Association between MTHFR gene polymorphisms and H-type hypertension in patients with ischemic stroke
Background Methylenetetrahydrofolate reductase (MTHFR) is a key enzyme in homocysteine metabolism. Its 677C>T and 1298A>C polymorphisms can reduce enzyme activity, potentially elevating homocysteine levels. H-type hypertension (hypertension with homocysteine ≥10 μmol/L) is an important risk factor for ischemic stroke, and its synergistic effect exacerbates vascular damage. However, the association between these MTHFR polymorphisms and elevated homocysteine levels in patients with hypertension complicated by ischemic stroke remains unclear. This study aimed to investigate the association between MTHFR gene polymorphisms and H-type hypertension in patients with ischemic stroke. Methods A total of 215 patients with ischemic stroke and hypertension admitted to the Department of Neurology at the Taian City Central Hospital from June 2021 to December 2022 were enrolled. General clinical data and biochemical indicators were collected. MTHFR genotyping was performed using a universal sequencing kit and a TL998A fluorescence detector. Linkage disequilibrium was analyzed via SHEsis software. Statistical analyses were conducted using SPSS 25.0. P < 0.05 indicates that the difference is statistically significant. Results Among patients with ischemic stroke combined with hypertension in this region, the proportion of H-type hypertension was 89.3%. The proportion of males in the H-type hypertension group was significantly higher than in the non-H-type hypertension group (P < 0.05). The genotype and allele distributions of MTHFR (677C>T) (risk allele: T) differed significantly between groups (P < 0.05): the H-type group had a higher frequency of the TT genotype (47.4% vs. 17.4%) and T allele (67.2% vs. 50.0%). Multivariate logistic regression analysis showed that the MTHFR (677C>T) TT genotype was an independent risk factor for H-type hypertension (P = 0.021, OR = 2.615, 95%CI [1.154–5.926]). For haplotypes with a frequency >3%, there were three haplotypes of MTHFR (677C>T)/(1298A>C). The C-A haplotype was a protective factor for H-type hypertension (P = 0. 028, OR = 0.485, 95%CI [0.252–0.934]), while the T-A haplotype was a risk factor (P = 0.022, OR = 2.029, 95%CI [1.096–3.756]). Conclusion In patients with ischemic stroke, the MTHFR (677C>T) TT genotype is an independent risk factor for H-type hypertension. For haplotypes with a frequency >3%, the C-A haplotype was a protective factor for H-type hypertension, whereas the T-A haplotype was a risk factor.
Zhou et al. (2025) Association between MTHFR gene polymorphisms and H-type hypertension in patients with ischemic stroke. PeerJ 13:e20210 https://doi.org/10.7717/peerj.20210
Risk factors for bronchopulmonary dysplasia in preterm infants: a systematic review and meta-analysis
Background Bronchopulmonary dysplasia (BPD) is the most common respiratory disease in preterm infants. As medical advancements have increased the survival rate of preterm infants, the prevalence of BPD has also increased, representing a significant societal burden. The pathogenesis of BPD is multifactorial, involving both genetic and environmental factors. Although numerous studies have examined risk factors for BPD, their findings are inconsistent. Few meta-analyses exist, yet most focus on risk factors for the development of pulmonary hypertension in infants with BPD. The primary aim of this study was to identify the risk factors for BPD. Methods The study protocol was registered with PROSPERO (CRD42024616871). A comprehensive literature search was conducted in the PubMed, Embase, Cochrane Library, and Web of Science databases for case-control and cohort studies investigating risk factors for BPD. The search was completed on 22 November 2024, and the data were analyzed using Review Manager 5.3.5 and Stata 15.1. Results A total of 23 studies were included in the analysis, encompassing 14,729 patients in the bronchopulmonary dysplasia (BPD) group and 19,101 in the non-bronchopulmonary dysplasia (non-BPD) group. The meta-analysis revealed that chorioamnionitis (CA) was associated with an increased risk of BPD (OR = 1.52, 95% CI [1.23–1.87]), as was premature rupture of membranes (PROM; OR = 1.42, 95% CI [1.02–1.98]). Additionally, hypertensive disorders of pregnancy (HDP) were identified as a significant risk factor for BPD (OR = 2.73, 95% CI [1.31–5.69]). Other notable risk factors included lower gestational age (GA; MD = −1.86, 95% CI [−2.35 to −1.38]), male sex (OR = 1.41, 95% CI [1.14–1.75]), and being small for gestational age (SGA; OR = 3.14, 95% CI [1.03–9.60]). Furthermore, the analysis indicated that mechanical ventilation (MV; MD = 16.55, 95% CI [9.68–23.41]), oxygen administration (MD = 50.91, 95% CI [37.40–64.42]), and blood transfusion (OR = 1.38, 95% CI [1.06–1.81]) were significant risk factors for BPD. Other variables that were identified as significant risk factors included patent ductus arteriosus (PDA; OR = 1.75, 95% CI [1.35–2.27]), sepsis (OR = 1.88, 95% CI [1.44–2.46]), and respiratory distress syndrome (RDS; OR = 6.37, 95% CI [4.00–10.13]). Conclusions Significant risk factors for BPD include CA, PROM, HDP, lower GA, male sex, SGA, MV, oxygen administration, blood transfusions, PDA, sepsis, and RDS. These findings hold potential clinical significance for predicting BPD pathogenesis.
