PLOS ONE Alerts: New Articles

Correction: Protocol for the development of a procedure guide on Laparoscopic Cholecystectomy: Beyond bile duct injury prevention

2026-06-18T14:00:00Z

by Camilo Ramírez-Giraldo, Daniela Álvarez-León, Alejandro Karduss-López, on behalf of Bogotá Task Force Collaboration Group

Quantitative evaluation of anti-sliding performance and dosage regulation of steel slag asphalt mixture facing service environment

2026-06-18T14:00:00Z

by Zhiqiao Cheng, Ping Li, Jingsheng Pan

In view of the practical demands for quantitative evaluation on skid resistance and scientific regulation of steel slag content of steel slag asphalt mixtures under service conditions, this study takes steel slag content, temperature and abrasion effect as research factors. Via accelerated loading abrasion tests, this paper investigates the evolution characteristics and quantitative evaluation models of two core skid resistance indicators namely British Pendulum Number (BPN) and Mean Texture Depth (MTD) under three steel slag contents and three temperature gradients. The results show that both BPN and MTD values of steel slag asphalt mixtures decrease obviously with the increase of abrasion cycles. High temperature can significantly accelerate the deterioration of skid resistance, which provides important experimental references for the optimization and regulation of steel slag content in service areas with different temperatures. BPN and MPN present generally high correlation under various temperatures and steel slag contents, which verifies the coordinated variation rule of the two skid resistance indicators under multi-factor conditions. From the perspective of staged abrasion degradation, the abrasion evolution processes of BPN and MTD can be clearly divided into low, medium and high abrasion stages. Their correlations differ greatly in different stages, laying a solid foundation for segmented prediction of skid resistance service life. The research findings further improve the quantitative evaluation system for skid resistance of steel slag asphalt mixtures oriented to actual service environment, and offer accurate data support and practical guidance for scientific adjustment of steel slag content in practical engineering.

Correction: The Covid-19 pandemic in Sweden: Prolonged and unevenly distributed effects on the volume of pediatric anesthesia and surgery demonstrated by data from the Swedish Perioperative Register

2026-06-18T14:00:00Z

by The PLOS One Staff

An improved grey wolf optimization algorithm for 3-D UWB indoor positioning

2026-06-18T14:00:00Z

by Jingmei Zhou, Bing Li, Shanshan Yang, Chungang Liu

Traditional Ultra-wideband (UWB) positioning algorithms cannot achieve ideal positioning results when facing multipath effects and non-line-of-sight (NLOS) factors. In order to improve the accuracy of UWB indoor positioning, this paper proposes an improved grey wolf optimization (GWO) algorithm for 3-D UWB indoor positioning in the NLOS environment. First, the Chan algorithm is used for initial tag positioning. Then, the search area of the GWO algorithm is constructed with the initial positioning result as the center. Next, the GWO algorithm’s optimization accuracy and convergence speed are improved through the improvement of Tent chaotic mapping, nonlinear convergence factor based on cosine function, and dynamic inertia weight factor. Finally, the optimized position of the tag is determined using the improved GWO algorithm. Experimental results show that this algorithm can converge to the global optimal solution faster and achieve higher positioning accuracy in complex experimental environments. Compared with the Chan, ChanTaylor, particle swarm optimization (PSO), GWO, and enhanced grey wolf optimization (AGWO) algorithms, the average positioning accuracy of the proposed algorithm is improved by 62.92%, 66.43%, 45.71%, 40.91%, and 37.76% respectively, demonstrating its high practical value.

Quantifying and modeling fabric surface roughness discrepancy: Consistency between physical and digital textures in online shopping

2026-06-18T14:00:00Z

by Eugene Lee, Youngjoo Chae

In digital textile commerce, the absence of tactile interaction limits consumers’ ability to perceive fabric properties, often leading to mismatched expectations and product dissatisfaction. This study aimed to quantify the perceptual discrepancy in surface roughness (RDP) between physical fabrics and their digital representations and to identify structural parameters that influence this discrepancy. Plain- and twill-woven fabric specimens were prepared with varying densities, weights, and thicknesses. Surface roughness of physical fabrics was measured using atomic force microscopy (AFM), while digital roughness values were extracted from scanned images using ImageJ. Statistical analyses, including correlation and regression modeling, were applied to identify key predictors of RDP. Results showed that in plain-woven fabrics, lower weft density and higher warp density under fixed fabric weight conditions yielded the lowest RDP values, whereas in twill-woven fabrics, the perceptual gap was minimized at higher fabric weights and lower weft densities. These findings provide practical insights for improving visual–tactile alignment in virtual textile presentation and can inform fabric structural design for enhanced accuracy in online representation. Future research may explore nonlinear modeling and multisensory feedback systems to further reduce perceptual discrepancies.

Harvester perceptions of pesticide impacts on snail collection along Cameroon’s Atlantic coast

2026-06-18T14:00:00Z

by Yannick Elysée Ewane Epée, Annick Niquaise Enangue Njembele, Christian Bernard Kaldjob Mbeh, Emmanuel Ndinga Go’o, Alexis Hamdja Ngoniri, Kingsley Agbor Etchu

The coastal regions of Cameroon comprising South-West, Littoral, and South are major agricultural hubs and important zones for harvesting African giant land snails (Achatinidae). Snail collection provides both a vital protein source for local consumers and a source of income for harvesters. Agricultural intensification has increased pesticide use in these areas, raising concerns about potential impacts on snail populations and human health. This study assessed harvesters’ perceptions of how pesticides influence the quantity and size of snails collected. A total of 211 harvesters from six localities (Kribi, Buea, Limbe, Mbanga, Njombe-Penja, and Dibamba) were surveyed through interviews and participant observations. Descriptive statistics and regression models were applied to explore socio-demographic influences on perceptions. Results showed that while 58% of harvesters believed pesticides reduce snail size, 61% did not perceive an effect on snail quantity. Snail collection was reported to be most successful during nocturnal periods and in October, aligning with ecological seasonality. Regression analysis revealed a weak but statistically significant association between perceptions of pesticide impacts and reported harvesting quantities (R² = 0.065), with perceived effects on snail quantity emerging as the only significant predictor. Despite awareness of pesticide risks, 63% of respondents expressed no interest in snail farming, citing preference for wild harvesting. This study highlights local knowledge on pesticide risks but also reveals a gap between awareness and adaptive practices. Findings are framed as perceptions, not direct ecological measurements, and they underline the need for awareness campaigns, sustainable harvesting practices, and supportive policies for alternative snail production systems.

