PLOS https://journals.plos.org/plosone/ customercare@plos.org https://journals.plos.org/plosone/feed/atom All PLOS articles are Open Access. https://journals.plos.org/plosone/resource/img/favicon.ico https://journals.plos.org/plosone/resource/img/favicon.ico 2026-06-05T13:46:44Z Simone Caetano Juvenal Mottola Junior Flora Finguerman Suzan M. Goldman Jacob Szejnfeld 10.1371/journal.pone.0351091 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Simone Caetano, Juvenal Mottola Junior, Flora Finguerman, Suzan M. Goldman, Jacob Szejnfeld</p> Monalisa M. J. Faulkner Fatima Jalloh Foray Mohamed Foray Sahr L. Gborie Mohamed B. Jalloh 10.1371/journal.pone.0350989 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Monalisa M. J. Faulkner, Fatima Jalloh, Foray Mohamed Foray, Sahr L. Gborie, Mohamed B. Jalloh</p> Background <p>Sickle cell disease is a major cause of childhood mortality in sub-Saharan Africa, yet country-specific burden estimates for high-prevalence settings in West Africa remain limited.</p> Objective <p>To describe Global Burden of Disease (GBD) 2023 modeled estimates of sickle cell disorders burden in Sierra Leone from 1990 through 2023, including temporal trends, age and sex patterns, and demographic contributors to mortality change.</p> Methods <p>We analyzed GBD 2023 modeled estimates for sickle cell disorders in Sierra Leone, including prevalence, deaths, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) as absolute counts and age-standardized rates. Temporal trends in age-standardized rates were assessed using log-linear regression. The Kitagawa-Das Gupta decomposition partitioned the change in estimated deaths into population growth, age-structure change, and age-specific mortality-rate changes.</p> Results <p>Estimated prevalent cases increased from 48,689 (95% UI, 42,588−56,140) in 1990–90,498 (78,126−105,815) in 2023. Estimated deaths increased from 408 (288−579) to 635 (438−862), while the estimated age-standardized mortality rate declined from 10.2 to 7.9 per 100,000 (APC, −0.46%; 95% CI, −0.64 to −0.29). Decomposition attributed 159.6% of the net increase in deaths to population growth, −7.8% to age-structure change, and −51.8% to lower modeled age-specific rates. In 2023, an estimated 49.5% of deaths occurred before age 20. Point estimates suggested possible higher male mortality, but uncertainty intervals were wide and compatible with no clear sex difference.</p> Conclusions <p>GBD estimates suggest that Sierra Leone’s absolute burden of sickle cell disorders increased substantially between 1990 and 2023, while modeled rates declined. These modeled estimates highlight a growing absolute burden and persistent early-life mortality, supporting the need for improved surveillance, newborn screening, infection prophylaxis, hydroxyurea access, and longitudinal care systems.</p> Lu Zhang Si Wang Jie Lei Lingrui Zeng Ailin Lu Yongqing Wu Yuan Shi Jing Yang Mengrui Yuan Hongyi Liu 10.1371/journal.pone.0350984 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Lu Zhang, Si Wang, Jie Lei, Lingrui Zeng, Ailin Lu, Yongqing Wu, Yuan Shi, Jing Yang, Mengrui Yuan, Hongyi Liu</p> Background <p>Diabetic peripheral neuropathy (DPN) is a common complication of type 2 diabetes mellitus (T2DM) and is closely linked to immune and inflammatory dysregulation. Multi-component pharmacological interventions have been explored as complementary approaches for metabolic and immune modulation; however, their effects on DPN and related mechanisms remain incompletely understood.</p> Methods <p>A rat model of T2DM-associated peripheral neuropathy was established, and a multi-component pharmacological intervention (MPCI) was administered for 8 weeks. Peripheral nerve dysfunction was evaluated by motor and sensory nerve conduction velocities (MNCV and SNCV), behavioral outcomes, and histological/ultrastructural assessments. In parallel, spleen tissues were collected for transcriptomic profiling. RNA sequencing was performed to identify differentially expressed genes and immune-related pathways, and representative molecules involved in inflammatory regulation were further validated using western blotting and quantitative real-time PCR in sciatic nerve tissue.</p> Results <p>MPCI administration significantly ameliorated peripheral nerve dysfunction in T2DM rats, as evidenced by improved nerve conduction velocities and pathological features. Transcriptomic analysis of spleen tissue revealed that MPCI was associated with broad remodeling of diabetes-related immune and inflammatory gene programs. In parallel, sciatic nerve analyses showed attenuation of NF-κB/c-Jun–associated inflammatory signaling and modulation of inhibitory regulators at both the protein and mRNA levels.</p> Conclusion <p>These findings indicate that MPCI improves T2DM-associated DPN and is associated with splenic immune remodeling and attenuation of peripheral nerve inflammatory signaling, providing exploratory evidence for associations between splenic immune transcriptomic remodeling and peripheral nerve inflammatory signaling.</p> Ziya Yıldız 10.1371/journal.pone.0350933 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Ziya Yıldız</p> Purpose <p>The association between presbyphagia (age-related swallowing decline) and urinary incontinence (UI) remains poorly understood. This study therefore investigated the relationship between presbyphagia and both UI and incontinence-specific quality of life (I-QOL) in a distinct population of functionally independent healthy elderly in a nursing home.</p> Method <p>The presence of presbyphagia was determined in 73 participants in the nursing home using the 100 ml water swallowing test (100mlSwal) and the Eating Assessment Tool-10 (EAT-10) tests. UI was determined using the International Consultation on Incontinence Questionnaire Short (ICIQ-SF) and I-QOL was determined using the King’s Health Questionnaire (KHQ). The presence of presbyphagia, age and female gender confounding factors were analysed by multiple regression analysis. Multiple linear and binary logistic regression analyses were performed with presbyphagia, age, gender, and handgrip strength. Binary logistic regression was used to calculate odds ratios for UI presence.</p> Results <p>Presbyphagia was significantly associated with UI (p = .001). Individuals with presbyphagia had 7.47-fold higher odds of UI. Presbyphagia was also significantly associated with multiple I-QOL sub-domains, including incontinence impact, role limitation, physical limitation, and emotions (all p < .001). Male gender was associated with higher UI presence (OR=5.16), but not with UI severity. Age showed no significant associations with UI or I-QOL.</p> Conclusion <p>Presbyphagia is independently associated with UI presence and poorer I-QOL in nursing home residents. Male gender was associated with higher UI prevalence but similar severity and I-QOL to females. These findings suggest an independent association between presbyphagia and UI, thereby contributing to the formulation of hypotheses aimed at understanding the complex interactions between oral frailty and the urinary system. Further research is needed to elucidate underlying mechanisms and explore the potential clinical implications of this association.