Impact of historical land use change on the brown bear habitat connectivity in the Polish Carpathians
Background Europe has undergone dynamic land use changes in recent decades that have affected the extent, quality, and connectivity of large carnivore habitats. However, the current distribution of large carnivores also depends on historical land use processes. In this article, we analyse the impact of historical land use changes on the potential connectivity of brown bear habitats in the region linking the western and eastern parts of the Carpathians, one of Europe’s biodiversity hotspots. Methods The analyses were conducted based on elevation, slope, and distance-based, land use-related variables representing four time periods: 1860s, 1930s, 1970s, and 2013, using cost surface and least-cost path analyses. We used two different approaches to create cost surfaces: weighted, where the weights differentiated between variables according to their relative importance, reflecting their role in either bear space selection or avoidance, and unweighted, where all the variables were treated as equally important. Results The results of both approaches showed a gradual improvement in habitat connectivity for brown bears over time, driven by the increase in forest cover observed over the whole analysed period. However, the dynamics of these changes were much higher after the forced post-war resettlement in the 1940s. These tragic events resulted in the removal of settlements over large areas, substantially reducing human pressure and allowing brown bears to spread into new territories, expanding their habitats and creating new connectivity opportunities. We found that up to 40% of the current corridor was stable since mid-19th century. Our analysis shows that the current population decline in many rural areas of Europe may have positive implications for the habitats and population connectivity of large carnivores, but careful planning is needed to avoid negative interactions with local communities.
Spatial and Geographic Information Science
Szwagierczak et al. (2025) Impact of historical land use change on the brown bear habitat connectivity in the Polish Carpathians. PeerJ 13:e20295 https://doi.org/10.7717/peerj.20295
Integrated bioinformatics screening and experimental validation: construction of a LUAD prediction model based on Treg-related genes
Background The 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. Methods A 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. Result Among 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. Conclusion We 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.
Zhao et al. (2025) Integrated bioinformatics screening and experimental validation: construction of a LUAD prediction model based on Treg-related genes. PeerJ 13:e20287 https://doi.org/10.7717/peerj.20287
IPI score as a new prognostic index in extensive stage small cell lung cancer
Background Personalized 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. Results Patients 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. Conclusion The 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.
Ağaoğlu et al. (2025) IPI score as a new prognostic index in extensive stage small cell lung cancer. PeerJ 13:e20343 https://doi.org/10.7717/peerj.20343
The association of maternal pre-pregnancy body mass index with macrosomia: a birth cohort study from China
Objective To investigate the association between pre-pregnancy body mass index (BMI) and the risk of macrosomia through a preconception-early pregnancy-birth cohort in China. Methods Among 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. Results A 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. Conclusions Pre-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.
Yan et al. (2025) The association of maternal pre-pregnancy body mass index with macrosomia: a birth cohort study from China. PeerJ 13:e20332 https://doi.org/10.7717/peerj.20332
Research progress of tsRNAs in kidney diseases
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.
Wang et al. (2025) Research progress of tsRNAs in kidney diseases. PeerJ 13:e20315 https://doi.org/10.7717/peerj.20315
A preliminary assessment of population genetic structure of the common vampire bat (Desmodus rotundus) in Colombia
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.
Van de Vuurst et al. (2025) A preliminary assessment of population genetic structure of the common vampire bat (Desmodus rotundus) in Colombia. PeerJ 13:e20306 https://doi.org/10.7717/peerj.20306
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)
Objectives To 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. Methods A 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. Results Through 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. Conclusions The 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.
Li et al. (2025) 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). PeerJ 13:e20280 https://doi.org/10.7717/peerj.20280
Patient satisfaction after outpatient hysteroscopy: a retrospective descriptive study
Background The 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. Methods A 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. Results A 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. Conclusions Outpatient 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.
Sanchez Carbonell et al. (2025) Patient satisfaction after outpatient hysteroscopy: a retrospective descriptive study. PeerJ 13:e20272 https://doi.org/10.7717/peerj.20272
TSCytoPred: a deep learning framework for inferring cytokine expression trajectories from irregular longitudinal gene expression data to enhance multi-omics analyses
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.
Choi et al. (2025) TSCytoPred: a deep learning framework for inferring cytokine expression trajectories from irregular longitudinal gene expression data to enhance multi-omics analyses. PeerJ 13:e20270 https://doi.org/10.7717/peerj.20270
Assessment of distinct effects of Parinari curatellifolia Planch.ex Benth Ethanolic leaf extract on glucose transport in different cell types
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.
Omale et al. (2025) Assessment of distinct effects of Parinari curatellifolia Planch.ex Benth Ethanolic leaf extract on glucose transport in different cell types. PeerJ 13:e20269 https://doi.org/10.7717/peerj.20269