PLOS ONE Alerts: New Articles

A Transgenic mouse tolerant to syngeneic cancer cells expressing truncated human epidermal growth factor receptor

2026-08-07T14:00:00Z

by Theresa Barberi, Rahila Khuroo, Alan D. Friedman

Epidermal Growth Factor Receptor (EGFR) is often present on the cell surface of a wide variety human malignancies, including non-small-cell lung cancer (NSCLC), glioblastoma (GBM), pancreatic ductal carcinoma (PDC), and castration-resistant prostate cancer (CRPC). Efforts to optimize immunotherapies targeting EGFR are limited by murine intolerance of human EGFR. To overcome this obstacle, we developed C57BL/6 mice in which a truncated variant of human EGFR (hEGFRt), lacking the ligand binding domain and cytoplasmic domain, is expressed from the CAG regulatory elements comprised of the CMV enhancer, β-actin promoter, and β-globin poly-adenylation signals. Cetuximab, a high-affinity, clinically available anti-human EGFR antibody, retains affinity for hEGFRt. The hEGFRt cDNA in the CAG-hEGFRt transgene is flanked by loxP sites to enable its excision thereby reducing interaction of hEGFRt-directed immunotherapies with normal tissues. The CAG-hEGFRt(f/f) transgene is abundantly expressed in hematopoietic lymphoid and myeloid cells, with low-level expression evident also in non-hematopoietic liver, lung, kidney, and brain. Mx1-Cre-mediated transgene excision in adult mice reduces hEGFRt ~ 5-fold in blood mononuclear cells. CAG-hEGFRt(f/f) adult mice are tolerant of syngeneic NSCLC, GBM, prostate, and PDC lines expressing hEGFRt. These mice retain hEGFRt tolerance after transgene deletion. CAG-hEGFRt(f/f) mice provide a new and important tool for the development of immunotherapies targeting hEGFR.

Influence of pelleting and β-mannanase on nutrient digestibility and metabolizable energy of DDGS, copra meal, palm kernel meal, and jatropha meal in precision-fed Single Comb White Leghorn roosters

2026-08-07T14:00:00Z

by Bounmy Keohavong, Musabbir Ahammed, Jong Suh Shin, Lohakare Jayant, Sang Jip Ohh

This study evaluated the effects of pelleting and β-mannanase supplementation on nutrient digestibility and metabolizable energy of four alternative feed ingredients distillers dried grains with solubles (DDGS), copra meal, palm kernel meal (PKM), and jatropha meal (JM) using precision-fed Single Comb White Leghorn roosters. Two independent precision-fed rooster assays were conducted. In Experiment 1, each ingredient was offered in mash form or as pellets produced under controlled conditions (<65 °C) to minimize heat-induced nutrient damage. In Experiment 2, mash samples were supplemented with β-mannanase (0.25% as-fed basis). Apparent dry matter digestibility, nitrogen retention, and metabolizable energy values, including apparent metabolizable energy (AME), nitrogen-corrected AME (AMEn), true metabolizable energy (TME), and nitrogen-corrected TME (TMEn), were determined. Pelleting improved dry matter digestibility, nitrogen retention, and all metabolizable energy parameters across ingredients (p < 0.05), with more pronounced responses observed in DDGS and jatropha meal. β-mannanase supplementation also enhanced nutrient utilization and energy utilization, particularly in copra meal and palm kernel meal, which are rich in β-mannan-containing non-starch polysaccharides. Overall, the results demonstrate that both pelleting and β-mannanase supplementation can improve the nutritional value of fibrous alternative feed ingredients, thereby supporting their more efficient use in poultry diets.

Correction: Calibrated early-warning models with fairness auditing and selective prediction for course withdrawal risk: Evidence from OULAD

2026-08-07T14:00:00Z

by Suhan Wu, Jingyi Duan, Min Luo

Proposing the use of a physiotherapist navigator in an acute cancer care setting in Ontario: A nationwide survey using a modified Delphi approach

2026-08-07T14:00:00Z

by Holly Edward, Danielle Lawrence, Alexander Grant, Alicia Page, Luciana Macedo, Sarah Wojkowski, Som D. Mukherjee, Jenna Smith-Turchyn

Objective

To engage health care providers in Canada to identify the roles, tasks, processes, assessments, and triaging decisions for a Physiotherapist (PT) Navigator role that will be implemented and evaluated in a future trial.

Methods

A two-round, online, modified reactive Delphi study was used. Any licensed health care practitioner in Canada who works with individuals with or beyond cancer was eligible to participate. Round 1 identified qualitative feedback on role domains to guide role improvement. Qualitative feedback was examined in duplicate using content analysis. Round 2 identified quantitative feedback to gather numerical data to establish consensus. Quantitative survey feedback was analysed using descriptive statistics including mean and standard deviation. Items were added to the role description if identified by ≥10% of respondents, and 75% was the threshold to define consensus. Lastly, a consensus meeting including end users was held to consider priority items and utility of role translation into clinical practice.

Results

Consensus on the PT Navigator role description was achieved following the two survey rounds (Round One; n = 34, Round Two; n = 18). Four domains were identified to define the role: process, assessment, triaging decisions, and duties and responsibilities. A figure visualizing the PT Navigator role was generated. Changes to the role after survey feedback included increasing appointment times with the PT Navigator, longer duration between follow-ups, patient self-referral, and additional objective testing. Consensus meeting feedback considered the variability in follow-up depending on different treatment timelines and an emphasis on promoting self-management strategies. Perceived usefulness of the role was high (mean 9.19/10; SD 2.12).

Conclusions

This modified Delphi study identified key domains that would inform development of a comprehensive PT Navigator role working with cancer patients. The role offers a novel approach to promote routine assessment and early intervention, with the aim towards integrating PTs meaningfully within cancer care settings in Canada.

Facilitators of and barriers to interprofessional learning between nurses and physiotherapists in hospital-based clinical practice: A scoping review

2026-08-07T14:00:00Z

by Kristina Åhlund, Anette Johnsson, Maria Rönnerhag

Introduction

Effective collaboration depends on mutual understanding of professional roles and responsibilities, making sustainable interprofessional learning (IPL) an integral part of hospital clinical practice. In this context, learning and collaboration reinforce one another and ultimately support better patient outcomes. However, the factors influencing IPL in hospital settings are not yet clearly understood. Therefore, this scoping review aimed to identify facilitators of, and barriers to, IPL in hospital-based clinical practice, focusing on nurses and physiotherapists.

