PLOS ONE Alerts: New Articles

Biomarkers of mitochondrial dynamics in idiopathic pulmonary fibrosis: Identification and validation through transcriptomic and single-cell analyses

2026-04-23T14:00:00Z

by Yongbin Wang, Peng Cheng, Zixiang Meng, Ying Zhang, Yan Li, Feifei Feng

Background

Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease that has increasingly been associated with dysregulated mitochondrial quality control and dynamics. However, the molecular mechanisms underlying these alterations remain incompletely understood. This study aimed to systematically identify and validate candidate biomarkers related to mitochondrial dynamics in IPF and to characterize their cell-type specificity and putative regulatory relationships.

Methods

We integrated bulk transcriptomic datasets from the Gene Expression Omnibus (GEO), single-cell RNA sequencing (scRNA-seq) data, and literature-derived mitochondrial dynamics gene sets. Candidate genes were identified through differential expression analysis and consensus clustering, followed by functional enrichment and protein–protein interaction (PPI) network analyses. A total of 101 machine-learning model combinations—including random forest, LASSO, and support vector machine—were constructed to select optimal feature genes. Diagnostic performance was assessed using receiver operating characteristic (ROC) analysis and further evaluated with artificial neural network (ANN) modeling. Additional analyses included chromosomal localization, immune infiltration profiling, multilayer regulatory network construction (transcription factors, lncRNAs, circRNAs), molecular docking prediction, and single-cell expression and pseudotime trajectory analysis. Key biomarkers were further evaluated by RT-qPCR in an independent clinical cohort.

Results

Integrated multi-omics and machine-learning analyses identified CD247, IL7R, and RETN as candidate biomarkers related to mitochondrial dynamics-associated pathways in IPF. Across independent transcriptomic datasets, RETN was upregulated, whereas CD247 and IL7R were downregulated, and each showed diagnostic value (single-gene AUC > 0.7). The ANN model based on these genes achieved encouraging discriminative performance (training AUC = 0.91; validation AUC = 0.82), and expression differences were confirmed by RT-qPCR in a modest independent cohort. Enrichment analyses indicated convergence on spliceosome-related pathways, and regulatory-network analysis highlighted interactions involving transcription factors and non-coding RNAs, including circRNA CDR1as. Molecular docking suggested putative interactions with selected compounds. Single-cell analyses suggested that dysregulation was most evident in monocyte-associated compartments in one publicly available scRNA-seq dataset, and pseudotime analysis indicated dynamic expression patterns, with early transient increases in CD247 and IL7R and progressive elevation of RETN.

Conclusion

Through multi-omics integration and machine-learning approaches, we identified and preliminarily validated CD247, IL7R, and RETN as candidate biomarkers related to mitochondrial dynamics–associated pathways in IPF. These findings provide transcriptomic and cell-type–specific evidence suggesting potential immune–mitochondrial associations in IPF and may inform future biomarker validation and mechanistic hypothesis generation.

Editorial Note: Risk factors for mild depression in older women with overactive bladder syndrome—A cross sectional study

2026-04-23T14:00:00Z

by The PLOS One Editors

Use of health communication materials by health-care providers for health education in low- and middle-income countries: A scoping review

2026-04-23T14:00:00Z

by Amlaku Nigusie Yirsaw, Gebeyehu Lakew, Adane Nigusie

Background

Health communication materials (HCMs) are widely used to support health education and promotion activities in clinical and community settings. However, evidence regarding their use by healthcare providers in low- and middle-income countries (LMICs) remains inconsistent. This scoping review aims to systematically map and describe the existing literature on the utilization of health communication materials by healthcare providers in low- and middle-income countries (LMICs).

Methods

This scoping review was conducted in accordance with the PRISMA-ScR reporting guideline and the Joanna Briggs Institute (JBI) framework for scoping reviews. The studies were searched from database inception to September 2025 using electronic databases (PubMed, ScienceDirect, Cochrane, and Hinari) were searched, and studies were selected based on predefined inclusion and exclusion criteria aligned with the Population–Concept–Context framework. Data extraction was performed using a standardized form, and findings were narratively synthesized spreadsheet by two independent reviewers. Findings were synthesized using descriptive numerical analysis and thematic analysis.

Result

A total of 728 records were identified. 715 were screened after removing duplicates. Following title/abstract and full-text review, 18 studies were included. HCMs, including printed, audiovisual, and electronic tools, were covered in these studies. NGO support, perceived utility, and material accessibility were facilitators, while organizational limitations, patient disengagement, limited availability, and inadequate training were major obstacles.

Conclusion

The use of health communication materials by healthcare providers in LMICs is influenced by contextual, institutional, and individual factors. While HCMs are widely available in many settings, their use remains inconsistent and is influenced by systemic challenges. Strengthening accessibility, provider training, culturally appropriate content, and integration into routine care may support improved implementation.

Plasma-activated water: Mechanism and treatment duration for postharvest disease control and shelf-life enhancement of mango under ambient storage

2026-04-23T14:00:00Z

by Mst. Habiba Tamanna, Showdia Sarmin, Umme Afroza Irin, Mst. Khadiza Khatun, Mamunur Rashid Talukder, Md. Mahmodol Hasan

In Bangladesh, a large quantity of mango is lost every year due to post-harvest diseases, particularly anthracnose and stem-end rot. Therefore, sustainable post-harvest management is crucial for reducing the losses. In this study, we investigated the effects of plasma treatments on mango to mitigate post-harvest losses. The mangoes were submerged in distilled water (DW), and then DW-submerged mangos were treated for 10 minutes employing multi-capillary bubble discharged plasma jet system using air and oxygen gases separately. Plasma treatments significantly influenced disease incidence, severity, and physio-chemical properties of mangoes. On the 10^th day, the Khirsapat mango, treated with a 10-minute air-discharge plasma, exhibited a significant (≤0.05) reduction in anthracnose incidence (20%) and severity (2.33%) compared with control (incidence 80% and severity 61.67%). Similarly, the 10-minute air-discharge plasma treatment consistently reduced the incidence (20%) and severity (15%) of stem-end rot. For the Fazlee variety, the incidence (22%) and severity (3.67%) of anthracnose were reduced compared with the control (89% and 56.67%), while stem-end rot was completely inhibited for up to 10 days under the 10-minute air-plasma treatment. In addition, both mango varieties showed increased total soluble solid (18% and 19%), retained good moisture content (77.82% and 85.34%), but reduced physiological weight loss (3.12% and 8.36%), and extended shelf life (6 days). Firmness degradation was lowest in air plasma treatment (4.20% in Khirsapat and 4% in Fazlee) compared to control (5.76% and 5.79%). It is interesting to note that the plasma treatment of both varieties showed higher mineral contents (K, Ca, Mg, and P), while Vit C declined modestly (16.0 and 25.10 mg/100g) compared to control. Therefore, a 10-minute air-discharge plasma treatment effectively reduced disease incidence and severity through enhancing TSS, mineral contents, physiological properties, and overall storage life that highlighting its potentiality as an eco-friendly postharvest technology.

