Proteomics Profiling of Bilirubin Nanoparticle Treatment against Myocardial Ischemia-Reperfusion Injury.

In myocardial infarction, ischemia-reperfusion injury (IRI) poses a significant challenge due to a lack of effective treatments. Bilirubin, a natural compound known for its anti-inflammatory and antioxidant properties, has been identified as a potential therapeutic agent for IRI. Currently, there are no reports about proteomic studies related to IRI and bilirubin treatment. In this study, we explored the effects of bilirubin nanoparticles in a rat model of myocardial IRI. A total of 3616 protein groups comprising 76,681 distinct peptides were identified using LC-MS/MS, where we distinguished two kinds of protein groups: those showing increased expression in IRI and decreased expression in IRI with bilirubin treatment, and vice versa, accounting for 202 and 35 proteins, respectively. Our proteomic analysis identified significant upregulation in the Wnt and insulin signaling pathways and increased Golgi markers, indicating their role in mediating bilirubin nanoparticle's protective effects. This research contributes to the proteomic understanding of myocardial IRI and suggests bilirubin nanoparticles as a promising strategy for cardiac protection, warranting further investigation in human models.

Donor fat-to-muscle ratio and kidney transplant outcomes: A proposition of metabolic memory.

AIMS: The impact of donor abdominal fat-to-muscle ratio (FMR) on kidney transplant (KT) outcomes was assessed. Given the transient nature of the donor's metabolic environment in transplant recipients, this study investigated the capacity of body composition to induce metabolic memory effects. MATERIALS AND METHODS: KT patients (n = 895) who received allografts from living donors (2003-2013) were included. Donor fat and muscle were quantified using pre-KT abdominal computed tomography scans. Patients were categorised into donor FMR tertiles and followed up for graft outcomes. Additionally, genome-wide DNA methylation analysis was performed on 28 kidney graft samples from KT patients in the low- and high-FMR groups. RESULTS: Mean recipient age was 42.9 ± 11.4 years and 60.9% were males. Donor FMR averaged 1.67 ± 0.79. Over a median of 120.9 ± 42.5 months, graft failure (n = 127) and death-censored graft failure (n = 109) were more frequent in the higher FMR tertiles. Adjusted hazard ratios for the highest versus lowest FMR tertile were 1.71 (95% CI, 1.06-2.75) for overall graft failure and 1.90 (95% CI, 1.13-3.20) for death-censored graft failure. Genome-wide DNA methylation analysis identified 58 differentially methylated regions (p < 0.05, |Δß| > 0.2) and 35 genes showed differential methylation between the high- (FMR >1.91) and low-FMR (FMR <1.27) groups. CONCLUSIONS: Donors with increased fat and reduced muscle composition may negatively impact kidney allograft survival in recipients, possibly through the transmission of epigenetic changes, implying a body-composition-related metabolic memory effect.

Identifying e-cigarette content on TikTok: Using a BERTopic Modeling approach.

INTRODUCTION: The use of hashtags is a common way to promote e-cigarette content on social media. Analysis of hashtags may provide insight into e-cigarette promotion on social media. However, the examination of text data is complicated by the voluminous amount of social media data. This study used machine learning approaches (i.e., Bidirectional Encoder Representations from Transformers [BERT] topic modeling) to identify e-cigarette content on TikTok. METHODS: We used 13 unique hashtags related to e-cigarettes (e.g., #vape) for data collection. The final analytic sample included 12,573 TikTok posts. To identify the best fitting number of topic clusters, we used both quantitative (i.e., coherence test) and qualitative approaches (i.e., researchers checked the relevance of text from each topic). We, then, grouped and characterized clustered text to each theme. RESULTS: We evaluated that N=18 was the ideal number of topic clusters. The 9 overarching themes were identified: Social media and TikTok-related features (N=4; "duet", "viral"), Vape shops and brands (N=3; "store"), Vape tricks (N=3; "ripsaw"), Modified use of e-cigarettes (N=1; "coil", "wire"), Vaping and girls (N=1; "girl"), Vape flavors (N=1; "flavors"), Vape and cigarettes (N=1; "smoke"), Vape identities and communities (N=1; "community"), and Non-English language (N=3; Romanian and Spanish). CONCLUSIONS: This study used a machine learning method, BERTopic modeling, to successfully identify relevant themes on TikTok. This method can inform future social media research examining other tobacco products, and tobacco regulatory policies such as monitoring of e-cigarette marketing on social media. IMPLICATIONS: This study can inform future social media research examining other tobacco products, and tobacco regulatory policies such as monitoring of e-cigarette marketing on social media.

