PLOS ONE Alerts: New Articles

Correction: Nonlinear dose-response of mind-body exercise in older adults with mild cognitive impairment: A systematic review and meta-analysis

2026-10-22T14:00:00Z

by Yan-Fang Peng, Xi Chen, Guo-Qing Zhu, Guang-Cai Qu

The impact of perceived social support on college athletes’ academic burnout: The moderating role of cognitive reappraisal within a serial mediation model

2026-10-22T14:00:00Z

by Guihua Xu, Xirui Yang, Qiyong Zhang

College athletes face substantial challenges from the combined demands of academic study and athletic training, placing them at elevated risk for academic burnout (AB). This study examined how perceived social support (PSS) is associated with AB by testing the mediating roles of mental toughness (MT) and athlete burnout (ATHB) and the moderating effect of cognitive reappraisal (CR). Using a cross-sectional design, 1,918 college athletes from over 20 Chinese universities completed standardized questionnaires assessing PSS, MT, ATHB, CR, and AB. Serial and moderated serial mediation were analyzed with the PROCESS macro (Models 6 and 89) while controlling for demographic and sport-related variables. PSS was directly and negatively associated with AB (β = −0.122, p < 0.001), with significant indirect associations separately through MT and ATHB and sequentially through MT and ATHB. CR showed path-specific moderation: at higher levels of CR, the negative PSS–AB association was stronger, but so was the positive ATHB–AB association, whereas the MT–AB association did not differ significantly across CR levels. Thus, CR should not be interpreted as having a uniformly buffering role. These findings may inform future multicomponent support approaches aimed at strengthening PSS and MT and identifying and addressing ATHB, while applying CR-related training cautiously and with attention to the specific pathway involved. The effectiveness and boundary conditions of such approaches require longitudinal or experimental testing.

Predicting under-five child mortality in Zambia: Machine learning versus parametric survival models

2026-10-22T14:00:00Z

by Kassaye Getaneh Arge

Background

In sub-Saharan Africa, child mortality remains a critical public health challenge, with Zambia exhibiting some of the highest rates in the region. While survival analysis has identified key risk factors, these methods often fail to capture complex non-linear interactions and the dynamic, time-varying nature of longitudinal markers like birth intervals. This study aimed to develop and compare predictive survival models to improve risk stratification for under-five mortality using the 2024 Zambia Demographic and Health Survey (ZDHS).

Methods

A cohort of 35,610 live births was initially identified, with a final analytic sample of 9,362 singleton births and 1,236 mortality events (13.2%) after applying exclusion criteria for maternal age and data completeness. We compared four modeling frameworks for predictive comparison: Cox Proportional Hazards (Cox PH), Lasso Cox regression, Random Survival Forests (RSF), and Gradient Boosting Machines (GBM), alongside a Bayesian Joint Model for inference on the birth interval and mortality association. The proportional hazards assumption was assessed using Schoenfeld residuals, and stratified Cox models were employed to address time-varying effects. Model performance was evaluated using nested cross-validation with mother-level outer folds and time-dependent Concordance Indices (C-index) and Area Under the Curve (AUC) metrics across a 48-month follow-up period.

Results

Under nested cross-validation, the four survival models demonstrated comparable predictive performance, with C-indices ranging from 0.745 (Cox PH) to 0.750 (Gradient Boosting Machine) and Integrated Brier Scores ranging from 0.095 to 0.096; pairwise comparisons across models were not statistically significant (DeLong’s test: all p > 0.05). The Bayesian Joint Model revealed a significant association between the longitudinal birth interval process and the hazard of death (α=0.035, 95% CI: 0.023–0.048, p < 0.001), supporting the maternal depletion hypothesis. Variable importance analysis identified birth interval and maternal age as the most influential predictors of child survival, followed by previous child deaths. Stratified analysis of the Cox model revealed significant effects for maternal education (Secondary: HR = 0.426, 95% CI: 0.318–0.570) and previous child deaths (HR = 1.648, 95% CI: 1.529–1.777).

Conclusion

Advanced survival modeling using joint modeling techniques provides deeper biological insights into child mortality dynamics, and machine learning and traditional survival models offered equivalent predictive discrimination and calibration in this analysis. These findings support targeted public health interventions focusing on birth spacing, maternal age, and enhanced monitoring for high-risk families as critical strategies for reducing under-five mortality in Zambia.

CohAlign: Predicting the first-order noise susceptibility of gradients in equivariant quantum neural networks

2026-10-22T14:00:00Z

by Hassan Ugail, Newton Howard

Quantum neural networks learn by following gradients, and on real hardware those gradients are washed out by noise. Predicting how quickly this happens, before any finite noise experiment or circuit sweep is run, remains an open problem. We present CohAlign, an open source toolkit that computes the first order noise susceptibility of the ensemble second moment of a specified parameter gradient in a charge conserving brickwork quantum neural network. The computation needs only a classical description of the circuit, the noise model, the prepared state, the readout and the initialisation prior. The predicted quantity is distinct from training convergence or final accuracy. The key observation is that only the part of the noise that a measurement can actually see matters. A purposefully constructed control channel makes this clear, damaging the operator carrying a gradient at nearly the maximal rate while the measured gradient remains exactly as predicted and untouched. We validate the predictions against separately evaluated finite difference slopes across the benchmark suite, including a signed coherent case, in exact simulations at eight and ten qubits and on two circuit topologies.

Prevalence and determinants of tobacco use among university students in Lebanon: Implications for smoke-free campus policies

2026-10-22T14:00:00Z

by Mohamad Ali Hijazi, Deema Rahme, Dana Jammoul, Lynn Al Jawiche, Mohamad Alameddine

Background

The tobacco epidemic is a global public health threat, with addiction often starting in the early adulthood stage of life. The Middle East Region is slow in adopting smoke-free campus policies, and few studies have examined smoking attitudes and behaviors among university students and their perspective on such policies.

Objective

The objective of this study was to determine the perceptions, knowledge, attitudes, and behaviors toward smoking (used to denote using any tobacco products) and smoke-free campus policies among university students aged between 17 and 30 years old at a large multicampus academic institution in Lebanon.