Stage-specific associations of mineralization markers with CKM syndrome: Nationwide survey and genetic evidence for Alkaline phosphatase’s unique clinical role

2026-06-18T14:00:00Z

by Lei Hua, Yongshou Tao, Liangru Shen

Background

Cardiovascular-Kidney-Metabolic (CKM) syndrome involves disordered mineralization processes. Herein, we investigated the serum alkaline phosphatase (ALP), calcium, and phosphorus across CKM stages.

Methods

This study analyzed 15,233 eligible participants in National Health and Nutrition Examination Survey (2009–2018) using survey-weighted multinomial logistic regression to assess associations of ALP, calcium, and phosphorus. Restricted cubic splines assessed non-linear relationships, while Cox models examined mortality risks. Two-sample Mendelian randomization (MR) explored causal relationships.

Results

Relative risk ratios (RRRs) and 95% confidence intervals (95% CI) were calculated with multinomial logistic regression. Compared with stage 0, ALP was positively associated with the likelihood of being classified into stage 2 (RRR, 1.23[95% CI, 1.11–1.37]), stage 3 (RRR, 1.99 [95% CI, 1.48–2.67]), stage 4a (RRR, 1.29 [95% CI, 1.14–1.46]), stage 4b (RRR, 1.35 [95% CI, 1.16–1.58]). Per mg/dL increase in serum calcium levels was associated with a higher likelihood of being classified into stages 2 (RRR = 2.13, 95% CI: 1.55–2.94) and CKM stage 4, while per mg/dL increase in serum phosphorus was associated with stage 3 classification (RRR = 2.85, 95% CI: 1.77–4.59) and the results remained consistent after standardizing the markers using z-scores. ALP’s 4th quartile was associated with the highest mortality risks (CKM-cause hazard ratio = 2.20; all-cause hazard ratio = 2.15). MR analysis indicated potential causal effects of ALP on cardiovascular disease and of chronic kidney disease on ALP.

Conclusions

ALP demonstrates consistent associations with all CKM stages. These findings indicate that ALP-related mechanisms need further exploration.

Knowledge, attitudes, and practices regarding asthma management among pharmacists in palestine: A cross-sectional study

2026-06-18T14:00:00Z

by Dima Masri, Haneen Joulani, Alisse Nasser, Dala N. Daraghmeh

Background

Pharmacists can play a key role in asthma management through patient education, inhaler technique assessment, and promoting evidence-based care. This study assessed Palestinian pharmacists’ general asthma knowledge, asthma pharmaceutical care knowledge, attitudes, practices, and perceived barriers to asthma management.

Methods

A cross-sectional study was conducted from March to June 2025 in Palestine. Data were collected using a self-administered online questionnaire (convenience/volunteer-response sampling; response rate not determinable). General asthma knowledge was scored by awarding 1 point per correct response (range 0–17) and categorized as poor (0–8), fair (9–11), and knowledgeable (12–17). Data were analyzed using SPSS, bivariate associations were tested using chi-square test, or Fisher’s exact test, and multivariable linear regression was used to identify independent predictors. A p-value of < 0.05 was considered statistically significant.

Results

A total of 402 participants (137 male and 265 female) participated in this study. Overall, 57.2% were classified as knowledgeable in general asthma knowledge. Pharmacists working in hospital settings showed a significantly higher asthma knowledge in comparison with those working in community pharmacies (β = 0.110, p = 0.032). However, the model explained minimal variance (R² = 0.037) and was not statistically significant overall (overall model p = 0.144). No pharmacists’ characteristics were significantly associated with asthma pharmaceutical care knowledge (R² = 0.027; overall model p = 0.378) or attitudes and practices (R² = 0.014; overall model p = 0.850).

Conclusion

Pharmacists demonstrated mixed asthma knowledge with gaps relevant to updated guideline-based care, alongside practice barriers and clinically important practice gaps. Given the very low R² values, observed associations should be interpreted cautiously. Structured continuing professional development and targeted training may improve pharmacists’ uptake of updated recommendations and strengthen asthma pharmaceutical services.

Focus shifts in contextual and lexical cue interactions in GPT models

2026-06-18T14:00:00Z

by Wonil Chung, Keonwoo Koo

Transformer-based language models have demonstrated sensitivity to a range of linguistic dependencies, yet it remains unclear how they represent information-structural focus and integrate discourse and lexical focus cues during ellipsis resolution. We investigated GPT-style models’ interpretation of elliptical remnant continuations in double-object constructions by manipulating contextual focus via preceding interrogatives (who vs. what) and lexical focus via the particle only, whose surface position was varied. Using word-by-word surprisal as an index of processing difficulty, we conducted three experiments with GPT-2 models (Small–XL) and GPT-Neo. In Experiment 1 (no only), models robustly tracked the wh-induced discourse focus, assigning higher surprisal to remnants that mismatched the contextually focused constituent. In Experiment 2 (only preceding the indirect object), contextual focus continued to dominate, indicating that discourse cues were maintained despite the presence of a competing lexical marker. In Experiment 3 (only preceding the direct object), lexical focus effects became stronger: models favored remnants aligned with the lexically biased direct object, consistent with locality-based cue weighting when only is adjacent to that object. Comparisons with human reaction-time data revealed broad convergence in contextual-focus sensitivity but divergence when the remnant was compatible with one cue but not the other, with GPT-style models exhibiting a stronger bias toward alignment with only than humans. Together, these findings suggest that the tested models maintain discourse-level focus representations while integrating multiple focus cues in a proximity-sensitive manner, revealing both overlap and limits in their alignment with human processing.

