Comparative Assessment of Acute Pulmonary Effects Induced by Heated Tobacco (IQOS) Aerosol Inhalation in a Murine Model

doi:10.21203/rs.3.rs-4667724/v1

Download PDF

Article

Comparative Assessment of Acute Pulmonary Effects Induced by Heated Tobacco (IQOS) Aerosol Inhalation in a Murine Model

https://doi.org/10.21203/rs.3.rs-4667724/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Tobacco smoking remains a major global health concern, causing preventable deaths and economic strain. Although new tobacco products such as heat-no-burn (HnB) are safer alternatives to traditional cigarettes, research on their associated risks remains limited. This study aimed to investigate the effects of HnB smoke exposure on the lungs compared with traditional cigarettes and the combined use of HnB and cigarettes through experiments using a mouse model. We quantitatively analyzed changes in the levels of 92 blood plasma proteins using the proximity extension assay method and observed significant changes in their levels in mice exposed to different smoke conditions. Specifically, certain proteins increased in the HnB smoke-exposed group, including CCL20, CXCL1, and PDGF receptor, suggesting activation of the nicotine pathway. Comparative analysis with traditional cigarette smoke-exposed mice further highlighted similarities and differences in their protein expression profiles. This study contributes to a better understanding of the biological mechanisms underlying the harmful effects of alternative nicotine delivery systems and identifies potential biomarkers associated with the harmful effects of HnB smoke exposure. However, the precise impact of nicotine on the immune system may be influenced by various factors, necessitating further research.

Health sciences/Pathogenesis/Inflammation/Acute inflammation

Health sciences/Biomarkers

electronic nicotine delivery systems

lung injury

model animal

smoking

toxicity test

Tobacco smoking remains a global public health concern, contributing significantly to preventable deaths worldwide. Use of tobacco, a complex mixture comprising over 5,000 toxic and carcinogenic substances¹, is a well-established risk factor associated with cardiovascular diseases, chronic obstructive pulmonary disease, and various cancers^2–5. Despite extensive public health efforts, 1.14 billion people smoked in 2019, resulting in 7.69 million deaths and 200 million disability-adjusted life-years globally⁶, imposing substantial health and economic burdens and thus incurring significant direct healthcare costs.⁷

Various tobacco products have emerged in the market since the introduction of a new type of liquid-based electronic cigarette (e-cigarette) in 2003, which vaporizes a liquid containing nicotine and other substances^8,9. Philip Morris International's IQOS, approved by the U.S. Food and Drug Administration as a modified-risk tobacco product, represents one of the recent innovations in tobacco products. IQOS, which provides controlled nicotine delivery through heat instead of combustion, potentially making it less harmful, is marketed as an alternative to traditional smoking¹⁰. Such heat-not-burn (HnB) tobacco products align with global trends and have gained considerable popularity, including in South Korea, where users perceive them as a relatively less harmful option to quit smoking¹¹.

However, compared with the extensive research on the harmful effects of traditional tobacco, studies on the effects of emerging tobacco products and nicotine delivery systems such as HnB remain limited. Additionally, despite Philip Morris's official data claiming lower harmful components in HnB¹², HnB may actually produce more inflammatory cytokines¹³. Therefore, this study aimed to investigate the harmful effects of these emerging tobacco products and their underlying mechanisms using acute animal models through proteomic analysis. Furthermore, we comprehensively examined the impact of the new tobacco product compared with the effects of traditional tobacco smoke by comparing the HnB group with a conventional cigarette smoke group, a mixed group of the two, and a control group.

A total of 18 mice were initially utilized, with each treatment group (the HnB group, tobacco smoking group, and a mixed group exposed to both types of smoke) consisting of five individuals, except for the control group, which comprised three mice. However, experimental animals in the tobacco smoking and HnB groups died during the blood sampling process because of clotting. Therefore, samples could not be obtained from these groups.