</p> Trial registration <p>ClinicalTrials.gov NCT06827561</p> Sidartawan Soegondo Gaga Irawan Nugraha Farid Kurniawan Ana Asmara Jannati Dicky L. Tahapary 10.1371/journal.pone.0350857 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Sidartawan Soegondo, Gaga Irawan Nugraha, Farid Kurniawan, Ana Asmara Jannati, Dicky L. Tahapary</p> Background <p>The Awareness, Care, and Treatment In Obesity maNagement Asia Pacific (ACTION APAC) online survey identified perceptions, attitudes, and barriers to effective obesity care among People with Obesity (PwO) and Health Care Professionals (HCP) across nine APAC countries. Here, we present findings from Indonesia.</p> Methods <p>This was a cross-sectional, observational, descriptive survey in PwO (≥18-year-old) with self-reported body mass index of ≥25 kg/m² and HCPs who spent ≥50% of their time in direct patient care. The survey was conducted between 20 April, 2022 to 11 May, 2022. The questionnaires were approved by the institutional review board as per local regulations.</p> Findings <p>A total of 1,000 PwO and 200 HCPs completed the survey. Notable differences were observed among PwO and HCPs in acknowledging obesity as a chronic disease (54% PwO and 90% HCPs), considering weight loss as PwO responsibility (91% PwO and 17% HCPs) and in agreeing that PwO were motivated to lose weight (76% PwO and 50% HCPs). Almost, two-thirds (67%) of PwO perceived themselves as either overweight or normal weight while only 30% discussed weight with their HCPs in the past five years. Financial concerns (45%) and assuming self-responsibility for weight loss (43%) were cited as the top reasons for not discussing. Only 53% HCPs initiated weight conversations, as they believed that PwO were either not motivated (55%) or not able to lose weight (51%). When discussed, most (68%) HCPs recommended lifestyle changes.</p> Interpretation <p>Our study identified gaps in understanding obesity as a disease and its management among PwO and HCPs, highlighting a need for increased awareness to improve obesity care in Indonesia.</p> Angelo Maria Sabatini 10.1371/journal.pone.0350827 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Angelo Maria Sabatini</p> This study applies symbolic time series analysis and Markov modeling to explore the phonological structure of <i>Evgenij Onegin</i>—as captured through a graphemic vowel/consonant (V/C) encoding—and one contemporary Italian translation. Using a binary encoding inspired by Markov’s original scheme, we construct minimalist probabilistic models that capture both local V/C dependencies and large–scale sequential patterns. A compact four-state Markov chain is shown to be descriptively accurate and generative, reproducing key features of the original sequences such as autocorrelation and memory depth. All findings are exploratory in nature and aim to highlight structural regularities while suggesting hypotheses about underlying narrative dynamics. The analysis reveals a marked asymmetry between the Russian and Italian texts: the original exhibits a gradual decline in memory depth, whereas the translation maintains a more uniform profile. To further investigate this divergence, we introduce phonological probes — short symbolic patterns that link surface structure to narrative-relevant cues. Tracked across the unfolding text, these probes reveal subtle connections between graphemic form and thematic development, particularly in the Russian original. By revisiting Markov’s original proposal of applying symbolic analysis to a literary text and pairing it with contemporary tools from computational statistics and data science, this study shows that even minimalist Markov models can support exploratory analysis of complex poetic material. When complemented by a coarse layer of linguistic annotation, such models provide a general framework for comparative poetics and demonstrate that stylized structural patterns remain accessible through simple representations grounded in linguistic form. Camilla Bjelland Joseph Sieka Veronica Millicent Dzomeku HaEun Lee Wahdae-Mai Harmon-Gray Emmanuel K. Nakua Jody R. Lori 10.1371/journal.pone.0350823 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Camilla Bjelland, Joseph Sieka, Veronica Millicent Dzomeku, HaEun Lee, Wahdae-Mai Harmon-Gray, Emmanuel K. Nakua, Jody R. Lori</p> Background <p>To address the delayed provision of obstetric emergency care in Ghana and Liberia, our team previously implemented a mobile obstetric emergency referral system (MORES) connecting rural health facilities (RHFs) and district hospitals through a South-South-North triangular collaboration. This secondary qualitative data analysis aimed to synthesize the perceived barriers and benefits associated with the adoption of MORES in Ghana and Liberia. To guide this cross-context synthesis, we utilized Rogers’ Diffusion of Innovation Theory.</p> Methods <p>The analysis included individual interviews conducted among 29 district hospital providers and 33 rural health facility (RHF) workers in Liberia. In Ghana, 11 midwives at a district hospital participated in a focus group discussion. The codes were developed utilizing an inductive process. Thematic analysis was utilized to compare adoption across countries through the Diffusion of Innovation Theory.</p> Findings <p>Four themes were identified from the healthcare workers in Ghana and Liberia: compatibility, relative advantage, resource barriers, and limited implementation. According to healthcare workers, MORES was compatible with everyday workflow and had significant relative advantage, contributing positively to adoption. Healthcare workers were able to prioritize patient conditions upon presentation with increased referral information. Resource barriers and the limited implementation across districts restricted widespread adoption of MORES. Healthcare workers in both countries cited inconsistent access to ambulances as a barrier to complete obstetric referrals and in Liberia, the need for financial support for data and network connectivity was referenced. There were nuances by country, within the four themes. In Ghana, providers used MORES to facilitate follow-up on patients who did not complete referrals, contributing to MORES’ relative advantage.</p> Conclusions <p>MORES has the potential to reduce obstetric emergency referral delays in Ghana and Liberia. If the resource barriers and limited implementation of MORES are addressed, healthcare workers may continue to adopt and use the MORES system. Policy makers can address referral delays through the scale up of MORES, a compatible intervention with great relative advantage.