bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis
Authors: Vali Masoumeh , Nezhad Hossein Motahari , Kovacs Levente , Gandomi Amir H 
Published: January 2025

Abstract
This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-traumatic stress disorder (PTSD) predictive models. We conducted a systematic review and random-effect meta-analysis summarizing predictive model development and validation studies using machine learning in diverse samples to predict PTSD. Model performances were pooled using the area under the curve (AUC) with a 95% confidence interval (CI). Heterogeneity in each meta-analysis was measured using I2. The risk of bias in each study was appraised using the PROBAST tool. 48% of the 23 included studies had a high ROB, and the remaining had unclear. Tree-based models were the primarily used algorithms and showed promising results in predicting PTSD outcomes for various groups, as indicated by their pooled AUCs: military incidents (0.745), sexual or physical trauma (0.861), natural disasters (0.771), medical trauma (0.808), firefighters (0.96), and alcohol-related stress (0.935). However, the applicability of these findings is limited due to several factors, such as significant variability among the studies, high and unclear risks of bias, and a shortage of models that maintain accuracy when tested in new settings. Researchers should follow the reporting standards for AI/ML and adhere to the PROBAST guidelines. It is also essential to conduct external validations of these models to ensure they are practical and relevant in real-world settings.
Mapping provider and consumer voices using the AACTT framework: a focus group study of advance care planning
Authors: Guccione Lisa , Best Stephanie , Fullerton Sonia , Aranda Sanchia , Francis Jill J. 
Published: January 2025

Abstract

Background
The provision of healthcare is complex. When evidence-practice gaps are identified, interventions to improve practice across multi-level systems are required. These interventions often consist of multiple interacting components and behaviours. To effectively address these complexities, it is crucial to first identify the specific roles and actions required at each stage of the intervention. This approach enables a thorough examination of what is working well and what needs to be optimised. The action, actor, context, target, time (AACTT) framework provides a consistent approach to identifying key elements such as ‘who’ (actor) does ‘what’ (action), ‘where’ (context), ‘to or with whom’ (target) and ‘when’ (time). To our knowledge the AACTT has not yet been applied: 1) to specify complex interventions across patient journeys; and 2) to investigate consumer views, despite the importance of patient-centred care.

Aim
Using advance care planning (ACP) as an exemplar complex healthcare process, we describe a method for using the AACTT framework to 1) map a complex model of care across a patient journey 2) capture the consumer perspective; and 3) operationalise these perspectives by comparing across groups and identifying alignments or misalignments.

Methods
Two groups were recruited (healthcare professionals and consumers). Informed by the AACTT framework, four focus groups discussed the process of ACP across existing care pathways. Maps visually representing the perspectives and preferences of healthcare professionals and consumers were co-created iteratively. Qualitative data was deductively coded to the AACTT framework and inductively coded to identify themes within domains. Maps were circulated for critical feedback and refined.

Results
Healthcare professional (n-13) and consumer perspectives (n = 11) highlighted what is ‘currently occurring’ in practice, what is ‘not occurring’, and what ‘should be occurring’ to align practice with consumer preferences of care. Comparing participant perspectives identified that most misalignment occurred within the actor, context, and time domains. Misalignment was found predominantly in actions ‘occurring sometimes’, with no converging perspectives reported for the context and time domains.

Conclusion
This novel application of the AACTT framework systematically brings in the consumer voice in ways that may influence the delivery of care. This approach to specifying healthcare professional and consumer perspectives across a complex care pathway identifies barriers that are not found with traditional mapping methods or in current applications of the AACTT framework.
A realist evaluation to explain and understand the role of paramedics in primary care
Authors: Eaton Georgette , Wong Geoff , Tierney Stephanie , Williams Veronika , Mahtani Kamal R. 
Published: January 2025

Abstract

Background
In response to the unsustainable workload and workforce crises in primary care, paramedics (with their generalist clinical background acquired from ambulance service experience) are increasingly employed in primary care. However, the specific contribution paramedics can offer to the primary care workforce has not been distinctly outlined. We used realist approaches to understand the ways in which paramedics impact (or not) the primary care workforce.