Method

This scoping review followed the Arksey and O’Malley framework. A systematic literature search was conducted in three databases: PubMed, CINAHL, and Scopus, from inception to July 2026. Inclusion criteria were empirical scientific articles focusing on facilitators and barriers to IPL, applicable to adult hospital settings and including both nursing and physiotherapy perspectives. Grey literature, studies evaluating specific educational interventions or conducted in clinical settings with dedicated IPL initiatives beyond routine daily practice, and studies conducted in paediatric, maternity, or psychiatric settings were excluded. The database search yielded 1,973 articles, of which 11 were included following screening of 33 full-text articles.

Results

The included studies identified a range of facilitators to IPL including factors that supported socialization and familiarization (n = 6), building a positive team climate (n = 5), and conducive organizational structures (n = 10). Barriers included limiting structural prerequisites (n = 5), constraining interprofessional interactions (n = 4), and non-conducive prevailing workplace culture (n = 5).

Conclusion

Sustainable IPL requires organizational structures that enable regular interaction among professionals, inclusive team cultures, and collaborative leadership. This ensures that learning continues even as staff members change, and that essential knowledge is retained in hospital-based clinical practice, so that patients receive care based on their needs. This review may therefore support hospitals and educational organizations in creating conditions that support the systematic integration of IPL into both education and clinical practice and thereby sustain IPL and collaboration between nurses and physiotherapists.

Correction: Load identification method for pepper harvesting drum based on dynamic chaotic characteristics of vibration-torque coupling

2026-08-07T14:00:00Z

by Chen Wei, Jin Lei, Xinyan Qin, Yunshu Xiao, Zhi Wang, Shiguo Wang, Bin Li, Xiaohu Guo, Chengfu Wang

Dual regulatory mechanisms of YGP1 expression in response to glucose availability in Saccharomyces cerevisiae

2026-08-07T14:00:00Z

by Megumi Sato, Kaoru Irie, Yasuyuki Suda, Tomoaki Mizuno, Kenji Irie

Cells adapt to fluctuating nutrient conditions by dynamically regulating gene expression, ensuring survival under stress. Ygp1, a secretory yeast glycoprotein, is one such gene that is induced by nutrition deprivation, particularly glucose starvation. In this study, we investigated the regulatory mechanisms underlying nutrition-deprivation-responsive changes in gene expression, focusing on YGP1 expression. Under glucose-rich conditions, YGP1 expression was positively regulated by the RNA-binding protein Puf5, a member of the Puf family. This regulation ensured rhythmic YGP1 expression during M phase of the cell cycle. The Puf5-mediated control targeted a specific 60-nucleotide region in the YGP1 promoter (−600 to −540 from the start codon), and this regulation was partly mediated by the acid stress-responsive transcriptional activator Haa1. In addition, upon glucose exhaustion (diauxic shift), YGP1 expression was strongly induced by the stress-responsive transcription factors Msn2 and Msn4 through the stress-response elements in the YGP1 promoter. Further analysis of the physiological significance of YGP1 expression revealed that the Puf5-mediated regulation contributes to the acid stress responses, and YGP1 expression supports cell survival in the puf5Δ background. In summary, YGP1 expression is regulated by two distinct factors in a glucose availability-dependent manner: Puf5 under glucose-rich conditions and the Msn2/Msn4 during glucose starvation. Especially, Puf5-mediated regulation contributes to the acid stress responses and subsequently supports long-term cell survival.

The PROGAIN trial: A randomized controlled trial of high-protein peripheral parenteral nutrition on nitrogen balance and recovery after gastric cancer surgery — study protocol

2026-08-07T14:00:00Z

by Jong Hyuk Yun, MinJee Han, GaRam Bae, Hyunsub Shin, GeumJong Song, MyoungWon Son

Introduction

Patients undergoing curative gastrectomy for gastric cancer are vulnerable to perioperative protein loss, negative nitrogen balance and delayed recovery. Conventional peripheral parenteral nutrition (PN) formulations may not provide sufficient protein at clinically practical infusion volumes, and whether high-protein (amino acid–enriched) PN improves postoperative nitrogen balance after gastrectomy has not been tested in a randomized controlled trial. The PROGAIN trial evaluates the effect of perioperative high-protein PN on nitrogen balance and recovery outcomes in this population.

Methods and analysis

PROGAIN is a single-center, randomized, open-label, parallel-group superiority trial with blinded laboratory assessment and coded-group analysis of the primary endpoint. The trial will enroll 110 patients with gastric cancer scheduled for curative gastrectomy. Participants are allocated 1:1 to high-protein PN or conventional PN, administered through a peripheral intravenous line on the day before surgery and postoperative day (POD) 1 through POD 5. PN is delivered at a daily caloric target of 20 kcal/kg/day using a stepwise schedule informed by an institutional retrospective audit of oral intake. The primary outcome is nitrogen balance on POD 5, calculated using a simplified Blackburn equation. Secondary outcomes include nutritional indices, skeletal muscle index, glycemic control, postoperative complications classified by Clavien–Dindo grade and functional recovery measures. The primary analysis will compare the two arms using a two-sample t-test in the intention-to-treat population. The trial has 80% power to detect a between-group mean difference of 3 g/day at a two-sided α of 0.05.

Ethics and dissemination

The trial is approved by the Institutional Review Board of Soonchunhyang Cheonan Hospital and conducted in accordance with the Declaration of Helsinki and ICH–Good Clinical Practice. Findings will be disseminated through peer-reviewed publication, scientific meetings and results reporting on ClinicalTrials.gov.

Trial registration

ClinicalTrials.gov, NCT07488611.