Young adults’ perspectives on chlamydia-related subfertility and a potential predictive subfertility test: A mixed-methods study in the Netherlands

2026-06-18T14:00:00Z

by Bernice M. Hoenderboom, Zoïe W. Alexiou, Charlotte M. M. Peters, Karlijn Kampman, Colette van Bokhoven-Rombouts, Christian J. P. A. Hoebe, Birgit H. B. van Benthem

Background

Chlamydia trachomatis (chlamydia) infection control could be more effective if focused on morbidity- rather than prevalence reduction. A predictive test, identifying those at higher risk for chlamydia-subfertility, could be developed to enhance targeted chlamydia control. However, do young adults with a uterus (hereafter “young adults”) want to know their subfertility risk?

Methods

A sequential mixed methods study was conducted among young adults in the Netherlands to explore perspectives on chlamydia, subfertility, and a potential subfertility test. Five focus groups with Sexual Health Center (SHC) visitors were held to identify potential benefits, barriers, and requirements; results were analysed thematically and used to inform a questionnaire. This questionnaire was distributed online via SHCs and social media. Descriptive statistics and modified Poisson regression were used to assess benefits and barriers of learning one's subfertility risk.

Results

Nineteen young adults participated in the focus groups, and the resulting themes informed the questionnaire. These included perceived benefits (mental preparation, anticipation, reassurance after a “no increased risk” result), perceived barriers (mental burden of an “increased risk” result, need for blood sampling), and requirements (accuracy, accessibility, follow-up). The questionnaire was completed by 426 participants (median age 22, IQR 20–24). High perceived susceptibility was reported by 11% for chlamydia and 23% for chlamydia‑related subfertility; perceived severity was high for chlamydia and chlamydia-related subfertility, 75% and 88%, respectively. Willingness to use a risk test was 78%. Relief after a “no increased risk” result was expected by 89%, while an increased‑risk result was expected to enhance preparedness (86%) and elicit worry (83%). Additional considerations included motivation for safer sex, negative effects on relationships, and questioning the value of knowing.

Conclusion

Young adults are concerned about chlamydia‑related subfertility, resulting in high willingness to use a risk test. The expected benefits and barriers should be carefully considered in test development.

Stigmatizing attitudes and misconceptions about obesity among Spanish healthcare professionals

2026-06-18T14:00:00Z

by David Sánchez-Carracedo, Albert Fornieles-Deu, Dimitra Anastasiadou, Stuart W. Flint

Weight stigma and misconceptions about obesity among healthcare professionals (HCPs) may negatively affect healthcare quality and access for people living with obesity (PLWO). However, no previous research has examined these attitudes and beliefs in Spanish HCPs. This cross-sectional online study examined weight stigma and obesity-related beliefs among 922 HCPs recruited via Spanish professional and academic obesity-related organizations ((74.1% female, mean BMI = 23.73 kg/m² (SD 3.89), mean age = 43.73 years (SD 12.45), range 23–75, 88.7% provide care for PLWO)). Anti-fat attitudes were measured using the Dislike subscale of the Anti-Fat Attitudes questionnaire (AFA) and the Fat Phobia Scale (F-Scale). ANOVAs adjusted for sociodemographic variables, weight status, and weight bias internalization were conducted. Overall, Spanish HCPs surveyed reported negative attitudes toward PLWO. Lower weight status was consistently associated with higher stigma scores. Younger age (F-Scale) and working in the private sector (Dislike) were associated with higher scores. Differences across specialties were observed, with obesity physicians reporting the lower stigma levels. A substantial proportion of HCPs endorsed beliefs emphasizing personal responsibility: 38% attributed overeating to individual causes, 66% believed obesity could be entirely prevented by a healthy lifestyle, and 59% believed it could be cured through lifestyle changes. Many also attributed weight loss difficulties, poor compliance, and weight regain to lack of motivation and lifestyle choices, and over half considered lifestyle or psychological interventions the most effective treatment for severe obesity. Endorsement of these beliefs was consistently associated with higher stigma scores. These findings provide national evidence that weight stigma among Spanish HCPs is present and linked to beliefs framing obesity as primarily under individual control. These attitudes and knowledge gaps may contribute to inappropriate care and unfair treatment of PLWO. Addressing responsibility-focused beliefs may be a key step towards reducing stigma and improving the quality of obesity care in Spain.

Thyroid V40 as a potential early predictor of hypothyroidism following hypofractionated locoregional breast radiotherapy

2026-06-18T14:00:00Z

by Moemen Khalifa, Maher Soliman, Abbas Omar, Mohamed Abouegylah, Amr Munir Ameen, Yomna Mahmoud Mohamad, Waleed Arafat

Radiotherapy (RT) is used quite often among breast cancer patients, and because these patients now live longer than they used to, long-term treatment-related adverse effects, such as hypothyroidism, are becoming increasingly relevant. Radiation-induced hypothyroidism is a late side effect of radiation to the thyroid gland, which could develop months to years after radiotherapy. However, there are insufficient data on hypothyroidism in patients with breast cancer who receive locoregional RT, which usually affects a portion of the thyroid gland. In this prospective study, we aimed to evaluate the association between radiation dose to the thyroid gland and early thyroid dysfunction in breast cancer patients treated with hypofractionated locoregional radiotherapy, and to establish potential planning objectives that could help in sparing the thyroid gland. Our study included 109 women who received 3-D conformal locoregional breast radiotherapy. These patients had normal thyroid function prior to start of radiotherapy. Patients had follow-up thyroid function tests 6 months after finishing radiotherapy. Based on dose volume histograms (DVH), the percentages of the thyroid volume, and ipsilateral thyroid lobe, receiving 5, 10, 15, 20, 25, 30, 35, and 40 Gy (V5, V10, V15, V20, V25, V30, V35, and V40 respectively), in addition to the mean and maximum thyroid doses, were estimated. Follow-up assessment of thyroid function and statistical analysis unveiled incidence of radiotherapy induced hypothyroidism to be 8.3%. Possible risk factors included high maximum radiation dose and V40 to the thyroid gland and the ipsilateral thyroid lobe, as well as high mean dose and smaller volume of the ipsilateral thyroid lobe. The likelihood of hypothyroidism was significantly increased with V40 of >5% of the thyroid gland, and V40 of >11% of the ipsilateral thyroid lobe. Further study is recommended for larger populations and longer follow-up periods.