Methods
A realist evaluation was undertaken, consisting of three independent but inter-related research studies:

In WP1, a mixed-methods cross-sectional survey of paramedics in primary care in the UK was conducted to comprehend the existing practices of paramedics within the NHS.

WP2 involved an analytic auto-netnography, where online conversations among paramedics in primary care were observed to understand paramedics’ perceptions of their role.

WP3 utilised focused observations and interviews to delve into the impact of paramedics on the primary care workforce. This comparative study collected data from sixty participants across fifteen sites in the UK, and twelve participants across three sites in a specific region in Canada, where Community Paramedicine is well established.

Results
The culmination of findings from each phase led to the development of a final programme theory, comprising of 50 context-mechanism-outcome configurations (CMOCs) encompassing three conceptual categories: Expectations associated with paramedics in primary care, the transition of paramedics into primary care roles, and the roles and responsibilities of paramedics in primary care.

Conclusions
Our realist evaluation used a mixed-method approach to present empirical evidence of the role of paramedics in primary care. It offers insights into factors relating to their deployment, employment, and how they fit within the wider primary care team. Based on the evidence generated, we produced a series of practice implementation recommendations and highlighted areas for further research.
Extracellular cold-inducible RNA-binding protein in CNS injury: molecular insights and therapeutic approaches
Authors: Lapin Dmitriy , Sharma Archna , Wang Ping 
Published: January 2025

Abstract
Central nervous system (CNS) injuries, such as ischemic stroke (IS), intracerebral hemorrhage (ICH) and traumatic brain injury (TBI), are a significant global burden. The complex pathophysiology of CNS injury is comprised of primary and secondary injury. Inflammatory secondary injury is incited by damage-associated molecular patterns (DAMPs) which signal a variety of resident CNS cells and infiltrating immune cells. Extracellular cold-inducible RNA-binding protein (eCIRP) is a DAMP which acts through multiple immune and non-immune cells to promote inflammation. Despite the well-established role of eCIRP in systemic and sterile inflammation, its role in CNS injury is less elucidated. Recent literature suggests that eCIRP is a pleiotropic inflammatory mediator in CNS injury. eCIRP is also being evaluated as a clinical biomarker to indicate prognosis in CNS injuries. This review provides a broad overview of CNS injury, with a focus on immune-mediated secondary injury and neuroinflammation. We then review what is known about eCIRP in CNS injury, and its known mechanisms in both CNS and non-CNS cells, identifying opportunities for further study. We also explore eCIRP’s potential as a prognostic marker of CNS injury severity and outcome. Next, we provide an overview of eCIRP-targeting therapeutics and suggest strategies to develop these agents to ameliorate CNS injury. Finally, we emphasize exploring novel molecular mechanisms, aside from neuroinflammation, by which eCIRP acts as a critical mediator with significant potential as a therapeutic target and prognostic biomarker in CNS injury.
MaveDB 2024: a curated community database with over seven million variant effects from multiplexed functional assays
Authors: Rubin Alan F. , Stone Jeremy , Bianchi Aisha Haley , Capodanno Benjamin J. , Da Estelle Y. , Dias Mafalda , Esposito Daniel , Frazer Jonathan , Fu Yunfan , Grindstaff Sally B. , Harrington Matthew R. , Li Iris , McEwen Abbye E. , Min Joseph K. , Moore Nick , Moscatelli Olivia G. , Ong Jesslyn , Polunina Polina V. , Rollins Joshua E. , Rollins Nathan J. , Snyder Ashley E. , Tam Amy , Wakefield Matthew J. , Ye Shenyi Sunny , Starita Lea M. , Bryant Vanessa L. , Marks Debora S. , Fowler Douglas M. 
Published: January 2025

Abstract
Multiplexed assays of variant effect (MAVEs) are a critical tool for researchers and clinicians to understand genetic variants. Here we describe the 2024 update to MaveDB (https://www.mavedb.org/) with four key improvements to the MAVE community’s database of record: more available data including over 7 million variant effect measurements, an improved data model supporting assays such as saturation genome editing, new built-in exploration and visualization tools, and powerful APIs for data federation and streamlined submission and access. Together these changes support MaveDB’s role as a hub for the analysis and dissemination of MAVEs now and into the future.
Developing generic clinical trial animated explainer videos in the UK: results of a survey and case study
Authors: Calvert Clare , Barber Vicki S. , Appelbe Duncan , Sprange Kirsty , Nollett Claire , Lugg-Widger Fiona , Tanner Samantha , Richards Duncan B. 
Published: January 2025

