PLOS ONE Alerts: New Articles

Correction: Exploring the physical, mental, and social dimensions of middle-aged adults for active and healthy aging: A cross-sectional study

2026-04-28T14:00:00Z

by The PLOS One Staff

From discrimination to growth? Student stress in the association between perceived discrimination and posttraumatic growth among African international students in South Africa

2026-04-28T14:00:00Z

by Juliette Bih Nkarenbi, Erhabor S. Idemudia, Lawrence Ejike Ugwu

Background

International students relocating across borders often face perceived discrimination, a form of cumulative adversity that may undermine well-being and may also be relevant to growth-related outcomes. Little is known about how perceived discrimination is associated with posttraumatic growth (PTG), and whether student stress helps explain that association, among African international students in South Africa.

Methods

We surveyed 781 non-South African students aged 18–49 (54% men, 46% women) enrolled at four public universities across Gauteng, North West, Western Cape, and Free State. Perceived discrimination was assessed with the relevant subscale of the Acculturative Stress Scale for International Students; student stress was measured with four subscales (academic, interpersonal, physical and environmental) of the Student Stress Inventory; and PTG was measured with five subscales (personal strength, new possibilities, improved relationships, spiritual growth and appreciation of life) of the Posttraumatic Growth Inventory. Parallel multiple-mediator models and quadratic regression were used to estimate indirect associations and nonlinear patterns, adjusting for age and gender.

Results

Perceived discrimination was moderately and positively associated with all student stress domains. It was not directly associated with most PTG facets, except for a small positive association with personal strength. Total indirect associations through student stress were nonsignificant; however, specific indirect paths diverged. Interpersonal stress showed positive indirect associations with improved relationships, new possibilities, and personal strength, whereas academic and environmental stress showed negative indirect associations with several PTG facets. Small positive quadratic terms indicated U-shaped associations between perceived discrimination and improved relationships, new possibilities, and personal strength, with the lowest estimated PTG values occurring at modestly low levels of discrimination.

Conclusions

Perceived discrimination was associated with PTG through distinct student-stress patterns. Academic and environmental stress showed negative associations with several PTG facets, whereas interpersonal stress showed positive associations with some PTG facets. These findings should not be interpreted as suggesting that discrimination is beneficial; rather, they indicate heterogeneous responses to adversity. Interventions should prioritise reducing discrimination and related stressors while strengthening supportive resources for international students in South Africa.

Ulinastatin attenuates capillary leakage and suppresses FoxO1-dependent angiopoietin-2 in sepsis-associated acute lung injury via PI3K pathway

2026-04-28T14:00:00Z

by Yating Lv, Yanfei Meng, Haiying Rui, Tongqin Li, Jing Zhang, Jie Liu, Xin Ma, Jiaqi Wang, Yamin Yuan, Yujing Jiang, Xiaoxi Yan, Miaobo Li, Xiaorong Dong, Bei Zhang, Li Ma

Sepsis-associated acute lung injury (SALI) is characterized by endothelial barrier dysfunction and capillary leakage. Ulinastatin (UTI), a serine protease inhibitor with recognized clinical benefits in sepsis, has been reported to protect endothelial function, but the underlying mechanisms remain incompletely defined. This study investigated the protective effects of UTI against SALI and its specific mechanism of action. We found that UTI attenuated lung injury and endothelial dysfunction in both cecal ligation and puncture (CLP)-induced septic rats and LPS-stimulated human umbilical vein endothelial cells (HUVECs). UTI treatment reduced the expression of angiopoietin-2 (Ang-2), a key mediator of vascular destabilization, and exerted similar protective effects on endothelial function as dexamethasone (DEX). Mechanistically, UTI was demonstrated to have a stable interaction and favorable binding affinity to PI3K by docking and activating the PI3K/Akt signaling pathway. This led to phosphorylation and subsequent nuclear export of the transcription factor FoxO1, thereby suppressing FoxO1-dependent Ang-2 transcription. The protective effects of UTI on capillary leakage and junctional protein integrity were abolished by the PI3K inhibitor wortmannin. In conclusion, our findings demonstrate that UTI alleviates SALI by disrupting an Ang-2-mediated vicious cycle via the PI3K/Akt/FoxO1 pathway, revealing a novel mechanistic insight into its therapeutic action against sepsis-induced vascular leakage.

Machine-learning framework for conditional estimation and scenario-based projection of the heat index for public health interventions

2026-04-28T14:00:00Z

by Mohammad A. H. Mollah, Amrin Binte Ahmed, Zihanul Islam Zijan, Ananta Asim Joy, Rumana Rois

Background

Heatwaves are becoming more frequent and intense in Bangladesh, particularly in urban areas such as Dhaka, where the combined effects of extreme heat and humidity pose serious public health risks. Temperature-based warning systems frequently underestimate physiological heat stress.

Methods

This study proposes a machine-learning framework to estimate and project the Heat Index (HI) using 3-hourly meteorological records from 2014 to 2023. Because HI is a deterministic function of air temperature and relative humidity, the framework performs conditional estimation of HI based on meteorological predictors rather than independently forecasting HI itself. Five models: ARIMAX, SARIMAX, Random Forest Regressor (RFR), XGBoost, and Long Short-Term Memory (LSTM), were trained using air temperature, relative humidity, and seasonal indicators as predictors. For scenario-based projections beyond 2023, future temperature and humidity were approximated using historical monthly averages, generating scenario-based HI projections that preserve seasonal and diurnal patterns. These projections represent climatological scenarios rather than true meteorological forecasts.