HIF-2α drives osteoarthritis progression via suppression of the HDAC4-ATF4-CHOP signaling axis

2026-06-18T14:00:00Z

by Pinpin Jiang, Hang Wang, Yujia Li, Yuanyu Zhang, Jingrui Huang, Yukun Xu, Dahai Rong, Danni Ruan, Yao Wang, Jie Yuan, Pengcui Li

Hypoxia-inducible factor-2α (HIF-2α) is a key regulator of cellular adaptation to hypoxia, but its role in osteoarthritis (OA) remains incompletely defined. This study aimed to investigate the contribution of HIF-2α to OA pathogenesis and the underlying molecular mechanisms. Human cartilage specimens were collected to examine HIF-2α expression and components of the histone deacetylase 4 (HDAC4) signaling pathway using Western blotting, quantitative real-time PCR, and immunohistochemistry. An in vitro OA model was established in chondrocytes using interleukin-1β (IL-1β), followed by HIF-2α knockdown with small interfering RNA and overexpression via adenoviral transduction. Chondrocyte apoptosis was assessed by flow cytometry and TUNEL staining. To evaluate in vivo effects, HIF-2α was silenced using an adeno-associated viral vector in a rat OA model induced by anterior cruciate ligament transection (ACLT). Disease progression was assessed by X-ray, computed tomography (CT), FMT® small animal in vivo fluorescence molecular tomography imaging system, Safranin O staining, and immunohistochemistry. HIF-2α expression was significantly increased in cartilage from OA patients and ACLT rats. In vitro, HIF-2α modulation altered HDAC4 expression and downstream apoptotic signaling. Knockdown of HIF-2α reduced chondrocyte apoptosis and attenuated cartilage degeneration in vivo. These findings indicate that HIF-2α promotes OA progression by regulating chondrocyte apoptosis and matrix homeostasis through the HDAC4-ATF4-CHOP pathway. This study identifies a previously unrecognized mechanism linking HIF-2α to OA and highlights its potential as a therapeutic target.

PTPRE promotes gastric cancer cell resistance to 5-fluorouracil by inhibiting ferroptosis via the Src/FAK/TRIB3 axis

2026-06-18T14:00:00Z

by Ming Liu, Xiaomei Liao, Fangchao Wang, Pengqing Jiao, Zhongkai Wang

Acquired drug resistance is a major cause of failure in gastric cancer treatment. The protein tyrosine phosphatase receptor type E (PTPRE) plays an oncogenic role in certain tumours; however, its function in chemotherapy-resistant gastric cancer remains unclear. Therefore, we analysed PTPRE expression in gastric cancer using The Cancer Genome Atlas. In vitro experiments were then conducted to investigate the effects of PTPRE on the resistance of cancer cells to 5-fluorouracil (5-FU) and its potential mechanisms. The results were further validated in vitro using xenograft studies. We found that PTPRE is upregulated in gastric cancer tissues and participates in the induction of 5-FU resistance. Mechanistic studies revealed that PTPRE suppressed ferroptosis in gastric cancer cells and promoted 5-FU resistance by activating the Src/FAK pathway to upregulate TRIB3 expression. In summary, PTPRE suppresses ferroptosis in gastric cancer cells via the Src/FAK/TRIB3 signalling pathway, thereby inducing 5-FU resistance. Intervention with PTPRE and its downstream targets may represent a potential approach for the clinical treatment of 5-FU-resistant gastric cancer.

Waist-to-height ratio identifies children with lower physical activity and reduced cardiorespiratory fitness: Longitudinal evidence from Norwegian primary schools – The Health Oriented Pedagogical Project (HOPP)

2026-06-18T14:00:00Z

by Per Morten Fredriksen, Nandu Goswami, Asgeir Mamen

Objectives

Childhood obesity and physical inactivity are major global health concerns because of their links to cardiometabolic risk factors that may persist into adulthood. Waist-to-height ratio (WHtR) has emerged as a practical indicator of central adiposity and metabolic risk. Moderate-to-vigorous physical activity (MVPA) and cardiorespiratory fitness are important factors in reducing obesity-related risk. This study investigated the association between WHtR, physical activity, and fitness in children aged 6–12 years.

Methods

The Health Oriented Pedagogical Project (HOPP) is a longitudinal cohort study conducted from 2015 to 2020 and including 2297 Norwegian children. WHtR was examined as the main time-varying exposure. Separate linear mixed models were fitted for MVPA, sedentary time, Andersen intermittent running test performance, and VO₂peak as outcomes, with age, sex, and socioeconomic status included as covariates.

Results

Each 0.1 unit increase in WHtR was linked to a −0.62 min/day reduction in average MVPA. Higher WHtR was associated with lower MVPA and lower cardiorespiratory fitness, including both Andersen test performance and VO₂peak. No clear association was observed between WHtR and sedentary time.

Conclusion

In this longitudinal cohort, higher WHtR was associated with lower physical activity and lower cardiorespiratory fitness. WHtR may therefore serve as a simple screening indicator for identifying children who may warrant closer assessment of fitness, physical activity, and cardiometabolic risk.

Start order and medal outcomes: An analysis of apparatus finals in men’s artistic gymnastics

2026-06-18T14:00:00Z

by Chih-Yu Chen, Kuang-Hui Chen, Kang-Hao Lu

Purpose

This study examined the relationship between start order and competition outcomes in men’s artistic gymnastics apparatus finals.

Methods

Competition outcomes from three Olympic Games and nine World Championships were analyzed. Ordinal-based analyses, including Spearman’s rank-order correlation and Kendall’s tau-b, were conducted to examine the relationship between start order and final rankings. Logistic regression was used to assess the association between start order and medal attainment. In addition, Mann–Whitney U tests were used to compare final rankings between start-order groups; independent-samples t-tests were used to assess differences in Difficulty (D) scores, Execution (E) scores, and total scores; and Chi-square tests were used to evaluate associations between start-order grouping, medal attainment, and continental affiliation.

