM, Sharma SK, Cooney TF, et (1997) The diamond 13C/12C isotope Raman pressure sensor system for high-temperature/pressure diamond-anvil cells with reactive samples. J. Appl Phys 82: 3256-3265.
  13. Balakrishnan K, Veerapandy V, Fjellvag H, Vajeeston P (2022) First-principles exploration into the physical and chemical properties of certain newly identified SnO2 ACS Publ. 7: 10382-10393.
  14. Hellwig H, Goncharov AF, Gregoryanz E, Mao H, Hemley RJ (2003) Brillouin and Raman spectroscopy of the ferroelastic rutile-to CaCl2 transition in SnO2 at high Physical Review B 67: 174110-1174110-7.
  15. Shieh SR, Kubo A, Duffy TS, Prakapenka VB, Shen G (2006) High-pressure phases in SnO2 to 117 Phys. Rev. B 73: 014105-1–014105-7.
  16. Betechtin AG (1964) Lehrbuch der speziellen VEB Deutscher Verlag für Grundstoffindustrie, Leipzig, PG: 679.
  17. Thomas R, Rericha A (2025) Extreme element enrichment by the interaction of supercritical fluids from the mantle with crustal rocks. Minerals. 15: 1-10.
  18. Enkovich PV, Brazhkin VV, Lyapin SG, Novikov AP, Kanada H, et (2016) Raman spectroscopy of isotopically pure (12C, 13C) and isotopically mixed (12.5C) diamond single crystals at ultrahigh pressures. Journal of Experimental and Theoretical Physics. 123: 443-451.

Interpretation of the Lorentzian Distribution of Tin in the Variscan Ehrenfriedersdorf Deposit/Germany

DOI: 10.31038/GEMS.2025712

Abstract

The Lorendian distribution, also known as the Cauchy distribution, is commonly used in statistical physics and geostatistics to describe here the distribution of some aspects of elements. When applied to the study of tin in the Ehrenfriedersdorf deposit, the Lorendian distribution provides valuable insights into the spatial distribution and concentration patterns of tin within this historic mining area. Furthermore, the Lorendian distribution shows that Sn is extraordinarily soluble and concentrated in the fluid/melt on the critical point corresponding to 25.7% H2O of the pegmatite solvus curve (T vs. H2O in the melt) and in the immediate vicinity of this point, determined by maximal concentration Ic at the critical point xc and the width (half width at half maximum (HWHM) of the curve in the melt-H2O system). The strong Lorendian relationship between Sn and water and especially the strong relationship to the critical point (C.P.) of the silicate melt shows convincing that Sn is related to the supercritical fluid coming from mantle depth, also instigated by the occurrence of diamond, lonsdaleite, 13C-rich graphite, and orthorhombic cassiterite, e.g., as cotunnite-type cassiterite. We also show that other elements (Be, B, P, Cl, Zn, As, Cs, Sn, Ta, and W) have similar behavior in water-rich silicate melt systems.

Keywords

Lorentzian curve, Sn distribution, Solvus curve, Rb and Cs enrichment, Sauberg mine, Ehrenfriedersdorf/Germany

Background

The origin of tin deposits and the nature of the Sn transport in the past are often discussed controversially (e.g., Kosals 1976 [1], Liu et al. 2020 [2]). Before Liu et al. (2020) [2], the discussion was mostly restricted to the solubility of SnO2 in water-rich solutions up to 400°C. Ehrenfriedersdorf, located in the Central Erzgebirge region of Germany, has a rich history of tin mining dating back to the medieval period [3]. The deposits around them have very complex geology and mineralization patterns, which make them an ideal candidate for applying advanced analytical and statistical methods such as the Lorentzian distribution to analyze their tin content and its origin. The surrounding granite was discussed, in the past, exclusively as the source of Sn (primarily cassiterite). At the beginning of the intensive analytical study of melt inclusions in granite and pegmatite quartz from the Ehrenfriedersdorf, starting in 1995 [4], we often observed high runaway trace element data that could not interpreted. With time, the amount of such runaway data increases significantly. A correlation with other elements was not possible at that time [5]. Beginning with the determination of water in glasses and melt inclusions (Thomas, 2000) [6], the situation improved from year to year (see also Thomas 2024a) [7]. It appears fast that many main and trace elements in melt inclusions show strong correlations with the water in them. Thomas et al. (2019 and 2022) – [8,9] showed that many elements correlate with water of the melt inclusions according to Gaussian and manly Lorentzian curves. Furthermore, it was revealed that often, the critical point (C.P.) of the solvus curves (correlation of the water concentration in the silicate melt and the homogenization temperature) and the sharp peak of the Lorentzian curve coincide. The connection between the solvus curve and the Lorentzian curve is illustrated by Thomas and Rericha (2024a) [10] in Figure 2b in there.

Characteristics of the Lorentzian Distribution for Tin

The Lorentzian curve (according to Hendrik Antoon Lorentz (1853-1928), a Dutch physicist) is a mathematical function that describes a peak (here the maximal Sn concentration in ppm) centered at a specific position (here the critical water concentration (25.7 %) in the silicate melt) and is characterized by w, which is the half-width at half maximum (HWHM).

The Lorentzian curve is, in our case:

I(x) = Ic * (w/2)2/((x-xc)2 + (w/2)2)                                 (1)

With:

I(x) height of the Sn concentration (ppm) at the water concentration x (%),

Ic     maximal concentration of the Sn (ppm) at xc (center), identical with the C.P. of the complete system,

w    width is the half-width at the half-maximum (HWHM). x water concentration (%),

xc    water concentration (%) at the critical point (solvus and Lorentzian curves),

y0 offset is the shift of the curve from its original position along the y-axis), which is the Clarke value for Sn (3 ppm according to Rösler and Lange, 1975 [11],

A area – is the result of integrating the Lorentzian curve over all values of x,

R2     correlation coefficient.

The following Figure 1 shows the typical form of the Lorentzian distribution of tin (in ppm) versus water concentration (in %) in melt inclusions from the pegmatite system in the Sauberg tin deposit near Ehrenfriedersdorf. For the Lorentzian fitting, we used the Origin 6.1 program. As we can see from Table 1, using equation (1), the calculated Lorentzian curve is identical.

Figure 1: Tin distribution in melt inclusions in quartz from the granite-pegmatite system (Sauberg mine near Ehrenfriedersdorf). The maximal Sn concentration is 16300 ppm at a water concentration of 25.7%.

Figure 1 shows the Lorentzian distribution of Sn vs. H2O, and in Table 1 are the resulting data summarized. The center (25.7 % H2O) is the position of the peak’s center, which corresponds to the critical point of the solvus curve and the maximum (height) of the Sn concentration (here, 16400 ppm Sn). Width is the half-width at half-maximum (HWHM). The offset refers to the displacement of the Lorentzian curve from its original position along the x-axis (H2O concentration) corresponding to 644 ppm.

Table 1: Lorentzian fit of Sn, determined in silicate melt inclusions from the pegmatite system of the Sauberg mine near Ehrenfriedersdorf (46 measuring points). Each point is the mean of 5 to 10 single measurements. The values in the second data row are calculated using Equation 1.

Area Center Width Offset Height R2
  A xc w yo

Io

 
Measured

57799 ppm2

25.7% H2O 2.3% H2O 644 ppm Sn 16295 ppm Sn

0.9843

Calculated

58871 ppm2

25.7% H2O 2.3% H2O (603 ppm Sn) 16295 ppm Sn

1.0000

The offset of the calculated data is, of course, zero – the value of 603 ppm Sn results from the average difference between measured and calculated Sn values. By the way, equation (1) of the Lorentzian curve can be advantageously used for the analyses of analytically determined outlayers. The offset for the calculated case is zero. However, the difference between measured and calculated Lorentzian curves results in a value of 603 ppm Sn. The error (standard deviation) of the offset is ± 348 ppm Sn and results mainly from the values at the tails. The offset represents the concentration of Sn in the surrounding rocks, introduced by the supercritical fluids/melts.

Interpretation of the Results

The application of the Lorentzian distribution to the analytically determined tin and water concentrations in the Ehrenfriedersdorf deposit reveals a significant clustering of tin-rich zones. The location parameter “center” indicates the central area of the highest Sn concentration of 16300 ppm and corresponds with the solvus crest (C.P.) of the water-silicate system, which lies for Sn at 25.7 % H2O in the silicate melt. The low value for the C.P. of the solvus is beside the water content in the melt, the result of the sum of further compounds (Be, B, F, P, rare alkalis, and others) in the volatile-rich melt. The position of the critical point varies a little bit by the variation of the critical elements and compounds. For Be, BO3, PO4, Cl, Zn, As, Cs, Sn, Ta, and WO4, the result from 355 measurements for the critical point lies at 26.9 ± 1.30 % H2O in the silicate melt (see Table 2 and Thomas et al. 2022 [9], and Thomas and Rericha 2023) [12]. Besides H2O, B, rare alkalis (Rb, Cs), and P, fluorine likewise has a determining meaning for the position of the solvus crest as well as the maximum of the Gaussian and Lorentzian curves in the granite-pegmatite system in the Ehrenfriedersdorf district.

Table 2: Lorentzian fit of elements and compounds, determined in silicate melt inclusions from the pegmatite system of the Sauberg mine near Ehrenfriedersdorf. Each point (n) is the mean of 5 to 10 single measurements. For the calculation, we used the Origin 6.1 program. The units are in Table 1.

Element/Compound

Area Center Width Offset Height

n

Be

131560

26.0 8.88 284 11810

14

BO3

153500

25.5 7.67 0 12730

23

PO4

1331000

28.5 7.49 13001 13100

29

Cl

147040

27.2 4.98 902 18782

63

Zn

208400

27.0 5.78 0 22950

9

As

46433

30.2 3.19 521 9266

20

Cs

266000

26.0 5.63 1300 30000

18

Cs1)

25082

26.0 5.31 1340 30060

119

Sn

59124

25.7 2.30 704 16414

35

Ta

50148

27.4 9.87 86 3236

18

WO4

73258

26.8 7.41 303 6292

7

Average  

26.9 ± 1.3

     

Sum 355

Cs in granite from Ehrenfriedersdorf; n – the sum of measurements.