Results

The Random Forest Regressor (RFR) achieved the highest conditional estimation accuracy, with the lowest RMSE (0.85°C) and highest R² (0.987) on the test set. Empirical 95% prediction intervals achieved 98.85% coverage, indicating slightly conservative uncertainty bounds. Scenario-based projections yielded mean HI values of 29.02°C (optimistic), 29.90°C (moderate), and 31.33°C (pessimistic). A substantial proportion of projected 3-hourly periods fall within the “Extreme Caution” category (32–41°C), indicating persistently elevated heat-stress exposure under climatological assumptions.

Conclusion

The proposed framework demonstrates strong potential for generating high-resolution scenario-based HI projections by capturing nonlinear temporal dynamics and sub-daily variability. These findings can support scenario-based early warning systems and inform adaptive urban heat-management strategies in climate-vulnerable cities such as Dhaka, although results should be interpreted as conditional projections rather than deterministic forecasts. Unlike conventional HI studies, this framework translates meteorological inputs into high-resolution, operational heat-risk insights by modeling temporal persistence at sub-daily scales.

Economic burden of pulmonary arterial hypertension in Switzerland

2026-04-28T14:00:00Z

by Yuki Tomonaga, Mona Lichtblau, Silvia Ulrich, Sabina A. Guler, Patrick Yerly, Benoît Lechartier, Jean-Marc Fellrath, Anne Bergeron, Louise Bondeelle, Silviu-Mihail Chirila, Andrea Favre-Bulle, Sandro Stoffel, Matthias Schwenkglenks

Objectives

Pulmonary arterial hypertension (PAH) is a rare, progressive condition associated with high morbidity and healthcare resource utilization. This study aimed to estimate the annual direct and indirect costs of PAH in Switzerland, from a societal perspective.

Materials and methods

A cross-sectional cost-of-illness study was conducted across six Swiss PAH centres between April and December 2024. Adult patients with confirmed PAH (World Health Organization [WHO] Group 1) were invited to complete a standardized questionnaire on work productivity losses, informal care, and healthcare utilization outside the enrolling centre. Clinical data on hospitalizations, outpatient visits, diagnostics, and treatments at the enrolling centre were extracted from medical records. Disease-specific costs were calculated by multiplying resource use and work losses by Swiss-specific unit costs and extrapolated to one year. Estimates were stratified by WHO functional class (WHO-FC) and ESC/ERS 2022 risk strata.

Results

Among 124 participants aged between 18 and 89 years, the mean disease-specific total annual cost per patient was €138,958. Direct healthcare costs represented 78.5% of this amount (€109,114), driven primarily by pharmacological treatment (65% of total costs). Indirect costs amounted to 21.5% (€29,844). Costs increased with disease severity, ranging from €81,957 in WHO-FC 1 to €166,569 in WHO-FC 4, and from €130,970 in ESC/ERS low risk to €291,728 in ESC/ERS high risk. The total national burden was estimated at €48.5 million annually.

Conclusions

PAH imposes a substantial economic burden in Switzerland, largely due to treatment costs and productivity losses. These findings highlight the need for strategies to reduce disease progression and associated societal costs.

Developmental constraints in the repeated evolution of male tail characters in rhabditid and diplogastrid nematodes

2026-04-28T14:00:00Z

by Karin Kiontke, Simone Kolysh, Rocio Ng, David H. A. Fitch

A longstanding question in evolutionary biology is how change might be restricted or biased due to developmental constraints. To address this question, we investigated three recurrently evolving characters in rhabditid nematode male tails: tail tip morphogenesis, the number of genital papillae (GPs or “rays”), and phasmid position relative to the three most posterior GPs. This new analysis incorporates taxa (rhabditids Cruznema tripartitum, Haematozoon subulatum, Poikilolaimus oxycercus, diplogastrid Diplogasteroides nasuensis, and outgroup representative Brevibucca saprophaga) representing more and deeper divergence points in the rhabditid phylogeny than in previous analyses, allowing better resolution of ancestral states and changes. Analysis of GP characters was accomplished via immunofluorescent staining of adherens junctions at different stages of GP development and laser microbeam ablations of GP primordia. Findings include the following: (1) Loss and gain of tail tip morphogenesis occurred multiple times, possibly involving differences in fusion. (2) The pattern of GP anlagen in early L4 males is highly conserved and compatible with the previously proposed “archetype,” but is established at different developmental times in different species, consistent with constraint on GP patterning by the cell lineage and anteroposterior and dorsoventral patterning systems. (3) The stem species of Rhabditina likely had 8 GPs, with the second GP (v2) gained after the divergence of Poikilolaimus; within rhabditids, a different GP (v6) appears to be lost twice independently. (4) Laser ablation showed that changes in phasmid position relative to GPs are not due to changes in cell lineage, but instead due to migratory switches in the relative positions of precursors of phasmid socket cells and GPs; these cell migrations occur at different developmental times in different species. In summary, our results indicate a strong constraint imposed on the cell lineage and dorsoventral positioning of GP precursors, with GP pattern diversity allowed by cell-specific migratory behavior.