Using Computer Vision to Detect E-cigarette Content in TikTok Videos.

INTRODUCTION: Previous research has identified abundant e-cigarette content on social media using primarily text-based approaches. However, frequently used social media platforms among youth, such as TikTok, contain primarily visual content, requiring the ability to detect e-cigarette-related content across large sets of videos and images. This study aims to use a computer vision technique to detect e-cigarette-related objects in TikTok videos. AIMS AND METHODS: We searched 13 hashtags related to vaping on TikTok (eg, #vape) in November 2022 and obtained 826 still images extracted from a random selection of 254 posts. We annotated images for the presence of vaping devices, hands, and/or vapor clouds. We developed a YOLOv7-based computer vision model to detect these objects using 85% of extracted images (N = 705) for training and 15% (N = 121) for testing. RESULTS: Our model's recall value was 0.77 for all three classes: vape devices, hands, and vapor. Our model correctly classified vape devices 92.9% of the time, with an average F1 score of 0.81. CONCLUSIONS: The findings highlight the importance of having accurate and efficient methods to identify e-cigarette content on popular video-based social media platforms like TikTok. Our findings indicate that automated computer vision methods can successfully detect a range of e-cigarette-related content, including devices and vapor clouds, across images from TikTok posts. These approaches can be used to guide research and regulatory efforts. IMPLICATIONS: Object detection, a computer vision machine learning model, can accurately and efficiently identify e-cigarette content on a primarily visual-based social media platform by identifying the presence of vaping devices and evidence of e-cigarette use (eg, hands and vapor clouds). The methods used in this study can inform computational surveillance systems for detecting e-cigarette content on video- and image-based social media platforms to inform and enforce regulations of e-cigarette content on social media.

Content Analysis of YouTube Videos Related to E-Cigarettes and COVID-19.

BACKGROUND: E-cigarettes are frequently promoted on social media and portrayed in ways that are attractive to youth. While the COVID-19 pandemic significantly affected people's lives, less is known about how the pandemic influenced e-cigarette-related marketing and information on social media. This study examined how e-cigarettes were portrayed on youtube, one of the most popular social media platforms during the COVID-19 pandemic. METHODS: We searched for combinations of search terms related to e-cigarettes (e.g., "electronic cigarette" and "vape") and COVID-19 (e.g., "corona" and "COVID") in July of 2021. To be included in analyses, videos must be: uploaded after February 1, 2020, in English, related to e-cigarettes and COVID-19, and less than 30 min in length. We conducted a content analysis of included videos, coding for uploader characteristics, what e-cigarette products were showcased, and specific themes that intersected between e-cigarettes and COVID-19. RESULTS: We examined N = 307 videos and found that N = 220 (73.6%) discussed the health effects of e-cigarette use on COVID-19, followed by videos on how COVID-19 affects e-cigarette sales (N = 40, 12.9%), face mask-related videos (N = 16, 5.1%; e.g., vape tricks including masks) and instructional videos (N = 10, 3.2%; e.g., sanitizing vape devices during COVID-19). Instructional videos had the highest number of likes (Median = 23; IQR = 32) and comments (Median = 10; IQR = 7). CONCLUSIONS: Our findings support the need for continuous surveillance and research on novel vaping-related content in reaction to policies and events, such as the global pandemic. More research is needed to understand the impact of this content on young people's perceptions and use of e-cigarettes.

Adolescents and Young Adults Use of Social Media and Following of e-Cigarette Influencers.

