title: PeerJ description: Articles published in PeerJ link: https://peerj.com/articles/index.rss3?journal=peerj&page=30 creator: info@peerj.com PeerJ errorsTo: info@peerj.com PeerJ language: en title: Integrated bioinformatics screening and experimental validation: construction of a LUAD prediction model based on Treg-related genes link: https://peerj.com/articles/20287 last-modified: 2025-11-11 description: BackgroundThe prognosis of lung adenocarcinoma (LUAD) is poor, and clinical treatment mainly comprises a combination of traditional therapy and immunotherapy. However, the role and mechanism of tumor-infiltrating regulatory T cells (Tregs) in immunotherapy remain controversial. Therefore, we aimed to determine the role of Tregs in LUAD and to construct a relevant prognostic model for future clinical treatment.MethodsA LUAD dataset was downloaded from the Gene Expression Omnibus (GEO) database, screened, integrated, and divided into test and validation datasets. CIBERSORT and weighted correlation network analysis (WGCNA) algorithms were combined to screen for Treg cell-related modules. Minimum absolute contraction and selection operator (LASSO) and univariate and multivariate Cox regression analyses were used to screen genes in the key modules and construct Treg-related prognostic models. Then, the expression differences of genes in the prognostic model were analyzed, and the results were verified by Western blotting.ResultAmong all cluster modules, the correlation between the brown module and Treg s (R2 = 0.43, P = 1e − 30) was the highest. After LASSO and univariate and multivariate Cox regression screening, six genes (ADARB2, B3GALT, FER, LTB4R2, N6AMT1, and SCN9A) were selected to construct the prognosis model, and the prognosis of low-risk patients was found to be better than that of high-risk patients. Finally, the SCN9A gene with the highest correlation with the model was selected and verified using Western blot analysis. The results showed that the expression of Treg surface markers in LUAD cells was increased, and the expression of SCN9A was decreased compared with that in normal lung epithelial cells.ConclusionWe identified the role of Treg-related genes in LUAD, constructed and verified a related prognostic model, and explored a potential therapeutic target, SCN9A, to provide a new perspective for the clinical treatment of LUAD. creator: Tian Zhao creator: Yan Yao creator: Yan Sun creator: Qingliang Lv creator: Changgang Sun creator: Yining Cheng creator: Chundi Gao creator: Jing Zhuang uri: https://doi.org/10.7717/peerj.20287 license: https://creativecommons.org/licenses/by-nc/4.0 rights: ©2025 Zhao et al. title: IPI score as a new prognostic index in extensive stage small cell lung cancer link: https://peerj.com/articles/20343 last-modified: 2025-11-10 description: BackgroundPersonalized prognostic assessment in extensive-stage small cell lung cancer (ES-SCLC) necessitates a comprehensive understanding of systemic inflammatory markers and their impact on survival outcomes. This study aimed to evaluate the prognostic significance of a novel Inflammatory Prognostic Index (IPI) score, derived from four inflammation-related biochemical markers—albumin, C-reactive protein (CRP), neutrophils, and lymphocytes—in patients with ES-SCLC.Methods Patients diagnosed with ES-SCLC were eligible if adequate clinical, pathological, and follow-up data were available. The IPI score was derived using the formula: C-reactive protein × neutrophil-to-lymphocyte ratio (NLR)/serum albumin. The threshold value for the IPI score was identified using receiver operating characteristic (ROC) curve analysis within the cohort and was applied in an exploratory manner. Based on the predefined cut-off, patients were stratified into low- and high-IPI groups. The log-rank test was used to compare survival times, while Kaplan–Meier curves and Cox regression analyses assessed variables associated with long-term survival. Overall survival (OS) served as the primary endpoint, and progression-free survival (PFS) was evaluated as a secondary endpoint.ResultsPatients with a high IPI score had a mean OS of 9 months (95% CI [4.8–13.2]), while those with a low IPI score had a mean OS of 23 months (95% CI [11.4–34.6]), a statistically significant difference (p = 0.005). The prognostic significance of IPI was confirmed in both univariate (p = 0.003) and multivariate (p = 0.012) analyses.ConclusionThe IPI score in ES-SCLC patients was associated with prognosis, with a high IPI score indicating poorer OS. These findings should be considered hypothesis-generating and warrant validation in larger