</p> Patrick Schmidt Klaus G. Nickel 10.1371/journal.pone.0350817 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Patrick Schmidt, Klaus G. Nickel</p> The raw materials people used for making stone tools may contain information about their territory, exchange routs or the selection criteria they employed during provisioning. In this study, we measure the mechanical properties of different tool-stones used by foragers living during the Middle Stone Age at Sibhudu Cave in South Africa. The site yielded a long and continuous sequence that saw transitions between different raw materials and tool forms. We evaluate the quality of these different stones for tool making and use, attempting to find correlations between selected raw materials and the tools made from them. We find that the raw materials used at Sibhudu have substantially different qualities, some being easy to flake but weak upon use, some being tough during stone knapping and resistant during use. Comparing these data with the appearance and disappearance of tool types throughout the Sibhudu sequence, we note that tool-stones requiring lower flaking forces were more often retouched than those requiring great forces. Elongated products, blades, were mostly made from materials with better fracture predictability, suggesting an understanding of the basic requirements for standardising the tool knapping process. Use-related qualities, such as resistance to dulling, appear to have been of lesser importance at Sibhudu. Our results suggest that the site’s occupants had a good understanding of the qualities of rocks for specific knapping processes. María Yehisiri Martín–Báez Candelaria de la Merced Díaz-González 10.1371/journal.pone.0350813 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by María Yehisiri Martín–Báez, Candelaria de la Merced Díaz-González</p> Introduction <p>Type 1 diabetes mellitus (T1DM) is the most common chronic endocrine disorder in childhood, making teachers key agents in ensuring a safe school environment. The main objective of this study was to evaluate the attitudes and prejudices of teachers at Public Early Childhood and Primary Education Centres (ECPECs) in the municipality of San Bartolomé de Tirajana (SBTGC), on the island of Gran Canaria (Canary Islands, Spain), regarding the care of students with T1DM.</p> Materials and methods <p>A descriptive cross-sectional study was conducted. The target population consisted of 264 teachers from seven ECPECs schools in the municipality of SBTGC, Gran Canaria. Data collection was carried out using the validated instrument <i>Teacher Negative Attitudes Index toward the Care of Students with Type 1 Diabetes Mellitus (INAPAD-18)</i>, which allowed for the evaluation of teachers’ attitudes and provided an answer to the study’s main objective. The research was approved by the Research and Drug Ethics Committee (CEIm) of Las Palmas.</p> Results <p>The final sample consisted of 126 participants, representing a participation rate of 47.72%, which did not reach the size required for statistical representativeness. A total of 15.87% of teachers reported currently having students diagnosed with T1DM. The mean number of years of experience working with students with this condition was 3.77 years [0–35years]. A marked gender disparity was observed, with a predominance of women (84.12%). The mean score obtained on the INAPAD-18 questionnaire was 47.02 (range: 18–90). In this instrument, lower scores indicate more favourable attitudes toward the care of students with T1DM. Although male participants showed more favourable attitudes compared to their women, this difference was not statistically significant (p > 0.05).</p> Discussion/Conclusion <p>The results indicate generally favourable attitudes, with moderately low INAPAD-18 scores. However, slight deficiencies were observed in teachers’ training and perception, consistent with findings from previous similar studies. The ECPEC schools <i>Juan Grande</i> and <i>Las Dunas</i> stood out for demonstrating the most positive attitudes. It is necessary for educational institutions to implement specific measures aimed at teacher training in order to improve attitudes and ensure appropriate attention to the needs of students with T1DM.</p> Xuejin Ye Sheng Chen Lin Guo Xiaohan Ma Lingling Wu Yiwen Li Ting Zhang Peng Jiang Hongjun Gao 10.1371/journal.pone.0350811 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Xuejin Ye, Sheng Chen, Lin Guo, Xiaohan Ma, Lingling Wu, Yiwen Li, Ting Zhang, Peng Jiang, Hongjun Gao</p> Background <p>Acute kidney injury (AKI) complicates the course of critical illness and carries high short- and long-term mortality rates; however, reliable early prognostic markers remain limited. The leuko-glycemic index (LGI), the product of white blood cell counts and blood glucose, has shown prognostic value in other acute conditions; however, its role in intensive care unit (ICU) patients with AKI remains unexplored.</p> Methods <p>In this multicenter retrospective cohort study, we analyzed 112,235 adult ICU admissions from the MIMIC-IV (n = 54,840) and eICU-CRD (n = 57,395) databases. Patients with multiple ICU stays and those aged <18 years were excluded. The LGI was calculated within 24 h of admission and stratified into quartiles (Q1–Q4). The primary endpoints were 30- and 90-day in-hospital mortality, and the secondary endpoint was overall in-hospital mortality. Kaplan–Meier survival curves, multivariable Cox proportional hazards models, and restricted cubic splines (RCS) assess the association between LGI and outcomes, with subgroup and interaction analyses for key comorbidities.</p> Results <p>Higher LGI quartiles were associated with progressively worse survival (p < 0.0001). In the fully adjusted models, each unit increase in LGI conferred a small but significant rise in 30-day (HR 1.01; 95% CI 1.01–1.01) and 90-day mortality (HR 1.01; 95% CI 1.01–1.01), while Q4 versus Q1 yielded HRs of 1.22 (95% CI 1.13–1.31) and 1.21 (95% CI 1.13–1.30), respectively. RCS demonstrated a nonlinear relationship, and the associations persisted across subgroups.</p> Conclusion <p>LGI may be an independent biomarker associated with short-term mortality in ICU patients with AKI. Its potential clinical relevance warrants further investigation and validation in larger cohorts.</p> Kazuhiro Omori Kohei Furukawa Masatoshi Usubuchi Tomofumi Hamada Tadahiko Shien Michihiro Yoshida Yuki Nakatsuka Katsuyuki Hotta Soichiro Ibaragi Shogo Takashiba 10.1371/journal.pone.0350803 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Kazuhiro Omori, Kohei Furukawa, Masatoshi Usubuchi, Tomofumi Hamada, Tadahiko Shien, Michihiro Yoshida, Yuki Nakatsuka, Katsuyuki Hotta, Soichiro Ibaragi, Shogo Takashiba</p> Oral mucositis is a frequent and debilitating adverse event observed in patients undergoing chemotherapy or radiotherapy. Current management strategies are limited in duration, require frequent application, and fail to address the mechanical irritation from teeth. A novel device, Soft Protector CPC, was developed to overcome these limitations. This multicenter, randomized, two-arm, open-label, confirmatory trial aims to evaluate the efficacy and safety of Soft Protector CPC in patients with breast cancer undergoing chemotherapy. A total of 154 participants will be randomly assigned in a 1:1 ratio to receive either oral care with Soft Protector CPC or oral care alone. The primary endpoint will be oral mucositis as assessed according to the Common Terminology Criteria for Adverse Events (CTCAE) v3.0 during the comparative treatment period. The secondary endpoints will include CTCAE v3.0 during the continuous treatment period, oral mucositis, pain (CTCAE v5.0), quality of life (Patient Reported Outcomes-CTCAE version 1.0 [PRO-CTCAE v1.0], the 15-item oral health questionnaire of the European Organization For Research And Treatment Of Cancer [EORTC QLQ-OH15], and the pain Numeric Rating Scale), onset and site of mucositis, completion of chemotherapy, use of rescue medications, technical feasibility, and patient preference. The safety endpoints will include adverse events, device malfunction, and laboratory tests. This trial is expected to establish the clinical utility of the Soft Protector CPC for the prevention and management of oral mucositis, with the potential to improve the patients’ quality of life and adherence to cancer therapy. This study was approved by