Xiong et al. (2025) Risk factors for bronchopulmonary dysplasia in preterm infants: a systematic review and meta-analysis. PeerJ 13:e20202 https://doi.org/10.7717/peerj.20202
Seasonally modulated nonlinear effects of PM2.5 on pediatric respiratory health: evidence from a time-series analysis in urban China
Background Although many studies have shown that fine particulate matter (PM2.5) is associated with respiratory diseases (RDs) in children, fewer studies have examined this association in developing countries. We aimed to use the latest PM2.5 standards to investigate the interaction between PM2.5 and RDs among children in Guangzhou. Methods We included 18,291 pediatric inpatients aged 0–14 years with a primary diagnosis of RDs admitted to hospitals in Guangzhou, China, from January 1, 2018, to December 31, 2021. The association between PM2.5 and RDs was analysed using a non-linear distributed lag model, and additional subgroup analyses were performed based on sex and season. Results The association of PM2.5 with RDs showed a zigzag shape. Specifically, the cumulative effects of PM2.5 at the 25th, 50th, and 75th percentiles, with a lag of 0–14 days, were associated with increases in the relative risk (RR) of RDs by 0.4% (95% confidence interval (CI) [1.000–1.007]), 3.4% (95% CI [1.004–1.065]), and 7.7% (95% CI [1.010–1.149]), respectively. Additionally, for each 10 µg/m3 increase in PM2.5 concentration, the on-the-day lagged effect on lag day 4 and lag day 7 was associated with an elevated risk of RDs, with RR of 1.018 (95% CI [1.002–1.034]) and 1.016 (95% CI [1.000–1.032]), respectively. Additionally, PM2.5 exposure significantly increased the risk of RDs in boys and elevated that risk in children during both summer and winter seasons. Conclusions This study reveals a significant effect of PM2.5 exposure on RDs in children, with notably elevated risks during summer and winter seasons. These findings underscore the critical importance of implementing air quality improvement measures to safeguard children’s health, particularly in developing countries.
Liu et al. (2025) Seasonally modulated nonlinear effects of PM2.5 on pediatric respiratory health: evidence from a time-series analysis in urban China. PeerJ 13:e20187 https://doi.org/10.7717/peerj.20187
Development and validation of the AUDEXCEL algorithm as a diagnostic tool for occupational noise-related hearing disorder
Background Occupational noise-related hearing disorder (ONRHD) is an occupational disease that poses a significant challenge for workers both globally and locally. To address this, the study aimed to develop and validate AUDEXCEL, an Excel-based algorithm designed to diagnose ONRHD among workers in Malaysia. Materials & Methods This cross-sectional study involved audiograms from 320 workers. These audiograms were first analyzed by experienced occupational health doctors (OHDs) to establish a gold standard diagnosis. The same audiograms were then assessed using the AUDEXCEL algorithm, which was validated through 5-fold cross-validation. Validity (sensitivity, specificity, positive predictive value, and negative predictive value) and reliability (Cohen’s kappa coefficient) were evaluated for normal hearing, hearing loss, hearing impairment, permanent standard threshold shift (PSTS), temporary standard threshold shift (TSTS), and noise-induced hearing loss (NIHL). Results The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for normal hearing, hearing loss, PSTS, and TSTS were all 100.0%, with perfect agreement (κ = 1.000). For hearing impairment, sensitivity, specificity, PPV, and NPV were 100.0%, 99.5%, 99.5%, and 100.0%, respectively, with almost perfect agreement (κ = 0.994). For NIHL, sensitivity, specificity, PPV, and NPV were 90.3%, 98.0%, 95.0%, and 96.1%, respectively, also showing almost perfect agreement (κ = 0.922). Conclusions AUDEXCEL demonstrated high validity and reliability in replicating expert diagnoses and may serve as a supportive diagnostic aid for ONRHD. However, its use should be complemented by clinical and occupational exposure assessments due to the inherent complexity of diagnosing ONRHD.