BACKGROUND: With high rates of both e-cigarette and social media use among adolescents and young adults (AYAs), social media influencers who promote e-cigarettes are particularly concerning but are understudied. We examined the association between AYAs' use of 11 different social media platforms (e.g. Facebook, Twitter, Instagram, TikTok, and YouTube) and exposure to social media e-cigarette influencers. OBJECTIVES: From November 2022 to February 2023, we conducted an online, US national survey of AYAs (14-29 years) who endorsed past-30-day e-cigarette use. We used binomial logistic regression to examine associations between the frequency of use of each social media platform and following e-cigarette influencers, controlling for age, sex, race, ethnicity, e-cigarette use frequency, and other tobacco and substance use (i.e., alcohol and cannabis). The model was stratified by adolescents (14-17 years; n = 293) and young adults (18-29 years; n = 654). RESULTS: The most frequently used social media platforms were Snapchat, TikTok and Instagram among adolescents, and YouTube, Instagram and TikTok among young adults. In adjusted models, following e-cigarette influencers was associated with more frequent use of TikTok (adjusted odds ratio [95% CI]; 1.33 [1.05, 1.68]) and Pinterest (1.18 [1.02, 1.38]) among adolescents, and more frequent use of Twitter (1.17 [1.06, 1.29]) among young adults. CONCLUSIONS: The use of different platforms was associated with exposure to e-cigarette influencers: TikTok and Pinterest among adolescents and Twitter among young adults. These findings can inform tobacco regulatory policy and social media platform restrictions of e-cigarette influencers on the platforms that are popular among AYAs.

Patterns and Reasons for Being Uninsured Among Sexual Minority Adults Before and After the Affordable Care Act Implementation.

Purpose: We aimed to identify the self-reported reasons for being uninsured and sociodemographic factors associated with uninsurance among lesbian, gay, or bisexual (LGB) adults before and after the Affordable Care Act (ACA). Methods: We analyzed the 2013-2018 National Health Interview Survey data using multivariable logistic regression models to estimate the odds of being uninsured and the prevalence of self-reported reasons for not having insurance among LGB adults aged 18-64 years. Results: The study included 2124 LGB adults. The weighted uninsured rate decreased significantly from 19.6% in 2013 to 13.2% in 2017-2018 (odds ratio 0.61; 95% confidence interval 0.47-0.78). The primary reason cited for not having insurance post-ACA was similar to pre-ACA, with cost-related factors being the most commonly reported (31.5%). Conclusion: The overall uninsured rate decreased among LGB adults from 2013 to 2018, whereas disparities across subpopulations remained. Cost-related factors remained significant barriers to obtaining insurance coverage.

Use of ENDS devices and modifications to vape cannabis among adolescents and young adults who also vape nicotine.

BACKGROUND: Electronic nicotine delivery systems (ENDS) are the most used tobacco product among adolescents and young adults (AYAs) and are increasingly used to vape cannabis. It is unclear what vaping devices and ENDS modifications are used most frequently by AYAs who vape both nicotine and cannabis. METHODS: AYAs (aged 14-29) reporting ENDS use in the past 30 days were recruited via Qualtrics (N = 1,011). We conducted three multivariable logistic regression models examining differences in likelihood of: 1) vaping cannabis in the past 30 days; 2) mixing cannabis and nicotine liquids; and 3) using nicotine devices to vape cannabis; based on type of vaping device used most often, controlling for age, socio-economic status, gender, race, frequency of ENDS use, and other cannabis use. RESULTS: 40 % (n = 405) of AYAs reported vaping both nicotine and cannabis in the past 30 days. AYAs who used vape pens most often were more likely to have vaped cannabis concentrates in the past 30 days compared to individuals using disposable vapes (aOR = 2.72, 95 %CI = 1.75-4.21, p < 0.001). AYAs who used open systems most often (i.e., vape pens, mods, or e-hookah) were more likely than individuals using closed systems (i.e., disposable vapes, rechargeable pods or cigalikes) to combine nicotine and cannabis e-liquids (aOR = 2.03, 95 %CI = 1.43-2.89, p < 0.001) or use a nicotine device to vape cannabis (aOR = 1.66, 95 %CI = 1.17-2.34, p = 0.005). IMPLICATIONS: Co-use of cannabis and nicotine via similar devices, particularly vape pens and other open-systems, warrants collaborative regulatory efforts to mitigate co-use of both substances, with a particular need for increased regulation of cannabis vaping products.

Modification of Electronic Nicotine Delivery Systems Among Adolescents and Young Adults.