Despite these challenges, we performed proteomics analysis using a proximity extension assay (PEA; Olink Target 96 Mouse Exploratory Panel). The cycle threshold (Ct) value was measured for 92 proteins per sample, and normalized protein expression (NPX) values were calculated from Ct values using inter-plate control (IPC). Samples and protein assays were filtered using two strict thresholds. Differences in the expression of the 92 investigated proteins were observed among the three treatment groups and the control group.

Heatmap

Hierarchical clustering analysis with a heatmap (Euclidean distance, complete linkage) clustered the proteins and samples based on their expression, and common patterns of grouping within cigarette-exposed mice in the heatmap were obtained using the PEA. In the cigarette exposure groups, various proteins, particularly CCL20, CXCL1, and PDX5, were consistently elevated (Fig. 2).

PEA proteomic analysis

Comparing control with cigarette-exposed mice

Comparing the unexposed control mice with those exposed to cigarette smoke revealed notable alterations in the plasma levels of GDNF, FOXO1, PRDX5, TGFA, AXIN1, CA13, PPP1R2, CCL2, PLIN1, QDPR, EPCAM, CCL3, HGF, IL1A, CXCL9, MAP2K6, CXCL1, DCTN2, TNFSF12, and CCL20, with increases in CCL2, CCL3, and CXCL1 and decreases in HGF levels (Fig. 3).

Comparing control with dual-smoked mice

Comparison of the dual-smoked mice with the control group revealed significant differences in plasma levels of GDNF, FOXO1, PRDX5, TGFA, AXIN1, FST, NADK, SNAP29, CA13, PPP1R2, PLIN1, QDPR, RIOX2, PLXNA4, EPCAM, CCL3, HGF, IL1A, DDAH1, CXCL9, MAP2K6, CXCL1, DCTN2, and TNFSF12, with increases in CCL3 and CXCL1 and decreases in FOXO1, GDNF, EPO, NADK, SNAP29, PPP1R2, QDPR, HGF, CXCL9, and TNFSF12 (Fig. 4).

Comparing control with HnB-smoked mice

Comparing control with HnB-smoked mice revealed significant differences in plasma levels of CLMP, MATN2, CPE, GCG, GDNF, TNFRSF11B, TGFB1, PLA2G4A, TGFA, CCL5, EPO, FST, RGMA, TNNI3, NOTCH3, CNTN1, S100A4, PPP1R2, ADAM23, DLK1, CCL2, ENO2, WFIKKN2, FAS, PLXNA4, EPCAM, VSIG2, SEZ6L2, IL1A, IL23R, DLL1, IL10, ACVRL1, LGMN, MAP2K6, IL1B, CASP3, APBB1IP, WISP1, PDGFB, CXCL1, LPL, EDA2R, NTF3, CCL20, TNR, PARP1, and TNF, with increases in TGFB1, S100A4, FAS, EPCAM, PLXNA4, CASP3, and CCL20 and decreases in GDNF and PPLR2 (Fig. 5).

In this study, the harmful effects of exposure to the smoke of a HnB product were compared with traditional cigarette smoke using an animal model and analyzed through PEA analysis. Notably, the levels of multiple proteins, including CCL20, CXCL1, and PRDX5, consistently increased in the cigarette exposure group, with a clear consistent pattern evident in the heatmap. Importantly, these increases were also observed in mice exposed to HnB smoke. Additionally, the significant elevations of CCL2, CXCL9, and platelet-derived growth factor (PDGF) receptor in HnB-exposed mice indicate their association with the nicotine pathway. Therefore, these characteristic protein profiles may serve as potential biomarkers for understanding the harmful effects of HnB in the future, providing valuable insights for further research and clinical applications.