Retraction: How well do software assistants for minimally invasive partial nephrectomy meet surgeon information needs? A cognitive task analysis and literature review study

2026-04-28T14:00:00Z

by The PLOS One Editors

Expression of Concern: Detection of Plant DNA in the Bronchoalveolar Lavage of Patients with Ventilator-Associated Pneumonia

2026-04-28T14:00:00Z

by The PLOS One Editors

Editorial Note: Repertoire of Intensive Care Unit Pneumonia Microbiota

2026-04-28T14:00:00Z

by The PLOS One Editors

Editorial Note: Serologic Prevalence of Amoeba-Associated Microorganisms in Intensive Care Unit Pneumonia Patients

2026-04-28T14:00:00Z

by The PLOS One Editors

Multiscale mechanisms of green concrete regulated by silicon-to-calcium ratio: Physico-mechanical properties, hydration structure, and durability performance

2026-04-28T14:00:00Z

by Jiayuan Lou, Yiwen Liang, Wenhua Zha, Qiang Su

To explore efficient pathways for the resource utilization of silicon-rich solid wastes in low-carbon concrete, this study proposes a synergistic regulation strategy centered on the silicon-to-calcium (Si/Ca) ratio. Three types of silicon-rich solid wastes-glass sand, glass powder, and rice husk ash-were incorporated to produce waste glass and rice husk concrete (WGRC). The effects of varying Si/Ca ratios on the workability, mechanical properties, and durability of WGRC were systematically investigated. Furthermore, the underlying mechanisms were elucidated through microstructural analysis. The results indicate that WGRC exhibits optimal overall strength within a Si/Ca ratio range of 0.46 ~ 0.58. When the Si/Ca ratio ranged from 0.52 ~ 0.58, WGRC demonstrated superior resistance to water penetration and sulfate attack, with the lowest mass loss rate (0.54% after 180 drying-wetting cycles) and the smallest ultrasonic velocity reduction (only 2.6%). At a Si/Ca ratio of 0.58, the carbonation resistance was maximized, yielding the lowest carbonation rate. In addition, the Si/Ca ratio within the C-S-H gel increased progressively with curing age, though the rate of increase slowed after 90 days. A shear damage constitutive model was developed to accurately describe the nonlinear response characteristics under varying Si/Ca ratios and shear angles, validating the coupling relationship among composition, structure, and performance. These findings provide new theoretical insights and design strategies for the synergistic utilization of multiple solid wastes in low-carbon concrete. They also offer a scientific basis for enhancing the mechanical and durability performance of WGRC, thereby contributing significantly to the advancement of sustainable construction materials.

Image quality improvement of liver ultrasound using unsupervised deep learning

2026-04-28T14:00:00Z

by Jaeyoung Huh, Joo Hyeok Choi, Eun Sun Lee, Jong Chul Ye, Jeong Eun Lee, Hyun Jeong Park, Byung Ihn Choi

Chronic liver disease (CLD) and subsequent liver cirrhosis (LC) are common causes of death and healthcare-related socio-economical costs worldwide. Ultrasound (US) is the first-line imaging modality for assessing the liver and associated hepatocellular carcinomas. Poor quality liver US images caused by aging or inadequate management of US equipment, can pose significant challenges in both diagnosis and treatment. From this perspective, the aim of this study was to enhance and assess the image quality of liver US obtained from an older, lower-performing device using a deep learning approach. A neural network based on a switchable cycle generative adversarial network (CycleGAN) was trained in an unsupervised learning setting, with low-quality images as inputs and high-quality images as targets. The study included consecutively acquired grey-scale liver US examinations from both a 12-year-old and a 4-year-old US device. Images from the older device served as inputs, while images from the newer device were used as targets for the deep learning-based algorithm. Image quality was evaluated by two experienced reviewers. The algorithm significantly improved the brightness, contrast, and overall quality of the reconstructed liver US images (p < 0.001), as assessed by both reviewers. However, no significant differences in image resolution and reverberation artifacts were noted by one of the reviewers. The weighted kappa values for image quality and diagnostic performance ranged from 0.225 to 0.838, indicating fair to almost-perfect inter-reader agreement. The proposed algorithm effectively enhances low-quality liver US images to high diagnostic quality, thereby potentially supporting clinical assessment and intervention in patients with LC.

Ecological patterns in the Porto-Novo Lagoon (Benin, West Africa): A review with implications for SDG 6.3.2 and EU-WFD readiness toward ecological status classification

2026-04-28T14:00:00Z

by Metogbe Belfrid Djihouessi, Gildas Djidohokpin, Romaric Christian Marc Hekpazo, Akilou Amadou Socohou, Lewis Zounon, Zacharie Sohou, Abou Youssouf, Martin Pépin Aina