prospective cohorts. creator: Ahmet Burak Ağaoğlu creator: Ferhat Ekinci creator: Mustafa Şahbazlar creator: Atike Pınar Erdoğan uri: https://doi.org/10.7717/peerj.20343 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Ağaoğlu et al. title: The association of maternal pre-pregnancy body mass index with macrosomia: a birth cohort study from China link: https://peerj.com/articles/20332 last-modified: 2025-11-10 description: ObjectiveTo investigate the association between pre-pregnancy body mass index (BMI) and the risk of macrosomia through a preconception-early pregnancy-birth cohort in China.MethodsAmong the 12,254 women initially recruited between July 2018 and December 2021, a total of 11,438 (drop out rate: 6.66%) mother–infant pairs were included in the final analysis after excluding participants with missing data on key variables or lost to follow-up. We collected basic demographic characteristics and lifestyle behavior information of the subjects through questionnaires and practical measurements, and conducted further follow-up for pregnancy outcomes. The study assessed the association between pre-pregnancy BMI-defined categories (underweight, normal weight, overweight, and obesity) and macrosomia using multivariable logistic regression models, adjusting for sociodemographic characteristics, lifestyle behaviors, and maternal clinical factors during pregnancy. A linear trend test was also conducted. Moreover, we utilized restricted cubic spline models with three knots (placed at the 10th, 50th, and 90th percentiles of BMI) and polynomial regression to investigate the non-linear relationship of pre-pregnancy BMI with macrosomia.ResultsA total of 11,438 subjects were included in this study, among whom 645 infants were diagnosed with macrosomia, resulting in a prevalence of 5.64%. The results indicated that, compared with the normal weight group, overweight women had a significantly higher risk of macrosomia (odds ratio (OR) = 1.66, 95% CI [1.35–2.01]), as did obese women (OR = 1.66, 95% CI [1.13–2.45]), while underweight women had a significantly lower risk (OR = 0.55, 95% CI [0.41–0.73]). A similar association pattern between pre-pregnancy BMI and grade 1 macrosomia was observed, consistent with that for overall macrosomia. The use of restricted cubic splines revealed that the prevalence of macrosomia/grade 1 macrosomia increased with rising pre-pregnancy BMI. Furthermore, when we stratified the data by covariates, the nonlinear relationship between pre-pregnancy BMI and macrosomia/grade 1 macrosomia persisted. The results of the polynomial regression showed a gradual increase in fetal birth weight with increasing pre-pregnancy BMI levels.ConclusionsPre-pregnancy overweight and obesity were associated with higher risks of macrosomia. Therefore, these findings suggest that promoting healthy weight management before conception may be an effective public health strategy to reduce the risk of macrosomia and improve perinatal outcomes. creator: Mingxin Yan creator: Yunbo Zhang creator: Doudou Zhao creator: Yan Zhao creator: Danmeng Liu creator: Li Shan creator: Yang Mi creator: Leilei Pei creator: Pengfei Qu uri: https://doi.org/10.7717/peerj.20332 license: https://creativecommons.org/licenses/by/4.0/ rights: © 2025 Yan et al. title: Research progress of tsRNAs in kidney diseases link: https://peerj.com/articles/20315 last-modified: 2025-11-10 description: Transfer RNA-derived small RNAs (tsRNAs) are a class of regulatory non-coding RNAs generated through enzymatic cleavage of precursor or mature tRNAs. In recent years, tsRNAs have garnered growing interest in nephrology due to their diverse biological functions and potential clinical significance. This review summarizes current research on the roles of tsRNAs in kidney diseases, including their involvement in gene expression regulation, signal transduction, apoptosis, and inflammation-related pathways. We further highlight their emerging mechanistic contributions in conditions such as acute kidney injury, chronic kidney disease, and glomerulonephritis. Finally, we discuss the prospects of tsRNAs as novel biomarkers for early diagnosis, prognosis assessment, and therapeutic targeting in renal disorders, aiming to offer new insights into kidney disease pathogenesis and management. creator: Jialing Wang creator: Yanzhe Wang creator: Fengqin Li creator: Xinmiao Xie creator: Xinyue Chen creator: Tong Wu creator: Xiaoxia Wang uri: https://doi.org/10.7717/peerj.20315 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Wang et al. title: A preliminary assessment of population genetic structure of the common