Both conventional cigarettes and e-cigarettes are primarily designed to deliver nicotine, providing immediate satisfaction through vapors. Traditional cigarettes contain carcinogenic chemicals such as nitrosamines, which are inhaled following combustion, whereas e-cigarettes only contain nicotine and relatively harmless organic solvents. Consequently, e-cigarettes are often portrayed as safer alternatives to tobacco¹⁶. However, the effects of nicotine on the immune system are nuanced and vary among studies. Notably, cigarette smoke comprises many harmful substances beyond nicotine that can adversely impact health. Nicotine is absorbed into the body through cigarette smoke, triggering various physiological changes, some of which are related to the immune system. Cells of the immune system generate and release various compounds, including cytokines, to regulate inflammation and immune responses in the body. Nicotine can influence the production and release of cytokines, potentially affecting immune responses^17,18. However, the specific effects may depend on factors such as the dose, duration, and frequency of nicotine exposure, and individual differences. In this study, we observed elevated levels of CCL2, CXCL9, and PDGFB in mice exposed to e-cigarette smoke, indicating activation of a nicotine-related immune pathway.

CCL2, a chemokine also known as MCP1, plays a crucial role in inflammation and immune responses. It is associated with inflammatory reactions triggered by environmental factors and is released by multiple cells, including macrophages, monocytes, and epithelial cells^19,20. Notably, CCL2 overexpression influences proliferation, migration, and tumor growth factor (TGF)-β1 expression in lung epithelial cells when exposed to cigarette smoke extract. Additionally, it acts as a regulator in the generation of pro-fibrotic mediators and migration in fibroblasts²¹. Therefore, CCL2 could be vital in controlling extracellular matrix turnover by stimulating intermediary molecules, such as TGF-β1, α-smooth muscle actin, and interleukin (IL)-6, in pulmonary fibroblasts. Hence, CCL2 could be a potential therapeutic target for managing idiopathic pulmonary fibrosis. Other studies suggest that CCL2 is a potent pro-inflammatory chemokine that serves as a chemoattractant for myeloid cells and has been extensively studied as a predictor and potential driver of tumor cell growth and metastasis^22,23.

Tobacco smoking can induce inflammatory and autoimmune diseases via genetic/epigenetic changes, increased oxidative stress, and free radical production, leading to enhanced proliferation of B and T cells, reduced T regulatory cell function, elevated pro-inflammatory cytokines (IL-1β, IL-6, IL-8, and tumor necrosis factors), and increased expression of chemotactic cytokines such as recombinant human CXCL9 (MIG), thymus and activation-regulated chemokine, and interferon-inducible T cell α chemoattractant^24–36. CXCL9 plays an important role in many diseases, including external infection, autoimmune diseases, tumor treatment, lymphoma³⁷, and fatty livers³⁸. Changes in these inflammatory markers and cytokines can lead to cancers at 18 different tumor sites and a range of other chronic diseases, including coronary heart disease, stroke, and chronic obstructive pulmonary disease^39,40. Notably, research on the specific interaction between CXCL9 and nicotine/e cigarettes is still evolving, and conclusive evidence remains unavailable. Therefore, considering the broader context of nicotine and e-cigarette use, including their potential effects on overall health and immune function, is crucial.

The impact of nicotine, present in both tobacco products and e-cigarettes, on different bodily functions has been thoroughly examined. Notably, nicotine exposure may affect the generation and function of growth factors such as PDGFB. PDGFB is a signaling protein implicated in diverse cellular functions such as cell growth, proliferation, and differentiation, with a notable contribution to tissue repair and wound healing. Nonetheless, the precise relationship between PDGFB and nicotine or e-cigarettes is currently under investigation, and conclusive findings have been yet reached. Von Willebrand factor (vWF), PDGFB, HIVEP1, and GPX3 were identified as venous thromboembolism associated biomarkers in the VEBIOS cohort, and the vWF and PDGF-B associations were replicated in FARIVE⁴¹. Notably, various chemicals such as flavorants and additives in e-cigarettes may have different effects on the body, and the impact of heating these compounds and their potential toxic effects are also understudied. Furthermore, the method of delivering nicotine via e-cigarettes may differ from that of traditional tobacco products, potentially influencing its interaction with signaling proteins such as PDGFB. Current research have indicated elevate PDGFB levels in e-cigarette users, but the specific effects and mechanisms of these interactions are still actively being studied. As research progresses, a deeper understanding of the relationship between PDGF-B and nicotine/e-cigarettes will be necessary.