Urban tropical lagoons provide vital services yet face nutrient loading, macrophyte blooms, and episodic hypoxia. This scoping review compiles four decades of hydromorphological, physico-chemical, and biotic evidence for Benin’s Porto-Novo Lagoon and assesses readiness for UNEP SDG 6.3.2 Level 1 reporting and a EU Water Framework Directive (WFD)-oriented exploratory gap analysis rather than an operational assessment. The lagoon is strongly seasonal, shaped by Ouémé inflows and marine intrusions; eutrophication symptoms and floating macrophytes have intensified since the 1980s. Core SDG 6.3.2 Level 1 parameter-group proxies (pH, DO, EC, PO₄-P) are moderately covered, but nitrogen evidence is scarce and time-continuous station series are rare. A completeness audit indicates about 60% coverage for SDG-related variables and lower maturity for WFD biological elements, meaning that formal SDG compliance-based classification (“good and not good”) and any Ecological Quality Ratios based WFD ecological status classification cannot be derived from the compiled literature. Near-term priorities are therefore framed as readiness building, focused on strengthening consistent in situ series for the SDG core groups; context-adapted complementary sources may support gap filling and interpretation but do not substitute Level 1 requirements. For WFD, the evidence base highlights prerequisites for future work, including transitional water-body delimitation and type-specific reference conditions, standardised Biological Quality Elements monitoring, and priority-substance surveillance. Comparison with Ébrié, Lekki, and Sakumo II underscores the value of governance and monitoring designs that avoid data fragmentation.

Ten-year natural history of visual function in Japanese patients with Leber hereditary optic neuropathy: A retrospective cohort study

2026-04-28T14:00:00Z

by Yasuyuki Takai, Akiko Yamagami, Mayumi Iwasa, Kenji Inoue, Ryoma Yasumoto, Hitoshi Ishikawa, Masato Wakakura

Leber hereditary optic neuropathy (LHON) is a mitochondrial optic neuropathy that typically causes severe bilateral central vision loss. Although several natural-history studies have reported visual outcomes, long-term trajectories beyond 5 years remain incompletely quantified, particularly in Asian cohorts. We performed a single-center retrospective cohort study at a tertiary eye hospital in Japan. Among 174 genetically confirmed LHON patients, we identified 27 patients (53 eyes) who presented within 6 months of onset and were followed continuously for ≥10 years. Best-corrected visual acuity (BCVA, logMAR) was collected from onset to 120 months. Piecewise linear mixed-effects models with patient- and eye-level random effects were fitted over three phases (Acute, < 12 months; Chronic, 12–60 months; Late Chronic, 60–120 months). Kaplan–Meier analyses estimated time to achieving BCVA ≤1.6 and ≤1.3 logMAR. BCVA worsened rapidly after onset, followed by gradual improvement and then an approximately horizontal course. During the Chronic phase, BCVA showed a small but statistically significant improvement (overall −0.030 logMAR/year, 95% confidence interval (CI) −0.045 to −0.015; −0.025 logMAR/year, 95% CI −0.044 to −0.007 in a pre-specified m.11778G > A subgroup). In the Late Chronic phase, estimated slopes were close to zero (+0.003 logMAR/year, 95% CI −0.007 to +0.013 overall), with wide CIs compatible with small long-term improvement or deterioration. By 10 years, the cumulative probabilities of achieving BCVA ≤1.6 and ≤1.3 logMAR were approximately 45% and 26%, respectively. In this Japanese LHON cohort with ≥10 years of continuous follow-up, BCVA showed limited improvement during the early chronic period, and we did not detect a clear directional trend thereafter. Given the modest sample size and selection of long-term attendees, these estimates should be interpreted as descriptive, phase-specific benchmarks rather than definitive evidence of long-term stability or ethnic differences.

High-speed trains versus air transport vectors for mass transfers of critically ill patients: The TRANSCOV cohort study

2026-04-28T14:00:00Z

by Chatpimuk Thipayamaskomon, Olivier Grimaud, Pierre Tattevin, Lionel Lamhaut, Emmanuelle Leray, Noemie Letellier, Sahar Bayat, Christophe Fermanian, Sylvie Martin, Jean-Marc Philippe, Eric Maury, Marc Noizet, François Braun, Manuel Dolz, Marc-Antoine Sanchez, Hélène Coignard-Biehler, Nathalie Prieto, Hugues Delamare, Virginie Cayré, Pierre Carli, Albert Vuagnat, Julien Pottecher, Agnès Ricard-Hibon, the TRANSCOV Investigators

Background

The first COVID-19 epidemic wave hit the East and Ile-de-France regions in France, resulting in overwhelmed intensive care units (ICUs). Alongside helicopters and planes, high-speed trains were used for the first time to mass-evacuate critically ill patients. This study aimed to compare outcomes of patients evacuated by trains and by aircrafts.

Methods

This was a multicentre retrospective cohort study. Between 13 March and 10 April 2020, 38 ICUs in France transferred patients with severe COVID-19 to 60 ICUs in unaffected regions and countries. Patients were divided into the train group (n = 130) and the air group (n = 163). The study outcomes included 28-day case-fatality, destination ICU length of stay and post-transfer Sequential Organ Failure Assessment (SOFA) score.

Results

Age and comorbidity did not differ between groups. Although patients spent more time (+2 hours) and travelled further (+250 km) in the train group than in the air group, the median post-transfer SOFA score was lower in the train group (6 vs 7; p = 0.03). The 28-day mortality rates were not different (train/air unadjusted incidence risk ratio: 0.96; p = 0.94). The ICU stay duration was shorter (−6 days) in the train group, but this difference was reduced after adjusting for clinical events, such as nosocomial infections.