Results

Ordinal correlation and logistic regression analyses showed no significant associations between start order and final rankings or medal attainment across apparatuses. Start-order grouping had limited influence on final rankings across most apparatuses. A significant effect was observed only in the pommel horse, where second-half gymnasts achieved higher E-scores and won more medals. Medal distributions between European and non-European athletes were similar across apparatuses and start-order groupings.

Conclusion

Overall, start-order grouping had minimal effects. However, pommel horse results highlight the importance of execution stability. The findings support the general fairness of the current judging system and Code of Points. Future research should examine warm-up procedures under revised FIG regulations and extend analyses to women’s artistic gymnastics.

A study protocol for mixed-methods evaluation of the structure, design, and availability of medical student wellbeing programs

2026-06-18T14:00:00Z

by Neel Godbole, Sugy Choi, Kwanbo Shim, Yuning Liu, Jason Hu, Jennifer Wong, PhiYen Nguyen, Sze Wan Celine Chan, Lan Doan, Nelson Lin, Vanessa Salcedo, Stella S. Yi

Introduction

In recent years, there has been growing concern over the wellbeing and mental health of medical students in the United States, driven by the academic, personal, and professional challenges inherent in medical school. Recent data indicates that medical students experience higher rates of psychological stress, anxiety, and depression compared to the general population, with the COVID-19 pandemic exacerbating these challenges. Medical student suicide, linked to burnout and depression, highlights the urgent need for effective wellbeing support. Despite the documented barriers to mental wellbeing, such as self-imposed pressures, imposter syndrome, stigma around help-seeking, and financial difficulties, medical student wellbeing programs remain understudied at the structural and design level.

Methods

This is a multi‑phase qualitative study (sequential-exploratory) that combines a web-based environmental scan and content analysis with key informant interviews and focus groups, using methodological triangulation to develop a framework for evaluating wellbeing programs. First, we will conduct a web-based content analysis of publicly available resources across medical school websites. We will identify key characteristics of wellbeing programs, such as mental health resources, structural well-being components, and culturally integrated approaches. Then, we will conduct key informant interviews with medical school administrative staff to discuss wellbeing programs in detail and hold focus group interviews with medical students to gather their perspectives on how to improve their health and wellbeing. Based on the findings from these three components, we will develop a comprehensive and standardized framework for evaluating medical school wellbeing programs that can be used across institutions.

Ethics and dissemination

Human Research Ethics Approval was obtained from the NYU Langone Health Institutional Review Board (IRB ID: i25-00965). The content analysis results and qualitative themes extracted from key informant and focus group interviews will be made available to all study participants. They will also be disseminated in a peer-reviewed journal.

Short-term effects of bone meal powder on soil phosphorus availability, seed germination, and early growth parameters of Malabar Spinach (Basella alba)

2026-06-18T14:00:00Z

by Aishwa Roy, Protima Sarker

There is a growing need to find alternatives to chemical fertilizers, particularly for Phosphorus supply. Chemical fertilizers contribute to environmental problems and natural phosphate resources are depleting. The main objective of the study was to examine the effect of bone meal powder (BMP) as an organic fertilizer on soil phosphorus availability, seed germination, and early growth performance of Malabar spinach (Basella alba). Two experiments were conducted: soil chemical analysis and pot experiment. Experiment 1 referred to highly saline soil-High Electrical Conductivity (EC) and Experiment 2 used non-saline- Low Electrical Conductivity (EC) soil. The treatments included: T1: High EC soil; only potting media; no BMP, T2: High EC soil amended with BMP, T3: Low EC soil; only potting media; no BMP, T4: Low EC Soil amended with BMP. All treatments were used to analyze the soil chemical properties, including soil pH, EC and Phosphorus. For the pot experiment, treatments (T3 and T4) were combined in a completely randomized design with three replicates and the data were collected on germination and early growth parameters of malabar spinach. Results revealed that the application of BMP increased soil pH, EC and notably improved phosphorus availability, compared to the control in both soils. However, BMP negatively affected germination and early growth variables in experimental soil 2. In spite of the great differences in shoot length were observed in the application of BMP, only minor differences were found in root lengths and fresh weight. The correlation analysis showed that mean germination time had negative relationships with growth parameters. The findings suggest that BMP may have potential as an inexpensive and eco-friendly fertilizer, although further large-scale field experiments are necessary to confirm its effectiveness. These results may inform researchers, stakeholders, and agricultural practitioners regarding the potential use of BMP.

The use of immersive technologies in learning about postpartum hemorrhage: Protocol for a systematic review and meta-analysis

2026-06-18T14:00:00Z

by María Jose Montiel Bravo, Mariana Ferrandini Price, Manuel Pardo Rios, Marina Sanchez Gomez, Grasiela Piuvezam, Gidyenne Christine Bandeira Silva de Medeiros, Carmen Amalia Lopez Lopez

Postpartum hemorrhage is one of the leading causes of maternal morbidity and mortality worldwide, and its proper management requires both technical and non-technical skills. This study describes the protocol for a systematic review evaluating the effectiveness of immersive technologies in training healthcare professionals in the management of this obstetric emergency. This protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (CRD420250614446). The search will be performed in the following databases: PubMed, Embase, Scopus, ScienceDirect, Web of Science, Cochrane Library, LILACS, Enfispo and CUIDEN. Intervention studies (clinical trials ‐ randomized or non-randomized) and quasi-experimental studies will be included. The risk of bias will be assessed using appropriate tools according to study design: the Risk of Bias 2 (ROB 2) tool for randomized controlled trials and the Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool for non-randomized and quasi-experimental studies. Two independent researchers will conduct all assessments, and any disagreements will be consulted with a third reviewer. The data analysis and synthesis will be performed using Review Manager software version 5.4. We will conduct the study in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) guidelines. The review will summarize the current evidence on the use of virtual reality, augmented reality, and mixed reality in education and training for postpartum hemorrhage management. The planned systematic review will identify and synthesize the available evidence on how immersive technologies may improve learning about postpartum hemorrhage.