In contrast, the scale parameter “width” (2.3 % water for Sn) provides information on the spread and extent of these high- concentration zones related to the C.P. and the influx of the supercritical fluid at this point. The “offset” is the shift in direction y (Sn-concentration) of the Lorentzian curve from the original position along the x-axis (water concentration). The value of the offset (644 ppm Sn) interprets we as the minimum enrichment of Sn against the value of tin in the surrounding Sn-poor granite system, which is, according to Hösel (1994) [13], ≤ 200 ppm Sn (as a result of redistribution and ore deposit formation. The “height” represents the solved maximal Sn concentration in the supercritical fluids (SCGF). Note that the SCGF also carries solid minerals like orthorhombic cassiterite, diamond, and graphite. The interpretation of the “area” is a bit difficult. The area under the Lorentzian curve represents, in our case, the total concentration of Sn, here 57799 ppm2 in the studied granite-pegmatite system. If we take the Clarke value of Sn for granites, which is three ppm (Rösler and Lange, 1975) [11], then we have an exceptional enrichment of tin in the considered granite-pegmatite system of nearby 20.000 fold. That is remarkably high. Alone, the Sn concentration comes directly with a supercritical fluid, which is about the 5500-fold amount of the Clarke number, is dramatically high. The regular presence of carbon (as C, CO2, CH4 ) in the SCGF shows plausibly that the Sn transport occurs as Sn2+, probably as hydroxocomplexes like ([Sn(OH)x]n-) or as Sn4+ in more complicated compounds as (Na, K)[Sn(OH, Cl, F)3CO3] (Kosals, 1976). Rb and Cs can take the place of Na and K (see Thomas and Rericha, 2023) [14]. Cs increase the number of the H2O molecules in the surrounding OH shell (Pietsch, 1938) [15] up to 13. It is necessary to stress that SCGFs show very different solvency caused by density- dependent solubility, enormously changed polarizability, strongly increased diffusion rates and reactivity, and extremely low viscosity.

One point is here also important: if, for example, one element is in two compounds with different anions present, then the formation of overlapping Lorentzian curves with different xc values is possible (see Figure 3 in Thomas and Rericha, 2024b) [16,17]: the distribution of Be in two distinct species, beryllonite versus hambergite with xc1 at 25.5 % H2O and xc2 at 31.0 % H2O. From the Lorentzian curve type for some elements, it follows clearly that their solubility is not directly related to the water concentration in the melt. The highest solubility is clearly associated with the H2O concentration, representing the critical point (C.P.). At this point, the melt inclusion-bearing quartz grows very fast and traps “samples” of the surrounding medium as melt inclusions. Through fast processes, the boundary layer composition changes steadily (fast diffusion in a low viscous SCGF). Therefore, the composition of the single melt inclusions changes too (see, e.g., Borisova et al., 2012 [18], Table 2 in them, representing two different melt inclusions lying together in one growth zone). Lorentzian distributions of elements are not only water-rich silicate melt-related. Another example is the relationship of Cs, Rb, and B in the Ehrenfriedersdorf granite. Figure 2 shows such a plot. As Table 3 shows, the concentration of the rare alkalis Rb and Cs is very high in granite from the Sauberg mine near Ehrenfriedersdorf.

Table 3 shows the data for this passable Lorentzian plot and demonstrates that B- Rb and Cs-rich melt fractions are generated and penetrate the present granite rock. An exact interpretation of this remarkable plot (Figure 2) is, at the moment, not possible. More analytical, microscopical, and Raman work is necessary.

Figure 2: Lorentzian distribution of Cs versus boron obtained from melt inclusions in granite quartz from the Sauberg mine near Ehrenfriedersdorf.

Table 3: Cs and (Rb + Cs) distribution in melt inclusions in quartz from the granite- system (Sauberg mine near Ehrenfriedersdorf). The maximal Cs and Rb + Cs concentrations are 58477 and 65756 ppm (sum = 12.4%) at a boron concentration of 2.26%.

Measured

Area Center Width Offset Height

R2

 

A

xc w yo

Io

 
Cs-B

53529 ppm2

2.26% B2O3 0.58% B2O3 13113 ppm Cs 58477 ppm Cs 0.928

Cs+Rb-B

62463 ppm2 2.26% B2O3 0.60% B2O3 23854 ppm Rb + Cs 65756 ppm Rb + Cs

0.905

Rb gives no Lorentzian distribution with B2O3 – therefore, the low R2 value using the sum of Rb and Cs.

Alone from the small number of examples, we see that the geochemistry of the Variscan Sauberg mine is highly complex. The standard correlation of elements gives no satisfactory answers to the complex processes working at the formation of this tin deposit (see Author Collective, 1963) [19]. Regardless of the input of SCGF, the genetic origin of this tin deposit is not solvable. Primary the tin mineralization in Ehrenfriedersdorf is not uniformly distributed but instead concentrated in specific geological structures, here pegmatites or pegmatite-like bodies, influenced or generated by supercritical fluids or melts (in short, geofluids (SCGF)). The classic idea of the hydrothermal origin of cassiterite is now untenable. The sharp Lorentzian peak related to the critical point of the solvus curve is a strong hint of the impact of supercritical fluids coming from mantle deeps (with temperatures >1000°C). This idea is supported by orthorhombic polymorphs of cassiterite (e.g., the cotunnite-type cassiterite inclusions in cassiterite crystallized at a pressure of about 10 – 40 GPa (Thomas 2025) [20]. Note, however, that orthorhombic cassiterite is metastable at low pressures. The transition into tetragonal cassiterite is mostly irreversible by kinetic barriers. Such a barrier may be the “shock-like” transition from the supercritical to the under- critical state. The occurrence of orthorhombic cassiterite is supported by the occurrence of diamond, lonsdaleite, and graphite inclusions with extreme isotope composition: 13C-rich diamond and graphite versus 12C-rich ones. The SCGFs are excellent media for the potent and selective separation of isotopes (e.g., 12C/13C or H/D by diffusion effects and solubility differences (see Thomas 2024b [16,17], 2025 [20] and Thomas and Rericha 2024a) [10].

Implications for Mining and Exploration

Understanding the Lorentzian distribution of tin in the Sauberg deposit has practical implications for mining and exploration in the whole Variscan Erzgebirge/Krušnohořy region. By identifying the central and peripheral zones of tin concentration, mining operations are optimizable to target the most economically viable areas. That can lead to more efficient extraction processes and reduced operational costs. The highest Sn concentration is related to rock parties rich in pegmatites or pegmatite-like bodies (see Schröcke, 1954) [21]. Furthermore, the substantial input of Sn by SCGF changed the old ideas of the dominance of tin granites for the generation of workable deposits. The high level of tin in the granites in question is the result of the interaction between SCGF and the granites. The high water and Sn content at the critical point (C.P.) favor the formation of pegmatites and pegmatite-like structures with this element and others (see above). It is quite conceivable that under the famous Pb-Zn deposit of the Freiberg mining district (Rösler et al. 1968) [22] is a large tin deposit. Hints are REE-rich fluorite globules like that from Zinnwald (Thomas 2024c) [23] in yellow low-temperature fluorite from Halsbrücke near Freiberg and the reverse of very high concentration of Pb (1790 ppm) [as cotunnite], Zn (85120 ppm) [as (K, Pb, Cs)2 Zn(Cl, Br)4] and Ag (100 ppm) [as chlor-, brom- and iodargrite] in high-temperature fluid inclusions in quartz of the Sauberg mine (see Boriosova et al. 2012 [18] and Thomas et al., 2019 [8]). The Clarke values for Pb, Zn, and Ag are, according to Rösler and Lange (1975) [11], 20, 40, and 0.05 ppm, respectively [24].

That interpretation results from the Lorentzian distribution, which offers insights into the geological processes that led to the formation of the tin deposits. The distribution pattern may reflect the influence of SCGF, their way from the mantle into the crustal regions, which later formed fault structures and other geological factors that concentrated tin in specific areas over geological periods via hydrothermal re- deposition and crystallization as cassiterite. Tin is highly soluble in SCGFs, as we can see from their Lorentzian distribution. However, an essential part of tin comes from mantle depths (10 – 40 GPa) as solid phases like the cotunnite polymorph of cassiterite. It is well- known that the high-pressure and high-temperature polymorphs of cassiterite, e.g., orthorhombic phases, are formed at 10 – 40 GPa or higher. Typically, they transform back to tetragonal cassiterite upon decompression. As we see in many examples (Thomas, 2025 [25] and Thomas and Rericha, 2023 [12,14]), this process can be inhibited by fast cooling, particularly by the transition from the supercritical to the critical and under-critical state outwit.

Conclusion

The Sauberg tin deposit provides a robust framework for understanding the spatial variability and clustering of tin mineralization. The insights gained from this statistical approach can inform both current mining practices and future exploration efforts, ultimately contributing to the efficient and sustainable exploitation of this valuable resource (at the moment, this is an abandoned mining district). However, we can learn a lot from the two-dimensional element distribution (elements versus water concentration. The distribution of the trace elements in melt inclusions in granites and pegmatites in relationship with the water content of the same inclusions shows clearly Lorentzian curves with the maximum concentration at the critical point of the solvus and that of the Lorentzian curves. These results give robust hints for the origin of Sn and other elements via supercritical fluids (SCGF). A critical rethinking of the origin of this and other analog mineral deposits is necessary.

Acknowledgment

The Author thanks the members of the working group, which builds up for the first time a usable measuring chamber at DESY for the study of micrometer-large fluid and melt inclusions in a quartz matrix. Besides the Author, the following scientists belong to this group: Prof. A. Knöchel (DESY Hamburg), Dr. J. Walter, Prof. Althaus (both from Karlsruhe), Dr. M. Haller, Dr. M. Radtke (both from DESY Hamburg), Dr. W. Klemm, TU Bergakademie Freiberg. Thanks also go to Dr. D. Rhede (GFZ Potsdam) for the longstanding cooperation in the microprobe analysis of melt inclusions and to Dr. J.D. Webster (AMNH New York) for performing the SIMS analyses.

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Sinai… The land of Turquoise – Egypt’s Strategic Stock of Mineral Wealth

DOI: 10.31038/GEMS.2025711

 

Let us first emphasize some important facts about the mining and mineral resources sector in Egypt:

  1. Despite the great potential of the mineral wealth sector in Egypt and the spread of many mineral ores in most Egyptian deserts and in large proportions, this sector does not participate in the national product except by a very small percentage represensing not more than 1% in the country’s national product.
  2. Experts and specialists emphasize that mineral wealth represents the third side in building the economies of countries along with agriculture and industry, and from here it is necessary to exploit these resources optimally, according to procedures and measures to activate research and exploration operations, and use the best ways to extract and exploit them in an economic manner.