the Clinical Research Review Board and registered with the Japan Registry of Clinical Trials, jRCTs062250005, on April 18, 2025. Yanan Zhu Qian Wang Huiying Jia Gaiyun Zhao Yunpeng Lü Xinhong Zhang Haijing Dong 10.1371/journal.pone.0350800 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Yanan Zhu, Qian Wang, Huiying Jia, Gaiyun Zhao, Yunpeng Lü, Xinhong Zhang, Haijing Dong</p> This randomized controlled trial is aimed at evaluating whether external fixation of the urinary catheter to the body surface represents a low-value nursing intervention for patients undergoing transurethral resection of the prostate (TURP). A total of 208 patients who received indwelling urinary catheters after TURP in a tertiary hospital in Qingdao, China between June 2024 and May 2025 were randomly assigned to one of two groups: a nonexternal fixation group (n = 103) and an external body surface fixation group (n = 105). A between-group comparison of outcomes included postoperative hematuria, incidence of catheter-associated urinary tract infection (CAUTI), unplanned catheter removal, occurrence of urinary catheter-related meatal pressure injury (UCR-MPI), and associated economic costs. No significant differences were observed between the two groups in terms of postoperative hematuria or CAUTI incidence (P > 0.05). Unplanned catheter removal did not occur in either group. However, UCR-MPI occurred significantly more frequently in the external fixation group (9 patients) than it did in the nonexternal fixation group (1 patient) (P < 0.05). Additionally, the external fixation group incurred higher costs for personnel and consumables. External fixation of the urinary catheter to the body surface after TURP is associated with increased economic costs, reduced patient comfort, and a higher incidence of UCR-MPI, which indicates that it constitutes a low-value nursing practice. Nonexternal fixation appears to be a safe and effective alternative for post-TURP patients undergoing early mobilization. The PLOS One Editors 10.1371/journal.pone.0350792 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by The PLOS One Editors </p> Sameh S. M. Soliman Tasneem B. Alhamidi Shifaa Abdin Ahmed M. Almehdi Mohammad H. Semreen Razan B. Alhumaidi Sarra B. Shakartalla Mohamed Haider Mohamed I. Husseiny Hany A. Omar 10.1371/journal.pone.0350791 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Sameh S. M. Soliman, Tasneem B. Alhamidi, Shifaa Abdin, Ahmed M. Almehdi, Mohammad H. Semreen, Razan B. Alhumaidi, Sarra B. Shakartalla, Mohamed Haider, Mohamed I. Husseiny, Hany A. Omar</p> Eui Jun Lee Jae Yun Jung Do Kyun Kim Joong Wan Park Young Ho Kwak 10.1371/journal.pone.0350770 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Eui Jun Lee, Jae Yun Jung, Do Kyun Kim, Joong Wan Park, Young Ho Kwak</p> Pediatric emergency triage is a safety-critical task, and recent studies have explored whether artificial intelligence, including language models, can support triage decision-making; however, evidence on fine-tuned open-weight language models remains limited. We conducted a retrospective benchmark study using de-identified triage records from a tertiary pediatric emergency department in Korea collected from January 2020 to April 2025. After exclusions, 74,170 encounters were included. Each encounter was reconstructed into a case-level text sequence from triage-time structured variables and nurse-authored narratives. Qwen3-8B-Base was fine-tuned with Low-Rank Adaptation and Group Relative Policy Optimization using a safety-oriented reward design and was compared with a structured-data XGBoost model on a common evaluable test subset of 14,832 encounters. The fine-tuned model achieved an accuracy of 58.60%, a macro-F1 score of 0.417, and a quadratic weighted kappa of 0.535. Within-one-level agreement was 97.13%, and strict under-triage, defined as true Korean Triage and Acuity Scale levels 1 or 2 predicted as levels 4 or 5, occurred in 0.65% of cases. The structured-data comparator showed higher overall performance, with an accuracy of 69.40%, a macro-F1 score of 0.618, and a quadratic weighted kappa of 0.651. However, the fine-tuned model showed fewer extreme errors and lower strict under-triage in selected high-acuity groups, at the cost of higher over-triage. In this real-world pediatric benchmark, the fine-tuned language model did not surpass the structured-data comparator in overall performance but showed a distinct safety-oriented error profile. These findings support its potential role as a decision-support aid for human triage review rather than an autonomous triage system. External and prospective validation will be necessary before clinical implementation. The PLOS One Editors 10.1371/journal.pone.0350703 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by The PLOS One Editors </p> Yang Cheng Jaekuk Lee Florence Martin William Rand 10.1371/journal.pone.0350661 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Yang Cheng, Jaekuk Lee, Florence Martin, William Rand</p> Artificial intelligence (AI) tools are increasingly embedded in higher education, yet limited research has examined how sustained AI usage intentions in AI-supported learning environments are associated with learning motivation and longer-term educational development. Treating AI use as a course-embedded learning experience rather than a discrete adoption decision, this study investigates how students’ perceptions of AI-supported learning are associated with continued usage intentions and how such intentions subsequently relate to academic interest and career-related intentions. Grounded in post-adoption technology continuance research, motivation theory, and Social Cognitive Career Theory, we develop and test a structural model linking perceived AI enhancement, interactivity, fun, and coolness to continued AI usage intentions, academic interest, and career-choice intentions. Survey data were collected from undergraduate students enrolled in business analytics courses and analyzed using structural equation modeling. The results show that perceived enhancement, interaction, fun, and coolness are each significantly associated with continued AI usage intentions in coursework. Continued AI usage intentions, in turn, are positively related to academic interest in business analytics, and academic interest statistically mediates the relationship between continued AI usage intentions and career-choice intentions. However, indirect effects from these antecedent variables to academic interest through continued AI usage intentions were not statistically significant. By conceptualizing continued AI usage intentions as an ongoing learning process that is linked to how students engage with disciplinary knowledge over time, this study advances understanding of the developmental role of AI-supported instruction in higher education. The findings contribute to research on technology, knowledge, and learning, and offer practical implications for designing AI-supported learning environments that foster sustained usage intentions, interest development, and future-oriented educational pathways. Amir Hossin Moradpour Dehnavi Abolfazl Alavi Amin Beigzadeh Ali Reza Yusefi 10.1371/journal.pone.0350651 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Amir Hossin Moradpour Dehnavi, Abolfazl Alavi, Amin Beigzadeh, Ali Reza Yusefi</p> Religious ceremonies can play a pivotal role in shaping ethical values among medical sciences