Methods

The study utilized a comprehensive cross-sectional study design. The questionnaire used in this study included validated tools for assessing smoking behaviors, such as the Global Adult Tobacco Survey (GATS); the Youth Tobacco Survey (YTS); and the Smoking Knowledge, Attitudes, and Practices (KAP) survey, as well as sections for investigating attitudes toward smoking and the smoke-free campus policy.

Results

This study reports an alarming prevalence of smoking on campuses (32.2%), with more than half of the surveyed smokers reporting attempts to quit smoking in the past 12 months (53.4%). The factors significantly associated with smoking included having family (OR 7.08, 95% C.I (2.83–17.69) or friends (OR 12.20, 95% C.I (5.48–19.76)) who smoke, as well as experiencing social, emotional, or mental distress (OR 4.09, 95% C.I (1.74–9.63)). Further analysis revealed that agreement with a smoke-free university policy was a significant factor associated with reduced odds of smoking (OR 0.58 95% C.I (0.45–0.78)), whereas the perceived unfairness of smoking bans on campuses was associated with increased odds of smoking (OR 1.87, 95% C.I (1.34–2.61)).

Conclusions

The results highlight a promising window of opportunity to implement evidence-based interventions to support students in quitting smoking. Interventions include educational programs to raise awareness of the dangers of tobacco use and programs to break the association between exposure to stress and smoking. Such programs could include a combination of awareness programs and organizing stress-reducing services, workshops, and consultations. Because the design is cross-sectional, these findings describe associations rather than causal effects; they nonetheless support the further evaluation of smoke-free campus policies as one component of a broader strategy to lower students’ smoking rates, mitigate peer influence and foster healthier campus environments.

Assessing the robustness of meta-analyses to variability in the frequency and timing of postoperative delirium assessment – a novel methodological approach

2026-10-22T14:00:00Z

by Maram Khaled, Harsha Shanthanna, Lehana Thabane, James Paul, Anthony Absalom, Sergio Bergese, Federico Bilotta, Douglas Campbell, Matthew Chan, Mark Coburn, David Cowan, Kamal Maheshwari, Edward Mascha, Robert D. Sanders, Daniel I. Sessler, Tim Short, Jessica Spence, Alparslan Turan, Dong-Xin Wang, Maria Wittmann, Maura Marcucci

Background

Postoperative delirium (POD) is a fluctuating confusional state occurring early after surgery. Given its fluctuating nature, POD detection is influenced by the frequency and timing of screening. Sparse assessments potentially underestimate the true incidence reported in individual studies, subsequently influencing the weight of studies in meta-analyses, and the results and precision of these meta-analyses.

Objective

To develop a method to evaluate the robustness of meta-analyses to the variation in the frequency and timing of POD assessment across included studies.

Methods

We developed an expert-based scoring system to rate studies according to the confidence that a patient reported not to have POD in the study truly did not, based on the reported timing and frequency of POD assessments. We describe how to use the system to generate hypothetical event rates for studies if the frequency and timing of POD assessment were optimal and how to use these rates in a sensitivity analysis of meta-analyses including these studies. We illustrate the method applying it to two meta-analyses as work examples, one of observational studies and one of randomized controlled trials (RCTs).

Results

In our work examples, the expert-based score for the individual studies ranged from 33–77% for the observational and 22–70% for RCTs meta-analysis. Sensitivity analyses showed a change in the pooled effect size, heterogeneity, and precision compared to the original estimates.

Conclusion

We present a method to evaluate the robustness of a meta-analysis of studies having POD as an outcome, when there is variation across individual studies in the frequency and timing of POD assessment. The confidence score acts as a preliminary index of the robustness of meta-analyses. Through work examples, we showed that the robustness depends on the characteristics of individual studies included.

TCLNet: A Thermal Contrast-Aware Lightweight Network for infrared object detection

2026-10-22T14:00:00Z

by Xiyuan Zhu, Hongtao Dang, Xiaoyuan Jin

Infrared object detection plays an important role in low-light and complex-environment perception. However, infrared images often exhibit low signal-to-noise ratio, weak target-background contrast, and limited texture information, which can degrade detection performance in small-target and cluttered-background scenarios while making it difficult to balance detection accuracy and model complexity. To address these challenges, this paper proposes TCLNet, a Thermal Contrast-Aware Lightweight Network for infrared object detection. TCLNet introduces a Thermal Contrast Encoder (TCE) to enhance local contrast-sensitive target representations and a Thermal-Guided Cross-Feature Attention (TGCA) mechanism to promote interactions between contrast-enhanced and semantic features, thereby improving target discrimination and suppressing background interference.Experiments were conducted independently on the M3FD, FLIR ADAS v2 (denoted as FLIR_2), and NUDT-SIRST1 datasets. TCLNet achieves mAP50 values of 60.5%, 45.4%, and 91.4%, respectively, corresponding to improvements of 12.8, 11.3, and 7.5 percentage points over the YOLO12n baseline. Meanwhile, the model maintains a compact size of approximately 2M parameters. These results demonstrate that TCLNet improves infrared target detection, particularly in low-SNR and small-target conditions, while achieving a favorable balance between detection accuracy and model complexity.

Can immersive virtual reality be an alternative world for eliciting consumer willingness to pay for food?

2026-10-22T14:00:00Z

by Toru Nakajima, Mizuki Mukai

This study examines whether consumers’ willingness to pay (WTP) for ready-to-eat cereals differs between immersive virtual reality (IVR) and real-world (RW) environments. Real choice experiments were conducted with 227 respondents who selected reservation dates without knowing whether they corresponded to the IVR or RW setting. To derive consumers’ WTP, random parameter logit models were estimated primarily in WTP space, while preference-space models were used as a robustness check. The results show no significant differences in WTP between IVR and RW for any of the cereal products tested. This suggests that consumers’ product choices in IVR environments are based on monetary valuations, similar to those in real environments. When combined with real economic incentives, IVR-based choice experiments may therefore yield WTP estimates comparable to those obtained from conventional real choice experiments. To our knowledge, this is the first study to compare WTP between IVR and RW environments using an incentive-compatible experimental design.