Using tree-based ensemble methods to produce a population-based mortality risk score in Ontario, Canada

2026-04-23T14:00:00Z

by Steven Habbous, Peter C. Austin, Shabnam Balamchi, Davood Astaraky, Roozbeh Yousefi, Munaza Chaudhry, Erik Hellsten

Introduction

Risk adjustment is critical in observational epidemiology to control for confounding of the exposure-outcome relationship. Accurate prediction of outcomes, such as mortality, can improve risk adjustment. In the present study, we compared logistic regression with a range of tree-based ensemble methods to predict 1-year mortality in the general population of Ontario, Canada.

Methods

Ontario adults (age 18 years and older) who were alive as of January 1, 2022 were included. Using a window of up to 3 years, various measures of health and healthcare utilization were captured from administrative databases. To predict 1-year mortality, we applied logistic regression, random forests, extremely randomized trees, adaptive boosting, gradient boosting, extreme gradient boosting, Newton boosting, and CatBoost. All models also included age and sex. Performance was evaluated using the area under the ROC curve (AUROC), the area under the precision-recall curve (PR-AUC), the Brier score, and a quantile-based version of the Integrated Calibration Index (ICI), reported in the 30% test set. Feature importance was assessed using CatBoost’s internal model structure, supplemented with permutation feature importance, explainable boosted machines, and marginal effects.

Results

A total of 12,080,801 Ontarians were included and 121,951 (1.0%) died within 1 year. Logistic regression showed excellent discrimination (AUROC 0.926; PR-AUC 0.256) and acceptable calibration (ICI 0.0022). The best model was CatBoost, which had the best discrimination (AUROC 0.933, PR-AUC 0.280) and calibration (ICI 0.0003). In sensitivity analyses of the CatBoost model, including more detailed definitions of cancer (to include its subtype) and chronic kidney disease (defined using serum creatinine instead of diagnostic codes) produced modest improvements in PR-AUC (0.290), along with substantially improved calibration amongst the highest-risk (70–100%) individuals. The most influential model-building feature was age. Residence in long-term care and receipt of palliative care was associated with the largest marginal effects.

Conclusion

The machine learning model CatBoost yielded the most accurate predictive model for 1-year mortality using individual comorbidities and additional measures of healthcare utilization for the general population. These findings demonstrate that machine learning methods can enhance risk adjustment efforts in observational studies, leading to more accurate confounder control and better support for health policy and epidemiologic research.

Relationships between pre-pandemic mental health, sociodemographic factors and health behaviours in older adults during the acute onset of COVID-19 in Australia: A descriptive analysis

2026-04-23T14:00:00Z

by Nicole Lovato, Sarah L. Appleton, Amy C. Reynolds, Tiffany K. Gill, Sean Martin, Gary A. Wittert, Robert J. Adams

Objective

To gain a comprehensive understanding of associations between mental health symptoms and sociodemographic and health factors assessed during COVID-19 restrictions in existing, longitudinal community-based cohorts.

Methods

Participants of The North West Adelaide Health Study (NWAHS, n = 982) and the Florey Adelaide Male Ageing Study (FAMAS, n = 338) in South Australia, undertook a COVID-19 impacts survey during October 2020-May 2021. The Centre for Epidemiologic Studies Depression Scale (score≥16;NWAHS) and the Beck Depression Inventory 1A (score≥13;FAMAS) were used to characterise mild-severe depressive symptoms. The Generalised Anxiety Disorder questionnaire was used to identify moderate-severe anxiety (score 10–21).

Results

Of 1,320 participants (male n = 797), 62.4% (n = 824) were aged ≥65years (range 36−100 years), and 37.8% reported workforce participation at the time of the COVID-19 survey. Depressive and anxiety symptoms were observed for participants aged 35−54years (OR=1.92,95%CI = 1.01–3.67), financial stress (1.81,1.02–3.21), change in overall food intake (increase and decrease), social support none/sometimes(2.74,1.48–5.07), low control/mastery since COVID-19 (6.00,3.37–10.6) and poor sleep during restrictions (7.94,4.25–14.8), independent of previous depressive symptoms (8.30,1.9–13.2). Change in mental health status from pre-COVID to COVID-19 restriction was associated with sex (p = 0.013) and age (p < 0.001), such that females and younger participants (35−54yr) reported depressive symptoms at both times. Younger adults (35-54 yr) showed a higher prevalence of depressive symptoms only during COVID-19.

Conclusions

Depressive and anxiety symptoms were consistent during COVID-19 relative to pre-COVID-19. Those with a history of depression, were more likely to report depressive and anxiety symptoms during COVID-19. Government-funded initiatives employed during future pandemics should consider tailored mental health and social support for vulnerable groups.

The microscopic mechanism of water immersion and collapsibility in Malan loess with different particle size

2026-04-23T14:00:00Z

by Li Li, Qinglong Zhang, Huandong Mu, Longhao Zheng, Yisong Bai

Collapsibility of loess is a widespread, highly destructive geological hazard on the Chinese Loess Plateau. Malan loess exhibits distinct regional particle size variations, but the collapsible deformation characteristics and underlying microscopic mechanisms of loess with different particle sizes remain insufficiently understood. This study selected sandy (Jingbian), silty (Yan’an), and clayey (Jingyang) Malan loess in Shaanxi as representative samples to investigate collapsible deformation and clarify intrinsic mechanisms. Results show particle size and clay content significantly affect loess’ physical-mechanical properties: particle shape transitions from angular to sub-rounded/rounded, with clay distributing as adhesion (sandy), bridging (silty), or filling (clayey). Collapse is dominated by clay softening, skeleton destruction, and void filling. Post-collapse, macropores (>50 μm) convert to mesopores (2–50 μm), porosity drops ~10%, and pore orientation homogenizes. Generalized collapse mechanism models for different particle size Malan loess are proposed, providing a theoretical basis for hazard mitigation.