students. However, participation in such ceremonies is often influenced by multiple academic, social, and cultural factors. This study aimed to explore the perceived value of religious ceremonies and the barriers affecting student participation in these practices within the context of their ethical development. This qualitative study was conducted at Sirjan School of Medical Sciences in southern Iran from March to July 2025, using a latent content analysis approach grounded in the interpretivist paradigm. Semi-structured, in-depth interviews were conducted with 33 students from diverse academic programs and backgrounds. Data were analyzed inductively based on Graneheim and Lundman’s framework using MAXQDA 2022 software. Trustworthiness was ensured through Lincoln and Guba’s criteria including credibility, confirmability, dependability, and transferability. Seven main themes and twenty- four subthemes emerged. The themes included: (1) Time and Academic Pressure (e.g., course overload, exam clashes); (2) Perceived Irrelevance (e.g., disconnection from professional goals); (3) Cultural and Personal Beliefs (e.g., secular upbringing, concerns about religious imposition); (4) Social Dynamics (e.g., fear of judgment, peer influence); (5) Institutional Support (e.g., lack of promotion, insufficient facilities); (6) Perceived Ethical Value (e.g., development of professionalism and compassion); and (7) Emotional and Community Benefits (e.g., stress relief, sense of belonging, spiritual recharge). While religious ceremonies hold perceived ethical and emotional value for many students, numerous academic, institutional, and cultural barriers limit participation. Integrating religious practices into educational contexts in a more inclusive, flexible, and voluntary manner could enhance students’ moral development without alienating diverse beliefs. Jung-Bin Park Youmin Shin Jihun Kim Yoon Jung Kim Seung-Bo Lee Eun-Hee Kim Joo Whan Kim Seung-Ki Kim Hee-Soo Kim Young-Gon Kim 10.1371/journal.pone.0350637 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Jung-Bin Park, Youmin Shin, Jihun Kim, Yoon Jung Kim, Seung-Bo Lee, Eun-Hee Kim, Joo Whan Kim, Seung-Ki Kim, Hee-Soo Kim, Young-Gon Kim</p> Background <p>Postoperative cerebrovascular events, including transient ischemic attacks, infarctions, and hemorrhages, remain a significant concern in pediatric patients with Moyamoya disease (MMD)undergoing surgical revascularization. This study aimed to develop an explainable deep learning-based classification model using intraoperative arterial blood pressure (ABP) waveform analysis for postoperative cerebrovascular events in pediatric patients undergoing surgery for MMD, with exploratory analysis of associated waveform-derived physiologic features.</p> Methods <p>This retrospective study included 181 pediatric patients (≤18 years) who underwent revascularization surgery for MMD, with an independent temporal holdout cohort of 79 patients reserved for validation. ABP signals were preprocessed using detrending, pulse segmentation, and normalization, then converted into image representations for deep learning classification. Various convolutional neural network (CNN) models, including ResNet50, ResNet34, DenseNet121, VGG16, and VGG19, were evaluated against Vision Transformer (ViT) architectures. Multiple image transformation methods were tested, and Grad-CAM analysis and statistical comparisons of waveform-derived physiologic features were conducted between patients with and without postoperative cerebrovascular events.</p> Results <p>The optimal model configuration achieved the best performance using raw pulse waveforms with three consecutive pulses per image. CNN-based models outperformed ViT-based models, with the highest internal classification performance observed using raw pulse waveforms (AUROC = 0.772, SD = 0.070).In the independent temporal validation cohort, the model achieved an AUROC of 0.738 ± 0.011 at the patient level. Grad-CAM visualization highlighted the diastolic runoff phase as a region of interest for classification. Four waveform-derived features related to arterial compliance were significantly associated with postoperative cerebrovascular events (p < 0.05).</p> Conclusions <p>In this study, CNN-based deep learning models demonstrated the feasibility of predicting postoperative cerebrovascular events from intraoperative ABP waveforms, with diastolic runoff dynamics emerging as a potentially relevant physiologic pattern. These findings are exploratory and require prospective multi-center validation before clinical application.</p> Nosayba Al-Damook Molham Sakkal Mostafa Khair Walaa K. Mousa Rose Ghemrawi 10.1371/journal.pone.0350628 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Nosayba Al-Damook, Molham Sakkal, Mostafa Khair, Walaa K. Mousa, Rose Ghemrawi</p> Metabolic reprogramming is central to cancer biology, enabling tumor cells to sustain rapid proliferation, resist stress, and adapt to therapy. However, these alterations are highly heterogeneous across cancer types, and current treatments rarely exploit subtype-specific metabolic vulnerabilities. To address this gap, we developed a unified bioinformatics framework that integrates transcriptomic profiling (UALCAN), drug–gene interactions (DGIdb), gene–disease associations (Open Targets), pathway enrichment (Enrichr), and protein–protein interaction networks (STRING/Cytoscape). This pipeline was applied to lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LSCC), breast cancer (BRCA), and metastatic breast tumors (MET500) to uncover cancer type–specific metabolic programs and prioritize translational targets. Our analysis revealed distinct signatures: LUAD showed glycolytic activation, LSCC coupled glycolysis with oxidative phosphorylation, BRCA favored anabolic and lipogenic pathways, and MET500 tumors adopted stress-adaptive states with elevated antioxidant and autophagy programs. Integration of pharmacological evidence highlighted clinically actionable interactions between metabolic genes and FDA-approved drugs, including ASNS–asparaginase, DHODH–teriflunomide, and G6PD–rasburicase. Gene–disease associations further prioritized G6PD, SLC2A1, and TK1 as robust targets strongly linked to lung and breast cancers. Pathway enrichment pinpointed the pentose phosphate pathway, pyrimidine metabolism, and glutathione metabolism as conserved axes sustaining tumor survival, while network analysis positioned the G6PD–PGD hub as a central metabolic node connecting glucose uptake, redox balance, and nucleotide biosynthesis. To place these bioinformatics-derived findings within a functional and clinical context, we complemented the computational analyses with patient survival assessment, clinical trial screening, and targeted literature appraisal. Survival analysis demonstrated cancer type–specific prognostic relevance for selected metabolic genes, while clinical and literature-based screening revealed both ongoing translational efforts and substantial gaps between computational target prioritization and experimental or clinical validation. This integrative analysis shows that cancer metabolism is altered in subtype-specific ways that can be systematically mapped to reveal potential therapeutic targets. By linking transcriptomic evidence with drug–gene interactions and clinical context, this framework provides a scalable approach for cancer metabolism research and supports the prioritization of pathways with potential translational relevance. Ika Saptarini Sri Masyeni Alida Roswita Harahap Astuti Giantini Pringgodigdo Nugroho Agus Handito Harimat Hendarwan Adityo Susilo Sotianingsih Haryanto Desi Fitriani R. Tedjo Sasmono Erni Juwita Nelwan 10.1371/journal.pone.0350610 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Ika Saptarini, Sri Masyeni, Alida Roswita Harahap, Astuti Giantini, Pringgodigdo Nugroho, Agus Handito, Harimat Hendarwan, Adityo Susilo, Sotianingsih Haryanto, Desi Fitriani, R. Tedjo Sasmono, Erni Juwita Nelwan</p> Background <p>Dengue virus (DENV) infection can manifest as dengue fever (DF) or dengue hemorrhagic fever (DHF), although DHF often becomes clinically apparent around defervescence. How complement components and other immune responses evolve over the course of illness from the febrile to recovery phase remains incompletely defined. This study characterized circulating complement activation and immune mediators in DF and DHF using paired febrile and early-recovery samples.