Analysis of molecular targets and mechanisms of Bisphenol F (BPF)-induced non-alcoholic fatty liver disease (NAFLD) based on network toxicology and molecular dynamics

2026-06-18T14:00:00Z

by Riwei Wang, Qiangming Liao, Xianwei Liu, Liang Sun, Yun Xia

Bisphenol F (BPF), a primary substitute for bisphenol A (BPA), is widely utilized in industrial production and daily life. However, its widespread environmental presence has raised concerns regarding potential health risks. This study aims to investigate the potential toxic targets of BPF in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). Initially, potential target genes of BPF were identified using the ChEMBL, STITCH, and SWISS databases. NAFLD-related genes were obtained from the OMIM and GeneCards databases, yielding a preliminary set of 28 overlapping candidate targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were subsequently performed to elucidate the biological processes and signaling pathways potentially affected by BPF. Differential expression analysis of transcriptomic data from NAFLD and normal liver tissues obtained from the GEO database (GSE260666) revealed that CYP2C19 and SHBG were significantly upregulated in NAFLD samples, suggesting their potential as key targets of BPF. Molecular docking simulations using AutoDock demonstrated stable binding conformations between BPF and both CYP2C19 and SHBG proteins, with favorable binding free energies indicating strong interactions. Furthermore, molecular dynamics simulations confirmed the structural stability of the protein-ligand complexes under simulated physiological conditions. These findings provide a theoretical basis for understanding the toxic targets and mechanisms of BPF in NAFLD pathogenesis and offer insights for the prevention and treatment of NAFLD associated with BPF exposure from plastic products.

Traffic condition prediction for highway within work zones under dynamic traffic organization changes

2026-06-18T14:00:00Z

by Feiping Xu, Bohan Liu, Hang Liu, Yonghao Wang, Jundong Wang, Chengcheng Wang

In the context of sustainable transportation development, reducing carbon emissions, energy waste, and noise pollution caused by traffic congestion has become an urgent task for achieving environmental and social sustainability. The key to this goal lies in mitigating and preventing traffic congestion, for which high accuracy traffic condition prediction models serve as essential tools. During the reconstruction and expansion of highways and urban arterial roads, frequent adjustments to traffic organization and changes in geometric alignment introduce dynamic and uncertain characteristics into the traffic system. Existing methods struggle to accurately predict traffic conditions in the modified sections. To address this challenge, this study proposes a Dynamic Bayesian Graph Convolutional Neural Network (DBGCN). The model incorporates road geometric parameters and dynamic traffic organization changes as key inputs. It employs a Dynamic Bayesian Network (DBN) to model multi-source dynamic information and infer a dynamic adjacency matrix that reflects latent spatiotemporal dependencies between nodes. This dynamic adjacency matrix is then input into a Graph Convolutional Network (GCN), which fuses spatiotemporal features with traffic flow data to achieve accurate traffic conditions prediction for upgraded sections. Validation on the Wuxuan highway demonstrates that the proposed method outperforms benchmark models in traffic conditions prediction accuracy and produces traffic conditions propagation diagrams with high interpretability.

Multi-scale closed-loop tuning via spatial frequency collaborative sensitivity for rice leaf disease detection

2026-06-18T14:00:00Z

by Yandong Song, Kang An, Lidong Wang, Bin Zhou

Rice is a fundamental food source for more than half of the global population, making stable yields and quality improvements vital for food security and sustainable agricultural development. Early infections of rice leaf diseases often exhibit subtle symptoms, while conventional control methods based on empirical judgment and routine pesticide application result in both yield losses and environmental pollution. A Multi-scale closed-loop tuning via spatial frequency collaborative sensitivity (MCCA-YOLO) model has been proposed in this paper with a multiscale closed-loop tuning and spatial frequency collaborative attention mechanism for the early detection and classification of rice crop diseases. MCCA-YOLO incorporates a closed-loop tuning compound network architecture that combines a dual-backbone feature extractor with a spatial frequency enhancement module to achieve system self-verification feedback, reducing transmission errors and enhancing the texture features of leaves. The framework implements a cross-scale weighted fusion and a deformable spatial hybrid attention enhanced bidirectional feature pyramid fusion network for dynamic feature adaptation, effectively accommodating the complex morphology of rice leaf lesions. By conducting comprehensive ablation studies and comparative experiments with existing techniques on the rice plant diseases v8 dataset, the proposed approach achieves a mean average precision (mAP) of 92.2%, outperforming well-established methods, while delivering superior precision (0.915) and recall (0.900). Extensive empirical validation of additional v9 and Rice Leaf Spot Disease (RLSD) datasets for rice plant diseases further demonstrates the model’s outstanding performance.

Leaf beetle diversity on a Southeast Asian continental island: Taxonomy, DNA barcoding, and preliminary evolutionary insights from Cat Ba Island, Vietnam

2026-06-18T14:00:00Z

by Dinh Thi Nguyen, Loan Thi Ho

Continental shelf islands in Southeast Asia remain poorly studied with respect to insect diversity and evolutionary history. Here, we provide an integrative assessment of species diversity, DNA barcode variation, diversification dynamics, and historical biogeography of leaf beetles (Coleoptera: Chrysomelidae) on Cat Ba Island, northern Vietnam. Based on field surveys, 36 morphospecies operational taxonomic units (OTUs) belonging to 30 genera and five subfamilies were documented, with Galerucinae representing the most species-rich lineage. DNA barcoding of the mitochondrial COI gene generated 31 Barcode Index Numbers (BINs), most of which represent new records in the Barcode of Life Data System, highlighting substantial undocumented genetic diversity. COI-based analyses were further used to explore broad temporal and evolutionary patterns. Within this exploratory framework, divergence-time estimation under a relaxed molecular clock suggests that major lineages may have originated during the early–middle Miocene, predating the formation of the present-day island. Diversification analyses support relatively constant rates through time with low inferred extinction, consistent with expectations for continental shelf island systems shaped by repeated connectivity and isolation. Model-based biogeographic analyses indicate predominantly localized ancestral ranges, with Cat Ba Island and adjacent mainland regions playing recurrent roles in the assembly of the fauna. Together, these results provide baseline taxonomic and genetic data for a poorly known insular insect assemblage while offering a preliminary evolutionary context that should be interpreted with caution and that can serve as a foundation for future biodiversity monitoring and comparative studies in dynamic island–mainland systems.