Risk prediction of combined fibrinogen degradation products, thrombomodulin, and maximum amplitude for assessing association with venous thromboembolism in patients with post-traumatic fractures

2026-04-23T14:00:00Z

by Shaoli Huang, Xiaoyan Wang, Hongwu Xin, Xihe Zhang, Wenying Luo

Background

Venous thromboembolism (VTE) is a globally prevalent severe disease associated with high morbidity and mortality. Currently, thrombomodulin (TM), fibrinogen degradation product (FDP), thromboelastography have been the subject of several research pertaining to VTE; However, the combined diagnostic efficacy of these tests for VTE remains unclear. Therefore, we proposed to investigate the diagnostic efficacy of TM, FDP, thrombelastography in predicting VTE.

Methods

The patients with traumatic fracture included in the study were divided into a VTE group (n = 44) and a control group (n = 56) based on imaging diagnosis. Spearman correlation was employed to analyze the relationship between coagulation-related markers and thromboelastography indices. Variables were analyzed using multifactorial logistic stepwise regression. Statistically significant indicators were included in the receiver operating characteristic curve to evaluate their diagnostic efficacy for VTE.

Results

The VTE group showed significantly higher levels of multiple coagulation-related parameters and thromboelastography indices compared to the control group. Specifically, D-dimer levels were 8.87 (4.77, 15.07) mg/L in the VTE group versus 2.36 (1.07, 5.73) mg/L in the control group (P < 0.001), and FDP levels were 36.45 (11.34, 73.75) μg/mL versus 7.96 (4.57, 12.73) μg/mL (P < 0.001). TM levels were also elevated in the VTE group at 11.74 (9.26, 13.27) TU/mL compared to 8.60 (7.20, 11.60) TU/mL in controls (P = 0.001). Among thromboelastography parameters, maximum amplitude (MA) was 72.06 ± 7.61 mm in the VTE group versus 67.03 ± 7.21 mm in controls (P = 0.001), and clot intensity (G) was 13,259.75 (9,346.48, 18,545.83) d/sc versus 9,659.70 (8,009.33, 13,480.40) d/sc (P = 0.004). Conversely, the blood clot formation rate was lower in the VTE group (1.25 [0.83, 1.40] vs. 1.30 [1.10, 1.58], P = 0.037). Linear correlation analysis revealed significant positive associations between platelet counts and both MA (r = 0.612, P < 0.001) and G (r = 0.588, P < 0.001). Multivariate logistic stepwise regression identified FDP (OR = 1.047, 95% CI: 1.025–1.070, P < 0.001), TM (OR = 1.215, 95% CI: 1.033–1.429, P = 0.019), and MA (OR = 1.104, 95% CI: 1.026–1.188, P = 0.008) as independent risk factors for VTE. ROC curve analysis demonstrated that the combined model of these three markers achieved the highest diagnostic efficacy, with an area under the curve (AUC) of 0.860 (95% CI: 0.789–0.931), sensitivity of 70.5%, and specificity of 85.7%.

Conclusion

Combined testing of FDP, TM, and MA holds clinical significance for clinicians to early predict the risk of VTE in post-traumatic fracture patients and implement preventive measures.

Quantification of pulmonary arterial pressure with 4D flow cardiac MRI velocity mapping in patients with suspected pulmonary hypertension: Comparison with right heart catheterization

2026-04-23T14:00:00Z

by Charlotte Dantoing, Roger Bouzerar, Yohann Bohbot, Isabelle Mayeux, Raphaël Pichois, Cédric Renard

Objectives

4D flow MRI is becoming a promising tool to assess pulmonary hypertension which remains a progressive fatal disease. The aim of this study was to compare the quantification of pulmonary arterial pressure derived from 4D flow MRI with right heart catheterization in patients with pulmonary hypertension.

Methods

Thirty-two patients (22 men, 10 women, mean age 62.6 years old) with known or suspected pulmonary hypertension were enrolled in this prospective study. Subjects were split into two consecutive groups, with the first 22 subjects dedicated to analysis and the last 10 subjects dedicated to validation. All patients underwent right heart catheterization and cardiac MRI examinations. Pulmonary arterial pressures were measured by catheterization. An accelerated kat-arc 4D flow MRI sequence allowed the analysis of cardiac blood and pulmonary artery (PA) flows. Multivariate linear regression models were obtained using stepwise, bottom-up and top-down covariate selection procedures.

Results

Using right heart catheterization as reference, the multivariate estimates of mean (mPAP) and systolic (sPAP) pulmonary arterial pressures only included 4D flow MRI parameters: mean helicity in right ventricle (RV), mean vorticity in right atrium (RA) and maximum cross-sectional PA area (A_max_PA). The models yielded mPAP = 0.04.A_max_PA + 0.061.mean_helicity_RV – 2.42 (R² = 0.69) and sPAP = 0.066.A_max_PA + 0.134.mean_helicity_RV – 0.613.mean_vorticity_RA + 23.98 (R² = 0.80). Bland-Altman bias were 0.42 and 0.38 mmHg, respectively.

Conclusion

This study suggests that kat-arc accelerated 4D flow MRI is a potential non-invasive technique for pulmonary arterial pressure estimation. Therefore, this short-duration sequence could become a useful diagnostic and follow-up exam for patients with pulmonary hypertension.