Yew et al. (2025) Development and validation of the AUDEXCEL algorithm as a diagnostic tool for occupational noise-related hearing disorder. PeerJ 13:e20149 https://doi.org/10.7717/peerj.20149
Antimicrobial activity of Andrographis paniculata intimate wash and commercial formulations against vaginal pathogens using the broth microdilution method
Background This study aims to evaluate the antimicrobial efficacy of a newly formulated Andrographis paniculata intimate wash in comparison with commercial brands (SebaMed®, Sumber Ayu, Lactacyd®, and Good Virtue & Co.) against vaginal pathogens. The antimicrobial activity of each formulation was tested against Streptococcus agalactiae, Escherichia coli, and Candida albicans. Additionally, Lactobacillus crispatus was tested to ensure the formulations did not inhibit normal vaginal flora. Methods The broth microdilution method was used to assess antimicrobial efficacy by calculating the percentage of microbial inhibition. Minimum inhibitory concentration (MIC) was determined for A. paniculata and commercial intimate washes against the tested pathogens, except for L. crispatus, due to the inability to observe turbidity. Minimum bactericidal concentration (MBC) was evaluated for the A. paniculata intimate wash against the same pathogens. Results The A. paniculata intimate wash showed the highest percentage of microbial inhibition across all tested pathogens. It also recorded MIC and MBC values of 3.125 mg/ml against E. coli and C. albicans. Among commercial products, SebaMed® demonstrated the strongest antimicrobial effect against S. agalactiae at the same MIC concentration. The study concluded that the A. paniculata intimate wash is a potentially effective treatment for selected vaginal pathogens at higher concentrations and may promote the growth of L. crispatus. SebaMed®, a clinically established product, also exhibited notable antimicrobial properties. However, further in vivo and clinical trials are necessary to confirm efficacy and assess toxicity. The study highlights the need for continued research into the potential of herbal intimate washes for treating vaginal infections.
Razian et al. (2025) Antimicrobial activity of Andrographis paniculata intimate wash and commercial formulations against vaginal pathogens using the broth microdilution method. PeerJ 13:e20144 https://doi.org/10.7717/peerj.20144
Biomechanical analysis of iliosacral and transiliac–transsacral screw combinations for fixation of undisplaced Denis II vertical shear fractures in dysmorphic sacrum
Background Percutaneous iliosacral screws (ISS) and transiliac-transsacral screws (TTS) are effective for treating posterior pelvic ring instability. However, the biomechanical stability of undisplaced sacral dysmorphism fractures remains underexplored. This study evaluated various ISS and TTS combinations to provide a clinical reference for fixing such fractures. Methods A finite element model of a complete Denis type II dysmorphic sacral fracture (extending through the sacral foramen) was developed. The stability of the posterior pelvic ring was evaluated using seven fixation techniques: S1-ISS (Group 1), S2-ISS (Group 2), S1-ISS + S2-ISS (Group 3), S2-TTS (Group 4), anterior S1-ISS + S2-TTS (Group 5), middle S1-ISS + S2-TTS (Group 6), and posterior S1-ISS + S2-TTS (Group 7). In all models, the anterior pelvic ring was fixed with pubic ramus screws. The upper sacral surface was subjected to six loading modes to simulate physiological states: standing, forward flexion, left flexion, right flexion, left rotation, and right rotation. The following parameters were recorded and analyzed: vertical displacement and sagittal angular displacement of the upper sacral surface, relative displacement of five pairs of observation points on the anterior fracture line, and maximum Von Mises stress and deformation of the S1 and S2 screws. Results The finite element analysis revealed that the maximum stress in all internal fixation groups across the six loading modes was below the yield strength of titanium alloy, indicating no risk of implant failure. Screw deformation was highest in G1 and lowest in G5 for the S1 segment, and highest in G2 and lowest in G 5 for the S2 segment. G5 also exhibited the minimum vertical and angular displacements of the sacral upper surface in all motion states. Conclusion This study demonstrates that S1-ISS combined with S2-TTS fixation provides excellent biomechanical stability for undisplaced vertical fractures of the sacral dysmorphism, particularly the combination of anterior S1-ISS and S2-TTS. This fixation method offers a promising clinical treatment option.