Sinai Peninsula is a triangle-shaped peninsula located in Egypt that has an area of about 60,000 square kilometers between the Mediterranean Sea (to the north) and Red Sea (to the south). Its land borders are the Suez Canal to the west and the Palestine-Egyptian border to the northeast. The Sinai Peninsula is in Southwest Asia while the rest of Egypt is in North Africa (Figure 1).

Figure 1: Location Map of Sinai Peninsula in the Arab Republic of Egypt

The Sinai Peninsula in the Arab Republic of Egypt is the crossroads of continents and the land of turquoise and the incubator of the most beautiful natural reserves on the planet not only that, God has blessed it with many mineral riches represented in many mineral ores, whether industrial such as cement industry raw materials (limestone, shale, gypsum, iron oxides, sand and gravel), ceramic industry raw materials (feldspar, albyte and kaolin) and ornamental stones (marble and granite) as well as metal ores that are involved in advanced technological industries (copper, lead, zinc, tungsten, molybdenum and manganese) and recently discovered in Sinai some of the precious metals (gold and silver). Sinai is famous for the presence of energy raw materials other than oil, which is coal ore, which is found in many areas, especially the G. Al-Maghara area in North Sinai, as well as the areas of Badaa and Thawra near the Abu Zenima area.

There are also a number of natural salts on the northern coasts of Sinai near the El-Arish City, which produce large quantities of table salt and other industrial salts. The Sinai Peninsula also contains the largest reserves of ultra-pure white sand, which is used in many important industries.

Based on the interest in the reconstruction of Sinai, it was necessary to draw attention to pay attention to its mineral resources and its many treasures and attract investment and reconstruction opportunities to it, so many geological, geophysical and mineralogical studies have tended to discover these mineral resources that can be developed and estimate the reserves of them and the work of many feasibility studies to exploit them optimally.

In this article, the researcher tries to shed light on the most important mineral wealth spread in the Sinai Peninsula in terms of their type and quantities, in order to direct decision-makers and those wishing to invest in the mining sector to the most important mining projects that can be established in the land of Sinai, which helps the emergence of new communities, provide job opportunities and increase the national income of the country.

Among the most important hidden mineral riches in the Sinai Peninsula are:

Turquoise

It is the most famous mineral of the Sinai Peninsula, and is found in the mountains of Wadi Al-Maghara and Sarabit in the city of Al-Tur, and was the first to think about mining turquoise in the last century, Major MacDonald, a retired English officer, in Wadi Al-Maghara in 1854 and built him a house at the foot of a hill inhabited by old miners, and he lived his wife there for five years in collecting the metal, but he did not achieve the success he begged for and died in 1870.

Oil

Petroleum is the most important mineral resource in Sinai. There are many oil fields, including the Gulf of Suez, Belayim, Assal and Abo Rdis, and the region’s reserves are estimated at about 237 million barrels of crude oil and natural gases.

White Sand

White sand is found in the Sinai Peninsula in the area of G. Abu Hittat – Paradise Plateau on the Nuweiba – Saint Catherine road and the Abu Zenima area with a total reserve of up to (155 million cubic meters or 330 million tons) of ultra-pure sand. These sands are involved in many important industries, including: luxury glass types – tableware – white glass – transparent packaging – optical glass – crystal – colored glass and others.

Ornamental Stones

Ornamental stones, especially granite of various kinds, are spread in the areas of Saint Catherine and Nubia, while marble of sedimentary origin and consisting of hard limestone rocks is found in the areas of Al-Hassana in central Sinai and these raw materials are used for many purposes, including: decorating buildings and facilities – floors – stairs – the manufacture of antiques and statues.

Kaolin

It is one of the distinctive raw materials in Sinai and is located on Nuweiba – Saint Catherine road and the proven reserves of it are estimated at about 15 million tons, as well as the Abu Zenima area, and the reserves are estimated at about 80 million tons and kaolin ores are used in many industries such as: ceramics and Chinese – white cement – medical industries – plastic – refractory bricks and refractories – sanitary ware.

Limestone

It is found in G. Labani, G. Al-Halal, Raysan Unaizah, G. Al-Maghara and G. Al-Jifjafa and is used in the manufacture of cement, chemical industries, fertilizers, paints and in construction and road construction.

Dolomites

It is found around the edges of G. Al-Maghara and G. Al-Halal and is used in construction, road construction and protection of port docks and has many uses, the most important of which are: the production of aggregates necessary for road paving and reinforced concrete, agriculture to improve the soil and restore its acid balance, cement industry, refractories for lining furnaces and molds used in steel production.

Coal deposits

Coal deposits are located in Sinai in G.Al-Maghara area and the proven reserves of it in G. Al-Maghara are 27 million tons, of which about 21 million tons can be mined, and there is also located in Abu Zenima and Oyoun Moussa areas, and the proven reserve has been estimated at about 18.5 million tons, it is used as fuel for power plants and cement factories.

The Carbon Baby

They are natural deposits containing carbon-coal materials, found east of Abu Zenima, and used as fuel in power plants and cement manufacturing. Its reserves are about 75 million tones per square kilometer.

Manganese Deposits

Manganese ores are found in South Sinai in the Um Bojmeh area, and appear as lenses associated with dolomite limestone rocks in the Middle Carboniferous Age, and this area has reserves of about 3 million tons, and is currently exploited by the wholly-owned Sinai Manganese Company, which replaced the British Sinai Company more than 66 years ago. There are also deposits of manganese ore in the Sharm el-Sheikh area of South Sinai, associated with iron ore, and the percentage of manganese in this area is about 45%, and this area is considered to have an estimated reserve of about 30 thousand tons, according to information documented by the Mineral Resources Authority. It is used in many important industries such as: pharmaceutical industries – battery industry – aluminum – bronze.

Lead, Zinc, Silver and Gold

Lead, zinc, silver and gold spread in the Sinai Peninsula in the area of Um Zureik and Al-Kid near the city of Dahab, it has been discovered high concentrations of lead and zinc in the area of Um Zureik west of the Gulf of Aqaba and about 45 km from the city of Sharm el-Sheikh . These concentrations exist in the form of ranges in sedimentary rocks and concentrations range from 1% to more than 12% for lead and from 1% to 8% for zinc . This has been monitored these concentrations superficially and in depth where monitoring it at a depth of 79 m in the form of a carrier layer and the results showed the presence of galena metal by between 1-3% and the main zinc mineral, which is sphalerite by between 1-8% with the monitoring of other high concentrations of silver (3000 ppm). There are also some studies that refer to the discovery of gold ore in the vicinity of sedimentary rocks near the Abu Zenima area, as well as some areas in the city of Taba.

Copper

The Sinai Peninsula is famous for the presence of copper ore, which has been exploited since the era of the pharaohs, and the most important areas that contain ore are the Samra area near the city of Dahab, Al-Ruqaita near Saint Catherine, and the monument and Sarabid Al-Khadem near the city of Abu Zenima. Copper is used in many important economic industries as well as in many alloys and in the manufacture of paints.

Sulphur

Sulfur and pyrite ores are among the raw materials that are used in many industries, especially the fertilizer industry, and sulfur ore is found in two areas, the first in north El-Arish, which is of sedimentary origin, and the second region, which is the Mount Ferrani area in South Sinai, where sulphur is present in the form of pyrite ore in large quantities.

Feldspar

It is located in South Sinai and is used in many important industries such as: glass industry – ceramics – toothpaste – sandpaper materials – borsillin – paint and polishing materials.

Black sand

The beaches of the city of El-Arish abound and contain a lot of heavy and important metals such as magnetite, illuminate, rutile, zircon and are used in many important iron industries such as the manufacture of paints – alloys dyes – textiles – paper – leather – glass and refractory bricks.

Gypsum Deposits

Gypsum deposits are located in the Ras Al-Malab area and Wadi Al-Seih in South Sinai and are used in many industries, the most important of which are: the manufacture of fertilizers – cement and other construction purposes.

Shale Sediments

Shale deposits are widely spread in the area of Abu Zenima, the area of Wadi Firan, the area of Al-Tur and the area of Oyoun Musa. It is used in many industries, including: ceramic industry – as a filter material – brick industry – cement industry – drilling fluids – refractories industry – cosmetics and some pharmaceutical preparations.

Sand and Gravel Deposits

Sand and gravel deposits are spread in various places in the Sinai Peninsula and these deposits are included in many purposes such as: the manufacture of building and construction materials and as filter agents in water purification plants.

Salt

Sodium chloride (table salt) is found around Lake Bardawil in the form of salts and is used in the production of table salt, food industries, chemical industries and drilling oil wells. The most recent use of salt is the use of rock salt mines as a safe place for burying nuclear waste.

Bentonite

It has economic importance in the drilling of oil and groundwater wells, and is located between the areas of Oyoun Moussa and Ras Sidr. Reserves are estimated at hundreds of millions of tons.

Groundwater

North Sinai Governorate enjoys a huge reserve of groundwater in a group of deep aquifers, which opens up investment opportunities in the agricultural and industrial fields and the subsequent reconstruction and other economic activities.

By reviewing the wealth of the Sinai Peninsula, it becomes clear to us the importance of benefiting from these riches from the establishment of industrial projects that increase the value of these raw materials, which absorb a lot of labor and establish new urban communities aimed at reconstructing Sinai and increasing its effectiveness in supporting national income, especially with the presence of various energy sources, road network, ports and other elements of infrastructure.

Treacher Collins Syndrome Type II with Cleft Palate: A Case Report

DOI: 10.31038/JDMR.2024723

Abstract

Treacher Collins syndrome (TCS) is a rare congenital craniofacial dysplasia characterized by malformations of the jaw, eyes, and ears, with an incidence of approximately 1 in 50000.This study reported a case of a 4-year-old male TCS patient presenting with cleft palate. The patient exhibited facial asymmetry, flat zygomatic bone and zygomatic arch, mandibular hypoplasia, and eye and ear abnormalities. Genetic testing confirmed a POLR1 D gene mutation, leading to a diagnosis of TCS type II. The patient underwent cleft palate repair surgery and demonstrated significant recovery postoperatively. Follow-up evaluations showed significant improvement in speech and palatal function. The diagnosis of TCS relies on clinical manifestations, imaging examinations, and genetic testing. Effective treatment necessitates multidisciplinary collaboration, encompassing craniofacial reconstruction, hearing enhancement, and speech therapy. A comprehensive treatment plan should be tailored to the patient’s age and severity of deformities to address the physiological function and psychological needs. Future efforts should focus on enhancing the application of molecular genetics in the diagnosis and treatment of TCS to improve prenatal diagnostic capabilities.