Neural network architectures and normalization techniques for automated sleep stage classification using rodent EEG and EMG signals

2026-04-23T14:00:00Z

by Jinyoung Choi, Hankil Oh, Minkyu Ahn

Accurate sleep stage classification in animal models is crucial for translational sleep research, enabling the study of mechanistic pathways and therapeutic interventions. Because manual scoring is labor-intensive and variable, artificial neural networks are increasingly used for automation. However, few models are tailored for animal sleep staging, and direct cross-model comparisons under consistent conditions remain limited. We presents a systematic evaluation of three representative neural architectures for automated sleep stage classification using rodent electroencephalogram and electromyogram: a conventional 1-dimensional convolutional neural network (1D-CNN), a 2-dimensional convolutional neural network (AccuSleep), and a convolutional neural network combined with bidirectional long short-term memory (DeepSleepNet). Performance was assessed under within-subject and cross-subject validation frameworks, comparing raw input, z-scoring, and mixture z-scoring. Both 1D-CNN and DeepSleepNet consistently outperformed AccuSleep, particularly for Rapid Eye Movement (REM), where AccuSleep exhibited marked deficits plausibly attributable to class imbalance. Class-wise analysis confirmed stable Non-Rapid Eye Movement (NREM) classification across models, while AccuSleep showed reduced robustness in REM and Wake. Normalization effects were model-dependent: raw data yielded superior outcomes for 1D-CNN and DeepSleepNet, whereas AccuSleep showed modest improvement in Wake detection under mixture z-scoring. Comparison with human electroencephalogram literature indicated that DeepSleepNet’s advantage over 1D-CNN is more pronounced in human datasets (especially NREM 1), likely reflecting differences in sleep architecture. These findings highlight the suitability of simpler CNNs for rodent sleep stage classification and underscore the importance of aligning preprocessing strategies with model architecture and data characteristics.

Effects of peppermint (Mentha x piperita L.) oil on cardiometabolic outcomes in patients with pre- and stage 1 hypertension: A placebo randomized controlled trial

2026-04-23T14:00:00Z

by Jonathan Sinclair, Benjamin Sant, XuanYi Du, Gareth Shadwell, Stephanie Dillon, Bobbie Butters, Lindsay Bottoms

Hypertension represents the predominant risk factor for cardiovascular disease morbidity and mortality; with significant healthcare utilization and expenditure. Pharmaceutical management is habitually adopted; although its long-term effectiveness remains ambiguous, and accompanying adverse effects are disquieting. Peppermint, which is rich in menthol and flavonoids, may exert potential benefits relevant to hypertension. This trial aimed to explore the effects of twice-daily peppermint oil supplementation in individuals with pre- and stage 1 hypertension. A 20 day, parallel randomized, placebo-controlled trial was adopted (NCT05561543). 40 individuals with pre- and stage 1 hypertension were randomly assigned to receive 100 μL per day of either peppermint oil or peppermint-flavoured placebo. The primary trial outcome was the between-group difference in systolic blood pressure from baseline to 20 days. Secondary outcome measurements were the between-group differences in anthropometric, haematological, diastolic blood pressure/resting heart rate, psychological wellbeing, and sleep efficacy indices. Statistical analysis was conducted on an intention-to-treat basis using baseline-adjusted linear regression models comparing post intervention values between trial arms with the corresponding baseline value entered as a covariate; adjusted mean differences (b), 95% confidence intervals, and effect sizes (d) were calculated. In relation to the primary outcome, adjusted systolic blood pressure at 20 days was significantly lower (b = −8.48 mmHg, 95% CI = −14.24 to −2.73, d = −0.94) in the peppermint trial arm (baseline = 130.05 mmHg, 20 days = 121.97 mmHg) than in placebo (baseline = 130.93 mmHg, 20 days = 131.05 mmHg). Loss to follow-up (N = 1) and adverse events (N = 1) were low, both occurring in the peppermint arm, and compliance was very high in the peppermint (93.3%) trial arm. Given the substantial health and economic burden associated with hypertension worldwide, these findings suggest that twice-daily peppermint supplementation may represent a simple, low-cost, and well-tolerated strategy to support blood pressure reduction in this population. Trial registration ClinicalTrials.gov NCT05561543

A rapid evaluation of quality of sedation and ventilation care processes for critically ill patients in Vietnam

2026-04-23T14:00:00Z

by An Luu Phuoc, Vo Tan Hoang, Truong Ngoc Trung, Nguyen Thien Binh, Vu Dinh Phu, Tran Minh Duc, Ha Thi Hai Duong, Tran Thi Diem Thuy, Duong Bich Thuy, Nguyen Thanh Nguyen, Le Thanh Chien, Doan Bui Xuan Thy, Nguyen Hoang Viet, Bui Ngoc Thanh, Vo Thi Hoang Dung Em, Jennifer Van Nuil, Abi Beane, Rashan Haniffa, Pham Ngoc Thach, Chau Minh Duc, Huynh Ngoc Hon, Nguyen Le Nhu Tung, Lam Minh Yen, Louise Thwaites, Duncan Wagstaff

Background

Sedation assessment, spontaneous awakening and breathing trials are evidence-based practices which can minimise harm from ventilation and sedation of critically ill patients. There are known difficulties in implementing these processes which are likely to be exacerbated in low-resource settings. This study aimed to describe current delivery of these care processes in three intensive care units in Vietnam; identify barriers and facilitators to their delivery; and describe local capacity for improvement.

Methods

We conducted a prospective rapid evaluation between 01/11/2021 and 31/12/2023 comprising registry-enabled measurement of daily care processes, process mapping, observations, focus group discussions, semi-structured interviews and a structured assessment of local capacity for improvement. Contextual determinants of care quality were analysed using the Consolidated Framework for Implementation Research. Organisational capacity for improvement was analysed using the Model for Understanding Success in Quality.

Results

Sedation was assessed qualitatively rather than using systematic tools. Spontaneous Awakening and Breathing Trials were both performed according to individual doctors’ clinical judgement in a non-protocolised manner. Barriers to delivering these processes included the lack of locally-adapted protocols, perceived safety concerns exacerbated by staffing shortages and lack of familiarity due to confusing terminology. Facilitators to improvement included quality improvement champions, registry-enabled audit and feedback, training, and partnerships within and between hospitals.

Conclusion

We identified opportunities to improve sedation and ventilation in the three study settings in Vietnam. The barriers to delivering the care processes we studied echoed those reported in high-income countries, but were exacerbated by local contextual factors such as staffing shortages and differences in professional roles. We developed recommendations for future improvement projects: implementing setting-adapted protocols, standardising terminology to improve documentation, engaging clinical staff with feedback, identifying champions, educate staff regarding the clinical processes and quality improvement and leverage existing internal expertise. These recommendations may have applicability to other care processes and/or settings.