Deep learning–driven fine-resolution finger movement recognition from surface EMG signals

2026-10-22T14:00:00Z

by Hiam Alquran, Hassan Alawneh, Mohammed Alsalatie, Ateka Khader, Wan Azani Mustafa, Khaled Zayed Alawneh

Surface electromyography (sEMG) has emerged as an impactful tool for controlling advanced prosthetic devices by detecting and recording muscle electrical activity during motion. This study presents a unique technique for recognizing nine distinct classes of finger movements by utilizing the Ninapro database. To address an underexplored domain of upper-limb prosthetic control, this research targets fine-resolution individual finger movements rather than the broad range of hand gestures. A custom-made one-dimensional convolutional neural network (1D–CNN) was developed and validated using a within-subject evaluation strategy and signals. The proposed model achieved an overall classification accuracy of 90.1%. An in-depth sensitivity/specificity analysis for each finger movement class was administered to gain key insights into current recognition capabilities. The findings presented in this study demonstrate the viability of fine-resolution finger-movement recognition, offering foundational insights that may inform the future development and refinement of control systems in the prosthetic field.

Otolin-1 for differentiating central and peripheral causes of acute continuous dizziness

2026-10-22T14:00:00Z

by Vincent W. Klokman, Merel J. J. Verhagen, Adriaan A. J. Ros, Karlijn F. de Laat, Korné Jellema, Dominique P. V. de Kleijn, Kim E. Jie

Background

Patients with isolated acute-onset continuous dizziness (iAOCD) are commonly seen at the emergency department (ED). Distinguishing peripheral vestibular disorders from central causes remains challenging. Existing diagnostic tools, including bedside examination and neuroimaging, have important limitations. Otolin-1, an inner ear–specific glycoprotein, has been proposed as a biomarker of peripheral vestibular pathology. This study evaluated whether otolin-1 could serve as a diagnostic biomarker for this differentiation.

Methods

This study analyzed samples from a prospective multicenter cohort of adult patients who were seen at the ED with acute onset, continuous dizziness without focal neurological deficits. Patients were included within 24 hours of symptom onset. Otolin-1 plasma concentrations were measured using an enzyme-linked immunosorbent assay. Final diagnoses (central versus peripheral) were determined by an expert panel based on clinical assessment, diffusion-weighted magnetic resonance imaging and 3-month follow-up.

Results

We analyzed 245 patients (179 peripheral, 66 central). Median otolin-1 concentrations did not differ significantly between peripheral and central causes (517.6 [IQR 443.7–592.8] pg/mL vs 487.9 [424.9–644.4] pg/mL; p = 0.349). No significant differences were observed in hyperacute (<4.5 hours after symptom onset) or acute (4.5–24 hours after symptom onset) subgroups. Similarly, otolin-1 concentrations did not differ between central iAOCD and specific peripheral diagnoses. Substantial overlap in concentration ranges was observed across all comparisons. Receiver operating characteristic analysis similarly showed no useful discrimination (AUC 0.539, 95% CI 0.455–0.623).

Conclusions

Otolin-1 does not differentiate between central and peripheral causes of iAOCD in the ED setting. Although biologically linked to inner ear pathology, otolin-1 lacks sufficient discriminatory value as a stand-alone diagnostic biomarker.

IL15.3, a synthetic antimicrobial peptide, attenuates LPS-induced inflammatory responses in RAW 264.7 macrophages via transcriptional and proteomic modulation

2026-10-22T14:00:00Z

by Chanapat Boonmark, Sittiruk Roytrakul, Fasawanya Saengyotha, Anupong Tankrathok, Anuwat Wanthong, Jureerut Daduang, Sakda Daduang, Arunrat Chaveerach, Nisachon Jangpromma

Inflammation underlies numerous pathological conditions, driving the need for safe and effective anti-inflammatory agents. Anti-inflammatory peptides (AIPs) are promising therapeutics due to their specificity, efficacy, and safety. This study evaluated the cationic antimicrobial peptide IL15.3 for anti-inflammatory activity and cytocompatibility in vitro. IL15.3 demonstrated low cytotoxicity in MTT assays using RAW 264.7 macrophages, normal human dermal fibroblasts (NHDF), and HaCaT keratinocytes. In LPS-stimulated RAW 264.7 cells, IL15.3 significantly reduced nitric oxide (NO) production and reactive oxygen species (ROS) in a dose-dependent manner without affecting cell viability. qRT-PCR analysis revealed significant suppression of iNOS, COX-2, TNF-α, and IL-6 mRNA expression, alongside downregulation of NF-κB, JNK, STAT1, and STAT3, and a reciprocal shift in Keap1/Nrf2 expression suggestive of possible antioxidant pathway activation. Label-free proteomic profiling identified 5,191 proteins, revealing a multi-modal mechanism of action. IL15.3 treatment exclusively induced 4 anti-inflammatory proteins (ISG15, PEX14, TNIP3, PR) and upregulated negative regulators NRG1, DAB2IP, IL-18BP and SOCS5. Critically, IL15.3 suppressed key pro-inflammatory mediators including IKKβ, JAK1, JAK3, JNK, and IL-1RAcP, demonstrating comprehensive modulation of NF-κB, JAK/STAT, and MAPK pathways. In silico molecular docking further predicted potential interactions of IL15.3 with iNOS and the Keap1 Kelch domain, offering preliminary structural insight consistent with its putative dual anti-inflammatory and antioxidant activity. Together, these findings indicate that IL15.3 exhibits potent anti-inflammatory and antioxidant activity through multiple mechanisms in LPS-stimulated macrophages at transcriptional and proteomic levels. The coordinated upregulation of negative regulators and suppression of central inflammatory mediators collectively suggest that IL15.3 may represent a promising therapeutic candidate for inflammatory disorders.