Keywords

Treacher Collins syndrome, Cleft palate

Introduction

Treacher Collins syndrome (TCS) is a rare congenital craniofacial dysplasia characterized by malformations of the jaw, eyes, and ears, with an incidence of approximately 1 in 50000 [1]. First reported by Edward Treacher Collins in 1900 [2], the syndrome can be classified into four clinical subtypes. Its primary clinical features include blepharophimosis, zygomatic dysplasia, conductive deafness, and mandibular dysplasia or micrognathia, with cleft palate cases being particularly rare [3,4]. This paper presents a case of a TCS patient with cleft palate, detailing the symptoms, diagnosis, treatment process, and follow-up results to provide a reference for clinicians in the diagnosis and treatment of this condition.

Case Report

A 4-year-old male patient was identified with facial deformity and cleft palate at birth. Examination revealed facial asymmetric, flat bilateral zygoma and zygomatic arch, a short mandibular ramus, wide orbital spacing, oblique palpebral fissures, absence of the lower eyelid, and missing lower eyelid eyelashes (Figure 1). The patient also exhibited bilateral auricle deformity, external auditory canal atresia with preauricular fistula (Figure 2), and a cleft palate extending from the uvula to the incisive foramen, with a maximum width of 2.5 centimeters (Figure 3). Hearing tests indicated moderate conductive hearing loss in both ears. Genetic analysis identified a heterozygous spontaneous mutation in the POLR1 D gene, leading to a diagnosis of TCS type II. The patient’s speech was unclear due to the cleft palate. Upon admission, the patient underwent cleft palate repair surgery under general anesthesia with tracheal intubation. Postoperative recovery was successful (Figure 4), and voice training commenced three months post-surgery. Follow-up evaluations at 6 months, 12 months, and 24 months post-operation showed well-recovered palate morphology, normal soft palate movement, significantly improved pronunciation, and no coughing during meals.

Figure 1: Facial asymmetric, flat bilateral zygoma and zygomatic arch, a short mandibular ramus, wide orbital spacing, oblique palpebral fissures, absence of the lower eyelid, and missing lower eyelid eyelashes.

Figure 2: Bilateral auricle deformity, external auditory canal atresia with preauricular fistula.

Figure 3: A cleft palate extending from the uvula to the incisive foramen, with a maximum width of 2.5 cm.

Figure 4: The palate healed well

Discussion

TCS is a rare craniofacial malformation with autosomal dominant inheritance, also known as maxillofacial dysplasia and deafness syndrome. It presents a highly variable phenotype, with about 40% of patients having a family history [3]. The cause of TCS is attributed to disrupted ribosome synthesis in cranial neural crest cells and neuroepithelial cells between the 2nd and 8th weeks of embryonic development. This disruption leads to a reduction in the number of neural crest cells migrating to the craniofacial region, resulting in hypoplasia of the first and second branchial arches [5].

TCS can present with various clinical types. According to studies by Splendor (2000), Teber (2004), and Vincent [6-8], the clinical features of TCS patients can be summarized as follows: (1) Craniofacial abnormalities: These include facial asymmetry, a low hairline, and facial hypoplasia, particularly affecting the mandibular and zygomatic complex. (2) Eye abnormalities: These are characterized by oblique palpebral fissures and lower eyelid defects. (3) Ear abnormalities: These include atresia of the external auditory canal, microtia, and conductive hearing loss, contributing to a characteristic ‘fish-like ‘ facial appearance. (4) Other rare clinical features: Dental abnormalities such as missing teeth (tooth dysplasia), tooth discoloration (enamel opacity), excessive tooth spacing, abnormal permanent teeth (eg, ectopic maxillary first molars), and occlusal disorders. Palatal abnormalities such as high-arched palate and cleft palate. Respiratory and feeding difficulties may arise from posterior nostril stenosis or atresia. Cardiac malformations are also possible in some cases [9,10]. Patients with a mild phenotype of TCS may exhibit almost no obvious clinical features and may require genetic testing for identification. Conversely, those with a severe phenotype may experience life-threatening ventilatory disorders due to obstruction of the posterior nasal foramen, glossoptosis, and other complications [11].

The clinical diagnosis of TCS is primarily based on clinical manifestations, imaging examinations, and pathogenic gene detection. X-ray imaging typically reveals several characteristic features: increased density of small mastoid bones, nasal protrusion with a wide, flat frontonasal angle, maldevelopment or defects in the zygomatic bone and zygomatic arch, narrow maxillary protrusion, small maxillary sinus, mandibular dysplasia with a short body and ascending ramus, and a deepened anterior corner notch. Ultrasound examination is valuable for the intrauterine diagnosis of TCS, with the fetus often presenting with polyhydramnios, absence of fetal swallowing activity, and poor development of the bilateral parietal diameter and head circumference. Known pathogenic genes associated with TCS include TCOF1, POLR1C, and POLR1D. Mutations in these genes can lead to reduced ribosomal RNA transcription and ribosome synthesis, which subsequently affect the development and differentiation of neural crest cells during the embryonic stage [6,7,12].

The clinical manifestations of TCS are similar to those of several other syndromes, necessitating differential diagnosis. These syndromes include Nager syndrome, Miller syndrome, Goldenhar syndrome, and Pierre Robin syndrome [13,14]. The facial features of Nager syndrome are similar to those of TCS, but Nager syndrome also presents with typical limb deformities such as thumb dysplasia or absence, polydactyly, and radial ulna bony fusion [15]. Miller syndrome is characterized by asymmetric upper and lower eyelid ectropion and defects, dysplasia of the fifth finger (toe), and a higher prevalence of cleft lip and palate compared to TCS [16]. Goldenhar syndrome is marked by hemifacial atrophy affecting the development of the ears, mouth, and mandible, and may also include vertebral abnormalities and dermoid cysts on the outer layer of the eye [14]. Pierre Robin syndrome is distinguished by micrognathia, glossoptosis, dyspnea, and cleft palate [17].

The comprehensive sequential treatment of TCS typically begins at birth and continues until growth and development are complete. Treatment should be tailored to the patient’s growth pattern, physiological function, and psychosocial needs. It is recommended to ensure and maintain basic life functions before the age of 2 years. If there is persistent corneal exposure between the ages of 2 and 5 years, orbital wall reconstruction should be performed for correction. If the mandible is underdeveloped between the ages of 6 and 10 years, mandibular traction should be performed. Speech therapy, craniofacial fracture reconstruction, and external ear reconstruction should be completed before the age of 12. Orthodontic-orthognathic treatment, correction of upper and lower jaw and nasal deformities, and social psychotherapy should be carried out between the ages of 13 and 18 years. Future treatment should incorporate molecular genetics, utilizing genetic tests for prenatal examinations in high-risk groups and monitoring fetal growth and development during the first three months of pregnancy.

The phenotypes of TCS vary greatly, ranging from mild to severe deformities. For example, airway obstruction caused by mandibular deformity can affect breathing, and eyelid defects can expose the cornea. Therefore, TCS treatment should follow a multidisciplinary comprehensive sequence approach, involving oral and maxillofacial surgery, plastic surgery, orthodontics, ophthalmology, otolaryngology, speech therapy, psychology, genetics, and nursing. Individualized treatment measures should be selected based on the patient’s age and degree of deformity.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethics Statement

The studies involving human participants were reviewed and approved by the ethics committee of Qingdao Women and Children’s Hospital

Informed Consent

The patient ‘s legal guardian provided written informed consent to participate in this study.

Author’s Contribution

Ting li: Conception and design of study, Acquisition of data, Data analysis and interpretation, Drafting of manuscript and critical revision, Approval of final version of manuscript.

Yuelin qin: Conception and design of study, Acquisition of data, Data analysis and interpretation, Drafting of manuscript and critical revision, Approval of final version of manuscript.

Ziyan lu: Acquisition of data.

Xuecai yang: Drafting of manuscript and critical revision, Approval of final version of manuscript.

Junwei wang: Drafting of manuscript and critical revision, Approval of final version of manuscript.

References

  1. Nguyen PD, Caro MC, Smith DM, et al. (2016) Long-term orthognathic surgical outcomes in Treacher Collins patients. J Plast Reconstr Aesthet Surg 69: 402-408. [crossref]
  2. Treacher Collins E (1900) Case with symmetrical congenital notches in the outer part of each lower lid and defective development of the malar bones. Trans Opthalmol Soc 20: 190-192.
  3. Shinde CV, Kohli S (2018) Treacher Collin’s syndrome: a case report with an augmented review! International Journal of Advanced Research 6: 141-146.
  4. Renju R, Varma BR, Kumar SJ, et al. (2014) Mandibulofacial dysostosis (Treacher Collins syndrome): A case report and review of literature. Contemporary Clinical Dentistry 5: 532-534.
  5. van Gijn DR, Tucker AS, Cobourne MT (2013) Craniofacial development: current concepts in the molecular basis of Treacher Collins syndrome. Br J Oral Maxillofac Surg 51: 384-388.
  6. Splendore A, Silva EO, Alonso LG, et al. (2000) High mutation detection rate in TCOF1 among Treacher Collins syndrome patients reveals clustering of mutations and 16 novel pathogenic changes. Hum Mutat 16: 315-322. [crossref]
  7. Teber OA, Gillessen-Kaesbach G, Fischer S, et al. (2004) Genotyping in 46 patients with tentative diagnosis of Treacher Collins syndrome revealed unexpected phenotypic variation. Eur J Hum Genet 12: 879-890. [crossref]
  8. Vincent M, Geneviève D, Ostertag A, et al. (2016) Treacher Collins syndrome: a clinical and molecular study based on a large series of patients. Genet Med 18: 49-56. [crossref]
  9. Campos PSSL, Taitson PF, Pinto da Silva LC, et al. (2022) Dental and health aspects in the co-occurrence of Treacher Collins and Down syndromes: Case report. Spec Care Dentist 43: 94-98. [crossref]
  10. Kadakia S, Helman SN, Badhey AK, et al. (2014) Treacher Collins syndrome: the genetics of a craniofacial disease. Int J Pediatr Otorhinolaryngol 78: 893-898. [crossref]
  11. Islam F, Afroza A, Rukunuzzaman M, et al. (2008) Treacher Collins Syndrome-A Case Report. Bangladesh Journal of Child Health 32: 33-36.
  12. Bowman M, Oldridge M, Archer C, et al. (2012) Gross deletions in TCOF1 are a cause of Treacher–Collins-Franceschetti syndrome. European Journal of Human Genetics 20: 769-777. [crossref]
  13. Thomas P, Krishnapillai R, et al. (2019) Treacher Collins Syndrome: A Case Report and Review of Literature. Oral Maxillofac Patho J 10: 90-94.
  14. Shete P, Tupkari J, Benjamin T, et al. (2011) Treacher Collins syndrome. Journal of Oral and Maxillofacial Pathology 15: 348-351.
  15. Rosa RF, Guimarães VB, Beltrão LA, et al. (2015) Nager syndrome and Pierre Robin sequence. Pediatrics international: official journal of the Japan Pediatric Society 57: e69-72. [crossref]
  16. Trainor PA, Andrews BT (2014) Facial dysostoses: Etiology, pathogenesis and management. American Journal of Medical Genetics Part C Seminars in Medical Genetics 163: 283-294.
  17. Shen YF, Vargervik K, Oberoi S, et al. (2012) Facial Skeletal Morphology in Growing Children With Pierre Robin Sequence. Cleft Palate Craniofac J 49: 553-560.

