Hyperhomocysteinemia and its association with decreased glomerular filtration rate in patients with chronic kidney disease: a comprehensive meta-analysis
Background Hyperhomocysteinemia (elevated homocysteine, Hcy) is common in chronic kidney disease (CKD) patients, but its effect on glomerular filtration rate (GFR), a key renal function indicator, is unclear. Objective This meta-analysis aimed to clarify the association between hyperhomocysteinemia (HHcy, defined as Hcy > 15 µmol/L) and reduced glomerular filtration rate (GFR) in chronic kidney disease (CKD) patients, hypothesizing that HHcy is associated with a more significant GFR reduction. To test this hypothesis, a comprehensive search was conducted in PubMed, Embase, Cochrane databases, and reference lists. The primary outcome of interest was the relationship between HHcy and GFR decline in CKD. Methods For this meta-analysis, we established clear inclusion and exclusion criteria to identify eligible studies. Studies were included if they involved patients with chronic kidney disease (CKD), employed randomized controlled, cross-sectional, or cohort study designs, included participants aged 14 years or older, and reported or permitted the calculation of glomerular filtration rate (GFR) and homocysteine (Hcy) levels. We excluded studies that were not in English, focused on acute kidney injury, end-stage kidney disease, or dialysis patients, lacked clear group definitions, were based on animal models, or used non-standard CKD definitions. A comprehensive search strategy was employed to identify relevant studies. We combined MeSH terms (e.g., “homocysteine [MeSH]” and “renal insufficiency, chronic [MeSH]”) with free-text keywords in major databases, including PubMed, Embase, and Web of Science. Additionally, we utilized the “related items” function and applied Boolean operators to refine search results. Data were synthesized through meta-analysis, and the mean ± SD of GFR in CKD patients according to Hcy levels were calculated for comparison. All databases were searched from their inception dates to June 2024. Results CKD patients with hyperhomocysteinemia had a lower GFR (SMD = 2.26, 95% CI [1.37–3.15]). However, significant inter-study heterogeneity (P < 0.01, I2 = 99.5%) was found. Five articles (Z 2016, Ye, Z 2017, Zhang, Y 2020, Shen, Z 2022, Wu, and J 2022) contributed to it (P = 0.015 < 0.05). Subgrouping them eliminated heterogeneity (P = 0.52, I2 = 0.00%). Sensitivity analysis showed individual article exclusion had little effect on the result. But Egger tests showed publication bias (P < 0.05), while scissors graph analysis supported result stability (P < 0.01). Conclusions In CKD, elevated Hcy is related to kidney function decline.
Chen et al. (2025) Hyperhomocysteinemia and its association with decreased glomerular filtration rate in patients with chronic kidney disease: a comprehensive meta-analysis. PeerJ 13:e20064 https://doi.org/10.7717/peerj.20064
Sleep and geriatric syndromes in elderly emergency patients in China: a cross-sectional survey
This study aims to assess the prevalence of abnormal sleep conditions and geriatric syndromes in elderly emergency patients in China and to explore the relationship between them. The convenience sampling method was used to recruit elderly patients in the Emergency Department of Yueyang Central Hospital in Hunan Province from July to November 2023. A total of 205 elderly emergency patients were included. Sleep conditions and four geriatric syndromes (frailty, sarcopenia, malnutrition, and cognitive impairment) were investigated. Logistic regression analysis was used to assess the relationship between sleep and the four geriatric syndromes. After adjusting for age, gender, marital status, education level, and number of comorbidities, it was found that patients with mild and significant daytime sleepiness were more likely to have frailty than those with no daytime sleepiness (OR = 2.509, p = 0.018; OR = 4.395, p = 0.048). Patients with mild and significant dissatisfaction with sleep quality were more likely to have sarcopenia than those with good sleep quality (OR = 4.153, p = 0.006; OR = 5.955, p = 0.013). Additionally, patients with normal sleep duration had a lower risk of malnutrition than those with insufficient sleep duration (OR = 0.353, p = 0.043), and patients with slight daytime sleepiness had a higher risk of malnutrition than those with no daytime sleepiness (OR = 3.414, p = 0.004). Finally, patients with mild daytime sleepiness were more likely to have cognitive impairment than those without daytime sleepiness (OR = 2.564, p = 0.026). This study indicates that improving sleep may be a favorable factor for controlling geriatric syndromes. However, as the single-center design and convenience sampling restrict generalizability, the results should be validated in multi-center studies using probability sampling.