Enhancing the solubility of puerarin via melt sonocrystallization

2026-08-07T14:00:00Z

by Yaxiang Gong, Jiafu Wen, Wenqi Liu

In this work, in order to improve the low solubility and poor oral bioavailability of puerarin, we first applied melt sonocrystallization (MSC) technology to systematically investigate the effects on its solubility and crystallographic properties. We applied MSC to treat puerarin, evaluated its solubilization effect using UV spectroscopy, and characterized it by dissolution rate, optical microscope, powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), Thermogravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR). Following MSC treatment, puerarin exhibited higher solubility and faster dissolution, the product displayed reduced particle size and a tendency to agglomerate. The results of PXRD, DSC, FTIR and TGA showed that the crystal form of MSC treated puerarin transformed into puerarin monohydrate, with a decrease in crystallinity and partial amorphization. The reduction in particle size and amorphization may be the driving forces of the increase in solubility and dissolution. In summary, MSC can significantly improve the solubility and dissolution of puerarin, providing new ideas for enhancing its bioavailability and improving its oral formulations.

Geometric morphometric analysis of maxillary molar sexual dimorphism: A cross-sectional study

2026-08-07T14:00:00Z

by Srikant Natarajan, Junaid Ahmed, Shravan Shetty, Nidhin Philip Jose, Sharada Chowdappa, Sunitha Carnelio

Objective

The sexual dimorphism of permanent maxillary molars has been extensively documented through metric and subjective shape analysis. The aim of this study was to evaluate sexual dimorphism in the shape of permanent maxillary first (UM1) and second molars (UM2) using geometric morphometric analysis.

Methods

This cross-sectional study analysed digitized dental casts from 60 males and 60 females. The casts were scanned using a laser surface scanner, and 28 three-dimensional landmarks, defined based on anatomical and geometric landmarks, were marked using SlicerMorph software. The shape data was then analysed using Procrustes superimposition, principal components analysis, regression, and discriminant function analysis to test the shape changes, allometry, and differences between the sexes.

Results

Centroid size did not differ significantly between sexes for UM1 and UM2 (p > 0.05). Shape differences were not significant in UM1 (p = 0.15) but were significant in UM2 (p = 0.01). Allometry was observed in both molars, with a greater contribution in UM2 (6.96%) compared to UM1 (2.39%) (p < 0.001). Discriminant function analysis identified patterns of shape variation between groups; however, these findings should be interpreted cautiously as no cross-validation was performed.

Conclusion

Geometric morphometric analysis identified significant shape differences in the maxillary second molar. These findings demonstrate the utility of 3D geometric morphometric analysis for assessing tooth shape variation and support its application to evaluating sexual dimorphism of maxillary molars. Further studies involving larger and more diverse populations are warranted to validate these findings.

A lightweight alignment-aware DBNet for surgical instrument code detection

2026-08-07T14:00:00Z

by Ke Yang, Yun Xue, Zhe Du, Shuchang Xu, Tian Tang, Zhifeng Qu

Reliable detection of engraved surface codes on surgical instruments is essential for end-to-end traceability, yet remains challenging in practice because metallic reflection, motion blur, scale variation and weak textures often hinder stable localization. Here we present LA-DBNet, a lightweight detection framework built on DBNet for this task. The model uses MobileNetV4 with LiteFPN to reduce complexity while preserving multi-scale feature representations. To better capture the elongated structure and edge features of engraved codes, we introduce a Directional Edge Collaborative Alignment (DECA) module to improve cross-scale feature alignment, and embed an Efficient Channel Attention (ECA) mechanism in the high-resolution feature layer to enhance responses relevant to the target and suppress noise caused by reflections. We further incorporate a region-weighted consistency learning strategy during training to improve robustness to degraded samples. On our surgical instrument code dataset, LA-DBNet achieves an F1 of 95.8%, improving DBNet by 3.6 percentage points, while reducing parameters to 3.35 M and reaching 33.6 FPS. On ICDAR2015, it attains an F1 of 86.1%. These results show that LA-DBNet improves detection performance while substantially reducing model size and maintaining efficient inference in surgical instrument code detection.

Impact of infection on decongestion and kidney outcomes in patients with cardiorenal syndrome type 1

2026-08-07T14:00:00Z

by Jonathan S. Chávez-Iñiguez, Jose J. Zaragoza, Ronaldo Escoto- Del Toro, Itzel Fong-Maravilla, Guillermo Navarro-Blackaller, Ramón Medina-González, Alejandro Martínez Gallardo-González, Luz Alcantar-Vallin, Juan A. Gómez-Fregoso, Eduardo Mendoza-Gaitán, Manuel Arizaga-Nápoles, Juan B. Ivey-Miranda, Guillermo García-García

Background

Infections are frequent precipitants of acute decompensated heart failure (ADHF) and may alter decongestive trajectories in patients with cardiorenal syndrome type 1 (CRS1), it may reduce diuretic efficacy and increase the risk of kidney injury. However, the impact of infection on decongestion and kidney outcomes in CRS1 remains unclear.

Methods

We conducted a prospective cohort study including 256 patients with CRS1 hospitalized at a tertiary center (2022–2024). Patients were stratified by the presence of infection, defined as clinical suspicion plus antibiotic therapy. The primary outcome was successful decongestion, assessed by symptoms, biomarkers (BNP/CA-125), and POCUS findings. Secondary outcomes included major adverse kidney events at 10 and 30 days (MAKE: death, kidney replacement therapy [KRT], or ≥25% eGFR decline).

Results

Seventy-two patients (28.1%) had infection, presenting with higher BNP (13,405 vs. 25,264 pg/mL, p = 0.012) and lower PaO₂ (45 vs. 65.5 mmHg, p = 0.019). Furosemide exposure was comparable (600 vs. 580 mg, p = 0.62). Successful decongestion occurred in 61.4% of patients with infection vs. 59.8% without infection (p = 0.83). Infection was not independently associated with decongestion (aOR 1.28, 95% CI 0.65–2.51) or MAKE-30 (aOR 1.26, 95% CI 0.57–2.79).

Conclusions

In CRS1, infection was associated with more severe baseline congestion but did not compromise decongestion rates or increase short-term MAKE. These findings support the notion that achieving decongestion is feasible in patients with ADHF due to infection without an incremental risk of MAKE.

Seasonal variation in the incidence of vitreous hemorrhage in proliferative diabetic retinopathy

2026-08-07T14:00:00Z

by Mirinae Kim, Young-Hoon Park

Purpose

To investigate whether seasonal alterations and meteorological factors are associated with the incidence of vitreous hemorrhage in patients with proliferative diabetic retinopathy (PDR).