Conclusion

High-speed train was a safe vehicle for remote transfer of critically ill patients. The selection of healthier patients and the better physiological and care conditions during the evacuation may explain the shorter ICU stays of patients transferred by trains.

Resilient nursing in ICU: Aadaptive practices beyond IPC protocols for MDRO management. A qualitative study

2026-04-28T14:00:00Z

by Eva Cappelli, Marianna Azzolini, Cristina Ferrari, Federica Canzan

This descriptive qualitative study explores how resilience among intensive care nurses is activated during the management of patients with multidrug-resistant organisms and how it shapes adherence to infection prevention and control practices under conditions of clinical urgency and organisational pressure. Data were collected between March and June 2025 in two Intensive Care Units through non-participant observations and twenty-one semi-structured interviews involving nurses, a head nurse, nurse assistants, and anaesthesiologists. Interviews were audio-recorded and analysed using inductive content analysis. The analysis identified three interrelated themes encompassing eleven categories: (a) individual and team-based dimensions of nurses’ resilience, (b) adaptive strategies employed by nurses in intensive care settings, and (c) dynamic interactions between professional resilience and organisational support. Resilience emerged as a multilevel and context-dependent process sustained by personal resources, teamwork, and enabling organisational conditions. These elements supported nurses in maintaining adherence to infection prevention and control protocols and safeguarding patient safety, even in highly complex and time-critical situations. However, the findings also revealed a “critical zone” of resilience characterised by constant adaptation, sustained operational pressure, and procedures perceived as difficult to implement in practice, which over time contributed to emotional fatigue and an increased risk of burnout. While professional resilience represents a crucial resource in intensive care, it cannot compensate for structural or organisational shortcomings. Sustainable infection control practices and high-quality care therefore require coherent organisational support systems that extend beyond individual and team-level resilience.

Geographic inequities in human papillomavirus vaccine non-uptake and its determinants among adolescent girls in Ethiopia: Evidence from the National Immunization Survey

2026-04-28T14:00:00Z

by Kibir Temesgen Assefa, Abebaw Gebeyehu Worku, Achenef Asmamaw Muche, Bisrat Misganaw Geremew, Mulat Adefris Woldetsadik, Kassahun Alemu

Introduction

Human papillomavirus (HPV) vaccination has emerged as the most effective method for preventing cervical cancer. Despite this, Ethiopia’s HPV vaccine non-uptake rate remains high, with significant geographic variation, and there is limited evidence on the geospatial determinants of these inequities. This study aimed to map the geographic inequities in HPV vaccine non-uptake and identify its determinants among adolescent girls in Ethiopia.

Methods

We conducted a secondary data analysis using the Ethiopian National Immunization Survey dataset. A stratified two-stage cluster sampling technique was used to select 467 enumeration areas (EAs) and a weighted sample of 5,341 adolescent girls. The geographic inequity of HPV vaccine non-uptake was analyzed using Moran’s I, Getis-Ord Gi statistics, and Kriging interpolation in ArcGIS 10.8. We employed geographically weighted regression analysis to identify geographic factors associated with inequity in HPV vaccine non-uptake.

Results

Forty-six percent (46%, 95% CI: 44.7–47.8) of adolescent girls did not receive the HPV vaccine, and there were geographical variations in vaccine coverage. Higher proportions of HPV vaccine non-uptake were identified in eastern Amhara, eastern Oromia, central and northern Somali, central Afar, and the urban administrative units of Dire Dawa and Harari. Poor attitude and poor knowledge towards the HPV vaccine, not living with parents, and urban residence were predictors of geographic inequities in HPV vaccine non-uptake.

Conclusions

The proportion of HPV vaccine non-uptake varied across Ethiopia, with geographic inequities identified in the eastern and northeastern parts of Ethiopia. Poor attitudes and knowledge about the vaccine, not living with parents, and urban residence contributed to these inequities. These findings highlight the need for targeted educational campaigns in areas with high non-uptake to improve knowledge and attitudes, alongside tailored strategies for regions where urban residence and not living with parents influence uptake.

IGNN: An improved graph neufral network with integrated attention and pre-message-passing for few-shot image classification

2026-04-28T14:00:00Z

by Jianxiong Chen, Bingwei Fu, Lin Zou

Graph Neural Network (GNN) faces limitations in few-shot image classification due to insufficient adaptive feature extraction and limited long-range dependency modeling. To address these challenges, this study proposes an Improved Graph Neural Network (IGNN) integrating two key innovations. Firstly, we design an Attention-Enhanced Feature Extraction module, which combines Efficient Channel Attention (ECA) and self-attention mechanisms, enabling the model to dynamically focus on discriminative intra-image details and inter-image contextual relationships, thereby improving feature representation robustness. Secondly, we introduce a gated recurrent unit (GRU)-based Pre-message-passing mechanism, which establishes cross-sample associations between support and query sets before message propagation, effectively capturing long-range dependencies and mitigating information smoothing. The experimental results of three public datasets demonstrate that our proposed framework outperforms the existing methods and shows significant potential. It offers a pragmatic tool for applications requiring rapid adaptation to limited data, such as remote sensing and medical image analysis.