Zhang et al. (2025) Sleep and geriatric syndromes in elderly emergency patients in China: a cross-sectional survey. PeerJ 13:e20194 https://doi.org/10.7717/peerj.20194
24-epibrassinosteroid and jasmine oil improve vegetative growth and productivity of Flame Seedless grapevines under abiotic stresses
Abiotic stresses such as high temperature, humidity fluctuations, and excessive light negatively impact grapevine physiological functions, resulting in irregular vegetative growth and reduced productivity. Natural plant growth regulators and essential oils offer potential eco-friendly strategies to mitigate these adverse effects. This study investigated the effects of foliar applications of 24-epibrassinosteroid (Br) at concentrations of 1, 2, and 3 mg/L and jasmine oil (JO) at 500, 1,000, and 1,500 µL/L on Flame Seedless grapevines exposed to abiotic stress. The treatments aimed to enhance vegetative development, nutrient uptake, biochemical attributes, and yield. Results showed that all treatments successfully improved the vegetative growth of Flame Seedless grapevines by increasing leaf area, shoot length, diameter, number of leaves/shoots, pruning wood weight, internode length, and coefficient of wood ripening. They also improved the mineral content in leaf petioles, total carbohydrates in canes, chlorophyll contents in leaves, and yield per vine. In addition, the quality of the Flame Seedless grapevine was improved by increasing cluster weight, length, width, berry firmness, length, width, soluble solids content (SSC), titratable acidity (TA), SSC/TA ratio, total sugars, phenols, anthocyanin, and flavonoids, activities of peroxidase (POX), phenylalanine ammonialyase (PAL), polyphenoloxidase (PPO) and catalase (CAT) enzyme in berry. Application of Br at 3 mg/L yielded the highest significant values for vegetative growth parameters, yield, and physical characteristics. While JO at a rate of 1,500 µL/L increased the total phenols, flavonoids, and anthocyanin, as well as PPO, PAL, POX activity, and CAT in the berry. Foliar application of Br and JO effectively mitigated the adverse effects of abiotic stress in Flame Seedless grapevines.
Alebidi et al. (2025) 24-epibrassinosteroid and jasmine oil improve vegetative growth and productivity of Flame Seedless grapevines under abiotic stresses. PeerJ 13:e20181 https://doi.org/10.7717/peerj.20181
Prediction of pathological complete response to neoadjuvant chemotherapy for invasive breast cancers based on longitudinal ultrasound and superb microvascular imaging: a single-center retrospective study
Purpose To examine whether dynamic alterations in conventional ultrasound (US) and superb microvascular imaging (SMI) can act as predictors of pathological complete response (pCR) following neoadjuvant chemotherapy (NAC) in breast cancer (BC). Methods This single-center, retrospective study included women with invasive BC who underwent NAC between January 2022 and December 2024. The features of conventional US and SMI characteristics of BC were analyzed before NAC and the change (Δ) after two cycles. Multivariate logistic regression analysis (Forward, Wald, α = 0.05) was used to screen factors independently associated with pCR. Area under the receiver operating characteristic curve (AUC) analysis was performed to confirm the predictive effectiveness and evaluate the internal validity through bootstrap resampling. A nomogram was created to graphically represent the predictive power of the various factors for pCR. Results Before NAC, the pCR group exhibited significantly higher negative rates for the estrogen receptor (ER) and progesterone receptor (PR). (P < 0.001 and P = 0.005, respectively) and significantly higher positive rates of human epidermal growth factor receptor 2 (HER2) and echogenic rinds (P < 0.001 and P = 0.029, respectively). Additionally, they exhibited significantly shorter largest diameters (LD) and shortest diameters (SD) (P = 0.001 and P = 0.003). After two cycles of NAC, patients who achieved pCR exhibited a significantly higher proportion of monochrome superb microvascular imaging (mSMI) that had not expanded, as well as disappearance of the echogenic rind (P < 0.001 and P = 0.002). Regarding the rate of change in LD, SD, and vascular index (VI), patients in the pCR group showed significantly higher values than those in the non-pCR group (all P < 0.001). The multivariate logistic regression model identified ΔVI (%), ΔSD (%), and SD to have the strongest association with pCR. The overall multivariate model demonstrated the best AUC (0.963), which was significantly higher than that of any single factor. Bootstrap resampling, calibration plots, and decision curve analysis (DCA) all demonstrated strong performance in both discrimination and calibration. Conclusion The baseline status of US and SMI, as well as the longitudinal changes, demonstrated good predictive performance for pCR in BC following NAC.