Decanoic acid additively suppresses IL-1β and enables pharmacologic dexamethasone dose-sparing in LPS/ATP-stimulated THP-1 macrophages

2026-10-22T14:00:00Z

by Melissa A. Hausburg, Kaysie L. Banton, Christopher D. Cassidy, Robert M. Madayag, Carlos H. Palacio, Jason S. Williams, Gregory W. Thomas, Raphael Bar-Or, David Bar-Or

Systemic inflammatory response syndrome, driven by trauma or infection, involves excessive innate immune activation. Dexamethasone (DEX), a synthetic glucocorticoid, suppresses inflammation, although adverse side effects limit its clinical use. The inflammasome, a multiprotein complex that assembles in response to inflammatory stimuli like ATP after lipopolysaccharide (LPS) priming, facilitates caspase-1 cleavage and release of the proinflammatory cytokine, interleukin (IL)-1β. We investigated whether DEX and decanoic acid (DA), a saturated medium-chain fatty acid, inhibited caspase-1 activity and IL-1β release in an LPS/ATP-stimulated THP-1 macrophage model and whether co-treatment would allow for pharmacologic DEX dose-sparing in vitro. PMA-differentiated THP-1macrophages were primed with LPS overnight and stimulated with ATP for 3 h in the presence of DA, DEX, or both. Viability and cytotoxicity were assessed. Caspase-1 activity and IL-1β were quantified, and EC₅₀ values were calculated by nonlinear regression. In control conditions, LPS/ATP stimulation induced 5.56 (q1: 3.51 – q3: 6.38) ng/mL of IL-1β release. DA and DEX inhibited IL-1β with full dose-response EC₅₀ values of 131.7 μM and 24.29 nM, respectively. DA concentrations exceeding 800 μM decreased cell viability. An 8 x 9-point DA/DEX dose matrix (0–500 μM DA; 0 to 1e4 nM DEX) was used to interrogate drug interaction for IL-1β inhibition and caspase-1 activity. DEX EC₅₀ values remained within a narrow 95% confidence interval of 17.5–26.6 nM, regardless of DA background concentration. DA reduced caspase-1 enzymatic activity with a calculated EC₅₀ value of ~140 μM; whereas, DEX did not. These data show that DA and DEX act independently. Furthermore, compared to DEX alone, the presence of DA allowed for equivalent in vitro IL-1β suppression at lower DEX concentrations, supporting pharmacologic DEX dose-sparing. Determination of whether this pharmacologic effect translates to clinically meaningful corticosteroid dose reduction requires further study.

Global stakeholder preferences for point-of-care HIV nucleic acid amplification tests: A conjoint study

2026-10-22T14:00:00Z

by Kara M. Palamountain, Chethana Achar, Rebecca P. Kirby, Yukari C. Manabe, Debi Boeras, Michal Maimaran

Introduction

This study aimed to assess global stakeholder preferences for key attributes of point-of-care (POC) HIV Nucleic Acid Amplification Tests (NAAT), with the aim of informing product development to support progress toward UNAIDS 95-95-95 targets.

Methods

A web-based conjoint survey was conducted in August through November 2024 among HIV clinicians, laboratory professionals, and researchers. Participants were asked to evaluate hypothetical POC HIV NAAT profiles varying by six attributes: sensitivity / limit of detection (LOD), sample-collection method, turnaround time (TAT), result format, price, and power source. Relative importance and part-worth utilities were calculated to assess trade-offs in decision-making.

Results

One hundred three respondents from 33 countries, primarily in Africa (75%), completed the survey. The relative importance placed on the attributes in the conjoint task varied based on the setting. In community and home-based settings, participants prioritized fingerstick sample collection (25.90%) and faster TATs (28.8%), even at the expense of sensitivity (15.70%). By contrast, respondents from hospitals and health centers valued tests with high sensitivity (42.6%, 40.9%) and faster TATs (31.5%, 22.6%). Across all respondents, price (7.0%), result format (3.30%), and power source (7.25%) were less influential.

Conclusions

Stakeholders were willing to make trade-offs among desirable attributes, prioritizing rapid turnaround time, strong sensitivity, and fingerstick sampling over affordability, power requirements, and result format in the conjoint task. These preferences vary by level of care and by use case, underscoring the importance of aligning product features with contextual needs. Engaging stakeholders early in the design process is critical to ensure new POC HIV NAAT technologies are both acceptable and scalable in low-resource settings.

Institutional patterns in diagnosis and antifibrotic-era treatment uptake for IPF and PPF across U.S. centers

2026-10-22T14:00:00Z

by Bradley A. Sheffield, Brian J. Cassel, Apostolos Perelas, Patricia Sime, Peter Jackson

Purpose

For ten years, nintedanib and pirfenidone have been the only approved therapies for idiopathic pulmonary fibrosis (IPF), with nintedanib subsequently also approved for progressive pulmonary fibrosis (PPF). Previous studies demonstrate low antifibrotic (AF) uptake, but differences by site-of-care and AF uptake after seminal trials (IPF: INPULSIS/ASCEND; PPF: INBUILD) are not well characterized. We evaluated temporal trends in IPF and PPF diagnosis and AF use at academic (AC) versus non-academic (NonAC) centers.

Methods

Using the U.S. TriNetX Collaborative Network, we compared IPF and PPF incidence, prevalence, and AF use by center type using linear regression across post-trial and post–FDA-approval windows (IPF: 2015–2017, 2015–2024; PPF: 2020–2022, 2020–2024). Slope differences (Δslope) were calculated as AC minus NonAC annual slopes; therefore, positive values indicate faster increases at ACs, whereas negative values indicate faster increases at NonACs.