Differences in mainland–island genetic diversity in two moths suggest species-specific outcomes

2026-06-18T14:00:00Z

by Sei-Woong Choi, Da-Hee Jin, Hyerin An, Kiwoong Nam, Bora Shin

Genetic divergence along elevational gradients between mainland and island populations provides an opportunity to test the island genetic erosion model, which predicts reduced genetic diversity and increased differentiation in island populations. We examined two moth species, a geometrid moth (Alcis angulifera) and an erebid moth (Hydrillodes morosa), sampled along elevational gradients on Mt. Jirisan (mainland) and Mt. Hallasan (island) in southern South Korea. A total of 155 individuals were analyzed using mitochondrial cytochrome oxidase subunit I (mt COI) sequences. We identified 61 haplotypes across both species. A. angulifera exhibited similarly high genetic diversity on the mainland and island, whereas H. morosa showed overall lower diversity relative to A. angulifera but pronounced regional differences, with significantly higher haplotype and nucleotide diversity on the island. Mantel tests revealed significant genetic divergence between mainland and island populations but not within individual mountains, suggesting ongoing gene flow within elevational gradients. AMOVA indicated moderate differentiation in A. angulifera (F_CT = 0.08) and stronger differentiation in H. morosa (F_CT = 0.14), with most genetic variation occurring within populations. Gene flow estimates further highlighted contrasting patterns, with high connectivity in A. angulifera (Nm = 5.49) and restricted migration in H. morosa (Nm = 0.08). Together, these results indicate that while A. angulifera maintains genetic cohesion across regions, H. morosa exhibits stronger geographic and elevational structuring due to limited gene flow. Our findings do not support a universal reduction in genetic diversity in island populations; instead, they highlight the importance of species-specific ecological traits and geographic context in shaping genetic diversity patterns, suggesting that the island genetic-erosion pattern is more context-dependent than previously appreciated.

The validity and reliability of a biometrically accurate, photorealistic set of young adult body size scales based on 3D scans of White Europeans

2026-06-18T14:00:00Z

by Bethany J. Ridley, Piers L. Cornelissen, Robin S. S. Kramer, Nadia Maalin, Sophie Mohamed, Martin J. Tovée

Young adults are a high-risk group for weight-related health problems but are often overlooked in weight management intervention design. Validated visual tools that accurately depict body size are needed to improve communication and intervention strategies. This study validated innovative, photo-realistic, gender-specific body size scales of young adults (aged 18), created from 3D scans to depict systematic changes in adiposity. A total of 110 young adults (aged 18–25) completed two behavioural tasks: (1) estimating the relative size of the bodies and (2) ranking them in ascending order of weight. To assess reliability, participants repeated the tasks three days later. Participants accurately estimated relative body sizes and ranked the images in line with the systematic BMI changes across the scales. Test–retest analyses showed good to excellent reliability for both tasks. The young adult body size scales are anthropometrically accurate, reliable, and valid tools for body size estimation tasks. They provide a robust resource for research, clinical communication, and intervention design focused on young adults.

Biocontrol of rice blast by Pseudomonas mosselii PR5 through seed priming and foliar application reduces reliance on chemical pesticides

2026-06-18T14:00:00Z

by Razia Sultana, Prinon Saha, Shah Mohammad Naimul Islam, Mohammad Mahbubul Haque, Sourav Biswas Shuvo, Md. Mustafijur Rahman Khan, Seikh Jafor Ahmed

Rice blast caused by Magnaporthe oryzae is a destructive disease that can infect rice at any developmental stage. This study investigated the biocontrol potential of the endophytic bacterium Pseudomonas mosselii PR5 against rice blast in comparison with a chemical fungicide. Three blast-susceptible rice genotypes were evaluated under eight treatment combinations, including an absolute control, a pathogen-inoculated control, a fungicide control, and five PR5 application modes: seed priming (SP), seedling priming (SeP), bacterial culture filtrate (BCF) foliar spray, and the combinations SP + BCF and SeP + BCF. All treatments except the absolute control received pathogen inoculation. Both PR5 and the fungicide significantly reduced disease severity across the three genotypes. The pathogen-only treatment consistently recorded the highest percent disease index (PDI) and area under the disease progress curve (AUPDC). Among the bacterial treatments, SP + BCF produced the lowest AUPDC in V1 and V3, while the fungicide performed best in V2. PR5 inoculation also enhanced plant growth and yield. Shoot dry weight increased by 3.29–47.36% compared with the absolute control and by 10.10–107.43% compared with the pathogen-only treatment. Pathogen stress severely reduced root growth, whereas PR5, particularly in the SeP + BCF treatment, increased root biomass by 24.58–69.22%. Significant improvements in yield traits like grains per panicle, effective tillers, and reduced chaffy grains were observed, especially when priming was combined with BCF foliar application. SP + BCF achieved the highest yield and outperformed the fungicide in disease suppression. These results suggest that PR5-based seed or seedling priming combined with BCF foliar application is a promising strategy for sustainable rice blast management.

A deep learning-based automated Solar-Powered Fish Monitoring System

2026-06-18T14:00:00Z

by Emmanuel Ahene, Richmond Owusu Agyei, Rose-Mary Owusuaa Mensah Gyening, Kwasi Adu Obirikorang, Kate Takyi, Kwabena Owusu-Agyemang, Linda Amoako-Banning, Joojo Walker

Green fish farming represents an integrated aquaculture approach that rears aquatic organisms in controlled environments to improve production efficiency and environmental sustainability. Although significant, current green fish farming practices are labour-intensive and expensive due to grid energy dependency resulting in operational inefficiencies and elevated fish mortality. To address these key challenges, we propose a multidisciplinary approach that involves the development of a cost-effective, solar-powered automation system that integrates computer vision and deep learning techniques for real-time monitoring of fish behaviour, water quality, feeding, and waste management. First, we design the system architecture that enables automation and ensures accurate system performance under varying conditions. Second, following the architecture, we build a complete and cost-effective smart system that works along with an intelligent software framework that leverages computer vision and deep learning techniques. Utilizing custom datasets from video frames and environmental sensors, this system utilizes convolutional neural networks (CNNs) for fish behavior analysis, real-time disease detection via camera feeds, and precise feeding control through actuators. The design also incorporates a renewable energy subsystem, employing advanced photovoltaic panels and efficient battery storage to guarantee reliable power. The major contribution lies in the seamless integration of these multidisciplinary components. Furthermore, the system architecture is modular and scalable, making it suitable for both smallholder and commercial fish farms. Cost optimization with low-cost sensors and open-source software enables economic viability for resource-constrained farmers. Extensive simulation studies confirmed significant improvements in monitoring accuracy, reduced manual intervention, and enhanced operational sustainability.