vampire bat (Desmodus rotundus) in Colombia link: https://peerj.com/articles/20306 last-modified: 2025-11-10 description: Rabies virus (RABV) is a neglected tropical pathogen in Latin America predominantly transmitted to mammals by the common vampire bat (Desmodus rotundus). Transmission of RABV among D. rotundus individuals and colonies is a function of individual dispersal between colonies, patterns of which can be inferred from population genetic structure. Nevertheless, a baseline assessment of population genetic structure among D. rotundus individuals has been lacking for some areas of South America, including Colombia, where RABV has impacted some areas more heavily than others. To assess individual dispersal and hence population structure of D. rotundus across heterogenous landscapes in Colombia, we conducted a cross-elevational assessment of population genetic variation using nuclear microsatellite DNA markers. We quantified genetic variance and geographic distribution of genetically clustered D. rotundus individuals across the landscape of Colombia with reference to a comparator group of individuals from Mexico. We found population-level differentiation and genetic structure within our collection of samples, and we inferred patterns of dispersal and genetically effective migration between D. rotundus populations. Analysis of molecular variance (AMOVA) showed considerable variation among inferred populations in Colombia (14.9% of genetic covariance, df = 2, Sum of Squares = 164.9, Sigma = 1.28, ϕ = 0.15, p = 0.01), with an associated G′ST of 0.34. Direct migrant identification suggested 15 likely first-generation migrants among sites. We found that there were no statistically significant differences between the landscapes occupied by the inferred populations, though our limited sampling size suggests a trend toward differences in relation to elevation (t = 1.91, df = 71.72, p = 0.06). These results indicate that D. rotundus is mobile within the region, potentially contributing to RABV transmission among colonies. Our results support previous hypotheses ecological resistance-mediated patterns of dispersal for D. rotundus, and inform future research on the role of genetic connectivity in RABV transmission among bat colonies. creator: Paige Van de Vuurst creator: Analorena Cifuentes-Rincon creator: Andrea S. Bertke creator: Diego Soler-Tovar creator: Nicolás Reyes-Amaya creator: Fabiola Rodriguez Arévalo creator: Julieth Stella Cárdenas Hincapié creator: Jhon Rivera-Monroy creator: Luis E. Escobar creator: Eric Hallerman uri: https://doi.org/10.7717/peerj.20306 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Van de Vuurst et al. title: Development and validation of a functional assessment tool for Chinese inpatient rehabilitation: insights from a Delphi study based on the International Classification of Functioning, Disability, and Health (ICF) link: https://peerj.com/articles/20280 last-modified: 2025-11-10 description: ObjectivesTo develop and validate a functional assessment tool for inpatient rehabilitation in China using the International Classification of Functioning, Disability, and Health (ICF) Rehabilitation Set (ICF-RS) framework and the Delphi method.MethodsA three-round Delphi process engaged 15 experts to refine ICF-RS items via a 5-point importance questionnaire. Validation involved 2,574 inpatients assessed with a numerical rating scale. Reliability (Cronbach’s alpha) and structural validity (factor analysis) were evaluated.ResultsThrough three rounds of Delphi meetings, 10, 2, and 1 ICF items with mean importance scores below the threshold were respectively removed, resulting in 17 ICF items achieving expert consensus for inclusion in the final assessment tool, named ICF-RS-17. Expert authority coefficient was 0.81. Cronbach’s alpha exceeded 0.9. Factor analysis identified two factors explaining 68.86% (admission) and 73.25% (discharge) of variance, confirming structural validity.ConclusionsThe study developed a 17-item functional assessment tool, ICF-RS-17, demonstrating strong reliability and validity for inpatient rehabilitation. These findings help promote the application of the ICF in clinical settings, enhance rehabilitation clinical management, and potentially support the further development of rehabilitation insurance policies. creator: Jiahui Li creator: Guangxu Xu creator: Juan Jin creator: Na Li creator: Jianan Li creator: Shouguo Liu uri: https://doi.org/10.7717/peerj.20280 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Li et al. title: Patient satisfaction after outpatient hysteroscopy: a retrospective descriptive