Zuo et al. (2025) Prediction of pathological complete response to neoadjuvant chemotherapy for invasive breast cancers based on longitudinal ultrasound and superb microvascular imaging: a single-center retrospective study. PeerJ 13:e20171 https://doi.org/10.7717/peerj.20171
Unraveling the role of regulatory cell death in sepsis: an integrated analysis of bulk and single-cell sequencing data
Background Sepsis is a life-threatening condition characterized by systemic inflammation and dysfunction of multiple organs. Recently, regulatory cell death (RCD) has emerged as a distinct pathological feature and serve as a potential source of biomarkers or therapeutic targets in sepsis. Methods Comprehensive transcriptomic datasets of sepsis were accessed from the Gene Expression Omnibus (GEO) database. Genes involved in 18 RCD pathways were compiled from databases and published literature. The limma package was utilized to identify differentially expressed genes (DEGs). The Gene Set Variation Analysis (GSVA), CIBERSORT, Weighted Gene Co-expression Network Analysis (WGCNA), and receiver operating characteristic (ROC) analyses were combined to identify key RCDs pathways. Core RCD-related DEGs (RRDs) were selected using Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), and Random Forest (RF) machine learning methods. The expression patterns and diagnostic performance of the core RRDs were validated across multiple datasets and further confirmed through meta-analysis. Immune localization of RRDs was examined using single-cell transcriptomic data. Prognostic significance was evaluated using multivariate Cox analysis. Finally, the mRNA expression level was validated using quantitative real-time polymerase chain reaction (qRT-PCR). Results Zinc Finger DHHC-Type Containing 3 (ZDHHC3), Chloride Intracellular Channel 1 (CLIC1), Glutathione S-Transferase Omega 1 (GSTO1), Biogenesis of Lysosomal Organelles Complex 1 Subunit 1 (BLOC1S1), and Toll-Like Receptor 5 (TLR5) were considered as core RRDs, with monocytes and neutrophils serving as the principal cell types responsible for their overexpression and likely contributing critically to their downstream biological effects. Among them, ZDHHC3 and TLR5 were identified as independent risk factors for sepsis. Their significantly elevated mRNA expression in septic mice was confirmed by qRT-PCR. Conclusion Findings from this study underscored the crucial role of RCD pathways in the development of sepsis. Notably, ZDHHC3 and TLR5 were identified as novel and robust biomarkers for sepsis.
Cao et al. (2025) Unraveling the role of regulatory cell death in sepsis: an integrated analysis of bulk and single-cell sequencing data. PeerJ 13:e20167 https://doi.org/10.7717/peerj.20167
The effects of naproxen sodium on the growth, reproduction, survival, and feeding of a freshwater pond snail
Over-the-counter drugs are emerging contaminants in the environment. These contaminants often affect aquatic communities, including freshwater invertebrates. Nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly found in aquatic ecosystems worldwide and have documented negative effects on aquatic organisms. Naproxen is often suggested as a more environmentally friendly alternative due to less bioconcentration in fish. However, studies have yet to test the effects of naproxen on freshwater molluscs. This study exposed pond snails, Physa spp., to three nominal levels of naproxen sodium, 100 µg/L, 1,000 µg/L and 10,000 µg/L, along with a control, over a month-long experiment. We measured snail growth, survival, reproduction, and feeding. Naproxen reduced snail survival across all levels of naproxen exposure and the rate that snails fed at the highest level of naproxen. However, we did not detect an effect of naproxen on snail growth or reproduction rates, even at pollution levels well above those observed in natural systems. Naproxen reduced the grazing of Physa spp. only at our highest concentration, but reduced survival by at least 50% across all concentrations.