Results

Across both periods, IPF prevalence increased more rapidly at NonACs, while AF use was higher at ACs (2024: 33.5% vs 20.1%, p < 0.001). During the post-approval period (2015–2024), AF initiation and overall use rose faster at ACs: (AC–NonAC Δ slope +0.26 percentage points/year, p = 0.002; + 1.25 percentage points/year, p < 0.001). During the post-INPULSIS/ASCEND period (2015–2017), overall AF use rose faster at ACs (Δ slope +1.23 percentage points/year, p = 0.009), while AF initiation slopes did not differ significantly (Δ slope −0.22 percentage points/year, p = 0.155). PPF prevalence was similar across centers, with higher AF use at ACs in 2024 (17.1% vs 9.8%, p < 0.001). During the post-approval period (2020–2024), AF initiation and overall AF use increased faster at ACs (Δslope +1.16 percentage points/year, p < 0.001; + 1.94 percentage points/year, p = 0.009). During the post-INBUILD period (2020–2022), AF initiation rose faster at ACs (Δ slope +1.42 percentage points/year, p = 0.002), while overall AF slope differences were not significant. Outcome patterns for IPF revealed higher mortality and lung transplant in ACs, but lower respiratory failure and oxygen use. PPF showed higher respiratory failure and mortality in ACs, and no significant differences in lung transplant or oxygen use.

Conclusions

AF use in IPF and PPF was higher and rose faster at ACs, suggesting faster AC adoption and potential barriers at NonACs. Mixed outcome findings suggest referral and severity bias may partially explain differences, however, are unlikely to fully account for them. More research is needed to account for referral and severity bias. Given the small NonAC PPF cohort (n = 216), PPF findings should be interpreted with caution.

More than gaming: Examining executive functions in esports players

2026-10-22T14:00:00Z

by Serhat Yalçıner, Nahit Özdayı

The main purpose of this study was to determine the differences in executive function performance levels of esports players who play First-Person Shooter (FPS) and Multiplayer Online Battle Arena (MOBA) game types compared to non-video game players (NVGPs). Other purposes of the study are to examine the relationships of executive function components and their relationships with in-game rank and total game play time variables. The study groups consisted of ninety volunteer participants, all of whom were male young adults between the ages of 18 and 34, 30 of whom actively played FPS video games, 30 of whom actively played MOBA video games, and 30 of whom NVGPs. Corsi Block-Tapping Test (CBT), Wisconsin (Berg) Card Sorting Test (WCST), and Stroop Test Çapa Form (ST) were used as data collection tools. According to the findings of the study; FPS players had significantly higher scores than NVGPs (p < 0.001, F = 8.55) in CBT and less error percentage than the NVGPs (p < 0.01, F = 5.58) and MOBA players had significantly less interference time than NVGPs in the ST (p < 0.001, F = 7.66). In addition, there was a significant negative correlation between CBT and ST interference times for all players (p < 0.05; r = −0.28) and a significant negative correlation between in-game skill and ST interference times for FPS players (p < 0.05; r = −0.41). These findings suggest that digital video game experience shapes cognitive profiles based on genre-specific demands; while FPS gameplay primarily enhances visuospatial working memory capacity, MOBA gameplay fosters stronger inhibition control, with higher in-game skill level reflecting superior inhibitory control in FPS gameplay, and relationship of visuospatial working memory and inhibition components demonstrating an underlying interrelated structure.

Association of IL-6 and IL-10 serum levels with genetic variants in diabetic neuropathy: Clinical findings from a Bangladeshi patient cohort

2026-10-22T14:00:00Z

by Rajib Das, Sheikh Zahir Raihan, Shyamjit Paul, Mohammad Shamsul Arefin Patwary, Abul Kalam Azad Chowdhury

Background

Diabetic Neuropathy (DN) is a prevalent complication of diabetes linked to chronic inflammation. Interleukin-6 (IL-6) and Interleukin-10 (IL-10) are key cytokines implicated in DN pathogenesis. This study investigates the association of IL6 and IL10 gene polymorphisms and serum levels with DN in the Bangladeshi population.

Materials and methods

A case-control study was conducted with 225 participants: diabetic patients with DN (n = 75), diabetic patients without DN (n = 75), and healthy controls (n = 75). Genomic DNA was extracted for genotyping IL-6 (rs1800796) and IL-10 (rs1800896) SNPs via PCR. Serum cytokine levels were measured using ELISA.

Results

Serum IL-6 levels were significantly higher in the DN group than in the other study groups (p < 0.0001), with the highest levels observed among individuals with the IL-6 rs1800796 CC genotype. In unadjusted analyses, the IL-6 CC genotype was associated with increased odds of DN compared with healthy controls (OR = 4.813, 95% CI: 1.752–13.85, p = 0.0040), as was the IL-10 GG genotype (OR = 2.679, 95% CI: 1.000–6.751, p = 0.0373). However, neither IL-6 nor IL-10 genotype remained independently associated with DN after multivariable adjustment. Serum IL-10 levels did not differ significantly among the study groups (p = 0.0948). Combined genotype analyses showed several nominal associations, although these findings were exploratory. Serum IL-6 showed promising discriminatory ability in distinguishing patients with DN from the other study groups, whereas IL-10 demonstrated limited discriminatory performance.

Conclusion

These findings support further investigation of serum IL-6 as a potential candidate biomarker for diabetic neuropathy, whereas the independent contribution of the investigated IL-6 and IL-10 polymorphisms remains uncertain. Larger prospective studies with independent external validation are required before clinical application can be considered.

Integrated conservation of linear heritage landscapes from a biocultural diversity perspective: A case study of the Huizhou-Hangzhou Ancient Trail, China

2026-10-22T14:00:00Z

by Yuanliang Dong, Chengcheng Pan, Siyu Pan, Lei Zhang

Linear cultural heritage landscapes embody the long-term coupling relationships between ecological processes and human cultural practices, yet conservation models guided by a single ecological or cultural goal fail to meet their holistic management needs. Based on the perspective of biocultural diversity, this study takes the Huizhou-Hangzhou Ancient Trail (HHAT) as a case study and constructs a comprehensive conservation framework oriented toward spatial planning. Biodiversity and cultural diversity patterns are assessed and their spatial relationships are quantified using the coupling coordination degree model. The biocultural diversity index is further integrated with the Marxan systematic conservation planning model to identify Biocultural Core Protected Areas (BCCPA) and support differentiated spatial conservation strategies. The results indicate that biodiversity and cultural diversity along the HHAT exhibit a pronounced antagonistic coupling relationship: regions with antagonistic coupling account for 98.90% of the total study area, while coordinated regions make up only 0.02%. Based on the natural and cultural context of the study area, this pattern may be jointly influenced by rigid competition for small‑scale spatial resources, the dual effects of traffic corridors, and the cumulative effects of traditional livelihood activities. In response, an integrated conservation spatial pattern of one core area and two corridors is proposed, together with four conservation strategies: Conservation-Minimal Intervention, Conservation-Appropriate Revitalization, Restoration-Minimal Intervention, and Restoration-Appropriate Revitalization-enabling an effective translation from coupling diagnosis to spatial planning responses. This study advances understanding of biocultural interactions in mountainous linear heritage landscapes and provides a transferable methodological pathway for integrated conservation planning.