The limitation of the study lies in its reliance on animal models and observational data, which may not fully translate to human responses. Furthermore, the specific mechanisms underlying the observed protein elevation in response to HnB exposure require further elucidation through mechanistic studies. Nevertheless, this study is strengthened by its comprehensive evaluation of potential biomarkers associated with HnB exposure, providing valuable insights into the effects of alternative nicotine delivery systems on biological pathways and a solid foundation for future research on physiological responses to HnB exposure in humans.

In conclusion, the rise in specific proteins such as CCL20, CXCL1, and PDX5 observed in both cigarette and HnB users, along with the elevated levels of CCL2, CXCL9, and PDGFR in HnB smokers, indicates an association with the nicotine pathway and identifies potential markers for understanding the harmful effects of HnB. Although nicotine affects the immune system by initiating various bodily changes and altering cytokine release, its precise impact is intricate and can be influenced by other toxins in cigarette smoke. Therefore, the immune-modulating effects of nicotine should be analyzed in the wider context of the well-known health risks of smoking. Consequently, further investigation is imperative to fully grasp the intricate interplay between nicotine, other cigarette components, and immune function.

Animal preparation and ethical considerations

Specific pathogen-free male C57BL/6 mice (6 weeks old, weighing 20–25 g) were supplied by RaonBio Inc. (Raonbio, Yongin, Korea). The mice were housed in a controlled environment with a temperature of 21 ± 2°C and a relative humidity of 40–60%. They were maintained on a 12-hour light/dark cycle and had unrestricted access to food and water. All experimental procedures were approved by the Korea University Institutional Animal Care and Use Committee (Approval Number: KOREA-2022-0066), which were performed in accordance with the relevant guidelines and regulations. The study was conducted based on the ARRIVE guidelines 2.0 for transparent and comprehensive reporting of research involving animals.

Grouping and exposure protocol

The mice were divided into four groups, with each treatment group comprising five mice and the control group comprising three mice, resulting in a total of 18 animals. The treatment groups included the HnB group, the tobacco smoking group, a mixed group exposed to both types of smoke, and a control group exposed only to room air.

The experiment employed the Smoking Tester Line System (Three Shine Inc., Daejeon, Korea), exposing each group to tobacco and IQOS smoke 5 days a week for 4 weeks. Each day, the experimental animals were placed in dedicated cages, as shown in Fig. 1, and exposed while 20 cigarettes or IQOS sticks were consumed in sets of five at a time (taking approximately 30–40 minutes). The mixed group was alternately exposed to 10 cigarettes and 10 IQOS sticks. In the tobacco smoke group, we used the commercially available Marlboro Red (Korean Philip Morris, Seoul, Korea), whereas in the HnB group, HEETS bronze (Korean Philip Morris, Seoul, Korea) was used. Following the experiment, the animals were transferred to their housing facility after a sufficient period for smoke clearance.

Serum collection

After the final exposure, the experimental animals were subjected to isoflurane inhalation anesthesia and were operated by midline incision, exposing the heart and lungs. Subsequently, the animal was euthanized by obtaining blood directly from the heart. The collected blood was centrifuged at 2000 ×g for 10 min at 4°C, and the supernatant was stored at -70°C until further analysis.

PEA

Ninety-two proteins in the blood plasma were analyzed using the Olink Multiplex Target 96 Mouse Exploratory Panel (https://www.olink.com/products-services/target/search-olink-target-96/). Within each panel, 92 antibody probe pairs were designed to interact with target proteins present in the sample. The panels were selected because of their comprehensive coverage of various potential targets linked to critical biological functions, including cell regulation, development, metabolism, and organ damage.