</p> Methods <p>We conducted a multicenter prospective cohort study at five hospitals in Indonesia between November 2024 and October 2025. Patients with laboratory-confirmed dengue were classified as DF or DHF. Plasma concentrations of PTX3, C5a, IL-6, IL-10, IL-8, and CXCL10 were quantified in paired febrile and early recovery phase samples. Between-group differences, within-patient changes between the two time points, and correlations among immune mediators were assessed using appropriate statistical methods.</p> Results <p>We included 110 confirmed dengue cases in the analysis. PTX3 and IL-10 levels were significantly higher in DHF than in DF during early recovery, whereas no mediator differed significantly between severity groups during the febrile phase. Across phases, C5a increased significantly from febrile to early recovery in DHF but not in DF, whereas PTX3 decreased significantly in DF but not in DHF. Correlations among mediators were generally weak to moderate, with a reproducible PTX3–IL-10–CXCL10 module observed across both phases.</p> Conclusion <p>The measured mediators did not distinguish DF from DHF during the febrile phase, but differences emerged in early recovery, with higher PTX3 and IL-10 in DHF. Across phases, C5a increased significantly from febrile to early recovery in DHF, whereas PTX3 decreased significantly only in DF. A PTX3–IL-10–CXCL10 module was observed at both time points. Together, these patterns suggest that within-patient changes around defervescence or in the early recovery may be informative and warrant evaluation in larger, prospectively timed cohorts.</p> Xiaodong Zhang Lan Zou Dunfu Zhang Bangtao Yao Junge Chen Tianfeng Wei Zhouping Fu Xin Chang Lijuan Chen Yan Geng 10.1371/journal.pone.0350563 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Xiaodong Zhang, Lan Zou, Dunfu Zhang, Bangtao Yao, Junge Chen, Tianfeng Wei, Zhouping Fu, Xin Chang, Lijuan Chen, Yan Geng</p> Background <p>Forearm radial artery occlusion (RAO) is a common complication after transradial coronary procedures. Traditional patent hemostasis, relying on operator-dependent assessment, results in labor-intensive processes and inconsistent RAO rates.</p> Methods <p>This is a single-center, prospective, randomized, open-label, parallel-group superiority trial. We plan to enroll 818 patients scheduled for transradial coronary angiography. Participants will be randomly assigned (1:1) to either a novel balloon pressure monitoring system (integrating high-precision digital manometry with physiologically-phased decompression) or traditional patent hemostasis. The primary outcome is the incidence of ultrasound-confirmed forearm RAO at 24 hours post-procedure. Key secondary outcomes include rates of access-site vascular complications and bleeding events, as well as objective metrics of hemostasis efficiency. Recruitment Status: Recruitment commenced in September 2024 and is ongoing; the target sample size is anticipated to be reached by May 2026. Analysis will follow the intention-to-treat principle.</p> Results/ Trial Status <p>As a protocol paper, no results are reported. The trial is currently in the recruitment phase.</p> Conclusions <p>This trial will provide the first large-scale randomized evidence on whether digital manometry-guided compression reduces RAO, potentially bridging the efficacy-effectiveness gap between optimized research protocols and routine practice.</p> Trial registration <p>The trial was registered with the Chinese Clinical Trial Registry (ChiCTR) in August 2024, under the registration number ChiCTR2400088258.</p> Alaattin Ozen Ilknur Harmankaya Canan Ozdemır Mehmet Halıcı Oya Coskun Ekin Baran Guler Ozge Atılla Sumeyra Can 10.1371/journal.pone.0350496 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Alaattin Ozen, Ilknur Harmankaya, Canan Ozdemır, Mehmet Halıcı, Oya Coskun, Ekin Baran Guler, Ozge Atılla, Sumeyra Can</p> Background <p>Radiotherapy (RT) is a cornerstone of cancer management, substantially improving local tumor control and overall survival. However, a subset of patients fail to complete the prescribed RT course. Identifying the factors associated with treatment termination is essential to enhancing cancer care delivery and patient outcomes.</p> Methods <p>This retrospective, single-center analysis included 10039 patients who underwent RT between January 2020 and December 2024. Patients who terminated treatment before completion were identified in institutional RT records. Demographic and clinical characteristics, treatment intent, and reasons for termination were primarily evaluated using descriptive statistical analyses, with exploratory comparative analyses performed between curative- and palliative-intent groups.</p> Results <p>Between 01/01/2020 and 12/31/2024, RT was terminated in 297/10039 patients (2.96%). The most leading causes of termination was deterioration in performance status (143 patients, 48.1%). Of these, 170 patients (57.2%) had been treated with palliative intent. Lung cancer (96 patients, 32.3%) was the most frequent primary diagnosis, while the brain (92 patients, 31%) was the most commonly irradiated site. The median number of prescribed fractions was 13 (range: 2–44), and patients completed a median of 51.6% (range: 5–93%) of these fractions before termination. The most common reason was deterioration in performance status (48.1%). Treatment termination rates were significantly higher in palliative cases compared with curative cases (6.13% [170/2,772] vs. 1.75% [127/7,267]; χ² = 134.4; p < 0.001). Relative risk analysis indicated that palliative-intent patients had a 3.50-fold higher risk of treatment termination. Performance deterioration was more frequent in the palliative group (72.4% vs. 27.3%; p < 0.001). Treatment-related toxicity (grade III-IV) occurred predominantly in curative-intent patients (88.9% vs. 11.1%; p < 0.001).</p> Conclusion <p>Most RT terminations occurred among patients with poor performance status and advanced disease. These findings suggest that multidisciplinary supportive care may be relevant and should be evaluated in future prospective studies.