Pause characteristics of sentence production in Parkinson’s disease: Insights from sentence complexity and length

2026-04-23T14:00:00Z

by Fatemeh Mollaei, Huw Evans, Alexandra Pool

Purpose

Parkinson’s disease (PD) affects forward flow of speech including fluency disruptions in 90% of individuals. One of the main parameters affecting flow and fluency of speech is pause behaviour. However, the precise language characteristics of pauses, including sentence complexity and length, and how they contribute to the fluency disruptions of PD are not fully understood. This study examined how sentence complexity and length affect pause behaviour in PD.

Method

Seventy-one participants, comprising individuals with PD (n = 32) and neurotypical controls (n = 39), read a speech passage aloud. The number and duration of pauses, categorised by location (between, within sentences), sentence complexity (simple, complex), and sentence length (short, long) were analysed. Cognitive ability, assessed using the Montreal Cognitive Assessment (MoCA), and motor speech deficits (i.e., dysarthria) severity, assessed using a speech perceptual ranking, were evaluated and correlated with pause characteristics.

Results

Individuals with PD produced significantly more pauses across all categories compared to controls. However, only between-sentence and long-sentence pauses were significantly longer in duration. Pause frequency and duration in both groups were higher in more complex and longer sentences. Significant negative correlations were found between MoCA scores and number of pauses. Significant positive correlations were observed between dysarthria severity and duration of pauses.

Conclusion

These findings suggest that increased cognitive-linguistic demands—indexed by sentence complexity and length—may underlie pausing behaviour and contribute to fluency disruptions in individuals with PD. The results extend previous research by highlighting the potential cognitive-linguistic basis of motor speech dysfunction in PD.

A load forecasting method based on edge graph attention network

2026-04-23T14:00:00Z

by Mengze Gu, Xueping Li, Yao Cai

Given the increasing demand for high-accuracy power load forecasting, traditional load forecasting methods can capture long-term dependencies in time series, but cannot fully capture the complex relationships between multi-dimensional features. This paper proposes an innovative method to convert time series data into graph features. By constructing a graph structure based on time nodes, the time series forecasting problem is transformed into a graph-based load forecasting problem. On this basis, the Edge Graph Attention Network (EGAT) is used to combine the feature information of nodes and edges to further enhance the ability to represent feature interactions and improve the accuracy of load forecasting. This paper compares the EGAT model with common load forecasting methods, including gated recurrent units (GRU), multi-layer perceptron networks (MLP) and long short-term memory (LSTM). The results show that EGAT is effective at finding important features and understanding complex time patterns, which means it shows strong potential in predicting energy demand. A limitation of the proposed approach is its increased computational cost introduced by graph construction and attention-based aggregation, which may raise training time and memory usage for large-scale graphs. In addition, the forecasting performance can be influenced by the design of the time-series graph (e.g., connectivity patterns) and the availability/quality of edge features.

Correction: Functional impact of cardiac implanted devices on ipsilateral shoulder range of motion, scapular mobility, and self-reported quality of life

2026-04-22T14:00:00Z

by Cansu Cosgun, Muharrem Said Cosgun, Oznur Buyukturan, Buket Buyukturan

Correction: Combining lenalidomide with IL-2 family of cytokines enhances activating receptor and perforin/granzyme expression in NK cells

2026-04-22T14:00:00Z

by Alexandra Calescibetta, Robert Dalton, Nicole Fortenbery, Grace Ward, Sean Christiansen, Xianghong Chen, Pingyan Cheng, Tiffany Razabdouski, Annelise J. Glode, Nhan Tu, Thu Le Trinh, Jinghong Liu, Kenneth L. Wright, Sheng Wei, Erika Adriana Eksioglu

The role of SPP1 in evaluating the prognosis, immune infiltration, and drug sensitivity of hepatocellular carcinoma

2026-04-22T14:00:00Z

by Kai Cui, Xia Li, Yongrun Li, Zhong Li, Du Wang, Xinhong Wang, Shuxin Qin, Junjie Li, Jiaye Long

Background

Secretory phosphoprotein 1 (SPP1) has been linked to tumor progression and immune regulation, but its prognostic value, impact on the tumor immune microenvironment (TIME), and drug sensitivity in HCC remain unclear.

Methods

We performed a pan-cancer analysis using TIMER and validated SPP1 upregulation in six GEO datasets (GSE45436, GSE54236, GSE121248, GSE76427, GSE64041, and GSE60502) and HPA protein data. In TCGA-LIHC, we assessed overall survival (OS) and progression-free survival (PFS) using univariate/multivariate Cox analyses, ROC analysis, and a calibrated nomogram. We identified differentially expressed genes (DEGs) and performed GO/KEGG and GSEA analyses. Immune infiltration was estimated with CIBERSORT and TIMER, and relationships with immune checkpoints were explored. Drug sensitivity was predicted with pRRophetic using GDSC data. In vitro, SPP1 was knocked down or overexpressed in HCC cell lines to evaluate effects on proliferation, migration, invasion, and apoptosis via qRT-PCR, Western blot, CCK-8, colony formation, wound healing, Transwell invasion, and TUNEL assays.

Results

SPP1 was significantly upregulated in HCC at mRNA and protein levels. High SPP1 predicted poorer OS and PFS and was associated with higher histological grade, advanced stage, and greater T stage. The nomogram showed good calibration and discrimination. DEGs and enrichment analyses implicated cytokine receptor interaction, fatty acid metabolism, and PI3K-Akt signaling; GSEA confirmed immune- and metabolism-related pathways. High SPP1 correlated with higher immune/ESTIMATE scores, increased M0/M2 macrophages and dendritic cells, reduced CD8 + T cells, and upregulation of multiple immune checkpoints. Drug-sensitivity predictions showed high-SPP1 tumors were more sensitive to several anti-cancer drugs (e.g., sorafenib), while resistance to others was suggested. Functionally, SPP1 knockdown inhibited, while overexpression promoted, proliferation, migration, and invasion; knockdown increased apoptosis.

Conclusions

SPP1 acts as an oncogenic driver in HCC, associated with poor prognosis, an immunosuppressive TIME, and distinct drug-response patterns.