During the reaction, a proximity-dependent DNA polymerization event occurred between a pair of oligonucleotide-labeled antibodies targeting the protein of interest, leading to the generation of a PCR reporter sequence, which was then measured using real-time PCR^14,15. Internal, extension, and detection controls were utilized to monitor deviations, as outlined by the manufacturer (www.olink.com).

Proteins with a call rate below 85%, indicating targets where < 85% of individuals exhibited a measurable concentration above the limit of detection, were excluded from further analysis based on the recommended intra-plate variation of the manufacturer. NPX was determined by subtracting an external inter-plate control, with values set relative to a correction factor established by Olink and represented on a log2 scale, with the background level set at 0. Additional details regarding the PEA, including data processing and normalization, can be obtained from the manufacturer's website (www.olink.com).

Statistical analysis

Heatmaps were generated using R version 3.5.3 using the “pheatmap” package, involving scaling, normalization, and data reduction. For comparison of multiprotein analyses, NPX was used to denote the protein expression levels. NPX serves as a logarithmic scale relative quantification measure, enabling the detection of variations in individual protein levels across samples, thus facilitating the establishment of protein signatures. NPX values derived from each assay were used for the comparative analysis between the three treatment groups and the control. Statistical tests were conducted based on these NPX values, leveraging the group information. The volcano plot displays the estimated difference on the x-axis and -log10(p-value) on the y-axis. A horizontal and vertical dotted line denote a raw p-value of 0.05 and threshold in log2 ratio of fold change, respectively. Dots were color-coded according to the criteria for significant results. Box plots were employed to compare protein expression levels across groups, whereas bar plots were used to visualize the fold changes in protein expression for each comparison.

Conflict of Interest Statement

The authors have no conflicts of interest to declare.

Funding Sources

This study was supported by the National Research Foundation of Korea grant funded by the Korean government (MSIT) (No. 2021R1I1A1A01058820). Additionally, this work received support from the Dongguk University Research Fund of 2024.

Author Contribution

Conceptualization: BKK, WJY, and CYK; Resources: YSS, HJP, MKB, and JHC; Data curation: BKK, WJY, and YJC; Software: YSS, MKB, JHC, and CYK; Formal analysis: YSS, YJC, and CYK; Supervision: MKB, JHC, and CYK; Funding acquisition: BKK and CYK; Validation: BKK, WJY, and CYK; Investigation: YSS, YJC, HJP, MKB and YSC; Visualization: MKB and JHC; Methodology: YSS and CYK; Project administration: YSS, YJC, HJP, MKB, and JHC; Writing – original draft: BKK and WJY; Writing – review & editing: all authors.

Acknowledgements

We would like to express our gratitude to Editage (www.editage.co.kr) for their English language editing services.