Materials and Methods

This retrospective observational study included patients with PDR who visited Seoul St. Mary’s Hospital between January 2019 and December 2021. Among the 4,402 eyes with PDR, the presence of vitreous hemorrhage was determined. The monthly incidence of vitreous hemorrhage and meteorological data were obtained and analyzed.

Results

Among 4,402 eyes of PDR, vitreous hemorrhage was observed in 293 eyes (6.66%). The incidence of vitreous hemorrhage was high in May (9.37%, 31 of 331 eyes) and June (8.58%, 26 of 303 eyes). Poisson regression analyses revealed that temperature, humidity, and precipitation-per-hour did not influence the risk of vitreous hemorrhage. Thus, the observed seasonal variation in vitreous hemorrhage was not fully explained by the measured meteorological factors. The Wilcoxon signed-rank test revealed a significant difference between the intraocular pressure (IOP) at the time of hemorrhage (hemorrhage-IOP; hot season) and IOP at the visit immediately before the occurrence of hemorrhage (pre-IOP; cold season) groups (P = .029) and between the hemorrhage-IOP (warm season) and pre-IOP (cold season) groups (P = .041).

Conclusion

Vitreous hemorrhage in PDR showed seasonal variations, peaking in May and June. This pattern could not be fully explained by the meteorological variables evaluated; IOP-fluctuations caused by temperature changes and systemic factors such as seasonal changes in glycemic control may contribute to this variability. Further studies are warranted to elucidate the underlying mechanisms.

Understanding the usefulness–risk paradox in AI writing tool adoption: An extended technology acceptance model study in Chinese University L2 writing contexts

2026-08-07T14:00:00Z

by Tingxuan Li, Ziyu Liu, Deping Zou

Generative artificial intelligence (GenAI) is rapidly reshaping higher education, and AI writing tools have become increasingly prominent in second language (L2) writing contexts. However, the mechanisms underlying students’ adoption of these tools, as well as the perceived consequences of their use, remain insufficiently understood. Grounded in an extended Technology Acceptance Model (TAM), this study examines how AI self-efficacy (ASE), multidimensional perceived risk, and behavioral engagement (BE) are associated with Chinese university students’ adoption of AI writing tools in L2 writing-related tasks and their perceived writing-related outcomes. A total of 518 valid questionnaires were collected from undergraduate students with prior experience using AI writing tools for English writing, revision, translation, or other L2 writing-related tasks, and structural equation modeling was employed to test the proposed acceptance–use–outcome framework. The results show that ASE was positively associated with perceived ease of use (PEOU) and perceived usefulness (PU). While PEOU was negatively associated with overall perceived risk (OPR), PU was positively associated with OPR, indicating that students who perceived AI writing tools as useful also tended to report stronger awareness of potential risks. OPR was not significantly associated with attitudes toward AI writing tools. Attitude was strongly associated with behavioral engagement, which in turn was positively associated with both perceived positive and perceived negative writing-related outcomes, with the positive association being substantially stronger. These findings extend TAM in AI-mediated learning by showing that functional value and risk awareness may coexist rather than offset one another in L2 writing contexts. Because the study used cross-sectional self-report data, the findings should be interpreted as associations among perceived constructs rather than evidence of direct causal effects or objective improvement in writing performance. The study also offers practical implications for the responsible integration of AI writing tools in higher education.

Understanding primary care physicians’ perceptions of large language model adoption in clinical practice: A qualitative research protocol leveraging the technology adoption behavior framework

2026-08-07T14:00:00Z

by Benny Bikash Pokharel, Monica Hsu, Lindsay Hedden, Laura Nimmon, David E. Bloom, Sian H. Tsuei

Introduction

Large language models’ (LLMs’) rapid evolution and intersection with diverse groups and institutions require up-to-date policies, practices, and behaviors to ensure safe and effective implementation. Because physicians play a central role in care provision and face the dual mandate of embracing innovations and safeguarding patient welfare, understanding physicians’ views on LLMs can elucidate the complex interplay of technical, ethical, and professional considerations influencing LLM adoption.

Methods and analysis

This qualitative study aims to employ a descriptive qualitative design to explore how primary care physicians perceive the adoption of LLMs in the context of their clinical practice. We plan to use semi-structured interviews with purposively sampled primary care physicians from British Columbia, Canada. The data collection will draw on the technology adoption behavior framework, a novel model that integrates the most advanced theories of technological uptake. We expect to use thematic analysis drawing on deductive and inductive approaches to describe physicians’ perceptions. The multidisciplinary research team will prepare and conduct reflexive memos and discussions to ensure nuanced interpretations.

Dissemination

We aim to disseminate the findings through peer-reviewed journals, professional organizations, and policymaker briefings to support the development of policies, practices, and behaviors that support safe and effective LLM integration into health care.

Strengths and limitations

Utility of cell-free DNA in diagnosing tuberculous pleurisy: A systematic review and meta-analysis protocol

2026-08-07T14:00:00Z

by Yanqin Shen, Keying Du, Yuyang Ling, Liwei Yao

Background

Tuberculous pleurisy is the most common form of extrapulmonary tuberculosis. Diagnosis remains challenging due to the paucibacillary nature of pleural effusions, leading to low sensitivity of conventional microbiological methods and frequent reliance on invasive biopsy. Cell-free DNA (cfDNA), comprising fragmented genetic material released from host cells and pathogens into biofluids, presents a promising minimally-invasive biomarker. This protocol outlines a systematic review and meta-analysis designed to evaluate the overall diagnostic accuracy of cfDNA for tuberculous pleurisy and to identify factors influencing its performance.

Methods

This protocol is prospectively registered with PROSPERO. We will systematically search PubMed, Embase, Web of Science, Scopus, The Cochrane Library from inception to June 2027. Diagnostic accuracy studies directly comparing cfDNA detection (in pleural fluid, plasma/serum) against a composite reference standard for tuberculous pleurisy (including microbiological, histological, or clinical diagnosis) will be included. Two reviewers will independently screen studies, extract data, and assess risk of bias using the QUADAS-2 tool. A bivariate random-effects meta-analysis will be performed to calculate pooled sensitivity, specificity, positive/negative likelihood ratios, and diagnostic odds ratios. A hierarchical summary receiver operating characteristic curve will be plotted. Subgroup analyses and meta-regression will explore sources of heterogeneity. The GRADE approach will be used to evaluate the certainty of evidence.