Expression of Concern: Risk factors of progression to endometrial cancer in women with endometrial hyperplasia: A retrospective cohort study

2026-04-22T14:00:00Z

by The PLOS One Editors

Editorial Note: Cohort profile: The Endometriosis pain QUality aftEr Surgical Treatment (EndoQUEST) Study

2026-04-22T14:00:00Z

by The PLOS One Editors

Expression of Concern: Toll-Like Receptor 2 Targeted Rectification of Impaired CD8⁺ T Cell Functions in Experimental Leishmania donovani Infection Reinstates Host Protection

2026-04-22T14:00:00Z

by The PLOS One Editors

A Monte Carlo simulation study of sample size requirements for the Graded Response Model

2026-04-22T14:00:00Z

by Tatsuya Ikeda

Background

The graded response model (GRM) is commonly used in psychometrics to analyze ordinal response data. Despite its growing application in scale development and validation, sample size recommendations—such as those provided by the COSMIN guidelines (e.g., n ≥ 1000)—are often based on expert consensus rather than empirical validation. Furthermore, the extent to which the number of items (J) and the number of response categories (K) contribute to parameter estimation accuracy remains insufficiently explored.

Methods

We conducted a Monte Carlo simulation to examine how three design conditions—sample size (n = 500–1500), number of items (J = 5–50), and a number of response categories (K = 4–7)—influence the estimation accuracy of the latent trait parameter (θ) and the item discrimination parameter (a) under the GRM. For each condition, we generated a large population dataset based on predefined distributions for θ, a, and b, and then randomly drew samples (n) for estimation. The GRM was fitted using the EM algorithm. Estimation accuracy was evaluated using root mean squared error (RMSE), FPC-corrected RMSE, and Pearson’s correlation coefficient between true and estimated θ values.

Results

The RMSE of the discrimination parameter a decreased with increasing sample size (n) and number of items (J), while the effect of K was negligible. In contrast, the RMSE of θ was primarily influenced by J, with only minor effects from n and K. Notably, the Pearson correlation between true and estimated θ values consistently exceeded r = .98 across all conditions, suggesting high ordinal fidelity even with small samples. Increasing J beyond approximately 30 yielded diminishing returns in RMSE reduction.

Conclusions

Our findings suggest that sample size recommendations for GRM should be flexibly tailored to the measurement goal. For accurate estimation of θ, a sufficiently large number of items (e.g., J ≥ 30) can compensate for smaller sample sizes (n ≈ 500), whereas precise estimation of a requires larger samples (n ≥ 1000). The impact of increasing K was limited, indicating that additional response categories may not always enhance parameter recovery. These results provide empirically grounded guidance to support efficient and purpose-specific measurement designs in GRM applications.

Single-cell atlas of gastric cancer reveals malignant epithelial evolution and regulatory reprogramming of the tumor microenvironment

2026-04-22T14:00:00Z

by Xiulan Li, Mengqi Guo, Yunhan Wen, Bo Long

The inflammation–intestinal metaplasia (IM)–carcinoma cascade has been proposed as a framework for gastric cancer (GC) development, yet the cell-level heterogeneity and microenvironmental remodeling underlying this progression remain poorly characterized. Here, we constructed a single-cell transcriptomic atlas by integrating scRNA-seq data from chronic gastritis (superficial, CGS), IM, cancer-adjacent, and tumor tissues through a unified analytical pipeline. Seven major cell lineages were resolved. Relative to CGS, IM and GC tissues exhibited a progressive contraction of epithelial compartments accompanied by expansion of immune and stromal populations. Copy number variation (CNV) inference identified two tumor-restricted malignant epithelial subgroups—one biased toward differentiation and the other enriched for inflammatory and epithelial–mesenchymal transition (EMT) signatures—as well as putative proto-malignant intermediates that coexisted with phenotypically normal epithelium. Cell–cell communication analysis indicated broadly augmented crosstalk between epithelial cells and T cells, myeloid cells, and fibroblasts, with prominent involvement of a CD44–extracellular matrix (ECM) axis. Pseudotime trajectory analysis placed malignant epithelium at late positions along gastric and pyloric mucosal cell differentiation backbones, coinciding with increasing CNV burden and enrichment of stem-like transcriptional programs. Gene regulatory network analysis revealed coordinated activity of lineage-specification modules (HNF4/CDX, NR1H4/ESRRA), proliferative regulons (MYC/TFDP1), and inflammatory/EMT-associated programs (FOSL1/REL/NF-κB). In independent cohorts, elevated expression of several malignant-epithelium-associated transcription factors—including HNF4A, KLF3, FOSL1, TCF7L2, BCL3, RELB, ONECUT2, and MAF—correlated with unfavorable overall survival. Collectively, these findings provide single-cell-resolution evidence consistent with the proposed three-stage model of gastric carcinogenesis and highlight candidate transcriptional regulators warranting further investigation as potential early-detection biomarkers.

RMETNet: A cross-subject motor imagery EEG signal classification model based on TSLANet and riemannian geometry features

2026-04-22T14:00:00Z

by Yun Zhao, Dongyi He, Fudai Ren, Qingling Xia, Linhao Xu, Guanghui Xie, Xiaoling Zhang, Renqiang Yang, Shuaidong Zou, Bin Jiang

Motor imagery electroencephalogram (MI-EEG) analysis is essential for natural interaction and autonomous control in brain-computer interfaces (BCIs). However, deep learning models often struggle with inter-subject variability, which limits their ability to generalize across subjects. This study proposes RMETNet, a novel framework that integrates TSLANet, a spatio-temporal convolution module, and a multi-scale Riemannian geometry feature module. TSLANet suppresses noise and captures complex temporal patterns for preliminary signal decoding, while the spatio-temporal convolution module extracts higher-order representations. The Riemannian branch learns geometry-based distribution features across subjects, and the fused features are used for classification. To address inter-subject distribution shifts, RMETNet incorporates Maximum Mean Discrepancy (MMD) loss for domain adaptation, aligning feature distributions between source and target domains. Experiments show that on the four-class BCI Competition IV 2a (BCICIV2a) dataset, RMETNet achieved accuracies of 71.39% in the cross-subject setting and 80.71% in the subject-dependent setting; on the two-class BCI Competition IV 2b (BCICIV2b) dataset, it achieved 80.93% and 86.76%, respectively. The model consistently outperformed baseline algorithms. Ablation and visualization analyses further validated its effectiveness in reducing inter-subject feature distribution disparities and enhancing MI-EEG decoding. The code is available at: https://github.com/rokanfeermecer486/RMETNet.