OBJECTIVES: We assessed awareness and perceptions of, information sources about, and engagement in modifying electronic nicotine delivery systems (ENDS) among adolescents and young adults (AYAs). METHODS: AYAs (N = 1018) endorsing past-month ENDS use completed a survey on awareness and use of the following modifications: (1) refilling rechargeable cartridges/pods or (2) disposable pods, (3) rewicking or (4) recharging disposable pods, (5) modifying nicotine e-liquids (eg, changing propylene glycol/vegetable glycerin, nicotine), (6) combining nicotine and cannabis for simultaneous vaping, and (7) putting cannabis in ENDS designed for nicotine vaping. Logistic regression assessed how sources of information (eg, friends, social media, nonsocial media Web sites, vape shops) about and perceptions of ENDS modifications associated with ENDS modifications. RESULTS: Refilling (69.0% heard, 40.1% tried) and recharging the battery (66.4% heard, 35.8% tried) of disposable pods were most common. Friends (64.4%) and social media (46.7%) were the most common sources of information. Notable significant associations between information sources and modifications were: 1. nonsocial media Web sites and vape shops with rewicking and recharging disposable devices and modifying nicotine e-liquid; 2. nonsocial media Web sites with refilling rechargeable cartridges/pods and disposable pods; and 3. social media with recharging disposable devices and mixing nicotine and cannabis liquids. Perceptions of reduced harm and "coolness" were associated with various modifications. DISCUSSION: AYAs are aware of and modify ENDS for purposes unintended by manufacturers. ENDS policies should consider unintended ENDS use to safeguard public health. Prevention efforts should communicate about the potential harms of ENDS modifications.

Unintended exposure to e-liquids and subsequent health outcomes among US youth and adults.

This study aimed to determine the prevalence and predictors of oral, ocular, or dermal e-liquid exposure and subsequent outcomes (becoming sick, going to the hospital) in the US. We examined survey data from the Population Assessment of Tobacco and Health Study Wave 5 (2018-2019). The analytic sample included US youth (aged 12-17 years), young adults (aged 18-24 years), and older adults (aged ≥ 25 years) who reported e-cigarette use in the past 12 months. We first determined the prevalence of self-reported e-liquid exposure (in the mouth, skin, or eyes), subsequently "becoming sick" from the exposure, and "going to the hospital" after the exposure. We also examined associations between these outcomes and the device type used (refillable tank /mod system, replaceable prefilled cartridges, disposable/ other device type). E-liquid exposure was reported by 25% of youth (aged 12-17 years), 25% of young adults (aged 18-24 years), and 19% of older adults (aged≥ 25 years). Among individuals reporting e-liquid exposure, subsequent sickness was reported by 10% of youth11% of young adults, and 14% of older adults, and "going to the hospital" was reported by 3.5% of youth, 2.7% of young adults, and 6.8% of older adults. Among young adults, the use of a refillable tank /mod system was associated with higher odds of e-liquid exposure (aOR = 2.2, 95% CI = 1.2, 4.1) than the use of other device types, including disposables. The findings suggest that, at a minimum, e-cigarettes/e-liquids may need warning labels that state the risks of e-liquid exposure and packaging regulations that promote device and bottle designs that minimize e-liquid spills.

E-cigarette dependence and cooling flavor use are linked among youth.

BACKGROUND: E-cigarette flavors that produce cooling sensations may reduce nicotine harshness and enhance appeal among youth. While previous research has shown that use of cooling flavors is associated with more frequent vaping among youth, it is unknown whether the same holds true for e-cigarette dependence. This study examines the relationship between cooling flavor use and e-cigarette dependence among youth accounting for vaping frequency. METHODS: In Fall 2022, a survey was conducted among Connecticut high school students to assess past-month nicotine e-cigarette use, ever use of cooling flavors, cooling flavor types (e.g., fruit-cooling), and e-cigarette dependence. Analyses were restricted to those with past-month nicotine and nicotine-free e-cigarette use and complete data (n=204). Multivariable linear regressions were run to examine the association between cooling flavor use and e-cigarette dependence, adjusting for demographics, e-cigarette use characteristics, and other tobacco product use. RESULTS: 78.4% of the sample used cooling e-cigarette flavors, with 55.0% using mint-cooling flavors and 52.5% using fruit-cooling flavors. Regression results observed that cooling flavor use was associated with higher e-cigarette dependence (ꞵ=1.53, SE=0.63, p=0.017), with those who used cooling flavors having higher e-cigarette dependence than those who did not (M=5.78 [SD=5.33] vs. 2.84 [3.19]). CONCLUSIONS: Our results suggest that cooling flavor use is significantly associated with e-cigarette dependence among youth. While regulations often target menthol flavor, tobacco control agencies should consider restricting any flavor that can produce cooling sensations, even if they are not traditional menthol products, as cooling flavors is associated with youth e-cigarette dependence.

The role of artificial intelligence measured preoperative kidney volume in predicting kidney function loss in elderly kidney donors: A multicenter cohort study.