Environmental Contamination and Remediation
Becker et al. (2025) The effects of naproxen sodium on the growth, reproduction, survival, and feeding of a freshwater pond snail. PeerJ 13:e20163 https://doi.org/10.7717/peerj.20163
Prediction of ACL injury incidence and analysis of key features in basketball players based on multi-algorithm models
Background Basketball players are a high-risk group for anterior cruciate ligament (ACL) injuries. This study aimed to identify the critical factors contributing to ACL injuries in male basketball players and evaluate the performance of machine learning (ML) algorithms in injury prediction. Methodology This study protocol was registered with International Standard Registered Clinical/soCial sTudy Number (ISRCTN) (Registration number: 18009799). A total of 104 male collegiate basketball players volunteered to participate in this study. Data on the athletes’ profile, physical functions, basketball-specific skills, biomechanics, and electromyography (EMG) of seven lower limb muscles during unanticipated side-cutting maneuvers were collected. A 12-month follow-up was conducted to compare these variables between the injured (n = 11) and non-injured (n = 93) groups. Only the variables with significant differences between the groups were included in the predictive modeling. Results The performance of machine learning models in predicting ACL injury risk was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC). The AUC-ROC values ranged from 0.66 to 0.80, with the random forest algorithm achieving the highest performance (AUC-ROC = 0.80). The most influential predicting feature observed during the emergency stop phase, included a greater knee flexion moment, reduced knee flexion angle, increased backward ground reaction force, and increased activation of the vastus lateralis muscle. Conclusion The random forest model demonstrated superior predictive performance, providing valuable insights into the key risk factors associated with ACL injury among male basketball players. This study highlighted the importance of biomechanical testing based on sport-specific movements to accurately predict the ACL injury risk.
Guo et al. (2025) Prediction of ACL injury incidence and analysis of key features in basketball players based on multi-algorithm models. PeerJ 13:e20141 https://doi.org/10.7717/peerj.20141
Metabarcoding analysis reveals hidden eukaryotic plankton biodiversity in the Ross Sea, Antarctica
Background Environmental DNA (eDNA) analysis is a highly sensitive, non-destructive method that enables the detection of various species through DNA shed into environmental samples without requiring direct organism collection. This study sought to investigate the biodiversity and community structure of eukaryotic plankton, including phytoplankton and zooplankton, in the Ross Sea marine protected area (RSR MPA) using eDNA metabarcoding analysis. By examining their spatial and vertical distributions, the study underscores the importance of continuous monitoring for the conservation of the RSR MPA. Methods We collected 48 seawater samples from 16 sites in the Ross Sea region for eDNA metabarcoding analysis, targeting the 18S rRNA gene region of eukaryotic plankton in Antarctica. Bioinformatic processing and taxonomic classification were conducted to assess the diversity and community composition of phytoplankton and zooplankton. Results Phytoplankton communities were primarily composed of six phyla with their distribution patterns and the grouping of samples with similar community structures was found to be shaped by the ocean currents of the RSR MPA and various environmental factors, such as salinity and dissolved oxygen levels. Zooplankton communities consisted of 18 major taxonomic groups, exhibiting distinct horizontal and vertical distribution patterns with differences in taxonomic community structure and species diversity across depth groups. Notably, previously undetected Antarctic species were identified in the Ross Sea region, demonstrating the effectiveness of eDNA in revealing hidden biodiversity. Conclusions Analyzing eukaryotic plankton communities in the vast and extreme Antarctic environment based on eDNA has proven to be highly efficient, enabling the detection of a greater number of species, including those that were difficult to identify in previous studies. It was observed that in the Ross Sea Marine Protected Area, various species form distinct community structures such as phytoplankton and zooplankton, each inhabiting the area according to different environmental variables and habitat preferences. As a designated marine protected area, the Ross Sea’s unique ecosystem requires continuous monitoring and conservation efforts to address environmental changes. The genetic data obtained in this study contributes to expanding the database of Antarctic-specific species, facilitating more accurate and efficient analyses of Antarctic ecosystems in the future.