study link: https://peerj.com/articles/20272 last-modified: 2025-11-10 description: BackgroundThe aim of the study is to analyse the overall satisfaction level of patients undergoing diagnostic and/or therapeutic hysteroscopy in an ambulatory setting and examine factors related to satisfaction.MethodsA retrospective descriptive study was conducted to analyse outpatient hysteroscopies performed between January 2020 and June 2022 at the University Hospital of Igualada. Patient demographic and clinical data as well as hysteroscopic features were collected. A telephonic questionnaire on patient satisfaction was conducted retrospectively.ResultsA total of 435 hysteroscopies were analysed. Hysteroscopy was successful in 95.6% of them with a clinical remission in 69.8% of patients. The mean pain score was 3.33 (Visual Analogue Scale). An average overall satisfaction score of 9 was obtained. Pain was the main reason in patients with low satisfaction ratings. A positive correlation was found between the patient satisfaction score and the level of information received before the procedure. An inverse relationship was detected between the patient satisfaction score and the pain experienced during the hysteroscopy.ConclusionsOutpatient diagnostic and/or therapeutic hysteroscopy is a technique accepted by the majority of patients and with a high level of satisfaction. Variables such as pain or the previous information received are important and directly related to the final satisfaction level of the procedure. creator: Claudia Sanchez Carbonell creator: Jennifer Rovira Pampalona creator: Carla Oliveres Amor creator: Alexandra Caballol Arteaga creator: Maria Degollada creator: Pere Brescó Torras uri: https://doi.org/10.7717/peerj.20272 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Sanchez Carbonell et al. title: TSCytoPred: a deep learning framework for inferring cytokine expression trajectories from irregular longitudinal gene expression data to enhance multi-omics analyses link: https://peerj.com/articles/20270 last-modified: 2025-11-10 description: Cytokines play a crucial role in immune system regulation, mediating responses from pathogen defense to tissue-damaging inflammation. Excessive cytokine production is implicated in severe conditions such as cancer progression, hemophagocytic lymphohistiocytosis, and severe cases of Coronavirus disease-2019 (COVID-19). Studies have shown that cytokine expression profiles serve as biomarkers for disease severity and mortality prediction, with machine learning (ML) methods increasingly employed for predictive analysis. To improve patient outcome predictions, treatment adaptation, and survival rates, longitudinal analysis of cytokine profiles is essential. Time-series cytokine profiling has been linked to tumor response, overall survival in various cancers, and acute encephalopathy. Similarly, COVID-19 severity and patient outcomes correlate with cytokine expression dynamics over time. However, challenges remain due to the limited availability of time-series cytokine data, restricting broader experimental applications and robust predictive modeling. Recent advancements indicate that cytokine expression can be computationally inferred using gene expression data and transcription factor interactions. Inferring cytokine levels from existing gene expression datasets could enhance early disease detection and treatment response predictions while reducing profiling costs. This work proposes TSCytoPred, a deep learning-based model trained on time-series gene expression data to infer cytokine expression trajectories. TSCytoPred identifies genes relevant for predicting target cytokines through interaction relationships and high correlation. These identified genes are subsequently utilized in a neural network incorporating an interpolation block to estimate cytokine expression trajectories between observed time points. Performance evaluations using a COVID-19 dataset demonstrate that TSCytoPred significantly outperforms baseline regression methods, achieving the highest coefficient of determinataion (R2) and the lowest mean absolute error (MAE). Furthermore, cytokine data inferred by TSCytoPred enhances COVID-19 patient severity risk predictions, demonstrating the model’s clinical utility. TSCytoPred can be effectively applied to datasets with limited time points and accommodates longitudinal datasets containing irregular temporal gaps, thereby enhancing disease outcome analysis such as in COVID-19 cases and expanding the applicability of multi-omics datasets in rare disease contexts with missing multi-omics samples. TSCytoPred