BACKGROUND: The increasing use of kidneys from elderly donors raises concerns due to age-related nephron loss. Combined with nephrectomy, this loss of nephrons markedly increases the risk of developing chronic kidney disease (CKD). This study aimed to investigate the prognostic value of preoperative kidney cortex volume in predicting the loss of kidney function in elderly donors, by developing an artificial intelligence (AI)-based model for precise kidney volume measurement and applying it to living kidney donors. MATERIALS METHODS: A multicenter retrospective cohort study using data from living donors who underwent donor nephrectomy between January 2010 and December 2020 was conducted. An AI segmentation model was developed and validated to measure kidney cortex volume from pre-donation computer tomographic (CT) images. The association between measured preoperative kidney volumes and post-nephrectomy renal function was analyzed through a generalized additive model. RESULTS: A total of 1074 living kidney donors were included in the study. Validation of the developed kidney cortex volume model showed a Dice similarity coefficient of 0.97 and a Hausdorff distance of 0.76 mm. The measured cortex volumes exhibited an age-related decrease, which correlated with declining kidney function. Elderly donors showed greater decreases in estimated glomerular filtration rates (eGFR) post-donation compared to young donors (P=0.041). Larger preoperative remnant kidney cortex volume was associated with significantly less decline of eGFR post-donation than those with smaller preoperative remnant kidney cortex volume (P<0.001). CONCLUSION: This study highlights the critical role of preoperative kidney cortex volume in the donor assessment process, particularly for elderly donors. The fully automated model for measuring kidney cortex volume provides a valuable tool for predicting post-donation renal function and holds promise for enhancing donor evaluation and safety.

Optimum tacrolimus trough levels for enhanced graft survival and safety in kidney transplantation: a retrospective multicenter real-world evidence study.

BACKGROUND: The current study aimed to determine the optimal tacrolimus trough levels for balancing graft survival and patient safety following kidney transplantation. MATERIALS AND METHODS: We conducted a retrospective cohort study involving 11,868 kidney transplant recipients from five medical centers. The association between tacrolimus exposures (periodic mean trough level, coefficient of variability, time in therapeutic range) and composite allograft outcome (de novo donor specific antibody, biopsy-proven rejection, kidney dysfunction, and graft failure), as well as safety outcomes (severe infection, cardiovascular events, malignancy, and mortality) were assessed. Data were sourced from Clinical Data Warehouses and analyzed using advanced statistical methods, including Cox marginal structural models with inverse probability treatment weighting. RESULTS: Tacrolimus levels of 5.0-7.9 ng/mL and 5.0-6.9 ng/mL during the 2-12 month and 12-72 month post-transplantation periods, respectively, were associated with reduced risks of composite allograft outcomes. During the first post-transplant year, the adjusted hazard ratios (aHR) for composite allograft outcomes were: 0.69 (95% CI 0.55-0.85, P<0.001) for 5.0-5.9 ng/mL; 0.81 (95% CI 0.67-0.98, P=0.033) for 6.0-6.9 ng/mL; and 0.73 (95% CI 0.60-0.89, P=0.002) for 7.0-7.9 ng/mL (compared to levels ≥8.0 ng/mL). For the 6-year composite outcomes, aHRs were 0.68 (95% CI 0.53-0.87, P=0.002) for 5.0-5.9 ng/mL and 0.65 (95% CI 0.50-0.85, P=0.001) for 6.0-6.9 ng/mL. These optimal ranges showed reduced rates of severe infection (6 y), malignancy (6 y), and mortality (1 y). CONCLUSION: This multicenter study provides robust evidence for optimal tacrolimus trough levels during the periods 2-12 and 12-72 months following kidney transplantation.

Benefits of statin therapy within a year after kidney transplantation.

Cardiovascular disease remains a leading cause of morbidity and mortality after kidney transplantation (KT). Although statins reduce cardiovascular risk and have renal benefits in the general population, their effects on KT recipients are not well-established. We studied the effects of early statin use (within 1-year post-transplantation) on long-term outcomes in 714 KT recipients from the Korean cohort study for outcome in patients with KT. Compared with the control group, statin group recipients were significantly older, had a higher body mass index, and had a higher prevalence of diabetes mellitus. During a median follow-up of 85 months, 74 graft losses occurred (54 death-censored graft losses and 20 deaths). Early statin use was independently associated with lower mortality (hazard ratio, 0.280; 95% confidence interval 0.111-0.703) and lower death-censored graft loss (hazard ratio, 0.350; 95% confidence interval 0.198-0.616). Statin therapy significantly reduced low-density lipoprotein cholesterol levels but did not decrease the risk of major adverse cardiovascular events. Biopsy-proven rejection and graft renal function were not significantly different between statin and control groups. Our findings suggest that early statin use is an effective strategy for reducing low-density lipoprotein cholesterol and improving patient and graft survival after KT.