Reform of the National Institute of Mental Health: A Proposal

DOI: 10.31038/JNNC.2025811

Abstract

In the United States, the primary federal agency for funding mental health research is the National Institute of Mental Health (NIMH). For decades, the NIMH has prioritized research on genetics, biomarkers and related aspects of biological psychiatry, with no meaningful yield. It is time for a radical reorganization, restructuring and reconceptualization of NIMH spending.

Keywords

National Institute of Mental Health, Mental health, Research funding

The 2025 budget of the NIMH will be over 2 billion dollars [1]. After decades of focus on genetics, brain chemistry, biomarkers and related elements of biological psychiatry, and tens of billions of dollars spent, biological psychiatry in its current form has yielded zero findings of direct clinical relevance. The idea that there is an “underlying pathophysiology” to mental illness has been countered by a large body of NIMH-funded, published evidence – by the failure to find anything. Rather than continuing to fund endless efforts to identify biological causes of mental illness, it is time to rethink the paradigm and set a distinctly different research agenda.

This view is consistent with a statement made on the American Psychiatric Association website: “many factors contribute to the risk of mental illness, such as depression. Except in rare cases, genes determine just a small percentage of the risk of illness or response to medication. Age, lifestyle, general health, psychiatric symptoms and severity, and co-occurring conditions are usually more important factors in drug response.” [2]

Simple logic and common sense can tell you that the search for genes contributing to mental illness is futile. For example, genome-wide association studies (GWAS) currently involve tens of thousands of patients and tens of thousands of controls. Rather that demonstrating the advanced nature of such research, these numbers demonstrate that is time to give up on that line of investigation. The huge numbers are required in order to find anything of statistical significance in a given study. The findings are difficult or impossible to replicate from one GWAS to another, and the overall conclusion is that there are hundreds of risk genes, each contributing less than 2% to the clinical picture, as stated in DSM-5 [3]. The same set of risk genes has been identified for schizophrenia, bipolar disorder, depression and autism, proving that there is no genetic specificity to DSM-5 diagnostic categories.

The promise in grant applications and the psychiatric literature is the hope that – with just a few more years of research – something will be found, resulting in a truly scientific personalized psychiatry in which medications will be prescribed to target specific genetic dysregulations. If there are hundreds of risk genes then hundreds of medications targeting the functions and products of those genes would be required and an individual patient would require dozens of medications given that each genetic abnormality only accounts for under 2% of the clinical picture. Each medication will cost the patient thousands or tens of thousands of dollars per year.

The entire enterprise is guaranteed to fail. It is time to give up on it.

If asked, I would recommend the following reforms to the NIMH:

  1. Stop funding biological psychiatry in its current form.
  2. Prioritize psychological and social causes of mental illness, and psycho-social treatments.
  3. Stop all efforts to de-stigmatize mental disorders by saying they are brain diseases.
  4. Mandate that measures of childhood trauma be included in all funded research. This should include psychological, social, cultural and economic forms of trauma.
  5. Set ICD-11 complex-PTSD as the ruling paradigm: a poly-diagnostic response to complex psychological and social trauma accounts for a substantial proportion of serious mental illness.
  6. Dismantle negative attitudes towards dissociative disorders by requiring them, and dissociative symptoms, to be measured in the majority of funded studies. Pair this with explicit efforts to de-stigmatize borderline personality disorder and conceptualize it as an adaptation to psychological trauma – set this as a research funding priority (see 2 above).
  7. Provide extensive public education about the reforms.
  8. If the reforms are met with bureaucratic, committee and procedural barriers, withdraw funding until the NIMH and its bureaucracy complies.
  9. No reduction in the overall NIMH budget, only a re-allocation of resources.

If a reform at all resembling the above was adopted, the predicted response of organized psychiatry would be to decry it as anti-scientific and to say it was setting mental health back 50 years. Actually, it would transfer the focus to scientific study of the psychosocial aspects of mental health – and thereby correct an extreme imbalance that has dominated psychiatric research funding for decades [4].

References

  1. Torrey F, Simmons WW, Dailey L (2023) The NIMH research portfolio: An update. Primary Care Companion CNS Disorders 25(4), 23m03486. [crossref]
  2. https://www.psychiatry.org/news-room/apa-blogs/genetic-testing-to-improve-psychiatric-medication.
  3. American Psychiatric Association (2013) Diagnostic and Statistical Manual of Mental Disorders, 5th American Psychiatric Association, Washington, DC, p. 494.
  4. Ross CA, Pam A (1995) Pseudoscience in Biological Psychiatry. Blaming the Body. John Wiley & Sons, New York.

Incidence and Risk Factors of Sepsis in Adult Patients with Trauma: A Systematic Review and Meta-Analysis

DOI: 10.31038/IJOT.2025811

Abstract

Objective: To conduct a systematic review and analysis of the risk factors linked to sepsis in adult trauma patients, providing evidence-based medical evidence for reducing the incidence of sepsis following trauma.

Methods: Literature searches were conducted in the total of 9 databases from their inception to December 2023 on factors influencing sepsis in trauma patients. Meta-analysis was conducted using the meta package in R, and the model’s heterogeneity was assessed using the I² value.

Results: A total of 10 literatures were included, involving 65,866 adult patients admitted for trauma, with 5,165 cases of sepsis following trauma. The meta-analysis results showed that advanced age (MD=1.31,95%CI: 0.51~ 3.12), male gender (OR=1.21, 95%CI: 0.95~1.54), Injury Severity Score (ISS) (MD=5.99, 95%CI: 3.05~8.93), Glasgow Coma Scale (GCS) score (MD=-1.75, 95%CI: -2.68~-0.81), Acute Physiology and Chronic Health Evaluation (APACHE II) score (MD=4.37, 95%CI: 2.56, 6.17), Sequential Organ Failure Assessment (SOFA) score (MD=2.51, 95%CI: 2.30~2.73), mechanical ventilation (OR=4.71, 95%CI: 3.44, 6.45), blood transfusion (OR=2.20, 95%CI: 1.63~2.96), central venous catheterization (OR=2.74, 95%CI: 1.93~3.89), concurrent shock (OR=2.30, 95%CI: 1.70~3.10), and emergency surgery within 24 hours (OR=2.85, 95%CI: 2.00~ 4.07), were identified as independent risk factors for sepsis among trauma patients.

Conclusion: Sepsis in trauma patients is influenced by a variety of risk factors. Clinical medical staff should intervene early in High-risk patients with these factors should be targeted to reduce sepsis incidence among trauma patients.

Keywords

Trauma, Sepsis, Risk factors, Meta-analysis

Introduction

Trauma represents a major global health burden, accounting for around 9% of annual deaths and ranking among the leading causes of mortality worldwide [1]. The advent of advanced medical technologies has successfully curbed the early mortality rate among trauma patients. However, a significant number of survivors are at risk of developing sepsis in the days or weeks following the initial trauma [2]. Sepsis, a complex clinical syndrome arising from a dysregulated host response to infection, not only can precipitate septic shock and multiple organ failure but also substantially worsens the prognosis [3]. The development of sepsis is associated with an overactive and persistent inflammatory response in trauma patients and is a prevalent complication [4]. Existing studies have reported that the mortality rate among trauma patients with sepsis hovers between 17% and 23% [5], highlighting the gravity of this complication. Despite a plethora of research efforts, the majority of which are based on single-center data, there remains a lack of consensus regarding the identification of specific risk factors for sepsis in trauma patients.

Meta-analysis, a powerful tool that aggregates and quantifies the effect sizes of individual studies through systematic review, emerges as a promising approach to address this issue [6]. By comprehensively reviewing and dissecting the extant literature on the risk factors associated with post-traumatic sepsis, this study aims to systematically organize and deliberate upon these factors. The ultimate goal is to furnish a robust evidence-based foundation for clinical practice, thereby facilitating the early detection and prevention of sepsis in trauma patients and potentially ameliorating their outcomes.

Methods

Protocol and Registration

This research adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [7] and our systematic review protocol was recorded on PROSPERO (International Prospective Register of Systematic Reviews, with the registration number CRD42024537479). As the data utilized were publicly accessible, ethical committee approval was not pursued.

Retrieval Strategy

Literature Sources and Search Strategy Literature was retrieved from databases including China National Knowledge Infrastructure, Wanfang Data, China Science and Technology Journal Database, China Biology Medicine Literature Database, PubMed, Embase, Web of Science, Cochrane, CINAHL, and Scopus from their inception to December 2023. We utilized the keywords included trauma, traumatic, post-traumatic, multiple injuries, polytrauma, septic, sepsis, septicemia, multiple organ failure, factor, and risk. Databases for dissertations and trial registries were not searched. The specific search strategies employed for English databases are detailed in Appendix 1.

Inclusion and Exclusion Criteria

Inclusion criteria: 1) Age ≥18 years; 2) Study population consisting of trauma patients; 3) Sepsis diagnosed according to Sepsis-1, Sepsis-2, or Sepsis-3 criteria; 4) Independent risk factors determined through multivariate regression analysis. Exclusion criteria: 1) insufficient patient baseline data; 2) reviews, meta-analyses, commentaries, case reports, guidelines, letters, conference abstracts, and literature related to animal experiments; 3) abnormal data and/or not conforming to statistical rules. The predominant literature reviewed comprised case- control and retrospective cohort studies, predominantly authored in either English or Chinese. We excluded smaller studies (those with fewer than 50 patients) to avoid potential false negative results. Additionally, patients with burns were excluded because they have distinct risk factors, such as a compromised skin barrier, which could potentially elevate the risk of developing sepsis [8].