Zhao et al. (2025) Biomechanical analysis of iliosacral and transiliac–transsacral screw combinations for fixation of undisplaced Denis II vertical shear fractures in dysmorphic sacrum. PeerJ 13:e20139 https://doi.org/10.7717/peerj.20139
Characterizing programmed cell death features in osteoarthritis through integrative multiomics and machine learning analysis
Background Programmed cell death (PCD) is an essential biological process in maintaining tissue homeostasis and eliminating damaged or unnecessary cells. Signaling molecules profoundly affect cellular metabolism and are crucial in various diseases; however, their role in osteoarthritis (OA) remains unclear. This study aimed to systematically evaluate the predictive value, genetic alterations, and therapeutic implications of PCD-associated genes in OA. Methods We performed multiomics analyses, integrating transcriptomic and single-cell transcriptome data. The biological importance of PCD genes was investigated using differential expression analysis, functional enrichment analysis, pathway analysis, weighted gene co-expression network analysis, and many machine learning models. Additionally, we evaluated diagnostic efficacy, immune infiltration, and competing endogenous RNA networks associated with these genes. We established an in vitro OA model using hypoxic treatment of ATDC5 chondrocyte cells and conducted extensive research on the expression and function of key PCD-related genes. Results The key PCD gene was identified as markedly dysregulated in OA. Elevated expression of S100A9, PMAIP1, and EDA2R was observed in OA samples, indicating these genes as potential risk factors for OA. However, FASN expression was reduced in OA samples compared to the normal group, indicating its potential role as a protective gene in OA. Furthermore, PCD emerged as a reliable diagnostic marker with improved predictive accuracy. Functional experimental studies demonstrated that S100A9, PMAIP1, and EDA2R downregulation through small interfering RNA, alongside FASN gene overexpression through plasmid transfection, significantly ameliorated hypoxia-induced reductions in cell viability, decreased hyaluronan secretion, and increased secretion of inflammatory cytokines (tumor necrosis factor-alpha and interleukin-6). Conclusion Utilizing a multi-model synergistic artificial intelligence framework, we demonstrated the remarkable potential of PCD to provide individualized vulnerability assessments and customized recommendations for metabolic and immunotherapeutic interventions in OA. We identified abnormal expression of four hub genes associated with PCD and examined their biological functions, thereby facilitating new avenues for research into the role of PCD in OA and other immune-mediated diseases.
Sun et al. (2025) Characterizing programmed cell death features in osteoarthritis through integrative multiomics and machine learning analysis. PeerJ 13:e20104 https://doi.org/10.7717/peerj.20104
Contrasting microbial assembly patterns in the woody endosphere of hybrid and non-hybrid Populus trees
Endophytes asymptomatically infect virtually all plant species, yet little is known about endophyte community assembly and diversity within the woody tissues of forest trees. We utilised phylogenetic null models of alpha (ses.MNTDab and ses.MPDab) and beta diversity (ses.βMNTDab and ses.βMPDab) to infer the role of deterministic and stochastic ecological processes in structuring bacterial and fungal endophyte communities in the woody tissues of Populus deltoides and the naturally occurring P. × jackii hybrid complex (P. deltoides × P. balsamifera). Microbial communities were characterised through Illumina amplicon sequencing (MiSeq) of the ITS and 16S rRNA gene. We detected 227 fungal ASVs, which were mainly classified as Ascomycota (92.4%). Among the 667 bacterial ASVs detected, the majority were classified as phylum Actinobacteriota (47.6%) and Proteobacteria (44.9%). We predicted that hybridisation could lead to a host environment that applies weaker selective effects on microbial taxa due to variability in host chemical and morphological phenotypes. Although bacterial communities did not support our prediction, fungal assemblages of the hybrid host (P. × jackii) were more phylogenetically random within (ses.MNTDab) and between assemblages (ses.βMNTDab and ses.βMPDab) then the non-hybrid (P. deltoides)—consistent with an increased role of stochastic community assembly processes and less selective host environment. Host identity had a large influence on fungal community composition (weighted UniFrac R2 = 34%), which may result from the differences in fungal selection we detected between hosts. Conversely, host identity was a weaker predictor of bacterial composition (weighted UniFrac R2 = 13%), which may reflect the more dominant role of stochasticity we detected in bacterial assembly. Our findings provide evidence that host hybridisation may alter fungal assembly processes and diversity within the woody endosphere, leading to more phylogenetically diverse associations both within and between the fungal assemblages of hybrid trees. More broadly, our results highlight how genetically diverse host populations may promote microbial biodiversity within forests and hybrid transition zones.