Creatinine-cystatin C ratio and death with a functioning graft in kidney transplant recipients.

Death with a functioning graft is important cause of graft loss after kidney transplantation. However, little is known about factors predicting death with a functioning graft among kidney transplant recipients. In this study, we evaluated the association between post-transplant creatinine-cystatin C ratio and death with a functioning graft in 1592 kidney transplant recipients. We divided the patients into tertiles based on sex-specific creatinine-cystatin C ratio. Among the 1592 recipients, 39.5% were female, and 86.1% underwent living-donor kidney transplantation. The cut-off value for the lowest creatinine-cystatin C ratio tertile was 0.86 in males and 0.73 in females. The lowest tertile had a significantly lower 5-year patient survival rate and was independently associated with death with a functioning graft (adjusted hazard ratio 2.574, 95% confidence interval 1.339-4.950, P < 0.001). Infection was the most common cause of death in the lowest tertile group, accounting for 62% of deaths. A low creatinine-cystatin C ratio was significantly associated with an increased risk of death with a functioning graft after kidney transplantation.

Subchronic particulate matter exposure underlying polyhexamethylene guanidine phosphate-induced lung injury: Quantitative and qualitative evaluation with chest computed tomography.

Our study was to explore the effects of subchronic particulate matter (PM) exposure on lung injury induced by polyhexamethylene guanidine phosphate (PHMG-p) in a rat model. Specifically, we investigated pulmonary inflammation, fibrosis, and tumor formation using chest computed tomography (CT), and histopathologic examination. PHMG-p was administered intratracheally to 20 male rats. After an initial week of PHMG-p treatment, the experimental group (PM group) received intratracheal administration of PM suspension, while the control group received normal saline. This regimen was continued for 10 weeks to induce subchronic PM exposure. Chest CT scans were conducted on all rats, followed by the extraction of both lungs for histopathological analysis. All CT images underwent comprehensive quantitative and qualitative analyses. Pulmonary inflammation was markedly intensified in rats subjected to subchronic PM exposure in the PM group compared to those in the control. Similarly, lung fibrosis was more severe in the PM group as observed on both chest CT and histopathologic examination. Quantitative chest CT analysis revealed that the mean lesion volume was significantly greater in the PM group than in the control group. Although the incidence of bronchiolo-alveolar hyperplasia was higher in the PM group compared to the control group, this difference was not statistically significant. In summary, subchronic PM exposure exacerbated pulmonary inflammation and fibrosis underlying lung injury induced by PHMG-p.

Longitudinal long term follow up investigation on the carcinogenic impact of polyhexamethylene guanidine phosphate in rat models.

Polyhexamethylene guanidine phosphate (PHMG-p) is a major component in humidifier disinfectants, which cause life-threatening lung injuries. However, to our knowledge, no published studies have investigated associations between PHMG-p dose and lung damage severity with long-term follow-up. Therefore, we evaluated longitudinal dose-dependent changes in lung injuries using repeated chest computed tomography (CT). Rats were exposed to low (0.2 mg/kg, n = 10), intermediate (1.0 mg/kg, n = 10), and high (5.0 mg/kg, n = 10) doses of PHMG-p. All rats underwent repeated CT scans after 10 and 40 weeks following the first exposure. All CT images were quantitatively analyzed using commercial software. Inflammation/fibrosis and tumor counts underwent histopathological evaluation. In both radiological and histopathologic results, the lung damage severity increased as the PHMG-p dose increased. Moreover, the number, size, and malignancy of the lung tumors increased as the dose increased. Bronchiolar-alveolar hyperplasia developed in all groups. During follow-up, there was intergroup variation in bronchiolar-alveolar hyperplasia progression, although bronchiolar-alveolar adenomas or carcinomas usually increase in size over time. Thirty-three carcinomas were detected in the high-dose group in two rats. Overall, lung damage from PHMG-p and the number and malignancy of lung tumors were shown to be dose-dependent in a rat model using repeated chest CT scans during a long-term follow-up.