Expression of Concern: In quest of China sports lottery development path to common prosperity in 2035

2026-10-22T14:00:00Z

by The PLOS One Editors

Expression of Concern: The agricultural carbon reduction effect of digital rural construction under the dual carbon target

2026-10-22T14:00:00Z

by The PLOS One Editors

Expression of Concern: The allometric growth relationship between electricity consumption and economics in China

2026-10-22T14:00:00Z

by The PLOS One Editors

Expression of Concern: Decoupling agriculture pollution and carbon reduction from economic growth in the Yangtze River Delta, China

2026-10-22T14:00:00Z

by The PLOS One Editors

Assessing the impact of phylogenetic reconstruction error on genetic reassortment inference in segmented viruses

2026-10-22T14:00:00Z

by Hugo G. Castelán-Sánchez, Art F. Y. Poon

Recombination is an important process in the evolution of RNA viruses. For viruses with segmented genomes, recombination can occur by reassortment of entire genomic segments. This process has played a significant role in the adaptation and spread of influenza viruses with novel genomic combinations, i.e., antigenic shifts. Reassortment is usually identified by discrepancies between the topologies of trees reconstructed from different genomic segments, e.g., subtree prune and regraft (SPR) rearrangements. However, this phylogenetic discordance can also result from errors in tree reconstruction due to insufficient information. The objective of this study was to evaluate the contribution of phylogenetic reconstruction error to the inference of reassortment events from influenza A virus (IAV) genomes from avian hosts. We curated a dataset of 11,795 complete avian H5Nx IAV genomes and sampled subsets of HA sequences with different expected levels of reconstruction error. Next, we simulated molecular evolution along the trees reconstructed from these HA samples, varying rates of evolution and sequence lengths to correspond to the other genomic segments. Because these simulations had no reassortment, any phylogenetic discordance identified from the resulting trees must be caused by reconstruction error. We found that simulations from random samples yielded about 32% as many SPRs as obtained from real data. This false positive rate was reduced to 4% when simulating trees from the most genetically divergent subset of HA sequences. By modifying the simulated trees with SPR rearrangements, we observed a false negative rate of 8.5%, which increased with the number of SPRs per tree. Overall, we found that reassortment can be substantially overestimated from phylogenetic discordance, underscoring the need to account for phylogenetic uncertainty and sampling design when analyzing IAV datasets for reassortment.

YOLO-SOD: Color probability map-based fuzzy framework using deep models for face detection

2026-10-22T14:00:00Z

by Aniqa Saba, Muhammad Faizan Shirazi, Yawar Rehman, Muhammad Mubashir Khan

Detecting small faces remains challenging due to scale variation and limited discriminative cues at low resolutions. We address this with a two-pronged approach. First, we modify YOLOv5 by adding extra convolutional layers and small-object–focused detection heads that operate on larger, higher-resolution backbone feature maps, improving sensitivity to tiny targets. Second, we introduce a dynamic, image adaptive patching strategy for scale selection. We compute Cr channel color probability maps and measure the number and density of pixel clusters; a Fuzzy Inference System (FIS) uses these cues to select the most suitable patch size for near and far faces. On the WIDER FACE benchmark, our method attains 93.07% mAP@50 (Easy), 91.25% mAP@50 (Medium), and 84.45% mAP@50 (Hard). On our proposed local dataset, the proposed model achieves 49.36% mAP@50 for different size faces. Beyond faces, the approach generalizes to small object detection on VisDrone-DET2019, reaching 46.76 mAP@50. These results demonstrate that coupling small-object-aware architecture design with color-guided, fuzzy patch selection yields competitive mAP@50 for small and distant targets.

Combined transcutaneous electrical nerve stimulation and low-level laser photobiomodulation for postoperative pain after cesarean section: A randomized controlled trial

2026-10-22T14:00:00Z

by Alane Macatrão Pires de Holanda Araújo Sena, Ivan Daniel Bezerra Nogueira, Kássio Rafael Rocha de Sena, Íllia Nadinne Dantas Florentino Lima, Patrícia Angélica de Miranda Silva Nogueira

Introduction

Postoperative pain after cesarean section may delay recovery and impair function. Transcutaneous electrical nerve stimulation (TENS) and low-level laser photobiomodulation (PBM) are used for pain control, but the additional effect of combining these therapies remains unclear. This study investigated this effect.

Methods

A randomized clinical trial with four groups: combined TENS + low-level laser photobiomodulation (PBM), TENS alone, placebo, and control. Assessments were performed at 8–12 h (t1), 20–24 h (t2), and 44–48 h postpartum (t3). Outcomes included pain intensity, functional independence, functional capacity assessed by the Two-Minute Walk Test (2MWT), and cardiorespiratory variables. Two intervention sessions were applied after t1 and t2, except in the control group. Data were analyzed using mixed ANOVA and nonparametric equivalents when appropriate. Statistical significance was set at p < 0.05.