First steps towards distinguishing Mediterranean vegetation root marks on bones: An experimental approach

2026-06-18T14:00:00Z

by Alba Macho-Callejo, Dores Marin-Monfort, Aida Gutiérrez, Sara García-Morato, Yolanda Fernández-Jalvo

Root-bone interactions are common in buried skeletal remains, yet their diagnostic value remains largely unexplored because few controlled studies have linked root marks to specific plant types. Consequently, the potential of these marks to provide information about burial environments in archaeological, paleontological, and forensic contexts has been largely overlooked. Here, we present a long-term experimental study documenting root-induced bone modifications under natural field conditions in central Spain. Deer ribs were buried at various depths and for different lengths of time among three widespread Mediterranean trees and shrubs: holm oak (Quercus ilex), olive (Olea europaea), and grapevine (Vitis vinifera). Using optical and scanning electron microscopy, we identified distinct patterns of root engraving on cortical bone surfaces that varied by plant type. Holm oak roots produced sinuous, dendritic grooves; olive roots generated shallow, rectilinear markings; and grapevine roots formed linear-to-circular engravings, which were often associated with localized cracking. Mark intensity increased with burial depth and duration. These findings underscore the diagnostic value of root marks in identifying plant-specific signatures and offer a novel approach to recognizing plant activity in burial environments. This information improves taphonomic interpretations in various fields, including fossil reworking processes and forensic secondary burials.

Whole-genome characterization of halotolerant Enterobacter roggenkampii OSNO4 and its potential for climate-resilient agriculture

2026-06-18T14:00:00Z

by Sanjoy Kumar Mukharjee, Md. Faruk Hasan, Biswanath Sikdar

Plant growth-promoting rhizobacteria (PGPR) represent an eco-friendly strategy to improve crop yield under abiotic stress conditions. This study aimed to perform a comprehensive genomic and functional profiling of a halotolerant rhizobacterium to evaluate its multi-trait plant growth-promoting (PGP) potential and its precise contribution to mitigating salinity stress for climate-resilient agriculture. In the present study, 24 (8.5%) rhizobacterial isolates showed phosphate-solubilizing activity out of 283 isolated bacteria from rice rhizosphere. From these, strain OSNO4 was selected for detailed evaluation. The isolate demonstrated phosphate solubilization (solubilization index: 1.22) and potassium solubilization, indole-3-acetic acid (IAA) production (38.34 µg/ml), nitrogen fixation, siderophore and ammonia production, protease activity, and biofilm formation in vitro. Additionally, it showed tolerance to salinity (10% NaCl), drought (20% PEG 6000), temperature (45 °C), and a broad pH range. Strain OSNO4 further suppressed the growth of phytopathogenic fungi Fusarium concentricum by 54.23%. Whole-genome sequencing analysis identified the strain as Enterobacter roggenkampii (ANI 98.2%, dDDH 85.7%), with a 4.67 Mb genome harboring total 4,546 predicted genes and diverse functional subsystems. Comprehensive genomic study further revealed the presence of genes linked to nutrient mobilization, phytohormone biosynthesis, abiotic stress tolerance, and antifungal activity. Six biosynthetic gene clusters, including siderophore-related and putatively novel clusters were also identified. Pan-genome analysis revealed an open genome structure with high flexibility and genetic variability. Under salinity stress, OSNO4 inoculation significantly improved rice seed germination (52.22% to 85.56% at 100 mM NaCl; 42.22% to 72.22% at 150 mM NaCl), root and shoot development, and biomass accumulation compared to uninoculated controls. The strain also showed broad antibiotic susceptibility and non-hemolytic phenotype, suggesting its biosafe nature. In summary, these data demonstrate that E. roggenkampii OSNO4 possesses a robust repertoire of genomic determinants and functional capabilities, establishing it as a highly potent bioinoculant for deployment in climate-resilient and sustainable agroecosystems.

Perceptual no-reference image quality assessment with meta-learning by graph representation learning and multi-scale feature fusion

2026-06-18T14:00:00Z

by Yanru Jia, Longsheng Wei

No-reference image quality assessment (NR-IQA) aims to predict perceptual quality in alignment with the human visual system (HVS), yet existing methods face challenges in capturing long-range dependencies across distortion types and levels while preserving content fidelity during preprocessing. This paper presents a perceptually-driven NR-IQA framework that integrates meta-learning, graph representation learning, and multi-scale feature fusion to address these limitations. First, a meta-learning paradigm is employed to pre-train a self-calibrated convolutional backbone, which adaptively models spatial and channel-wise dependencies across scales, thereby enhancing the extraction of distortion-aware features while mitigating information loss caused by fixed-input preprocessing. Second, a graph representation learning module is introduced to explicitly encode the hierarchical relationships among distortion types, distortion levels, and image content. Nodes in the graph correspond to distorted images, while edges capture inter-sample similarities; these are jointly optimized via a graph convolutional network under dual supervision from a triplet-based distortion-type discriminator and a probabilistic distortion-level regressor that accounts for content-induced uncertainty. Extensive experiments on four benchmark datasets demonstrate that our method achieves better performance, with average SROCC and PLCC improvements of 3.6–36.6% over hand-crafted feature-based methods and consistent gains over deep learning-based approaches. Ablation studies and visualizations confirm that the proposed components collectively yield a more discriminative and generalizable distortion representation, closely mirroring human perceptual judgments.