Data Availability

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Talhout, R. et al. Hazardous compounds in tobacco smoke. Int J Environ Res Public Health 8, 613–628 (2011).
Teo, K. K. et al. Tobacco use and risk of myocardial infarction in 52 countries in the INTERHEART study: a case-control study. Lancet (London, England) 368, 647–658 (2006).
Sethi, J. M. & Rochester, C. L. SMOKING AND CHRONIC OBSTRUCTIVE PULMONARY DISEASE. Clinics in Chest Medicine 21, 67–86 (2000).
Sasco, A. J., Secretan, M. B. & Straif, K. Tobacco smoking and cancer: a brief review of recent epidemiological evidence. Lung cancer (Amsterdam, Netherlands) 45 Suppl 2, S3–9 (2004).
Choe, Y.-R. et al. Effective Timing of Introducing an Inpatient Smoking Cessation Program to Cancer Patients. Yonsei Med J 64, 251–258 (2023).
Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019. Lancet (London, England) 397, 2337–2360 (2021).
Pichon-Riviere, A. et al. The health and economic burden of smoking in 12 Latin American countries and the potential effect of increasing tobacco taxes: an economic modelling study. The Lancet. Global health 8, e1282-e1294 (2020).
Breitbarth, A. K., Morgan, J. & Jones, A. L. E-cigarettes-An unintended illicit drug delivery system. Drug and alcohol dependence 192, 98–111 (2018).
Lee, S. Y. & Shin, J. Association between Electronic Cigarettes Use and Asthma in the United States: Data from the National Health Interview Survey 2016–2019. Yonsei Med J 64, 54–65 (2023).
Czoli, C. D., White, C. M., Reid, J. L., RJ, O. C. & Hammond, D. Awareness and interest in IQOS heated tobacco products among youth in Canada, England and the USA. Tobacco control 29, 89–95 (2020).
Kim, J., Yu, H., Lee, S. & Paek, Y. J. Awareness, experience and prevalence of heated tobacco product, IQOS, among young Korean adults. Tobacco control 27, s74-s77 (2018).
Phillips, B. et al. An 8-Month Systems Toxicology Inhalation/Cessation Study in Apoe–/– Mice to Investigate Cardiovascular and Respiratory Exposure Effects of a Candidate Modified Risk Tobacco Product, THS 2.2, Compared With Conventional Cigarettes. Toxicological Sciences 149, 411–432 (2015).
Bhat, T. A. et al. Acute Effects of Heated Tobacco Product (IQOS) Aerosol Inhalation on Lung Tissue Damage and Inflammatory Changes in the Lungs. Nicotine & tobacco research: official journal of the Society for Research on Nicotine and Tobacco 23, 1160–1167 (2021).
Wik, L. et al. Proximity Extension Assay in Combination with Next-Generation Sequencing for High-throughput Proteome-wide Analysis. Mol Cell Proteomics 20, 100168 (2021).
Niroomand, A. et al. Corticotropin releasing hormone as an identifier of bronchiolitis obliterans syndrome. Sci Rep 12, 8413 (2022).
Marques, P., Piqueras, L. & Sanz, M.-J. An updated overview of e-cigarette impact on human health. Respiratory Research 22, 151 (2021).
Sopori, M. L. et al. Effect of nicotine on the immune system: possible regulation of immune responses by central and peripheral mechanisms. Psychoneuroendocrinology 23, 189–204 (1998).
Strzelak, A., Ratajczak, A., Adamiec, A. & Feleszko, W. Tobacco smoke induces and alters immune responses in the lung triggering inflammation, allergy, asthma and other lung diseases: a mechanistic review. International journal of environmental research and public health 15, 1033 (2018).
Abid, S. et al. CCR2/CCR5-mediated macrophage–smooth muscle cell crosstalk in pulmonary hypertension. 54 (2019).
Giebe, S. et al. Comparative study of the effects of cigarette smoke versus next-generation tobacco and nicotine product extracts on inflammatory biomarkers of human monocytes. Pflugers Archiv: European journal of physiology 475, 823–833 (2023).
García-Trejo, S. S., Medina-Pérez, D. M. & Balderas-Martínez, Y. I. J. T. R. E. e. C. Q.-B. Exposure to cigarette smoke extract induces proliferation and overexpression of CCL2 in A549 cells and migration in lung fibroblasts. 25, 1–12 (2023).