Expression of Concern: Hemorrhagic and thrombotic manifestations in the central nervous system in COVID-19: A large observational study in the Brazilian Amazon with a complete autopsy series

2026-04-28T14:00:00Z

by The PLOS One Editors

Retraction: High CASC expression predicts poor prognosis of lung cancer: A systematic review with meta-analysis

2026-04-28T14:00:00Z

by The PLOS One Editors

How host–guest interaction types shape value co-creation in urban tourism: The moderating role of AI technology stimuli

2026-04-28T14:00:00Z

by Guanxi Chen, Jiajun Chen

This study examines how different types of host–guest interaction relate to tourists’ value co-creation intention in urban tourism and whether artificial intelligence technology stimuli moderate these relationships. Grounded theory was used to identify the main constructs and relationships. Survey data were then analyzed using partial least squares structural equation modeling, and fuzzy-set qualitative comparative analysis was conducted to identify configurations associated with high value co-creation intention. The results showed that tourist–government interaction and tourist–resident interaction were positively related to tourist empowerment, and tourist empowerment was positively related to value co-creation intention. Neither tourist–government interaction nor tourist–resident interaction had a direct relationship with value co-creation intention. Artificial intelligence technology stimuli moderated the paths from tourist–government interaction to tourist empowerment and from tourist–government interaction to value co-creation intention. No moderating effect was found for the tourist–resident interaction paths. The fuzzy-set qualitative comparative analysis identified multiple configurations associated with high value co-creation intention.

Task complexity in exoskeleton setup and takedown: Procedural steps and usability problems as predictors of deployment performance

2026-04-28T14:00:00Z

by Jessica Sanchez-Balandran, Alejandra Martinez Fernandez, Laura Tovar, Priyadarshini Pennathur, Arunkumar Pennathur

Occupational exoskeletons show promise in reducing physical strain in industrial work, yet their industrial adoption remains limited. For exoskeletons to be used when performing tasks in industrial settings, they first need to be set up, then fitted and donned, and finally doffed, disassembled and stored for future use. Exoskeleton setup and takedown procedures can significantly impact industry deployment, adoption, and use, yet we have limited knowledge of the complexities in setup and takedown procedures and the resulting deployment barriers. The goals of this study were to understand how task complexity (number of task steps, usability problems and part count) in setup and takedown of exoskeletons impact task completion time and success, and present barriers in deployment. Twenty nine participants completed setup (assembly and donning) and takedown (doffing and disassembly) of four exoskeletons. We measured task times, success rates, task complexity (task step counts, part counts and usability problems). Hierarchical task analysis and heuristic assessments were performed to assess task complexity. Setup tasks, especially assembly, took the most time and exhibited the highest failure rates, whereas takedown tasks were faster and more successful. Participant-level regression analyses (N = 397 observations) showed that number of procedural steps was the strongest predictor, accounting for 66.9% of variance in completion times (β = 0.374, p < .001), with each additional step associated with approximately 22 seconds longer completion time. Usability problems also significantly predicted completion time (R² = 0.305, p < .001), while part count showed no significant association (p = .133). Our findings highlight that task complexity impact setup procedures significantly and can present a major deployment barrier. Moreover, our findings add new knowledge that number of steps, not part count, is the primary predictor of performance in setup procedures, and that usability problems differentially affect assembly and donning tasks.

Conserved molecular signatures of hygrosensory neurons in two dipteran species

2026-04-28T14:00:00Z

by Kristina Corthals, Ganesh Giri, Johan Reimegård, Allison Churcher, Anders Enjin

Small poikilothermic animals like insects rely on environmental sensing for survival. The ability to detect humidity through specialized sensory neurons is particularly critical, allowing them to maintain water balance across diverse environments. While recent studies have identified key receptors associated with humidity sensing, our understanding of the underlying molecular architecture of these sensory systems remains incomplete. Here, we conducted a comparative analysis of single-nucleus transcriptomes of humidity receptor neurons (HRNs) between the vinegar fly Drosophila melanogaster and the yellow fever mosquito Aedes aegypti. We identified 21 shared genes that contribute to the molecular identity of HRNs in both species. These genes encode proteins involved in transcriptional regulation, cellular signalling, enzymatic pathways and cellular organization. Through behavioural analyses, we demonstrate that two of these genes, the serotonin receptor 5-HT7 and the kinesin motor protein Kif19A, are both necessary for humidity-guided behaviours in adult flies. The conservation of these genes between species separated by over 150 million years of evolution suggests shared functional requirements for humidity sensing in dipterans. Our findings provide insights into fundamental principles of sensory neuron organization and offer a framework for understanding how specialized sensory systems evolve and maintain their function.