Conclusion

This review will provide pooled estimates of the diagnostic sensitivity and specificity of cfDNA for tuberculous pleurisy, evaluate its clinical utility, and identify key factors—such as sample type, detection technology, and pre-analytical procedures—associated with optimal performance. The findings will offer high-level evidence to guide clinical application and future research.Systematic review registration: PROSPERO Registration number: CRD420261424501

Building a sustainable management pipeline: Key predictors of nurse management aspirations in Ireland

2026-08-07T14:00:00Z

by Elaine Berkery, Nuala F. Ryan, Helen Purtill

Background

Against the backdrop of the shortages of nursing managers, this paper examines predictors of career aspirations among nurses in Ireland. Rather than viewing career aspirations as being determined solely by personal, job related or organizational factors we consider the individual nurse, within the context of their job, interacting with the overall organization and seek to ascertain how these factors are related to nurse’s career aspirations.

Objective

The objective of this study is to explore how personal, job-related, and organizational factors shape nurses’ career aspirations. The research question guiding this study is: “What variables relating to the individual, job or organization predict career aspirations among nurses?”.

Design

This cross-sectional study gathered questionnaire data from 263 nurses.

Setting

A large public hospital group in Ireland comprising 5 hospitals.

Methods

Pearson correlations provided an initial understanding of the bivariate relationships between scales measuring career aspirations and scales measuring resilience, job satisfaction, employee engagement, psychological safety, organizational citizenship behavior, and organizational commitment. Multivariate Linear Regression models examined factors independently associated with career aspirations.

Results

Correlational analysis identified statistically significant relationships between career aspirations and the individual, job and organizational scales, with resilience showing the strongest positive correlation (r = 0.418, p < 0.01). The Multivariate Linear Regression analysis identified having a postgraduate qualification (β = 2.92, 95% CI [1.38, 4.45], p < 0.001) and higher levels of resilience (β = 2.22, 95% CI [1.26, 3.19], p < 0.001) as statistically significant independent predictors of career aspirations.

Conclusion

The findings provide insights into developing strategies to create a pipeline of qualified nurses to optimize recruitment and succession planning for nurse managers, thereby building a sustainable workforce. Hospital managers should develop policies and programs that promote organizational support for further education and resilience-building workshops. These initiatives could encourage more nurses to pursue nursing management roles.

Improving carbon stock estimates in plantation forestry: Site-specific allometric equations for Gmelina arborea in Ghana’s Kwahu Highlands

2026-08-07T14:00:00Z

by Benjamin Wiafe Asare, Michael Ansong, Kwadwo Boakye Boadu, Prince Owusu

Accurate estimation of tree biomass and volume is essential for carbon accounting and climate reporting. This study developed site-specific allometric models for predicting stem volume and aboveground biomass of Gmelina arborea in the high-elevation Kwahu Highlands of Ghana. The trees were grouped into three DBH classes. DBH, total height, merchantable height, bole height, and crown dimensions of 45 trees were measured. Twenty-four of these were randomly destructively sampled for volume and biomass estimation. A range of linear, power, and log-linear regression models were evaluated to identify the most accurate predictors. Tree structural attributes changed systematically with DBH. As DBH increased, total height increases rapidly, bole height increased more gradually, and crown length showed strong growth. Expanded log-linear models [ln(Y) = a + b₁*ln(x) + b₂*ln(h) + b₃*ln(p)] incorporating DBH, total height, and wood density provided the best fit for both stem volume and biomass (R² > 0.90), with minimal error and strong agreement with observed values. Simpler DBH + height models showed significant deviations for biomass estimation but performed adequately for volume prediction. These findings highlight the importance of integrating multiple predictors in biomass models for unmanaged highland plantations. The resulting equations improve carbon stock estimation accuracy, supporting climate policy and sustainable forest management in tropical highland ecosystems.

A visual analytic method to investigate patterns and structures of missing data

2026-08-07T14:00:00Z

by Roy A. Ruddle

Datasets often have missing values. Understanding the locations and underlying reasons (missing data patterns and structures, respectively) is important to avoid analysis bias or building inappropriate models. However, investigating missing data patterns and structures presents significant challenges. To address them we developed a novel visual analytic method, which combines new purity metrics for three core types of pattern (block, monotone and disjoint) with seven different visualizations in an iterative workflow. We also conducted two case studies, one with a UCI Machine Learning Repository dataset and the other with a 21 million record/389 variable hospital dataset that had many interwoven missingness patterns. In the UCI case study, the method’s purity metrics and heatmaps revealed a rare data quality issue that affected 0.08% of records, but was not apparent when an existing correlation-based approach was used. Our method also implements perceptual discontinuity to ensure that small values are visible in bar charts, and that showed that two variables were missing values in 0.02% and 0.3% of records, respectively, rather than being complete as reported in the original UCI paper. The hospital dataset contained 595,171 unique combinations of missing values, but that overwhelming number was reduced to 57 comprehensible patterns by iteratively using purity metrics and heatmaps with the three core pattern types in our method. That revealed insights that ranged from uncovering rare and common data quality issues, to finding data dictionary errors, and making explicit relationships between groups of variables that may otherwise be hidden. The method also provides an explanation graph, which aids reproducibility by documenting the order in which patterns were found and acts as a tangible artifact that should help communicate the findings to stakeholders.