Forecasting model of Grapholita molesta (Lepidoptera: Tortricidae) in apple orchards

2026-04-22T14:00:00Z

by Hyunjung Kim, Seonwoong Nah, Hyeon-Ji Yang, DongGeun Choi, Sunghoon Baek

One of the most notorious pests, Grapholita molesta, has caused serious economic damage in apples. However, its phenology model with a defined equation during whole apple crop season has not been developed yet. Therefore, this study was conducted to develop a phenology model of G. molesta adult to predict its current and future occurrence patterns. The 1,087 occurrence data sets of G. molesta adults from 2013 to 2023 were collected from the Rural Development Administration in Korea. Temperature data of each occurrence data set of G. molesta were collected from the Korea Meteorological Administration. The phenology model of G. molesta adults were developed with the data sets from 2013 to 2023 with four-peaked Weibull functions. When validated with independent 2024 data, the model developed in this study accurately predicted adult occurrence and reduced prediction errors (in days) for G. molesta in Korean commercial apple orchards compared to previous studies. The model predicts that G. molesta adults will emerge earlier under climate change scenarios compared to current conditions. In conclusion, this study provides valuable information for controlling G. molesta populations in apple orchards.

Antitumoral immunity induced by gel ethanol ablation to treat unresectable colorectal cancer metastases in the liver

2026-04-22T14:00:00Z

by Jeffrey Yang, Robert Morhard, Hannah Huth, Baktiar Karim, John W. Karanian, Bradford J. Wood, Andrew S. Mikhail, Jenna L. Mueller

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. A quarter of CRC patients develop liver metastases. Treatment options for liver metastases include surgically removing the tumors or undergoing liver transplantation; however, many patients are ineligible for these treatments due to severe extrahepatic disease or lack of suitable donors. Radiofrequency ablation offers an alternative local treatment modality for resolving CRC liver metastases and is known to generate antitumoral effects to stunt contralateral tumor growth. However, radiofrequency ablation is not suitable for tumors situated near critical structures or large blood vessels. Ethanol ablation is an alternative treatment option where pure ethanol is directly injected into tumors to induce necrosis and is unhindered by the drawbacks from radiofrequency ablation. The addition of ethyl cellulose with ethanol (EC-ethanol) enhances its retention within tissue and subsequently improves tumor ablative efficacy. However, the antitumoral response following EC-ethanol ablation in CRC tumors is poorly understood. Thus, we utilized a CRC murine model to investigate the immune effects following EC-ethanol treatment. Studies in the single flank model demonstrated up to a 27-fold increase in IL-6 and KC/GRO pro-inflammatory cytokines within 6 hours post-treatment compared to sham treatments, along with a 4-fold increase in target-tissue necrosis and increased cytotoxic T-cells within the vicinity of the ablation zone over 7 days. Studies in the bilateral flank tumor model demonstrated that EC-ethanol ablation on the primary tumor resulted in a 1.6-fold increase in cytotoxic T-cells within the contralateral tumor after 7 days compared to the sham control group. Combining EC-ethanol treatment with radiofrequency ablation resulted in a more pronounced, 2-fold increase in cytotoxic T-cells within the contralateral tumor. Altogether, these results suggest that EC-ethanol potentiates antitumoral effects in CRC tumors and is a strong therapeutic candidate for treating CRC patients worldwide.

Beyond Clavulanic Acid biosynthesis: Exploring the broad regulatory impact of BldD in Streptomyces clavuligerus ATCC 27064

2026-04-22T14:00:00Z

by Luisa F. Patiño, Carlos Caicedo-Montoya, Rigoberto Ríos-Estepa

BldD is a global regulator of morphological development in Streptomyces, usually acting as a repressor of aerial mycelium formation. However, its role in metabolism and secondary biosynthesis in the wild-type strain Streptomyces clavuligerus remains poorly understood. In this study, we constructed a S. clavuligerus strain overexpressing bldD and compared it with the empty vector control strain during fermentation in soy protein isolate medium. For this, transcriptomic analyses were performed at 24 h and 72 h. We observed that BldD overexpression reduced CA production and repressed genes involved in cephamycin C biosynthesis, including lat and the pathway regulator ccaR. In contrast, genes associated with terpene biosynthesis, phage tail-like particles (CIS), and aerial mycelium formation (bldN, bldM, chaplins) were upregulated. These changes suggest that BldD may directly and indirectly redirects metabolic flux away from β-lactam biosynthesis while promoting morphological differentiation, alternative defense systems and a potential link with GlcNAc metabolism. By repressing β-lactam pathways and enhancing CIS and terpene gene expression, BldD shifts cellular priorities toward morphological development and ecological defense, underscoring species-specific differences from the well-studied model Streptomyces coelicolor. These results greatly contribute to the understanding of the regulatory mechanisms involved in CA biosynthesis.

Evaluation of large language models in medical examinations: A scoping review protocol

2026-04-22T14:00:00Z

by Weiqi Wang, Baifeng Wang, Yan Zhu, Zhe Wang, Suyuan Peng

Introduction

Standardized medical examinations, used to assess trainee clinical competencies, provide a rigorous means to verify LLM accuracy and reliability in medical contexts. Although current evaluations use these exams to test LLMs’ clinical reasoning, significant performance variations occur across different clinical scenarios. Existing methods struggle to adapt to evolving research needs. This study synthesizes prior research on LLMs in medical exams, highlighting current limitations and proposing future research directions.

Methods and analysis

The formulation of the protocol was guided by the standards set forth in the JBI Manual for Evidence Synthesis. Following the establishment of precise inclusion/exclusion criteria and search strategies, we will execute systematic searches in the PubMed and Web of Science Core Collection databases. The method encompasses literature review, data extraction, analytical frameworks, and process mapping. By employing this method, researchers maintain methodological rigor during the entire research process.

Ethics and dissemination

This protocol describes a method for performing a scoping review. The investigation focuses on the organized synthesis and examination of previously published research. It does not include human/animal experimentation or sensitive data collection. Ethical approval is not required for this literature-based study.