is publicly available at https://github.com/joungmin-choi/TSCytoPred. creator: Joung Min Choi creator: Heejoon Chae uri: https://doi.org/10.7717/peerj.20270 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Choi and Chae title: Assessment of distinct effects of Parinari curatellifolia Planch.ex Benth Ethanolic leaf extract on glucose transport in different cell types link: https://peerj.com/articles/20269 last-modified: 2025-11-10 description: Extracts of Parinari curatellifolia Planch.ex Benth have been used as a traditional medicine in Sub-Saharan Africa for the management of various ailments including diabetes and has been shown to reduce plasma glucose levels in rat models of diabetes. Treatment of a range of mammalian cell lines with P. curatellifolia ethanolic leaf extract (PCE) for 24–48 h, typically between 0 and 100 µg/mL, revealed different actions: in 3T3-L1 adipocytes, PCE markedly inhibited insulin-stimulated glucose transport (50% inhibition at 100 µg/mL), whereas by contrast PCE-treatment of Caco-2 cells, a model of the intestinal epithelia at the same concentration, increased glucose transport ∼2-fold. This effect was accompanied by increased glucose transporter-1 (GLUT1) levels but is independent of changes in the level of Akt, Adenosine monophosphate-activated protein kinase (AMPK) or p38. Our data suggest that the antidiabetic effects of extracts of P. curatellifolia may arise by increased absorption of glucose from the gut and thus distribution to other cells/tissues. Our data further highlight the importance of screening metabolic actions of plant extracts against multiple cell lines, as these can often exhibit distinct cell-type-specific responses, and further suggest that relatively low doses of PCE (up to 100 µg/mL) could warrant investigation in in vivo models of disease. creator: Simeon Omale creator: John C. Aguiyi creator: Samuel Ede creator: Layla Ryalls creator: Runfei Ye creator: Busra Basbaydar creator: Gwyn W. Gould creator: Shaun K. Bremner-Hart uri: https://doi.org/10.7717/peerj.20269 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Omale et al. title: Impact of insular landscape features on the population genetics of a threatened climbing palm, Korthalsia rogersii Becc., endemic to the Andaman Islands link: https://peerj.com/articles/20265 last-modified: 2025-11-10 description: Despite the critical structural and functional roles of palms in tropical forest ecosystems and their importance in the local economy and livelihood, palms face significant threats from habitat loss and economic exploitation. Many endemic palms on tropical islands warrant conservation strategies aimed at augmenting the existing gene pool to support effective management and long-term protection of genetic diversity. This study investigated the genetic diversity and structure of Korthalsia rogersii, a threatened climbing palm (rattan) endemic to the Andaman Islands in the Bay of Bengal, across seven known populations (including recently identified ones) using microsatellite markers. The aim was to formulate informed conservation strategies by understanding how the island landscape influences the population genetic divergence of the species. Although heterozygosity and bottleneck analyses did not reveal significant genetic diversity loss, a positive correlation between population size and the number of observed alleles points to a potential ongoing decline. Moderate to high genetic differentiation was observed between populations, with geographical isolation contributing to divergence, particularly in the Interview island population. Notably, the South Andaman population (Chidiya Tapu) harbours the highest number of private alleles, despite exhibiting low overall genetic divergence, indicating it may serve as a reservoir of lost genetic diversity. Further, the Bakultala population shows significant within-population relatedness and reduced allelic diversity, indicative of genetic isolation and demographic decline. These findings provide preliminary insights into the role of the island landscapes in the Andaman archipelago in shaping population genetic divergence among plant taxa. Effective conservation strategies should target gene diversity, genetic structure and hotspots of unique alleles identified in the study, prioritising both population size enhancement and genetic augmentation to ensure the long-term survival of K. rogersii. creator: Sarath Paremmal creator: Modhumita Dasgupta creator: Sreekumar VB creator: Suma Dev uri: https://doi.org/10.7717/peerj.20265 license: https://creativecommons.org/licenses/by/4.0/ rights: ©2025 Paremmal et al.