Risk appetite-enhanced game-theoretic approach for modelling mandatory lane-changing behaviour in freeway merging areas

2026-08-07T14:00:00Z

by Bingtong Wang, Shunchao Wang, Gaili He

Addressing adverse effects on traffic safety resulting from mandatory lane changes presents a significant challenge, necessitating the development of an empirically accurate method that incorporates drivers’ risk appetite into modelling merging behaviour. Game theory serves as a commonly utilized approach for analysing interactive lane-changing behaviour and accurately predicting various vehicle actions. This study introduces a game-theoretical decision-making model tailored for mandatory lane changes at freeway merging areas. The proposed model adopts a non-cooperative decision-making approach involving two players: the driver of the mainline vehicle and the on-ramp vehicle. The payoff function, encompassing both efficiency-based and safety-based payoffs, is asymmetrically designed to evaluate safety loss and efficiency gain, adhering to the principles of prospect theory. Specifically, an S-shaped value function is formulated to assess the payoffs, and a first-best weighting function considering loss aversion is established within the framework of probability perception. A bilevel optimization approach is employed to estimate the model parameters. The upper level entails a nonlinear programming problem aimed at minimizing the squared difference between observed and predicted strategies, while the lower-level programming seeks the Nash equilibrium solution. Vehicle trajectory data is utilized for model calibration and validation purposes. Validation on the US-101 and I-80 datasets shows that the proposed model achieves detection rates of 92.14% and 92.34%, respectively. The corresponding validation errors are also reported using MAE and RMSE, rather than treating MAE as classification accuracy. Comparative results against representative game-theoretic mandatory lane-changing models further indicate that incorporating prospect-theory-based loss aversion improves both behavioural interpretability and predictive performance.

Study protocol for a randomized controlled trial of a self-determination theory–based psychoeducational intervention to enhance autonomous motivation for exercise in female university students

2026-08-07T14:00:00Z

by Sonia García-Merino, Patricia Ruiz-Bravo, Germán Díaz Ureña

Physical inactivity, maladaptive exercise motives, and body image concerns are highly prevalent among young adult women and are associated with reduced psychological well-being and increased risk for disordered eating. Although previous interventions have addressed physical activity or body image separately, few have simultaneously targeted motivational quality and body-related perceptions within an integrated theoretical framework. This study protocol describes a randomized controlled trial designed to evaluate the effectiveness of a psychoeducational intervention based on Self-Determination Theory and using functionality-oriented body image strategies. The aim is to enhance autonomous motivation for exercise and improve psychological well-being among female university students in Health Sciences. Participants aged 18–25 years will be randomly allocated (1:1) to an experimental group or a wait-list control group following baseline assessment. Outcome measures will be collected at baseline (T0), post-intervention (T1), and six-month follow-up (T2). The intervention consists of six face-to-face group sessions that include autonomy-supportive strategies, competence-building activities, and functionality-based body image content emphasizing body capabilities rather than appearance. The primary outcome is autonomous motivation for exercise, assessed using the Behavioral Regulation in Exercise Questionnaire-3 and operationalized through the Relative Autonomy Index at six-month follow-up. Secondary outcomes include satisfaction and frustration of basic psychological needs, physical activity levels, positive body image, and risk of eating disorders. Data will be analyzed using mixed model for repeated measures under an intention-to-treat framework to account for repeated measures and missing data. Mediation analyses will examine whether changes in autonomous motivation explain the effects of the intervention on physical activity, positive body image, and eating disorder risk. This study will provide evidence on the effectiveness of an integrated, theory-based intervention targeting motivation and body image in young adult women. The trial is registered at ClinicalTrials.gov (Identifier: NCT07506343).

Global-key region collaborative noise-aware for electrocardiogram signal quality assessment

2026-08-07T14:00:00Z

by Jijie Fan, Huihui Chang, Han Han, Jiawei Luo

Wearable electrocardiogram (ECG) devices enable long-term cardiac monitoring due to their convenience and comfort. However, various types of noise, such as baseline drift, power-line interference, and motion artifacts, can severely degrade signal quality and compromise the reliability of automated diagnosis. Consequently, ECG signal quality assessment (SQA) plays a crucial role in ensuring accurate downstream analysis. Existing supervised SQA methods rely heavily on large-scale annotated datasets, which are costly and time-consuming to obtain in real-world applications. Although unsupervised anomaly detection methods alleviate the dependence on labeled data, most existing approaches primarily focus on global signal characteristics and directly utilize reconstruction errors or feature-space distances for anomaly detection, while overlooking discriminative noise-related regions. As a result, their ability to distinguish noise contamination from physiological signal variations remains limited, leading to suboptimal generalization performance. To address this limitation, we propose a global-key region collaborative noise-aware ECG signal quality assessment method (NA-SQA) for unsupervised settings. NA-SQA integrates both global information and key noise-region features to enable more accurate quality evaluation. Specifically, we generate low-quality signals and corresponding quality labels by injecting various types of artificial noise into high-quality ECG signals. All signals are then passed through an autoencoder to reconstruct high-quality ECG signals. Subsequently, the original signals are used for global quality prediction, while the difference between the original and reconstructed signals is treated as the key noise region for key-region quality prediction. By jointly optimizing the global and key quality prediction tasks, the proposed model effectively integrates global information with more discriminative noise-region features, thereby enhancing its generalization capability to unseen low-quality ECG signals. Extensive experiments on four public ECG quality assessment datasets, namely BUTQDB, Icentia11K, EHOQA, and EAWQA, demonstrate the effectiveness of the proposed approach. NA-SQA achieves F1 scores of 91.42%, 79.62%, 81.59%, and 81.56% on the four datasets, respectively, consistently outperforming state-of-the-art unsupervised ECG quality assessment methods and demonstrating superior robustness and generalization capability for ECG signal quality assessment in real-world noisy environments.

Induction of osteogenic differentiation of MSCs by GSK3β knockdown through GSK3β siRNAs transfection

2026-08-07T14:00:00Z

by Elena V. Galitsyna, Anastasiia A. Buianova, Tatiana B. Bukharova, Irina A. Krivosheeva, Mikhail Yu. Skoblov, Dmitriy V. Goldshtein

The development of effective strategies for treating bone defects can be based on gene therapy methods aimed at regulating the differentiation of osteoprogenitor cells. One of the approaches is to use siRNA molecules in knockdown systems for genes inhibiting osteogenic cell differentiation. In this work, we aimed at developingapproaches to induce osteogenic differentiation of mesenchymal stem cells (MSCs) by siRNAs-mediated knockdown of GSK3β siRNAs in cultures of MSCs derived from human adipose tissue (AD-MSCs). For this purpose, we compared the transfection efficacy of lipoplexes and polyplexes formed with one of four siRNA molecules and five commercial transfection agents most commonly used in laboratory practice. The most effective transfection agent was found to be linear polyethylenimine (PEI) which demonstrated high cytocompatibility both in free form and in polyplexes (even when maximum concentrations were used). Using the polyplexes formed by the newly designed siRNA and PEI, we constructed a highly efficient GSK3β gene knockdown system, which showed effectiveness in AD-MSC cultures. As a result, we demonstrated the osteoinductive properties of GSK3β siRNA molecules in these cultures. These results provide a methodological basis for future siRNA-based strategies targeting GSK3β in osteogenic applications, with in vivo studies needed to establish its translational potential.