</p> Laura Bravo-Merodio Jackie A. Olley-Williams Dominic Russ Georgios Gkoutos Meadhbh B. Brosnan Mark A. Bellgrove Magdalena Chechlacz 10.1371/journal.pone.0350452 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Laura Bravo-Merodio, Jackie A. Olley-Williams, Dominic Russ, Georgios Gkoutos, Meadhbh B. Brosnan, Mark A. Bellgrove, Magdalena Chechlacz</p> Education is often used as a surrogate measure of so called cognitive reserve (CR) benefiting cognitive functioning in later years. In line with Robertson’s theory we tested here a hypothesis that education acting on the noradrenergic system strengthen the right fronto-parietal networks to facilitate CR and maintain cognition throughout the lifetime. We used machine learning and mediation analysis to model interactions between neurobiological features (genetic variants in noradrenergic signalling, structural and functional fronto-parietal connectivity) and education (proxy of CR) on cognitive outcomes (measured here by general cognitive ability score calculated based on performance across a battery of cognitive tests) in the UK Biobank cohort. We show that: (1) interactions between education and neurobiological variables better explain cognitive outcomes than either factor alone; (2) among the neurobiological features selected using variable importance testing, measures of right fronto-parietal connectivity are the strongest mediators of the association between education and cognitive outcomes. Our findings offer novel insights into neurobiological basis of CR by pointing to between-networks connectivity, representing connections linking the default mode network with the right fronto-parietal network as the key facilitator of CR. Dong Li Liuyong He 10.1371/journal.pone.0350435 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Dong Li, Liuyong He</p> Lightweight, high-strength alloys are increasingly demanded in sports equipment. Magnesium (Mg) alloys are attractive due to their low density and high specific strength. This study systematically investigates the grain size–dependent high-cycle fatigue (HCF) behavior of AZ81 Mg alloy with comparable basal textures. The fine-grained (FG, ~ 8 μm) sample exhibits significantly improved mechanical performance compared with the coarse-grained (CG, ~ 62 μm) counterpart. The yield strength increases from 134.2 MPa to 164.5 MPa (~22.6%), and the ultimate tensile strength rises from 231.7 MPa to 283.7 MPa (~22%), while maintaining comparable ductility. More importantly, the fatigue strength at 10⁶ cycles increases from 80 MPa to 110 MPa, representing a 37.5% enhancement. Microstructural analyses reveal that grain refinement suppresses extension twinning and persistent slip band formation, while promoting the activation of <c + a> and non-basal <a> dislocations. The FG microstructure also contains finer and more uniformly distributed Mg₁₇Al₁₂ precipitates, facilitating Orowan strengthening. These combined effects reduce strain localization and delay fatigue crack initiation. The findings clarify the mechanistic origin of grain refinement–induced fatigue enhancement and provide guidance for the design of Mg alloys in weight-critical sports applications. Tri Nugraha Susilawati Herry Susanto Oanh Kieu Nguyet Pham Federika Kondororik Vivian Nanny Lia Dewi Hamdiah Ahmar Noviyati Rahardjo Putri Rogan Lee Minh Cuong Duong 10.1371/journal.pone.0350434 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Tri Nugraha Susilawati, Herry Susanto, Oanh Kieu Nguyet Pham, Federika Kondororik, Vivian Nanny Lia Dewi, Hamdiah Ahmar, Noviyati Rahardjo Putri, Rogan Lee, Minh Cuong Duong</p> Objectives <p>Malaria remains endemic in Indonesia, with high transmission rates observed in the Papua region. Routine surveillance data are essential to inform service delivery and optimize case management. This cross-sectional study examined malaria cases in Sorong City in 2024 reported through Indonesia’s national surveillance system to describe malaria burden across healthcare facilities, diagnostic and treatment practices, and predictors of hospital attendance and hospitalization.</p> Methods <p>All laboratory-confirmed malaria cases were analyzed, including demographics, malaria diagnosis, disease severity, treatment received, and hospitalization data. Descriptive statistics and logistic regression were used to identify determinants of hospital attendance and inpatient admission.</p> Results <p>Among 3,953 malaria cases, most patients were ≥15 years old (65.9%), males (59.4%), Papuan (54.2%), students (36.6%), and living in highly endemic areas (78%). Community health centers reported most cases (61.7%). Microscopy was the primary diagnostic tool (70.1%). <i>Plasmodium vivax</i> was the predominant species (65.5%), and nearly all infections were uncomplicated (99.9%). Notably, nearly 21% of patients received non-standard antimalarial regimens. Predictors of hospital attendance include older age (aOR: 1.02; 95% CI: 1.00–1.02; p = 0.001), non-Papuans ethnicity (aOR: 1.77; 95%CI: 1.51–2.07; p = 0.001), being housewife (aOR: 1.57; 95%CI: 1.02–2.42; p = 0.041) or student (aOR: 1.56; 95%CI: 1.05–2.31; p = 0.029), and living in moderate- (aOR: 2.01; 95%CI: 1.69–2.40; p = 0.001) or low- (aOR: 4.57; 95%CI: 2.01–10.39; p = 0.001) endemicity areas. Children <15 years were more likely to be hospitalized (aOR 1.9; 95% CI 1.18–3.06; p = 0.009).</p> Conclusions <p>Malaria remains a substantial public health burden, dominated by <i>P. vivax</i>, with community health centers serving as primary care providers. Older individuals were more likely to attend hospital, while younger children had a higher likelihood of hospitalization once diagnosed. Strengthening community-based services, promoting early treatment-seeking among children, and ensuring consistent adherence to national treatment guidelines are critical to reducing severe disease and hospital burden.</p> Yüksel Erkin Erkan Ozduran İlhan Celil Özbek Volkan Hancı 10.1371/journal.pone.0350402 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Yüksel Erkin, Erkan Ozduran, İlhan Celil Özbek, Volkan Hancı</p> Patients seeking information about Myofascial Pain Syndrome (MPS), which affects a large segment of the population, are increasingly turning to AI-based chatbots as an alternative to traditional methods. However, the medical accuracy of the content offered by these digital platforms, as well as its suitability to the “grade 6 reading level” standard, which determines its comprehensibility by patients, is a critical point of uncertainty. This study aims to fill this significant gap in the literature by systematically comparing MPS content generated by different AI models using readability indices, reliability, and quality metrics. The 18 most relevant keywords, derived from 25 keywords identified via Google Trends data, were queried using ChatGPT (GPT-5.2), Gemini 3 Flash, and Perplexity (Sonar-4 Large) models. The readability of the generated responses was analyzed using six different indices (FRES, FKGL, GFOG, CLI, ARI, SMOG), while content quality was assessed using GQS and EQIP scales, and reliability using DISCERN and JAMA scales by two independent observers. The responses generated by all AI models examined were found to be statistically significantly more complex than the suggested 6th-grade reading level (p < 0.001). In inter-model comparisons, ChatGPT exhibited the easiest readability [lowest linguistic difficulty] scores, while Perplexity scored significantly higher than both ChatGPT and Gemini in content quality and reliability metrics (JAMA, DISCERN, GQS, EQIP) (p < 0.05). Correlation analysis revealed a strong and positive relationship between quality and reliability parameters. Artificial