Literature Screening and Data Extraction

Search results were imported into EndNote X9 software (Clarivate Analytics, London, UK) for management. Two independent reviewers (Wang B and Shi Y) screened titles and abstracts against predefined inclusion/exclusion criteria, following Cochrane guidelines. Potentially relevant citations were subjected to full-text review. Data extraction was performed independently from all eligible studies using a standardized form, with a third researcher consulted to resolve any discrepancies. The main extracted content included: principal investigator, study design, publication region and year, sample size, characteristics of the study population (age, sex), follow-up period, identified risk factors, and outcomes of multifactorial regression analysis.

Quality Assessment of Literature

Two researchers (Zhu X and Dong C) independently assessed the quality of the literature using the Newcastle-Ottawa Scale (NOS) [9]. NOS scores categorized the literature into three quality levels: ≥7 (high quality), 4-6 (moderate quality), and <4 (lower quality). In the event of any disagreements during the assessment process, the opinion of a third researcher (Cao S) will be sought to resolve them.

Statistical Analyses

Statistical analyses were conducted using Review Manager (version 5.3), STATA (version 12.0), and the ‘meta’ package in R software. The categories of subgroup analyses of incidence included: age, year of publication, research region, diagnostic criteria for sepsis, and duration of follow-up. For categorical variables, the Odds Ratio (OR) and 95% Confidence Intervals (CI) were used to express the statistical effect size, while the Mean Difference (MD) and 95% CI were used for continuous variables. Heterogeneity across studies was evaluated with the intraclass correlation index (), which quantifies the proportion of total variation in study outcomes due to between-study variance (τ²) rather than chance [10]. ≥ 50% was considered indicative of significant heterogeneity. In these instances, a random-effects model was employed for meta-analysis; otherwise, a fixed-effects model was applied. Publication bias was assessed via Egger’s regression test and funnel plots, with P < 0.05 considered statistically significant.

Results

Study Characteristics

A preliminary collection of 3391 articles was obtained, and a total of 10 articles were ultimately included (Figure 1). The 10 articles included in this study were all retrospective cohort studies [11-20], published between 2004 and 2023. Upon summarizing the literature, there were 12 risk factors with ≥2 articles, including 10 articles on age [11-20] as a risk factor; 9 articles on male gender [11-19] as a risk factor; 8 articles on Injury Severity Score (ISS) [12-18,20] as a risk factor; 5 articles each on Glasgow Coma Scale (GCS) [13,14,17,18,20] Sequential Organ Failure Assessment (SOFA) [11,13-16], mechanical ventilation [13-17], and shock [12,14-17]as risk factors; 4 articles each on Acute Physiology and Chronic Health Evaluation II (APACHE II) [11,13,14,16], number of blood transfusions [13,15-17], and emergency surgery within 24 hours [13,15-17] as risk factors; 3 articles each on central venous catheterization [14-16] and diabetes [11,12,20] as risk factors. The study characteristics are shown in Table 1.

Figure 1: PRISMA diagram for identification of relevant studies. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Table 1: Baseline characteristics of studies included for analysis

Note:① Age (years); ② Sex (Male); ③ Injury Severity Score, ISS; ④ Glasgow Coma Scale, GCS; ⑤ Acute Physiology and Chronic Health Evaluation II, APACHE II; ⑥ Sequential organ failure assessment, SOFA; ⑦ mechanical ventilation, MV; ⑧ blood transfusion; ⑨ Central venous catheterization, CVC; ⑩ Shock: SBP < 90 mmHg at hospital; ⑪ Diabetes; ⑫ Emergency surgery: surgery within 24 hours.
aTR-DGU: Trauma Registry of the German Society for Trauma Surgery
NR: not reported

Outcomes of Incidence and Subgroup Analyses

There were 65,866 trauma inpatients, with 5,165 cases of sepsis and 60,701 cases without sepsis. The  was 100%, so a random-effects model was used. The results showed that the incidence of sepsis in adult trauma patients was 35.2% (95% CI: 17.8%, 52.7%) (Figure 2). Subgroup analyses were conducted based on age, publication year, study region, sepsis diagnosis criteria, and follow-up duration. The results showed: subgroup analysis by continent demonstrated a pooled incidence rate for the age group 30≤Age < 69 years was the highest at 37.9% (95% CI: 19.8%, 58.0%); when grouped by publication year, the incidence rate for the group after 2020 was 34% (95% CI: 15%, 56%), lower than the incidence rate for the group before 2020, which was 38.6% (95% CI: 22.9%, 55.6%); subgroup analysis by study region, the incidence rate was 60.1% (95% CI: 48.0%, 71.5%) in China, higher than the incidence rate in other regions was 10.3% (95% CI: 4.2%, 18.5%); when grouped by sepsis diagnosis criteria, the incidence rate for the group using the third edition of sepsis diagnosis criteria was 60.1% (95% CI: 48.0%, 71.5%), higher than the group using the first and second editions of sepsis diagnosis criteria; when grouped by follow-up duration, the incidence rate for the group with a follow-up duration of 32 to 72 months was the highest at 45.2% (95% CI: 22.5%, 68.9%). Supplemental Table 1 for details.

Figure 2: Forest plot of the incidence of sepsis in trauma patients

Outcomes of Sepsis Influencing Factors

An analysis was conducted on the 12 included influencing factors. For SOFA, mechanical ventilation, number of blood transfusions, central venous catheterization, shock, and diabetes, the was ≤30, so a fixed-effects model was chosen for analysis. For the remaining factors, the  was ≥50%, so a random-effects model was used. The study results indicated that, except for diabetes, all other factors were statistically significant (P<0.05) (Table 2).

Table 2: Meta-Analysis of Influencing Factors

Sensitivity Analysis

The pooled effect size and heterogeneity for the 12 influencing factors were estimated using both random-effects and fixed- effects models. The statistical results showed that, except for the ISS, the other influencing factors demonstrated good consistency, indicating a high level of reliability in the results of this study (Table 3).

Table 3: Sensitivity Analysis of Influencing Factors

Quality Evaluation and Publication Bias

The NOS scoring results showed that 7 articles scored ≥7 points [11,13-15,17-19] and 3 articles scored 6 points [12,16,20]. Quality evaluation is provided by Supplemental Table 2. Egger’s regression test was used to assess publication bias for the 10 articles that considered age as a risk factor for sepsis. The Egger’s regression test for funnel plot asymmetry supports this observation, yielding a non-significant result (p = 0.32), which indicates a low level of bias in the published findings. The contour-enhanced funnel plot as shown in Supplement Figure 1. For the other 11 influencing factors, the number of included articles did not reach 10, hence no publication bias analysis was conducted for them.

Discussion

The pooled average incidence of sepsis in adult trauma patients calculated from the studies was 35.2%, which is higher to the 31.1% reported by Amina Abliz et al. [21]. The estimation of incidence rates varies by region. This study found that the incidence rate in China is 60.1%, which is significantly higher than the 10.3% in other countries. The reason for this difference may be related to the data sources. Among the five foreign studies included, the data of three studies come from public databases. Such data sources may have a more representative sample of the general population, but issues such as data collection methods and quality control may lead to an underestimation of the incidence rate. In contrast, the data of the five domestic studies all come from hospitals, which means that the data mainly come from patients seeking medical treatment, and there may be selection bias. Hospital – based data tend to be biased towards patients with more severe or symptomatic conditions, which may overestimate the incidence rate. Furthermore, the decrease in the incidence of post – traumatic sepsis over time may be attributed to early diagnosis and intervention, continuous strengthening of hospital infection control measures, improvement of the trauma treatment system, and enhanced self – health awareness of patients after trauma. Finally, compared with previous standards, the Sepsis – 3 diagnostic criteria may have improved sensitivity. This comprehensive assessment method may lead to the diagnosis of more sepsis patients in early or sub – clinical states, thereby resulting in an increase in the incidence rate.

Advanced age is an important risk factor for sepsis in adult trauma patients. The elderly are more susceptible to sepsis due to factors such as immunosenescence, weakened cardiovascular function, poor nutritional status, and comorbidities [22]. Epidemiological studies have shown that the incidence of sepsis is higher in males than in females [23]. The results of this study indicate that the risk of sepsis in male trauma patients is 1.21 times higher than in females, which is close to the 1.3 times reported in a study from the United States [24]. This may be related to differences in sex hormone levels [25]. Although demographic-related influencing factors cannot be directly intervened, the development of sepsis in elderly male trauma patients should be closely monitored. Additionally, APACHE II and SOFA scores are used to assess the severity of patients’ conditions. The risk of sepsis is positively correlated with these scores. The lower the GCS score, the higher the risk of sepsis. Particularly, patients with severe brain injuries and coma have a higher incidence of sepsis and septic shock [26]. The ISS score provides a quantitative measure for assessing soft tissue injuries in trauma patients. This study found that ISS, APACHE II, SOFA, and GCS scores are all helpful for early identification of sepsis in adult trauma patients. Medical staff need to closely monitor patients with abnormal scores and take timely intervention strategies to prevent the occurrence of sepsis. Furthermore, the number of blood transfusions, mechanical ventilation, central venous catheterization, and emergency surgery are associated with an increased risk of sepsis in trauma patients. Blood transfusion may increase the risk of sepsis by suppressing immune responses [27]. Patients on mechanical ventilation are more likely to develop VAP, leading to sepsis [28]. Central venous catheterization increases the risk of central venous catheter-related bloodstream infections, especially in the intensive care unit, where such infections are common and potentially life- threatening [29]. Emergency surgery is also a risk factor for sepsis after trauma. The OR value of this study is 2.55, indicating that the risk of sepsis in patients undergoing emergency surgery is 2.55 times that of those undergoing elective surgery, which is close to the 2 times reported in previous studies [30].

Therefore, in the management of trauma patients, the necessity of blood transfusions, mechanical ventilation, central venous catheterization, and emergency surgery should be carefully assessed to reduce the risk of sepsis. Lastly, shock can predispose patients to sepsis by damaging microcirculation and reducing tissue perfusion, while sepsis can exacerbate shock by triggering widespread inflammatory responses and cardiovascular dysfunction [31]. Therefore, when trauma patients have shock, it should be promptly recognized and treated to reduce the incidence of sepsis.