Validation of expected objective performance indicators in surgical data analysis

2026-08-07T14:00:00Z

by Ye Li, Sreeram Kamabattula, Kiran Bhattacharyya, Max Berniker

Objective Performance Indicators (OPIs) quantify surgical activity by measuring critical aspects of a case (e.g., surgeon movements, interaction forces, etc.) at clinically meaningful steps. They are particularly useful in robotic-assisted surgery, where the information required to compute them can be harvested automatically, and early studies have found that they help quantify surgeon skill. However, since surgical procedures can be highly variable and the boundaries between surgical steps often subject to interpretation, OPIs become similarly variable. Yet, OPIs should be insensitive to this variability to remain informative and unambiguous. Previously we proposed a method for computing expected OPI values in a probabilistic framework that has theoretical support for being robust to this variability. Here we validate this method and compare it against the conventional approach on a large clinical dataset. Using 5408 annotated clinical steps from 1,016 clinical cases across seven procedure types, we performed an extensive comparison of this new method alongside the conventional approach. A series of analyses compared the resulting OPI values focusing on potential biases and the variability of their values in the presence of annotator noise. We found that the probabilistic method resulted in OPI values that were less often biased than their conventional OPI counterparts (49.37%, and 56.63% respectively), and the bias magnitudes were smaller. Finally, we found that the probabilistic method resulted in significantly less variable OPI values in 40.56% of comparison, whereas 8.52% showed the opposite. Our analysis suggests that the expected OPIs are more robust to annotator variability, with less bias and smaller variance. We suggest that this probabilistic approach holds promise for the computational analysis, and perhaps the conceptual interpretation, of surgical data.

The association between atherogenic index of plasma, cumulative atherogenic index of plasma and type 2 diabetes mellitus with chronic kidney disease among older Chinese adults: Findings from the CHARLS study

2026-08-07T14:00:00Z

by Yu Yi, Yiqi Chen, Shulan Feng, Fuhua Lu, La Zhang

Background

The impact of short-term atherogenic burden and long-term cumulative lipid exposure on the risk of incident T2DM with CKD remains unclear. This study examines the longitudinal associations between the Atherogenic Index of Plasma (AIP) and Cumulative Atherogenic Index of Plasma (CumAIP) with the development of T2DM complicated by CKD in middle-aged and older adults.

Methods

A total of 5,779 participants from the CHARLS cohort were included. AIP and CumAIP were used to represent short-term and long-term lipid burdens, respectively. Multivariable logistic regression and restricted cubic spline models were applied to assess the dose-response relationships, adjusting for 11 conventional covariates. ROC curve analysis was conducted to evaluate predictive performance. An exploratory analysis further evaluated incident CKD among participants with T2DM at baseline (n = 494).

Results

Both AIP and CumAIP were significantly associated with incident T2DM with CKD, with the highest quartiles showing modest but statistically significant associations with the outcome (AIP-Q4: OR: 1.013; 95% CI: 1.004–1.022; p < 0.05; CumAIP-Q4: OR: 1.017; 95% CI: 1.008–1.026; p < 0.001). Linear dose-response associations were observed across logistic regression and RCS regression models. ROC analysis showed that CumAIP demenstrated better discrimination than AIP (AUC 0.683 versus 0.650). In an exploratory analysis of participants with T2DM at the baseline (n = 494), both indices showed suggestive associations with incident CKD (AIP-Q4: OR: 1.050; 95% CI: 1.009–1.145; p = 0.025; CumAIP-Q4: OR: 1.081; 95% CI: 1.015–1.152; p = 0.016).

Conclusion

AIP and CumAIP is significantly associated with incident T2DM with CKD among Chinese middle-aged and older adults. CumAIP demonstrated superior predictive performance over single AIP measurement. These findings support the potential value of long-term lipid monitoring for identifying indivuduals at increased risk of T2DM with CKD. An exploratory analyses also suggested a similar associations with progression from T2DM to CKD; however, these findings require confirmation in larger cohorts.

Self-reported binary gender prediction from personality traits: Alignment between machine learning importance and classical effect sizes

2026-08-07T14:00:00Z

by Heeseung Cho, Yiyu Chen, Christian Wallraven

Gender differences in personality have been characterized using effect sizes such as Cohen’s d and multivariate measures such as the Mahalanobis distance. However, as machine learning models are increasingly applied to personality classification, it remains unclear how model-based feature importance relates to these classical measures of group separation. This study examined this relationship using two large-scale personality datasets comprising 18,062 participants in the Big5 and 44,324 participants in the 16PF. We trained multiple linear and nonlinear machine learning models (Logistic Regression, Random Forest, Extra Trees, LightGBM, and Explainable Boosting Machine) to predict self-reported binary gender from trait scores and derived feature-importance rankings using SHAP and permutation importance. These rankings were compared with univariate effect sizes, standardized linear discriminant weights, and trait-level contributions to the Mahalanobis distance. Across 20 model–resampling configurations, trait-importance rankings were highly stable in both datasets. In the Big5, univariate effect size rankings closely matched model-based importance rankings, with rank correlations of 0.98 to 1.00. Conversely, in the 16PF, alignment between univariate effect size and model-based importance was moderate (ρ=0.56−0.64), whereas alignment with multivariate discriminant structure remained strong (ρ=0.83−0.85). These findings indicate that divergence between univariate and model-based importance is consistent with covariance-mediated multivariate weighting rather than the emergence of novel predictive structure. When trait intercorrelations are limited, univariate summaries approximate multivariate importance; when covariance is substantial, multivariate geometry reshapes trait contributions, and model-based explainability metrics closely track the resulting discriminant structure.