Single-cell multiomics data analysis of potential receptors and therapeutic drugs for epilepsy patients comorbid with depression

2026-04-22T14:00:00Z

by Guiqin Bai, Xuerong Zhou, Cheng Xiong, Xi Kang, Ruiqi Huang, Dazhang Bai, Peilin Zhao, Tao Peng, Cheer Muer, Guohui Jiang, Shushan Zhang

Depression frequently cooccurs with epilepsy (EP) and has become a focus of clinical management, but effective pharmacological interventions remain limited. In this study, single-cell RNA sequencing (scRNA-seq) data were analyzed to identify changes in oligodendrocyte precursor cells (OPCs) in EP and major depressive disorder (MDD) patients, and intercellular communication and trajectory analyses were performed. Key therapeutic targets and pathways were identified via differentially expressed genes (DEGs), protein-protein interaction (PPI) networks, and gene ontology (GO) enrichment. A connectivity map (CMap) was generated to identify optimal drugs. Molecular dynamics simulation (MDs) and cell thermal stability migration assay (CETSA) were conducted to evaluate protein-drug interactions. The results revealed significant changes in gene expression in OPCs, with neuroligin3 (NLGN3)-neurexin (NRXN) signaling being the main pathway involved. Three hub genes correlated with NLGN3 were enriched in oxidative phosphorylation and mTORC1 signaling. Ziprasidone could effectively treat EP with MDD by strongly binding to NLGN3, forming two hydrogen bonds with a binding energy of −7.5 kcal/mol. This stable interaction was further confirmed by MDs and CETSA experiments. In conclusion, the NLGN3 protein interacts with ziprasidone to form stable complexes, which may activate the NLGN3-NRXN signaling pathway in OPCs and enhance synaptic remodeling by reducing neuroinflammatory responses.

Tracking tuberculosis control using detailed population health and satellite luminosity data: findings from Kazakhstan

2026-04-22T14:00:00Z

by Sultan Muratov, Charles Becker

Following the collapse of the Soviet Union, Kazakhstan, like many other formerly socialist countries, experienced a surge in tuberculosis (TB). Despite the successful efforts of Kazakhstan’s Ministry of Health in reducing TB related mortality, analysis of TB risk factors in Kazakhstan remains incomplete. This study takes advantage of detailed district-level population health data, and links TB to the presence of man-made environmental damage from the Semipalatinsk Nuclear Test Site and the desiccation of the Aral Sea. Using both propensity score matching and regression models, along with census and satellite nightlight (SNL) data, we examine TB incidence and prevalence from 2000 to 2018, focusing on regions affected by acute environmental disasters. Areas severely exposed to ionizing radiation have converging TB incidence and prevalence. In contrast, regions most affected by the Aral Sea’s desiccation continue to have elevated TB levels. Our results suggest that areas officially recognized as “zones of ecological catastrophe” and “zones of ecological crisis” have about 40% and 30% higher prevalence and incidence of TB, respectively. Further analysis of time trends reveals that the significantly elevated TB incidence in these areas appears to be driven by dynamics during 2000–2012 and is not present in more recent years. TB prevalence in the zones of ecological catastrophe and crisis also demonstrates a converging trend, though relative rates remain much higher.

Endorsement of the 32-item Consolidated Criteria for Reporting Qualitative (COREQ) and Standards for Reporting Qualitative Research (SRQR) by Chinese journals of nursing: A survey of editors and review of journal instructions for authors

2026-04-22T14:00:00Z

by Li Zhao, Jian Zeng, Kaiyan Hu, Bin Ma

Background

To investigate the endorsement of the 32-item Consolidated Criteria for Reporting Qualitative (COREQ) and Standards for Reporting Qualitative Research (SRQR) in the instructions for authors (IFA) of Chinese nursing journals. The awareness of Chinese editors of the COREQ and SRQR, together with their application and requirements for following the standards, were also investigated. These findings would assist as the endorsement, application, and promotion of the COREQ and SRQR in Chinese nursing journals, and improve the reporting quality of qualitative research in nursing.

Methods

Nursing journals were identified from the National Press and Publication Administration. The IFA and applications of the COREQ and SRQR were assessed. The editors of the journals were asked about their awareness of and demand for the COREQ checklist and SRQR standards, as well as their implementation at different stages of the publication process, including manuscript submission, editing, and peer review.

Results

A total of 29 nursing journals were included, and only 2 journals (6.9%, 2/29) mentioned the COREQ and SRQR in their IFA. Among the 24 surveyed editors, only 45.83% (11/24) and 33.33% (8/24) were aware of the COREQ and SRQR, respectively. None of the surveyed editors required authors to follow the COREQ/SRQR at the submission stage, editors to follow COREQ/SRQR in the journal editing and processing stage, and reviewers to use the COREQ/SRQR in the expert review stage.

Conclusion

Nursing journals in China endorsing the COREQ and SRQR constitute a small percentage of the total. In addition, both awareness and application of the COREQ and SRQR were poor among nursing journal editors. Therefore, we strongly recommend that the China Periodicals Association undertake measures to encourage and support the endorsement of biomedical research reporting guidelines in nursing journals. Also, the education and training of journal editors, researchers, and medical students on biomedical research reporting guidelines should be strengthened.

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Editorial Note: Cohort profile: The Endometriosis pain QUality aftEr Surgical Treatment (EndoQUEST) Study

Expression of Concern: Toll-Like Receptor 2 Targeted Rectification of Impaired CD8+ T Cell Functions in Experimental Leishmania donovani Infection Reinstates Host Protection

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Single-cell atlas of gastric cancer reveals malignant epithelial evolution and regulatory reprogramming of the tumor microenvironment

RMETNet: A cross-subject motor imagery EEG signal classification model based on TSLANet and riemannian geometry features

Forecasting model of Grapholita molesta (Lepidoptera: Tortricidae) in apple orchards

Antitumoral immunity induced by gel ethanol ablation to treat unresectable colorectal cancer metastases in the liver

Beyond Clavulanic Acid biosynthesis: Exploring the broad regulatory impact of BldD in Streptomyces clavuligerus ATCC 27064

Evaluation of large language models in medical examinations: A scoping review protocol

Single-cell multiomics data analysis of potential receptors and therapeutic drugs for epilepsy patients comorbid with depression

Tracking tuberculosis control using detailed population health and satellite luminosity data: findings from Kazakhstan

Endorsement of the 32-item Consolidated Criteria for Reporting Qualitative (COREQ) and Standards for Reporting Qualitative Research (SRQR) by Chinese journals of nursing: A survey of editors and review of journal instructions for authors

Expression of Concern: Toll-Like Receptor 2 Targeted Rectification of Impaired CD8⁺ T Cell Functions in Experimental Leishmania donovani Infection Reinstates Host Protection