Abstract

Background
Animated short videos used to explain a concept or project are often called animated explainer videos (AEVs). AEVs can supplement or provide an alternative to participant information sheets as a means of giving information about clinical research to potential participants. Current use of AEVs tends to focus on the specifics of a particular trial, yet there are many common aspects of clinical research regardless of the interventions being investigated that can be poorly covered in current trial materials. The EXPLAIN initiative aimed to determine the top generic clinical trial topics considered most important by different UK trial stakeholders. The top three topics were then turned into AEVs and have been made freely available for use.

Method
A list of generic clinical trial topics which often need explaining to potential trial participants when they are approached to take part in research was developed. Using a two-round Delphi survey of stakeholder groups (trial participants, patients, members of the public, site staff and clinical trials unit staff), the list of topics was expanded and prioritised to identify the topics most in need of clear explanation. The top three topics formed the basis of three AEVs, co-developed with patient and public partners.

Results
Two hundred twenty-eight responses were received to the first round of the Delphi survey, and 167 of these respondents also completed the second round of the survey. The three topics prioritised for creation of animated explainer videos were as follows: (1) What is consent? (2) Who decides what treatment I get/What is randomisation? (3) Is it safe to take part in a trial/How do you know a trial is safe? Following virtual meetings with patient and public partners recruited from the Delphi respondents, a script for each AEV was co-produced before being developed into an AEV by a company specialising in animated video production.

Conclusion
There are a wide range of generic concepts in which the use of animated explainer videos could be useful to improve participant understanding of clinical research. Via consensus survey across multiple stakeholders, we have determined a hierarchy of the importance of explaining these concepts. We envisage that the three AEVs created from this project will form the basis of a readily accessible library of animations to be utilised by trialists.
Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy
Authors: Wan Qi , Lindsay Clifford , Zhang Chenxi , Kim Jisoo , Chen Xin , Li Jing , Huang Raymond Y. , Reardon David A. , Young Geoffrey S. , Qin Lei 
Published: January 2025

Abstract

Background
Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. Manual segmentation of the tumor components is time-consuming and poses significant reproducibility issues. We compare the prediction of overall survival (OS) in recurrent high-grade glioma(HGG) patients undergoing immunotherapy, using deep learning (DL) classification networks along with radiomic signatures derived from manual and convolutional neural networks (CNN) automated segmentation.

Materials and methods
We retrospectively retrieved 154 cases of recurrent HGG from multiple centers. Tumor segmentation was performed by expert radiologists and a convolutional neural network (CNN). From the segmented tumors, 2553 radiomic features were extracted for each case. A robust feature subset was selected using intraclass correlation coefficient analysis between manual and automated segmentations. The data was divided into a 9:1 ratio and validated through ten-fold cross-validation and tested on a rotating test set. Features selection was done by the Kruskal–Wallis test. The Radiomics-based OS predictions, generated using Support Vector Machine (SVM), were compared between the two segmentation approaches and against OS prediction by the CNN model adapted for classification. Model efficacy was evaluated using the area under the receiver operating characteristic curve (AUC).

Results
The clinical model AUC for OS prediction was 0.640 ± 0.013 (mean ± 95% confidence interval) in the training set and 0.610 ± 0.131 in the test set. The radiomics prediction of OS based on manual segmentation outperformed automatic segmentation (AUC of 0.662 ± 0.122 vs. 0.471 ± 0.086, respectively) in the test set. Robust features improved the performance of manual segmentation to AUC of 0.700 ± 0.102, of automated segmentation to 0.554 ± 0.085. The CNN prognosis model demonstrated promising results, with an average AUC of 0.755 ± 0.071 for training sets and 0.700 ± 0.101 for the test set.