intelligence platforms have been observed to exhibit high potential in the production of medical information. However, linguistic barriers exceeding sixth-grade reading comprehension, along with reliability limitations of current models, prevent them from replacing professional medical consultation. Perplexity has been found superior in terms of academic quality, while ChatGPT has been found superior in terms of readability. Nevertheless, positioning these systems as complementary “secondary consultation mechanisms” supporting physician oversight in clinical decision-making processes is critically important for patient safety. Tommy Dharmawan Deandra Ardya Sutoyo Fona Qorina Nico Gamalliel Mohammad Kurniawan Dian Kusuma Ahmad Fuady 10.1371/journal.pone.0350393 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Tommy Dharmawan, Deandra Ardya Sutoyo, Fona Qorina, Nico Gamalliel, Mohammad Kurniawan, Dian Kusuma, Ahmad Fuady</p> High-quality health research is essential for evidence-based policymaking and health system strengthening. Indonesia has undergone major reforms in its health research governance. However, the country’s National Health Research System (NHRS) remains insufficiently mapped. This study aimed to assess the current status of Indonesia’s NHRS using the WHO framework, which includes four domains: governance, financing, creating and sustaining resources, and producing and using research. A qualitative approach was employed, combining an expert panel discussion and key informant interviews with 13 participants consisting of national and subnational stakeholders from government agencies, research organisations, and universities from May to December 2024. Data were analysed using the Framework Method guided by the NHRS framework and supplemented by the WHO Questionnaire on Country Resources for Health Research. This study found that, despite progress in Indonesia’s NHRS, weak governance, particularly poor coordination between national and subnational levels, remains the main challenge. Overall, the system is still fragmented, even though formal structures and institutions are in place. Governance is characterised by a highly centralised, top-down approach to agenda setting, with limited engagement of local institutions. Research financing is mainly programmatic and proposal-based, aligned with national priorities, but is constrained by limited sustainable domestic funding and unequal access to funding. In terms of resources, advanced research infrastructure and growing international collaboration indicate national commitment to health research; however, mismatches between infrastructure and human resource capacity persist. Finally, although research production and utilisation focus on measurable outputs and are supported by mechanisms for evidence use, effective pathways for translating research into policy and practice remain limited. Improving Indonesia’s health research system calls for an integrated national research agenda, well-defined institutional roles, and streamlined coordination between national and regional levels. Victor C.W. Tam Nelson C.Y. Yeung Anthony Wai Leung Kwok 10.1371/journal.pone.0350392 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Victor C.W. Tam, Nelson C.Y. Yeung, Anthony Wai Leung Kwok</p> Background <p>The ‘Intention-focused model’ is advocated for educating bystanders in Basic Life Support (BLS), consisting of cardiopulmonary resuscitation and automated external defibrillation. Although previous International Consensus on Cardiopulmonary Resuscitation statements have summarised barriers at the scene of out-of-hospital cardiac arrest, few studies have investigated how barriers perceived by trained laypeople affect their intention to deliver BLS (BLS intention) and the underlying mechanisms, especially during the COVID-19 pandemic when global fear of infection was persistently heightened. This study examines the relationship between perceived barriers (PB) and the Theory of Planned Behaviour (TPB) constructs, i.e., attitude, subjective norms (SN), perceived behavioural control (PBC) and BLS intention, as well as the role of concern about infection.</p> Methods <p>A cross-sectional online survey of 678 trained adult laypeople was conducted in 2022 using convenience sampling. Structural equation modelling was used to analyze the relationship between PB subscales, BLS intention, attitude, SN and PBC. Multigroup analysis was used to examine the potential moderating effect of concern about infection.</p> Results <p>A split-construct model consisting of two barrier subscales showed better model fit (χ2/df = 3.224, CFI = 0.966, RMSEA = 0.057) than the lumped-construct model (χ2/df = 3.732, CFI = 0.953, RMSEA = 0.064). Performance-related barriers had a strong significant association with PBC (β = −0.74, P < 0.001), while cultural barriers were significantly associated with attitude (β = −0.34, P < 0.001), and SN (<i>β</i> = −0.16, <i>P</i> < 0.001) were significant, but not for PBC (<i>β</i> = 0.01, <i>P</i> = 0.905). Attitude, SN, and PBC had significant effects on BLS intention (<i>β</i> = 0.14–0.56, <i>Ps</i> < 0.001). Multigroup analysis showed that concern about infection significantly moderated the relationship between cultural barriers and attitude (Low concern: <i>β</i> = −0.474, <i>P</i> < 0.001; High concern: <i>β</i> = −0.326, <i>P</i> < 0.001; Δχ²(1)=6.319, <i>P</i> = 0.012).</p> Conclusions <p>This study offers empirical evidence for integrating perceived barriers into an intention-focused model to predict laypersons’ willingness to perform resuscitation. Future research should focus on addressing priority concerns and transforming them into heightened willingness through enhancing positive attitudes, SN and PBC.</p> Huipin Lin Xiaoying Chen Lei Zhang Zhengyi Bao Sai Tang 10.1371/journal.pone.0350331 2026-06-04T14:00:00Z 2026-06-04T14:00:00Z <p>by Huipin Lin, Xiaoying Chen, Lei Zhang, Zhengyi Bao, Sai Tang</p> In recent years, power batteries have been widely used in electric vehicles, and the evaluation of state of charge (SOC) is an important parameter in battery management systems. Therefore, in this paper, we propose a time-series convolutional network that employs extended convolution and residual concatenation to efficiently process time-series data with parallelism and flexibility, and combines it with Unscented Kalman Filter (UKF) to further improve the accuracy and reduce the output fluctuation, so as to estimate the state of charge of lithium-ion batteries. We conducted experiments using the University of Maryland’s Dynamic Stress Test (DST), US06 test, and Federal Urban Driving Scheme (FUDS) datasets, and compared the proposed method with Convolutional Neural Networks (CNNs), Long and Short-Term Memory Networks (LSTMs), and Gated Recurrent Units (GRUs). Experimental results demonstrate that the proposed framework achieves superior estimation accuracy and robustness. Specifically, the proposed method achieves mean absolute error (MAE) values of 1.305%, 1.470%, and 1.015% under the DST, US06, and FUDS conditions, respectively, with an average Root Mean Square Error (RMSE) of 1.566% and a MAE below 1.263%. Compared with existing deep learning models, the proposed method reduces the SOC estimation error by approximately 7.6%–39.6% under different driving conditions. These results verify the effectiveness and robustness of the proposed hybrid SOC estimation framework.