Limitations

This meta-analysis has several limitations. Firstly, there is a certain degree of heterogeneity in the combined effect sizes of some risk factors, which may be related to factors such as the race, age distribution of the study subjects, and the quality of diagnosis and treatment in different medical institutions, and thus needs further improvement; Secondly, risk factors with less than 10 studies were not assessed for publication bias, so the possibility of bias cannot be ruled out. Moreover, the study did not categorize sepsis by severity, which could affect treatment strategies and outcome predictions.

Conclusion

In conclusion, the incidence of sepsis in adult trauma patients is high and influenced by various factors including age, gender, clinical scoring systems, invasive procedures, as well as comorbid conditions. Clinical medical staff can refer to the results of this study, deal with and prevent risk factors in a targeted manner, reduce the occurrence of sepsis, and thus improve the prognosis and quality of life of trauma patients.

CRediT Authorship Contribution Statement

Bingsheng Wang conceived and designed the study, independently completed database search. Wenhao Qi screening and data extraction and writing. Bing Wang, Xiaohong Zhu and Chaoqun Dong conducted statistical analysis, interpreted the analytical results, and provided technical support for methodological refinement. Yankai Shi, Jiani Yao and Xiajing Lou assisted in optimizing the research. Aili Shi and Shihua Cao reviewed and edited the manuscript.

Acknowledgements

This research was supported by the Medical and Health Technology Plan of Zhejiang Province (grant 2022507615); Key Research Project for Laboratory Work in Zhejiang Province Colleges, ZD202202; Zhejiang Province Traditional Chinese Medicine Inheritance and Innovation Project 2023ZX0950. 2024 research project of Engineering Research Center of Mobile Health Management System, Ministry of Education; First – class Undergraduate Course in Zhejiang Province, 2022, sponsored by the Education Department of Zhejiang Province (No.1133).

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Mycobacterium tuberculosis, Tuberculosis and Cancer

DOI: 10.31038/CST.20251011

Abstract

Tuberculosis (TB) is an infectious disease caused by mycobacteria, principally Mycobacterium tuberculosis. This disease can affect all organs but mainly the lungs, remains a major public health challenge, particularly in low and middle-income countries. TB disease can occur after infection and can cause death. There is evidence of an increased risk of cancer, particularly of the lung, in people with a history of TB or with an active form of the disease. The BCG vaccine, derived from a weakened strain of Mycobacterium bovis, offers protection against severe forms of tuberculosis in children and is also employed in the treatment of bladder cancer. The objective of this article is to examine the associations between Mycobacterium tuberculosis, tuberculosis and cancer.

Keywords

Mycobactium tuberculosis, Tuberculosis, Risk factors, Lung cancer

Introduction

Tuberculosis is an infectious disease caused by a mycobacterium of the tuberculosis group, mainly Mycobacterium tuberculosis, whose usual reservoir is man, more rarely Mycobacterium bovis or africanum. The incidence of tuberculosis remains high in countries with low or middle economic income, and this potentially fatal infectious disease remains a global public health issue. The infection initially remains latent, linked to airborne transmission of bacilli and can progress to tuberculosis disease, mainly in the lungs, with the possibility of poly-visceral extension, particularly via the haematogenous route, in immunodeficient patients. It can also cause sequelae and encourage the development of cancer, particularly lung cancer. However, this mycobacterium can play a role in the treatment of other cancers, and represents an area of research in this field.

Epidemiology

The causative agent of tuberculosis is Mycobacterium tuberculosis. In 2023, tuberculosis (TB) remains a major public health issue worldwide, although it is no longer one of the top ten causes of death on a global scale. However, it is the leading cause of death from infectious agents, ahead of HIV infection, having caused 1.3 million deaths. Of the new cases diagnosed, 70% were of the pulmonary variety. The eight countries accounting for more than two-thirds of global TB cases are India (26%), Indonesia (10%), China (6.8%), Philippines (6.8%), Pakistan (6.3%), Nigeria (4.4%), Bangladesh (3.6%) and Democratic Republic of Congo (2.9%). More than 400,000 people have developed a form of TB resistant to rifampicin, almost 80% of these have developed a multi-drug resistant form [1].

More than 80% of TB cases and 90% of induced deaths occur in low- and middle-income countries. The mortality rate due to tuberculosis is falling by around 3% a year, and an overall decline of 42% was observed over the period 2000-2017 [2]. It is estimated that more than 1.5 billion people (23% of the world’s population) are infected with the tubercle bacillus, and are thus at risk of developing TB [2].

The Tubercle Bacillus

Bacteriological Aspects

Mycobacterium tuberculosis (MBT) is a strict aerobic bacillus. This pathogenic agent has an outer lipid membrane bilayer ; it divides very slowly (16 to 20 hours) and is either very weakly ‘Gram-positive’ or does not retain its colour due to the high lipid and mycolic acid content of its wall. In nature, the bacterium can only develop inside the cells of a host organism. This acid-fast bacillus can be identified under the microscope. The most common staining method is the Ziehl-Nielsen stain, which highlights MBT in bright red. Auramine staining and luminescence microscopy can also highlight it [1-3].

The Mycobacterium tuberculosis complex (MBTC) includes four other mycobacteria responsible for tuberculosis: M. bovis, M. africanum, M. canetti and M. microti [3]. M. africanum is not very widespread, but it is a major cause of tuberculosis in Africa. M. bovis used to be a common cause of tuberculosis, but the pasteurisation of milk has virtually eliminated its responsibility in developed countries. M. Canetti is mainly responsible for tuberculosis in the Horn of Africa, while M. Microti can be implicated in immunocompromised individuals [3].

The other known pathogenic mycobacteria are M. leprae (Hansen’s bacillus), which causes leprosy, and M. avium and M. kansasii, classified as ‘non-tuberculous mycobacteria’ (NTM), which can cause pulmonary infections similar to tuberculosis. [4,5].

Calmette and Guérin bacillus developed from an attenuated strain of Mycobacterium bovis, is the basis of the tuberculosis vaccine. It is used to protect (80% efficacy for more 5 years) young children against serious forms of tuberculosis, such as tuberculous meningitis and miliary tuberculosis [2]. It is much less effective against other forms of TB, particularly pulmonary. It stimulates the immune system so that it can identify and fight the mycobacteria responsible for tuberculosis in the event of exposure. In countries where the incidence of TB is low (United States of America, Canada, Western Europe, Australia) the vaccine is less widely used or reserved for high-risk population groups. On the other hand, it is given to newborns in countries with a high incidence of tuberculosis, and to children living in environments where active cases of tuberculosis may be present. Health professionals or those working in high-risk environments (laboratories, etc.) may also be vaccinated. A single dose by intradermal injection is recommended in the first few weeks of life ; in older children, the absence of tuberculosis infection should be verified by a tuberculin or IGRA test prior to vaccination. This vaccine has a high rate of tolerance, with minor ulceration at the injection site being the only common side effect. Complications are rare, and include local abscesses and adenopathy in the drainage area. In exceptional cases, disseminated infections may occur in immunocompromised individuals [6].

Transmission of Infection

The risk of transmission of the infection from one person to another depends on several factors: the number of small (0.5 and 5 µm) contagious droplets (Flügge droplets) which can remain suspended in the air for up to 9 hours after they are emitted. The transmission of the same clone of bacteria from one patient to another has been proven by genotyping studies of mycobacteria [6].

People who are in frequent, close contact with people suffering from pulmonary, laryngeal or tracheobronchial tuberculosis, especially in a small, poorly ventilated space, are particularly exposed to the risk of infection when patients emit MBT during verbal exchanges, episodes of coughing, spitting or sneezing. It is estimated that a person with active tuberculosis can infect at least 10 to 20 people. People suffering from tuberculosis must therefore be isolated while their sputum is sterilised, and wear a protective mask, as must their carers [6] and any infection should be detected in people contacts.

Natural History of Tuberculosis Infection

Transmission of Infection

Defence mechanism against MBT. Once inhaled, the tubercle bacilli are deposited in the distal alveolar spaces, mainly in the upper parts of the lungs. They are phagocytosed by alveolar macrophages (AMs), accompanied by a local cell-mediated inflammatory response involving CD4 T lymphocytes (Th1), which activate AMs and stimulate the production of cytotoxic CD8 lymphocytes, thereby facilitating the response against intracellular MBT. Numerous cytokines are released, including interferon gamma (INFγ), interleukin 2 (IL2), tumour necrosis factor (TNFα) and the recruitment of circulating mononuclear cells, all of which play a part in the defence mechanism against this infection. Phagocytic dendritic cells carrying antigenic peptides reach the lymph node relays and present these antigens to CD4 T lymphocytes, which return to the lung to organize the formation of an inflammatory granuloma with a satellite lymph node reaction, leading to the formation of a lymph node-lung complex [6,7].

Latent tuberculosis infection (LTI) is characterised by a delayed hypersensitivity reaction to MBT, leading to positive tuberculin and IGRA tests (Interferon Gamma Release Assays), whether Quantiferon- TB Gold Plus or T-SPOT.TB. In 90% of cases, the body’s immune response prevents MBT proliferation and controls the infection in less than 10 weeks, resulting in latent tuberculosis infection. This is generally clinically asymptomatic and poses no risk of contagion. However, MBTs may persist in a quiescent state in macrophages for a long time [6,7].

In the context of tuberculosis (TB), it is important to note that 70% of cases progress to tuberculosis disease within two years of initial infection. Following this, the risk gradually decreases, though it appears to be lifelong. TB disease can occur as a result of a decline in cellular immunity or reinfection with MBT. This risk is increased at the extremes of life, particularly in children under the age of five who have not been vaccinated with the Mycobacterium bacille Calmette-Guérin (BCG) vaccine, and in people over the age of 65. People at particular risk may also develop TB disease, the main clinical symptoms of which are asthenia, weight loss, fever and coughing in the case of respiratory infection. Radiologically, the lesions predominantly affect the upper lungs and can take a variety of forms, including infiltrates, excavations, nodules, disseminated forms, mediastinal lymph node involvement and pleurisy. Extra-thoracic sites may or may not be associated (e.g. laryngeal, peripheral lymph nodes, bone, genitourinary, digestive) An inflammatory biological picture with anaemia is most often identified. Diagnosis is made by detecting MBT in sputum, or by bronchial aspiration using bronchoalveolar lavage. Culture on liquid or solid medium (Löwenstein-Jensen) is used to identify the type of MBT and its resistance to anti-tuberculosis drugs. Once treatment has been initiated, and provided the patient complies and the MBT are not drug-resistant, sputum and cultures can be sterilised in less than 2 months [6,7].