Hao, Q., Vadgama, J. V., Wang, P. J. C. C. & Signaling CCL2/CCR2 signaling in cancer pathogenesis. 18, 1–13 (2020).
Gschwandtner, M., Derler, R. & Midwood, K. S. J. F. i. i. More than just attractive: how CCL2 influences myeloid cell behavior beyond chemotaxis. 10, 2759 (2019).
Sokolowska, M. et al. Acute Respiratory Barrier Disruption by Ozone Exposure in Mice. Frontiers in immunology 10, 2169 (2019).
Durazzo, T. C., Mattsson, N. & Weiner, M. W. Smoking and increased Alzheimer's disease risk: a review of potential mechanisms. Alzheimer's & dementia: the journal of the Alzheimer's Association 10, S122-145 (2014).
Shein, M. & Jeschke, G. Comparison of Free Radical Levels in the Aerosol from Conventional Cigarettes, Electronic Cigarettes, and Heat-Not-Burn Tobacco Products. Chemical research in toxicology 32, 1289–1298 (2019).
Bergström, J. Tobacco smoking and chronic destructive periodontal disease. Odontology 92, 1–8 (2004).
Qiu, F. et al. Impacts of cigarette smoking on immune responsiveness: Up and down or upside down? 8, 268 (2017).
Heyn, J., Luchting, B., Azad, S. C. J. N. & Research, T. Smoking associated T-Cell imbalance in patients with chronic pain. 22, 111–117 (2020).
Andersen, A. M. et al. Cigarette and cannabis smoking effects on GPR15 + helper T cell levels in peripheral blood: Relationships with epigenetic biomarkers. 11, 149 (2020).
Hartmann, T., Marino, F. & Duffield, R. J. C. Tobacco smoking and acute exercise on immune-inflammatory responses among relative short and longer smoking histories. 123, 154754 (2019).
Jamil, A., Rashid, A. & Majeed, A. J. J. C. P. S. P. Correlation between genotoxicity and interleukin-6 in smokers: a rodent model. 28, 821–823 (2018).
Gonzalez-Quintela, A. et al. Serum levels of immunoglobulins (IgG, IgA, IgM) in a general adult population and their relationship with alcohol consumption, smoking and common metabolic abnormalities. 151, 42–50 (2008).
Yao, L., Liu, G., Huang, S., Li, W. & Li, Y. J. Z. y. x. z. z. Relationship between expression of HDAC2, IL-8, TNF-α in lung adenocarcinoma tissues and smoking. 96, 1410–1413 (2016).
Pace, E. et al. MiR-21 upregulation increases IL‐8 expression and tumorigenesis program in airway epithelial cells exposed to cigarette smoke. 234, 22183–22194 (2019).
Li, D., Li, J., Wang, L. & Zhang, Q. J. G. M. R. Association between IL-1β, IL-8, and IL-10 polymorphisms and risk of acute pancreatitis. 14, 6635–6641 (2015).
Maruoka, H. et al. IP-10/CXCL10 and MIG/CXCL9 as novel markers for the diagnosis of lymphoma-associated hemophagocytic syndrome. 93, 393–401 (2014).
Semba, T. et al. The FLS (fatty liver Shionogi) mouse reveals local expressions of lipocalin-2, CXCL1 and CXCL9 in the liver with non-alcoholic steatohepatitis. 13, 1–11 (2013).
Onor, I. O. et al. Clinical effects of cigarette smoking: epidemiologic impact and review of pharmacotherapy options. 14, 1147 (2017).
Shiels, M. S. et al. Cigarette smoking and variations in systemic immune and inflammation markers. 106, dju294 (2014).
Bruzelius, M. et al. PDGFB, a new candidate plasma biomarker for venous thromboembolism: results from the VEREMA affinity proteomics study. 128, e59-e66 (2016).

No competing interests reported.

supplementproteinlist.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Comparative Assessment of Acute Pulmonary Effects Induced by Heated Tobacco (IQOS) Aerosol Inhalation in a Murine Model

Status:

Version 1

Abstract

Figures

Introduction

Results

Heatmap

PEA proteomic analysis

Comparing control with cigarette-exposed mice

Comparing control with dual-smoked mice

Comparing control with HnB-smoked mice

Discussion

Methods

Animal preparation and ethical considerations

Grouping and exposure protocol

Serum collection

PEA

Statistical analysis

Declarations

Conflict of Interest Statement

Funding Sources

Author Contribution

Acknowledgements

Data Availability

References

Additional Declarations

Supplementary Files

Status:

Version 1