Metagenomic and taxonomic profiling of phyllosphere bacteria from Mangifera indica in response to urban air pollutants in Medellín, Colombia

2026-04-28T14:00:00Z

by Natalia Bernal Hernández, Héctor Alejandro Rodríguez Cabal, Nancy J. Pino, Sara Ramírez Restrepo, Luisa María Múnera Porras

Urban trees and their phyllosphere-associated microbiota constitute a promising nature-based solution for mitigating urban air pollution. In this study, we characterized the taxonomic composition, diversity patterns, and functional potential of bacterial communities inhabiting the phyllosphere of Mangifera indica in two urban sites of Medellín, Colombia, with contrasting pollution levels and across two time points, analyzing a total of 12 samples. We integrated 16S rRNA gene amplicon sequencing, performed on the Illumina MiSeq platform, with shotgun metagenomic sequencing generated on the Illumina NovaSeq 6000 platform to assess community structure and the presence of genes involved in the degradation of airborne organic pollutants. Bacterial assemblages were dominated by Pseudomonadota (Proteobacteria), Actinomycetota, and Bacteroidota, with genera such as Methylobacterium, Pseudomonas, and Serratia consistently prevalent. Alpha diversity was higher in the highly polluted downtown, while beta diversity was shaped primarily by temporal variation. Functional annotation of metagenome-assembled genomes (MAGs) uncovered genes encoding complete aromatic hydrocarbon degradation pathways, including naphthalene, toluene, xylenes, and benzoate. Both ortho- and meta-cleavage routes for catechol degradation were detected, with temporal shifts in pathway dominance linked to changes in the abundance of key degraders taxa. These results reflect genetic potential for xenobiotic degradation within the M. indica phyllosphere microbiota, modulated by environmental conditions. Our findings highlight the ecological role of phyllosphere bacteria as contributors of inferred functional capacity relevant to atmospheric bioremediation and supports their integration into microbiome-informed green infrastructure strategies.

Epidemiology and antimicrobial resistance of Enterobacteriaceae causing community-acquired urinary tract infections in Tétouan, Morocco (2022–2023)

2026-04-28T14:00:00Z

by Laila Farouk, Ayoub Ez-Zari, Lahcen Ouchari, Zine El Abidine Bzazou EL Ouazzani, Zakaria Mennane, Noureddine El Mtili

Background

Urinary tract infections (UTIs) are among the most common community-acquired bacterial infections and Enterobacteriaceae are the leading etiological agents. Rising antimicrobial resistance (AMR) within this family poses major challenges for empirical treatment. This study aimed to describe the species distribution and antimicrobial resistance patterns of uropathogenic Enterobacteriaceae isolated from outpatients in Tétouan, Morocco.

Methods

A cross-sectional descriptive study was conducted between April 2022 and December 2023 in three medical laboratories. Enterobacteriaceae isolated from urine cultures with significant bacteriuria were identified using the VITEK®2 system. Antimicrobial susceptibility testing was performed according to EUCAST 2021 guidelines. Extended-spectrum β-lactamase (ESBL) production was assessed using the Modified Double Disc Synergy Test (MDDST). Statistical analyses were performed using SPSS version 26, with significance set at p < 0.05.

Results

A total of 422 Enterobacteriaceae isolates were obtained, predominantly from female patients (74.9%). Escherichia coli was the most frequent species (83.4%), followed by Klebsiella pneumoniae (9.2%). High resistance rates were observed for ampicillin (60.9%) and ticarcillin (56.2%), while resistance to imipenem (1.2%) and ertapenem (0.9%) remained low. ESBL production was detected in 20 isolates (4.7%), with E. coli being the predominant ESBL-producing species (16/20; 80.0%), while K. pneumoniae exhibited a higher species-specific prevalence (4/39; 10.3%). Male patients exhibited significantly higher resistance to several β-lactams, while pediatric patients showed higher resistance to cephalosporins and aminoglycosides.

Conclusion

Uropathogenic Enterobacteriaceae circulating in the community of Tétouan exhibit substantial resistance to commonly prescribed oral antibiotics, although carbapenems remain highly effective. The moderate prevalence of ESBL-producing strains highlights the need for reinforced antimicrobial stewardship and continuous regional surveillance to guide empirical treatment and limit the spread of resistant pathogens.

Decision time is associated with future cooperation and social rewiring decisions in network public goods games

2026-04-28T14:00:00Z

by Zeyu Zhu

Previous research suggests that encouraging cooperation in social networks by engaging cooperators with defectors is only effective when individual heterogeneity is considered. However, this heterogeneity remains largely underexplored. Drawing on the drift-diffusion model, decision time captures this heterogeneity as an indicator of the feeling of conflict when individuals make cooperation decisions. Using secondary data from a previous public goods game experiment, this study first investigates how one’s decision time predicts one’s cooperation decision in the next round. A typical participant with a longer decision time is more likely to flip their decision. I then explore the relationship between this decision time and one’s willingness to connect to others when offered a chance. Faster defectors are more willing to connect to both cooperators and defectors than slower defectors. Faster cooperators are less willing to connect to defectors than slower cooperators, but no significant difference is found between faster and slower cooperators when offered to connect to fellow cooperators after controlling for environmental factors. The findings may serve as a foundation for transparent intervention strategies that facilitate cooperation by selectively engaging cooperator–defector pairs.