Risk Factors for TB Infection and TB Disease

The development of tuberculosis is influenced by various internal or external risk factors that increase the likelihood of infection or progression from latent infection to disease.

Internal Risk Factors: The innate deficiency of defences against MBT, with deficient production of INFγ or IL4, IL10, IL12, must be taken into account before vaccination with BCG vaccine [8].

Diabetes, which doubles the risk of LTI and quadruples the risk of TB disease, often with severe presentations (pulmonary excavations, disseminated forms, recurrences or resistance to anti-tuberculosis drugs). The explosion in the number of cases of diabetes worldwide could worsen the epidemiological situation for TB [8].

External Risk Factors: The poor socio-economic conditions and social insecurity in which people live, including precarious housing, detention, malnutrition, migration and difficulty in accessing healthcare, favour the development of TB [8-10].

Exposure to outdoor or indoor air pollution involving various pollutants (e.g. CO, CO2, SO2, O3, PM2.5 microparticles, PAHs) are risk factors for MBT infection [8].

Exposure to active or passive smoking causes dysfunction of the mucociliary escalator, which promotes the persistence of germs in the respiratory tract, and impairment of the mechanisms of anti- infectious immunity (reduced function of AMs, reduced release of TNF-α, imbalance in the CD4/CD8 ratio and reduced production of IFN-γ). Tobacco smoke could stimulate grow and/or the virulence of tuberculosis bacilli. In smokers suffering from TM, a reduction in IFN-γ response was noted, which may affect the performance of IGRA tests. In active smokers, the risk of pulmonary tuberculosis was assessed (OR= 2.6; 95% CI: 2.1 – 3.4). This risk is dose-dependent (CR = 4.4 for 10 cigarettes smoked daily; CR = 5 for 10 years of smoking). Smoking increases the risk of death from TB (RR =2.15 ; 95% CI: 1.38- 3.3), of recurrence of TB and of anti-tuberculosis drug-resistant forms (OR = 1.70; 95% CI: 1.3-2.23) [11].

Alcohol abuse, often associated with socio-economic disadvantage, is a risk factor for MBT infection and TB disease. Alcohol alters the immune response and phagocytic function of macrophages. The risk is dose-dependent ; four drinks a day quadruples the risk of developing TB [12].

HIV infection is a major driver of the TB epidemic, particularly in Africa, where almost 10% of TB patients are thought to be living with HIV. Widespread use of screening and antiretroviral treatment (ART) has led to a significant reduction in TB mortality in HIV-infected patients [8,13].

The use of corticosteroids to treat chronic inflammatory diseases is associated with an excess risk of developing TB; this risk is dose- dependent: prednisolone ≤ 15 mg per day (OR=2.8; 95%CI: 1.0-7.9), dose ≥ 15 mg per day (OR=7.7; 95% CI: 2.8-21.4), and increases with prolonged treatment [8].

Immunomodulatory drugs (anti-TNF) used to treat chronic inflammatory diseases may favour the development of TB; screening for LTI and prophylactic treatment are essential prior to their use [8]. Immunosuppressive drugs used during visceral transplantation may also favour the development of TB [8].

Renal failure, with or without dialysis, increases the risk of TB [8].

Finally, there is good evidence that people exposed to silica crystals or suffering from silicosis have a higher risk of TB [14].

Tuberculosis and Cancer

Studies show an association between tuberculosis and cancers. Patients with a history of pulmonary tuberculosis have a higher relative risk of cancer than the general population. Increased rates of lung cancer have been reported in regions where TB is endemic [15,16]. However, the association between TB and cancer is often multifactorial and depends on many factors (environment, comorbidities, smoking, immune status of the patient). In many cases, the co-occurrence of TB and cancer makes it impossible to determine the nature of the association between these two types of disease [15,16].

Tuberculosis is a Risk Factor for Cancer

Tuberculosis can promote the development of certain cancers, the mechanisms involved are complex and multifactorial.

General Mechanisms

Tuberculosis causes chronic inflammation in tissues, especially the lungs. This inflammation can damage the DNA of cells, promoting carcinogenesis. Tuberculosis granulomas cause fibrosis and tissue remodelling, creating a microenvironment conducive to cancer development. AM and immune cells produce reactive oxygen species (ROS) to fight infection, but these damage DNA and increase the risk of carcinogenesis [16-18].

Cofactors may be involved in carcinogenesis. People living with HIV, who are more susceptible to tuberculosis, have a weakened immune system, which can increase the risk of lung cancer, as well as Kaposi’s sarcoma, lymphoma and anogenital cancers. Exposure to substances such as silica, asbestos and polycyclic aromatic hydrocarbons all promote carcinogenesis. Smoking, which is common among TB patients, is a major risk factor for cancer, especially lung cancer [19,20].

Different Types of Cancer

Lung Cancer

Mycobacterium tuberculosis infection may increase the risk of lung cancer, which may be twice as common after TB as in the general population. In particular, squamous cell carcinoma, although other types such as adenocarcinoma and large cell carcinoma have also been reported. The prolonged chronic inflammation, oxidative stress with excessive production of pro-inflammatory cytokines (TNF-α, IL-6) and free radicals observed in TB cause DNA damage that is a factor in carcinogenesis. After TB disease, fibrotic lesions often form in the damaged areas, which are conducive to the growth of cancer cells (‘scar cancer’). By evading the immune system, Mycobacterium tuberculosis can cause local immunosuppression ; the imbalance in the immune response can create a microenvironment favourable to the growth of cancer cells. Finally, certain metabolites or molecules released by MBT may facilitate cell transformation by interfering with normal cell regulation mechanisms [20-23].

Extrapulmonary Cancers

Cancers can develop in the viscera affected by TB (e.g. lymph nodes, bones, peritoneum) by the mechanisms described above. In Denmark, a cohort study of 15,024 patients with tuberculosis (median follow-up 8.5 years) showed the occurrence of 1747 cancers. The risk of cancer 3 months after tuberculosis was 1.83%, reflecting a high standardised incidence ratio (SIR=11.09 ; 95% CI: 9.82- 12.48), particularly for malignant pleural mesothelioma (368.4), lung cancer (40.9), but also Hodgkin’s lymphoma (30.6), ovarian cancer (26.4) and malignant non-Hodgkin’s lymphoma (23.8) [24]. Other studies suggest an association between urogenital TB and an increased risk of bladder cancer, although this association is less well documented [16].

Practical Attitudes

Differential Diagnosis of Cancer and Tuberculosis

Patients with active or past tuberculosis must be carefully monitored, especially if they are smokers or have been exposed to carcinogens, to differentiate recurrent tuberculosis from lung cancer. Symptoms of lung cancer may mimic those of tuberculosis and require a thorough diagnostic work-up. In some cases, the two conditions may occur simultaneously [25-28].

Effects of Anti-tuberculosis or Cancer Chemotherapy

Anti-tuberculosis treatments are effective and cancer chemotherapies have made considerable progress. Both can be a source of immunosuppression or adverse events that interfere with the simultaneous treatment of cancer and TB [29,30]. TB can occur during cancer treatment [31].

Prevention and Patient Follow-up

Primary prevention. It is essential to ensure early diagnosis and treatment of TB, to monitor adherence to treatment and to follow the course of the disease to reduce the incidence of chronic infection and pulmonary sequelae. BCG vaccination in regions where tuberculosis is endemic. Socio-economic conditions and access to health care need to be improved [2,32].

Secondary prevention. Regular monitoring of patients allows early detection of signs of cancer. Chest CT scans are used to monitor scarring, and pulmonary function tests are used to detect dysfunction, especially in persistent smokers who should be helped to quit. Screening and management of diabetes is essential [33-35].

Mycobacteria in Cancer Treatment

The approach is to use the immunostimulatory properties of mycobacteria to activate the body’s immune defences against cancer cells. MBT are not used because of their pathogenicity, but attenuated strains such as the BCG vaccine are used for their anti-tumour effects [36,37].

BCG and Bladder Cancer

Mechanism of Action

Mycobacteria strongly activate macrophages, which secrete pro- inflammatory cytokines (such as TNF-α and IFN-γ), recruit other immune cells and activate T lymphocytes, which are essential for the anti-tumour response. Stimulation of the immune system in the vicinity of the tumour can induce a generalised immune response against cancer cells (bystander effect) [37,38].

Methods of Use

BCG is injected directly into the bladder (intravesical instillation). It causes local inflammation that attracts immune cells (macrophages, T lymphocytes) to the bladder. These immune cells then attack the cancer cells, reducing the risk of recurrence or progression.

Main Indications

Non-invasive bladder cancer (urothelial carcinoma) or following transurethral resection of the bladder. BCG significantly reduces the risk of recurrence and progression to an invasive form of this cancer [38].

Limitations

This treatment is well tolerated, although it can cause adverse effects such as cystitis and haematuria. Local or disseminated infection with BCG is rare [37,39]. Its efficacy is essentially limited to bladder cancer, but its value in other cancers is being investigated [40].

Therapeutic Prospects

Research is underway into genetically modifying mycobacterial strains to enhance their immunotherapeutic potential, while reducing their infectious risks. Genetically modified strains of MBT or M. smegmatis are being studied as experimental therapeutic agents. Components of mycobacteria could improve the efficacy of anti- cancer vaccines. Mycobacteria could be combined with immune checkpoint inhibitors (anti-PD-1 or anti-CTLA-4) to enhance their anti-tumour effect. Finally, the use of certain components, such as the lipids in the cell wall of mycobacteria, could make it possible to develop nanomedicines or targeted delivery systems [41-43].

Conclusion

Mycobacterium tuberculosis is the main cause of tuberculosis, which remains a major public health issue. The International Agency for Research on Cancer (IARC) has classified it as a carcinogen. There is evidence of an increased risk of lung cancer in patients with a history or active form of tuberculosis. The chronic inflammation, immunological disorders and genomic abnormalities induced by MBT infection underline the fact that it is a precursor to carcinogenesis [44]. One hundred years ago, the BCG vaccine against tuberculosis was developed from an attenuated strain of Mycobacterium bovis, and subsequently proved effective in treating bladder cancer. Research is needed to clarify the relationship between Mycobacterium tuberculosis, tuberculosis and cancer in order to improve our knowledge of oncogenesis and cancer prevention and treatment.

Contribution to the Article: All authors contributed to the writing and correction of this article.

Conflict of Interest: The authors declare that they have no conflict of interest.

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