Results

A total of 88 women were included. Pain intensity decreased significantly over time in the combined TENS + PBM group (1.82 ± 1.18 at t2 vs 1.30 ± 0.86 at t3; p = 0.008) and in the TENS group (1.59 ± 1.05 at t2 vs 0.95 ± 1.05 at t3; p = 0.025). Functional independence increased in the combined therapy group (14.9 ± 3.3 at t1 vs 17.1 ± 3.6 at t3; p = 0.034) and in the TENS group (15.2 ± 3.0 at t1 vs 17.5 ± 3.4 at t3; p = 0.028). Functional capacity improved in all groups between t2 and t3 in the Two-Minute Walk Test (Control: 63.5 vs 76.8 m, p = 0.002; Placebo: 50.3 vs 63.9 m, p = 0.002; Combined: 48.3 vs 65.2 m, p = 0.0006; TENS: 61.1 vs 72.2 m, p = 0.005). No significant differences were observed between groups (p > 0.05). A significant time effect was found for pain (p < 0.05) and functional independence (p < 0.001).

Conclusion

Pain decreased and functional independence improved during the postoperative period. However, the combination of TENS and low-level laser photobiomodulation did not provide additional benefits compared with the other groups.

Psychosocial profile of adults with Congenital Heart Disease according to documented history of anxiety disorders

2026-10-22T14:00:00Z

by Efrén Martínez-Quintana, Marta Isabel García-Suárez, María Alcántara-Castellano, Jesús María González-Martín, Fayna Rodríguez-González

Background

Adults with congenital heart disease (CHD) may experience substantial psychological distress. This study evaluated whether a documented history of anxiety disorders is associated with a distinct psychosocial profile in adults with CHD.

Methods

In this cross-sectional study, 45 adults with CHD were included: 21 with a documented history of anxiety disorders and 24 without. Psychosocial assessment included the EuroQol-5D-3L (EQ-5D-3L), Rosenberg Self-Esteem Scale (RSES), State–Trait Anxiety Inventory (STAI), and Beck Depression Inventory-II (BDI-II). Associations between psychosocial measures and documented anxiety history were assessed using multivariable logistic regression adjusted for sex, NYHA functional class, and CHD complexity. Moderate depression was additionally assessed using univariable logistic regression.

Results

Mean age was 35 ± 9 years in participants with a documented history of anxiety disorders and 31 ± 11 years in those without (P = 0.230); males accounted for 33% and 62%, respectively (P = 0.052). NYHA functional class II–IV was more frequent among participants with a documented history of anxiety disorders (67% vs. 25%; P = 0.018). Compared with those without a documented anxiety history, participants with anxiety history reported greater limitations in usual activities (P = 0.021), higher anxiety/depression scores on the EQ-5D-3L (P = 0.023), poorer self-rated health (P = 0.038), higher trait anxiety (31.2 ± 5.8 vs. 26.5 ± 5.2; P = 0.008), and greater depressive symptom severity (BDI-II median 19 vs. 3; P = 0.001). Self-esteem was also higher (RSES median 27 vs. 25; P = 0.006). After adjustment, BDI-II scores were positively associated with a documented history of anxiety disorders (OR 1.14, 95% CI 1.05–1.28; P = 0.011), while EQ-5D VAS scores were inversely associated (OR 0.64, 95% CI 0.38–0.97; P = 0.048). STAI-State, STAI-Trait, and RSES scores were not significantly associated with anxiety history. None of the variables assessed in the univariable analysis was significantly associated with moderate depression.

Conclusions

In adults with CHD, a documented history of anxiety disorders was associated with greater depressive symptom severity and poorer self-rated health after adjustment for relevant clinical factors.

Feasibility of a machine learning model for predicting weight gain after kidney transplantation machine learning and weight gain after kidney transplantation

2026-10-22T14:00:00Z

by Júlia de Melo Cardoso de Freitas, Pedro Lemos Ballester, Elis Forcellini Pedrollo, Camila Corrêa, Rafaella Câmara Rocha Menezes, Cristiane Bauermann Leitão, Gabriela Corrêa Souza

Background

Excessive weight gain after kidney transplantation adversely affects patient and graft outcomes. Machine Learning has been increasingly used to improve risk prediction across a range of transplant-related outcomes, yet its application to post-transplant weight trajectories remains unexplored. This study is the first to evaluate the feasibility of using Machine Learning algorithms to identify predictors of weight gain after kidney transplantation.

Methods

This retrospective cohort study analyzed 374 adult kidney transplant recipients. We developed an Elastic Net regression model with 10-fold cross-validation to predict body weight variation at 12 months post-transplant. The analysis screened a comprehensive set of demographic and clinical variables, including recipient characteristics, donor type, dialysis duration, and pre-transplant hypertension, to identify predictors within the training (75%) and testing (25%) datasets.

Results

Mean weight gain was 4.0 ± 7.4 kg. The Elastic Net model retained four predictors in the final model: female sex, deceased donor source, age, and pre-transplant body mass index. However, the model demonstrated limited predictive performance (R² = 0.10; Mean Absolute Error = 8.7%), indicating that baseline variables explain only a small fraction of the observed variability in weight change.

Conclusions

This pioneering study establishes an analytical benchmark and reveals the informational limits of standard clinical datasets for predicting post-transplant weight gain. While Machine Learning application is feasible, current demographic and clinical variables are insufficient for precise individual prediction. Future models must integrate more granular behavioral and pharmacological data to achieve clinically actionable risk stratification.

Patient experience in National digital health platforms: Evidence from patient-generated feedback in Saudi Arabia

2026-10-22T14:00:00Z

by Abdulmohsen Saud Albesher

National digital health platforms are becoming fundamental components of modern healthcare delivery; however, patient experience is commonly assessed using overall ratings or sentiment analysis, providing limited understanding of the specific dimensions that influence digital healthcare quality and service improvement. This study aimed to develop a multidimensional framework for understanding patient experience in a national digital health platform, examine variation across healthcare services, investigate changes over time, and identify evidence-based improvement priorities. A qualitative analysis was conducted using 97,034 Google Play reviews of Sehhaty, the Saudi national digital health platform, posted between 2019 and 2026. Reviews were analyzed using an inductive coding approach to develop a patient experience framework, followed by comparative analyses across healthcare services and longitudinal analyses across successive stages of platform development. Nine patient experience dimensions were identified. Patient experience differed considerably across healthcare services, indicating that improvement priorities were service-specific rather than uniform across the platform. Longitudinal analyses showed a shift from predominantly technical concerns during early deployment toward challenges involving service accessibility, integration, continuity of care, as the platform matured. These findings enabled the identification of service-specific priorities for improving digital healthcare delivery. Patient experience in national digital health platforms is multidimensional, service-dependent, and evolves alongside platform maturity. The proposed framework extends approaches based primarily on ratings or sentiment by transforming large-scale patient-generated feedback into actionable evidence for healthcare quality improvement and continuous evaluation of patient-centered digital health services.