Choi et al. (2025) Metabarcoding analysis reveals hidden eukaryotic plankton biodiversity in the Ross Sea, Antarctica. PeerJ 13:e20118 https://doi.org/10.7717/peerj.20118
Identification of diabetes related phenotype and diagnostic biomarkers in coronary artery disease
Background Diabetes mellitus (DM) and coronary artery disease (CAD) are closely interrelated clinical conditions. However, the combination analysis based on DM related CAD diagnostic model remains a gap. The primary objective of this study was to identify diagnostic models and diagnostic markers for CAD based on the association of diabetic phenotypes and attempt to explore them further in a mouse model. Methods We used data integration as well as multiple datasets for both coronary artery disease and diabetes to exclude bias as well as to improve reliability. We employed the least absolute shrinkage and selection operator (LASSO) regression algorithms to construct the CAD diagnostic model. Furthermore, we established mouse CAD model (low-density lipoprotein receptor deficient mice with high fat diet) to explore the crosstalk between the screened biomarkers and severe CAD progress. Results The intersecting genes from differential analysis and weighted correlation network analysis (WGCNA) results yielded 32 diabetes-related biomarkers. We then identified two diabetes-related phenotypes through the consensus clustering in CAD patients. Microenvironmental analysis revealed that phenotype 1 exhibited higher expression of most cytokines, inflammatory factors, interleukins, and related receptors. Immune cell composition in phenotype 1 showed increased infiltration compared to phenotype 2. The LASSO regression identified 16 diabetes-related genes and we further constructed a diagnostic model based on these genes, which the area under the curve (AUC) reached 0.8. Additionally, single cell immune analysis exhibited the location of these genes. KCNQ1, ATP6V1B1, MTDH, and ITPK1 were predominantly located in macrophages, indicating their potential in regulating macrophage during myocardial injury. Furthermore, We elucidated that KCNQ1 and ITPK1 exhibited high expression level in mouse CAD model in tissue level. exhibited similar expression trends with macrophage biomarkers (CD31 and CD68). The result of qPCR also indicated the elevated level of KCNQ1 and ITPK1, which exhibited crosstalk with CD31 and CD68 in mouse CAD model. Conclusion This study delves into the microenvironmental characteristics of diabetes-related phenotypes in CAD, constructing an optimal diagnostic model and validated the significance of diagnostic markers in mouse CAD model, which may offer insights that could be beneficial for clinical management in the near future.
Aihemaiti et al. (2025) Identification of diabetes related phenotype and diagnostic biomarkers in coronary artery disease. PeerJ 13:e20117 https://doi.org/10.7717/peerj.20117
Comparison of supervised versus home-based exercise programs following platelet-rich plasma injections in knee osteoarthritis: clinical outcomes from quasi-experimental study
Background Knee osteoarthritis (OA) is characterized by severe pain and decreased range of motion (ROM), mostly managed with conservative treatments. Therapies like platelet-rich plasma (PRP) intra-articular injections have gained fame for pain relief when surgery is a last resort. Objectives To compare the effectiveness of a supervised exercise program versus a home-based exercise program following PRP injections in terms of pain relief, ROM improvement, and disability reduction in knee osteoarthritis patients. Methods A quasi-experimental design was employed, enrolling 32 patients diagnosed with knee OA cases (age range: 40–60 years; 59% female), divided into two groups: a supervised exercise group (n = 16) and an unsupervised/home-based exercise group (n = 16). Both groups received two PRP injections spaced 15 days apart. The supervised group followed a structured exercise protocol, including cold packs post-injection for pain management. The program comprises three sessions per week for one month. The unsupervised group received similar exercises to be performed independently at home. Data analysis was conducted using parametric and non-parametric statistical methods based on data distribution. Results Both groups exhibited significant improvements from baseline to post-intervention in pain, ROM, and functional status (p < 0.05). The supervised exercise group demonstrated superior outcomes in pain reduction, knee flexion ROM, and Knee Injury and Osteoarthritis Outcome Score (KOOS). However, no significant difference was observed between groups for knee extension ROM (p = 0.378). Conclusion Both supervised and unsupervised exercise programs improved outcomes in knee OA patients following PRP injections; the supervised program showed greater pain relief, flexion ROM, and functional status. However, no significant difference was observed in knee extension ROM between the two groups.
Safdar et al. (2025) Comparison of supervised versus home-based exercise programs following platelet-rich plasma injections in knee osteoarthritis: clinical outcomes from quasi-experimental study. PeerJ 13:e19971 https://doi.org/10.7717/peerj.19971