Effectiveness of web-based educational videos on enhancing diabetes knowledge and empowerment among type 2 diabetes patients in primary care: A randomized controlled trial

2026-08-07T14:00:00Z

by Hui Zhu Thew, Poh Ying Lim, Tatt Quan Tan, Jun Hui Goh, Amelia Qiao Rou Yap, Ja Shen Choy, Chee Han Ng

Objective

This study evaluated the effectiveness of web-based educational video module on diabetes knowledge, empowerment, and clinical outcomes among adults with poorly controlled type 2 diabetes in a primary care setting.

Methods

A single-centre, parallel-group, randomised controlled trial was conducted at a public primary care clinic in Malaysia. Adults aged 18 years or older with type 2 diabetes for at least six months and poor glycaemic control were randomly assigned to receive either a web-based educational video intervention or standard care. The intervention consisted of culturally adapted, multilingual educational videos covering diabetes self-care, medication use, diet, physical activity, and complication prevention, supported by monthly follow-up reminders. Primary outcomes were diabetes knowledge and empowerment. Secondary outcomes included HbA1C, blood pressure, fasting lipid profile, body mass index, and waist circumference. Outcomes were assessed at baseline, three months, and six months.

Results

A total of 232 participants were randomised into intervention and control groups (n = 116 each), with mean age of 59 years old, slight male predominance (53.0%) and mostly Malay (43.1%), with obesity (51.7%). Following the web-based intervention, participants demonstrated significant improvements in diabetes knowledge (β = 23.74, 95% CI: 20.57–26.91) and empowerment (β = 11.53, 95% CI: 9.98–13.09) compared with those receiving standard care at both three and six months (p < 0.001). Improvements in HbA1C, blood pressure, fasting lipid profile, body mass index, and waist circumference were also observed in the intervention group relative to controls (p < 0.05).

Conclusion

A culturally adapted, web-based educational video module was associated with improvements in diabetes knowledge, empowerment, and cardiometabolic outcomes among adults with poorly controlled type 2 diabetes. These findings support the use of web-based education as a scalable adjunct to standard diabetes care in primary care settings.

Supporting open science practices at multidisciplinary scale

2026-08-07T14:00:00Z

by Devin Soper, Lauren Cadwallader, Iain Hrynaszkiewicz

Mothers’ home management practices during febrile seizures in children under six years of age in Jordan

2026-08-07T14:00:00Z

by Maha Atout, Nouraldun M. Alhsenat, Huda Gharaibeh, Fatimah S. Tarawneh, Atheer Qashou

Background

Febrile seizure is the most prevalent seizure disorder among young children, and it commonly occurs in the home setting, where mothers are often the first responders. First-aid management of febrile seizures is also important to avoid complications and help parents feel less anxious. Nevertheless, there is a paucity of evidence describing the home-management practices of mothers in Jordan.

Objective

The purpose of this study was to describe the home-management practices of mothers of children under six years of age with febrile seizures in Jordan and to determine factors associated with appropriate and inappropriate practices.

Methods

A cross-sectional descriptive survey design was used. Data were collected between August and December 2021 from mothers attending pediatric outpatient clinics and pediatric wards in two public hospitals in northern Jordan. A structured questionnaire developed by Elbilgahy and Abd El Aziz (2018) was used to assess mothers’ home-management practices. Predictors of mothers’ home-management practices were analyzed using SPSS version 26, descriptive statistics, Pearson correlation analysis, and backward multiple regression analysis.

Results

In total, 68.4% of the mothers exhibited proper home-management behaviors in the course of febrile seizure. The majority of mothers reported that they put the child in a safe position (86.9%), noticed the manifestations and duration of seizures (84.5%), and tried to decrease body temperature (85.7%). Nevertheless, a considerable percentage of them were panic (61.9%) and doing the wrong things like cardiac massage (23.8%). Regression analysis showed that higher maternal knowledge and more positive attitudes were significantly associated with better home-management practice scores, which explained 27% of the variance of home-management practices among mothers.

Conclusion

Despite the fact that over two-thirds of mothers showed proper actions, there were still gaps in some essential first-aid actions in case of febrile seizures. There were a number of factors that were linked to home-management practices by mothers, which underscored the need to enhance the education of caregivers about the first-aid management of febrile seizures. Specific educational programs by healthcare providers are required to enhance the response of caregivers and encourage safe home management of febrile seizures among children.

A novel approach to UAV control: Fuzzy PID-based ANFIS (FPIDANFIS)

2026-08-07T14:00:00Z

by Nigatu Wanore Madebo, Feleke Tsegaye Yareshe, Lebsework Negash Lemma

This paper presents a novel hybrid control strategy, the Fuzzy PID based Adaptive Neuro-Fuzzy Inference System (FPIDANFIS), designed to enhance the trajectory tracking performance of Unmanned Aerial Vehicles (UAVs). The distinct contribution of this work lies in its data-driven design approach: historical input–output data from a baseline Fuzzy PID (FPID) controller using tracking error and its derivative as inputs and FPID control signals as outputs are leveraged to train an ANFIS model that autonomously generates the adaptive FPIDANFIS controller. This methodology differs from existing studies by enabling the new controller to inherit the baseline controller’s behavior while introducing adaptive capabilities not present in conventional FPID frameworks. A dataset of 5001 samples is generated using MATLAB’s Neuro-Fuzzy Designer toolbox for offline training with a hybrid learning algorithm and Gaussian membership functions. Once trained, FPIDANFIS dynamically tunes control actions in real time, improving robustness and adaptability under uncertainty. The controller is evaluated across three scenarios: nominal trajectory tracking, tracking with input disturbances, and tracking under parameter variations. Performance is quantified using the Integral of Time-weighted Absolute Error (ITAE). Simulation results show that FPIDANFIS outperforms the baseline FPID controller, achieving a 42% ITAE reduction under disturbances and a 22.12% reduction under parameter variations. The proposed method introduces a data-driven, adaptive extension of the FPID framework and demonstrates significant improvements in UAV trajectory tracking accuracy, making it suitable for applications requiring precise and robust maneuverability.