Controlled numerical generation and reconstruction of off-axis digital holograms with object-specific frequency-domain filtering

2026-10-22T14:00:00Z

by Junsheng Lu, Xiaolong Shi, Jiaqi Sun, Shuhong Ren, Yanan Zeng

Deep-learning-based holographic reconstruction requires numerical data with reliable ground truth for training and quantitative evaluation. Experimental hologram acquisition and pixel-level phase annotation can be difficult to control, making physically defined numerical cases useful as reproducible benchmarks. Here, three analytically specified phase targets—a smooth Gaussian distribution, a four-level step distribution, and a radially structured Siemens Star—are used to generate off-axis digital holograms with known phase ground truth. A frequency-domain filtering procedure is applied before inverse Fourier reconstruction, followed by DCT-based global phase unwrapping. Reconstruction quality is quantified using root mean square error (RMSE), mean absolute error (MAE), correlation coefficient, and profile-based error analysis. The results show that reconstruction errors are comparatively small in smooth regions and increase near abrupt or high-spatial-frequency phase transitions. The three cases are therefore presented as controlled benchmark examples for algorithm verification and baseline comparison, not as a complete substitute for experimental holographic datasets or as a complete training corpus for deep-learning models.

Teaching and learning strategies for the derivative in engineering education: A scoping review protocol

2026-10-22T14:00:00Z

by Maritza Katherine Galindo Illanes, Denise Deyanira Chamorro Manríquez, Cristian Herrera Valdés

The derivative is a fundamental concept in engineering education, as it enables students to model and interpret phenomena related to rates of change, optimization, and the analysis of physical processes. However, its teaching in higher education often emphasizes decontextualized algebraic procedures, with limited integration of authentic engineering problems and interactive digital technologies. This protocol outlines a scoping review aimed at mapping the available evidence on teaching and learning strategies for the derivative in undergraduate engineering education that incorporate authentic engineering problems, with or without the support of digital technologies. The review will follow the methodological framework proposed by the JBI Manual for Evidence Synthesis and the reporting guidelines of PRISMA-ScR. The review is guided by the PCC framework: (P) undergraduate engineering students; (C) didactic strategies for teaching and learning the derivative grounded in authentic engineering problems, with or without the support of digital technologies; and (C) higher education engineering programs. Searches will be conducted in Scopus, Web of Science, ERIC, and SciELO for peer-reviewed publications published between 2000 and 2026 in English, Spanish, and Portuguese. Two reviewers will independently screen and select studies using Rayyan, and disagreements will be resolved by consensus. Data will be extracted using a pilot-tested data extraction form and synthesized through descriptive statistics, thematic categorization, and narrative synthesis. The review will provide a comprehensive mapping of didactic strategies, types of authentic problems, and reported learning difficulties related to the derivative in engineering education. The findings are expected to inform instructional design and support the development of evidence-based teaching practices in calculus courses for engineering students.

PREnatal Syphilis point-of-care ScreenING in an urban low-barrier clinic (PRESSING) study: Protocol for a prospective single arm feasibility trial

2026-10-22T14:00:00Z

by Njideka Sanya, Mary-Elizabeth Vaccaro, Medora Uppal, Sarah Glen, Chelsea Kirkby, Tehreem Zafar, Janet Gasparelli, Kate MacNeil, Stephanie Milliken, Jeffrey Pernica, Jacqueline Wong, Donald Brody Duncan, Marek Smieja, Amanda Ramdyal, Robin Lennox, Tim O’Shea, Anna Cvetkovic, Lawrence Mbuagbaw, Suzanne Turner, Laura Erdman

Introduction

Syphilis has resurged across North America, including syphilis in pregnancy. Congenital syphilis can be prevented by timely treatment of syphilis in pregnancy, but conventional syphilis screening is problematic for people facing barriers to care. Syphilis point-of-care tests (POCT) have improved prenatal syphilis management in low- and middle-income countries. There is minimal literature regarding POCT feasibility and effectiveness for prenatal syphilis screening in high-income countries, where barriers and challenges may differ.

Methods

Academic and community partners co-designed a prospective single-arm feasibility trial to evaluate syphilis POCT implementation at a low-barrier prenatal clinic in Hamilton, Canada. The INSTI HIV/syphilis POCT was integrated into routine clinical care for pregnant people with ≥1 risk factor for syphilis (unstable housing in the past year; substance use or accessing addictions services in the past year; > 1 sexual partner in the past year; history of sexually transmitted or blood-borne infection; presentation to care >20 weeks gestation). Sexual partners of newly diagnosed pregnant people are also offered POCT. Individuals offered POCT are invited to enroll in the study. The primary feasibility outcome is the proportion of pregnant participants who accept POCT at first offer. Secondary feasibility outcomes include valid POCT results on clinician’s first attempt and accurate POCT interpretation by clinicians. Secondary clinical outcomes include time to treatment initiation and completion of treatment among syphilis-positive participants. To promote inclusion of groups facing structural barriers to research, individuals declining study participation are enrolled for limited prospective chart review (primary feasibility outcome only). Target enrollment is N = 62 pregnant participants over 18 months. Baseline participant characteristics and outcomes will be descriptively analyzed. Community-based knowledge mobilization is ongoing.

Conclusion

This pilot study will generate novel feasibility data regarding prenatal syphilis screening with POCT in high-income countries and inform design of a multicenter implementation trial.

Trial registration

Clinicaltrials.gov NCT06829602; February 17, 2025. https://clinicaltrials.gov/study/NCT06829602