Grant et al. (2025) Contrasting microbial assembly patterns in the woody endosphere of hybrid and non-hybrid Populus trees. PeerJ 13:e20073 https://doi.org/10.7717/peerj.20073
ShinyDegSEM: an interactive application for pathway perturbation analysis in gene expression studies via structural equation modeling
Background Researchers in biology and bioinformatics are increasingly interested in unraveling the complex mechanisms underlying phenotypic variations. A key challenge lies in identifying perturbed biological pathways and understanding how these perturbations propagate through intricate gene regulatory networks. Results To address this challenge, we developed ShinyDegSEM, an interactive R Shiny application that leverages structural equation modeling (SEM) to facilitate pathway perturbation analysis in gene expression studies. ShinyDegSEM streamlines identifying differentially expressed genes (DEGs), generating pathway models based on biological knowledge, and evaluating these models to uncover perturbed pathway modules. This article is a tutorial to guide users through the analysis workflow, providing detailed explanations and examples. This feature ensures that even novice researchers can quickly grasp the concepts and apply the tool to their datasets. Conclusions The application integrates multiple steps, including DEG detection using significance analysis of microarray, perturbed pathway analysis with signaling pathway impact analysis, and SEM-based model refinement and comparison between experimental and control groups. The interactive interface of ShinyDegSEM allows researchers to easily upload their gene expression data, select appropriate criteria for DEG detection and pathway analysis, and visualize the results in intuitive graphs and tables. The tool provides insights into deregulated genes and modified gene-gene relationships within perturbed pathways.
Jiang et al. (2025) ShinyDegSEM: an interactive application for pathway perturbation analysis in gene expression studies via structural equation modeling. PeerJ 13:e20033 https://doi.org/10.7717/peerj.20033
DNA-based prediction of external ear morphology in the Chinese population: an exploratory study
Background The external human ear is a polymorphic and polygenic structure with individual uniqueness, making it a valuable target in forensic DNA phenotyping (FDP) studies. Previous genome-wide association studies have identified multiple genetic loci associated with variation in ear characteristics. However, research focused on predicting ear morphology within the context of FDP remains limited. This study aimed to develop DNA-based predictive models for external ear morphology in the Chinese population. Methods Digital photographs of 675 volunteers were used to score 13 ear phenotypes, each categorized into three levels. Multinomial logistic regression (MLR) was applied for genetic association analysis. Five predictive models—MLR, support vector machines, random forest, AdaBoost, and k-nearest neighbors—were developed and evaluated using 10-fold cross-validation. Results Genetic association analysis identified several influential single-nucleotide polymorphism (SNPs) for each ear phenotype. Among the five models, AdaBoost and MLR demonstrated superior performance, achieving area under the curve (AUC) values above 0.7 for predicting absent tragus cases (level_0). To simplify classification, binary models incorporating genetic interactions were constructed for absent tragus cases. Specifically, the AdaBoost model achieved an AUC of 0.74, while the binary logistic regression (BLR) model reached an AUC of 0.72. Conclusions These findings highlight the potential forensic application of genetic markers in predicting ear morphology within the Chinese population, contributing to the advancement of FDP research and practice.
Wang et al. (2025) DNA-based prediction of external ear morphology in the Chinese population: an exploratory study. PeerJ 13:e20169 https://doi.org/10.7717/peerj.20169