Safety-oriented and explainable machine learning for KSI crash risk prediction: Evidence from the United Kingdom

2026-04-28T14:00:00Z

by Khanh Giang Le

Road traffic crashes pose a serious public safety challenge, particularly due to fatal and serious injuries. Although machine learning (ML) has been widely used for crash severity prediction, many studies remain accuracy-oriented and insufficiently address class imbalance, decision thresholds, and probabilistic reliability. This study proposes a safety-oriented and explainable ML framework for predicting killed or seriously injured (KSI) crashes using nationwide United Kingdom traffic accident data from 2020–2024. Crash severity is reformulated as a binary classification task distinguishing slight injury crashes from KSI outcomes, aligning model objectives with road safety priorities. A Light Gradient Boosting Machine (LightGBM) model is developed with imbalance handling using SMOTE, safety-oriented decision threshold optimization, and probability calibration. Model performance is evaluated using ROC–AUC, precision–recall analysis, confusion matrices, the Brier score, and a utility-based evaluation metric, while interpretability is ensured through SHapley Additive exPlanations (SHAP). Results show that default threshold settings fail to adequately detect severe crashes. At an optimized threshold of 0.35, the model achieves a Recall(KSI) of 0.605 – representing a substantial 73% improvement compared to conventional configurations – while maintaining acceptable precision. In addition, probability calibration confirms reliable risk estimation (Brier score = 0.190), supporting risk-based interpretation. Comparative analysis demonstrates that the SMOTE-based model provides a more balanced and operationally effective trade-off than class-weighted learning. SHAP analysis identifies speed limit, road class, lighting conditions, and urban context as key variables associated with KSI risk. The findings highlight the importance of safety-oriented learning design and context-aware performance interpretation for effective, risk-based traffic safety management.

Fecal microbiota transplantation mitigates respiratory infection in rats exposed to hypobaric hypoxia by modulating the NLRP3 inflammasome and mucosal immunity

2026-04-28T14:00:00Z

by Huan Wang, Zhenyan Wu, Yaolei Zhang, Lijun Tang, Guangqing Shi, Lijie Ma, Zhu Huang, Jing Zhou

Objective

To investigate the role of the gut-lung axis in respiratory infection under hypobaric hypoxia and the therapeutic potential of fecal microbiota transplantation (FMT).

Methods

Rats were exposed to hypobaric hypoxia (simulated 5000 m) for 14 days. Gut microbiota and serum short-chain fatty acids (SCFAs) were analyzed via 16S rRNA sequencing and GC-MS. Rats were then infected with Streptococcus pneumoniae and treated with FMT. Lung inflammation, NLRP3 inflammasome activity, cytokines, bacterial load, and secretory IgA (sIgA) were assessed.

Results

Hypobaric hypoxia triggered gut dysbiosis, marked by reduced abundance of Firmicutes D and Lactobacillus, elevated Bacteroidota, and decreased SCFA levels..FMT restored microbiota composition, increased acetic and butyric acid levels, and attenuated lung inflammation. FMT also enhanced NLRP3 inflammasome activation (NLRP3, ASC, Caspase-1), elevated IL-1β, IL-6, and TNF-α in BALF, reduced bacterial colonies, and increased airway sIgA in infected rats.

Conclusions

FMT alleviates hypobaric hypoxia-aggravated respiratory infection by restoring gut microbiota, modulating SCFAs, and enhancing NLRP3-mediated mucosal immunity, highlighting the gut-lung axis as a therapeutic target.

Traffic flow prediction via dynamic hypergraph learning

2026-04-28T14:00:00Z

by SiWei Wei, Yang Yang, ChunZhi Wang

In the field of intelligent transportation systems, efficiently and accurately predicting traffic flow and its evolution trends has become an important and urgent research task. Graph neural networks have been widely used in traffic flow prediction problems, but many methods ignore the high-order relationship of patterns between traffic flow and traffic nodes. To address the above issues, we propose a Transformer-based Hypergraph Convolutional Network (TSHGCN) for traffic flow prediction. Firstly, we adopt a hypergraph structure to more effectively capture the high-order nonlinear spatial correlations between traffic nodes. Then, an improved Transformer network is proposed, which accurately captured the global temporal features among various traffic nodes by combining the time distillation mechanism and the self-attention network. In addition, we integrate the above spatiotemporal modeling through efficient channel attention mechanism and multi-scale temporal information fusion mechanism, accurately extracting spatiotemporal features and achieving the final refined representation of traffic flow. Experiments on the California datasets (PeMSD4 and PeMSD8) with 5 independent random seed runs and strict statistical tests show that the TSHGCN model achieves the best performance on core metrics (MAE, RMSE, MAPE) under a unified experimental setting, and the performance improvement over state-of-the-art baselines is statistically significant.

Design of a dynamics-based hydraulic controller for lifting manipulator wrist and its stability analysis

2026-04-28T14:00:00Z

by Bobo Li

Under the requirements of Industry 4.0, the performance requirements for improving the hydraulic controller of the mechanical hand wrist are getting higher and higher. To address issues such as response delay and insufficient accuracy in traditional methods, this study proposes a hydraulic control based on a dynamic model. The core innovation lies in embedding the dynamic model into the control loop and integrating multiple intelligent algorithms for closed-loop optimization. Experimental verification shows that the maximum trajectory tracking error of the SHD controller is only 0.28 mm, the fault detection accuracy is as high as 98.3%, and the energy conversion efficiency is 98.1%. It is significantly superior to existing advanced controllers in terms of accuracy, stability, and response speed, such as the controller combining quantum-inspired neural networks with robust control, the controller combining meta-learning with fuzzy wavelet control, and the controller combining federated learning with edge control. The above research results provide an efficient solution for the precise and intelligent control of hydraulic systems in complex lifting operations.