Conclusion
Manual segmentation-derived radiomic features outperformed automated segmentation-derived features for predicting OS in recurrent high-grade glioma patients undergoing immunotherapy. The end-to-end CNN prognosis model performed similarly to radiomics modeling using manual-segmentation-derived features without the need for segmentation. The potential time-saving must be weighed against the lower interpretability of end-to-end black box modeling.
Development of a control support system for smart homes using the analysis of user interests based on mixed reality
Authors: Sone Yuka , Matsumoto Chifuyu , Woo Jinseok , Ohyama Yasuhiro 
Published: January 2025

Abstract
In recent years, IoT technologies have made our daily lives more convenient and comfortable. In particular, these technologies are being actively utilized in our living environments through the development of various smart home appliances. As the pace of Digital Transformation (DX) quickens and digital platforms become integrated into diverse residential settings, the notion of the home we inhabit is taking on greater significance beyond merely a place for rest. Therefore, this paper explains the development of user-friendly interfaces for smart home systems used in our living rooms. An appropriate service can be provided accordingly if the user’s intent is specifically understood. Therefore, this paper explores the relationship between the user’s gaze and the control targets of the smart home using Mixed Reality (MR) devices. In this study, we introduce a novel smart home control system from a range of options. Our proposed system enables user analysis and remote control through the utilization of an MR device capable of tracking a user’s gaze. In addition, we investigate the perception of user interfaces and analyze the survey results conducted after using the interface system, discussing the validity of the proposed system.
Formulation for foliar and soil application of entomopathogenic nematodes for controlling the onion thrips Thrips tabaci Lindeman (Thysanoptera: Thripidae)
Authors: Metwally Hala M. S. , Saleh Mahmoud M. E. , Abonaem Mokhtar 
Published: January 2025

Abstract

Background
Onion thrips (Thrips tabaci Lindeman) are a main threat to onion (Allium cepa L.) production worldwide. Entomopathogenic nematodes (EPNs) are recommended as environmentally acceptable alternatives to chemical management for a wide range of economic insect pests. EPNs are widely used and provide good control over insect pests that live in the soil. Adjuvant-based formulation of EPN solutions has enhanced longevity and potency on foliage. In this study, tests were performed to compare two EPN application techniques for controlling the onion thrips in the open field. The first technique was the traditional spray technique, while the second one was the nematode-infected insect technique. Side experiments were conducted to investigate the influence of different adjuvants on the persistence of Steinernema feltiae (Filipjev) sprayed on onion plants in a semi-field setting.

Results
In semi-field experiments, the results suggested that Tween 80 or Xanthan was suitable for increasing the persistence of S. feltiae on onion plants. In the spray technique, application of Heterorhabditis bacteriophora (Poinar), at 1000 infective juveniles (IJs)/ml, combined with 0.3% Tween 80, reduced the thrips population on onion leaves by 63% in three days. However, it remained effective for only three days post-application. Using the nematode-infected insect approach, a single application of 10 H. bacteriophora-infected Tenebrio molitor L. larvae per 1 m of the row (70 cm between rows) remained effective in the onion field for 5 weeks, following treatment, generating a pest population reduction of up to 77%, while the same rates of S. feltiae reduced the pest population by up to 59%.

Conclusions
In onion fields, the nematode-infected insect technique was proved to be more effective and long-persisted than the traditional spray technique for controlling T. tabaci in onion fields. Further research work is still needed to improve the ease of use of the recommended approach.
Early dual antiplatelet therapy (DAPT) administration within 6 h post-coronary artery bypass grafting (CABG): an audit, pilot study, and follow-up analysis
Authors: Chen Yen Chuan , Abdul Aziz Khairul Anuar , Md Taib Mohamed Ezani , Mohamed Yunus Alwi , Gaaffar Intan Fariza 
Published: January 2025

Abstract

Background
The optimal timing for administering dual antiplatelet therapy (DAPT) post-coronary artery bypass grafting (CABG) remains a subject of debate. This study aimed to evaluate the safety and efficacy of early DAPT administration within 6 h post-CABG, following the implementation of a new standard operating procedure (SOP). This study was conducted in three phases at the National Heart Institute of Malaysia. Phase 1 involved a clinical audit of 80 isolated CABG patients to evaluate current DAPT practices. Phase 2 was a pilot study involving 320 patients to establish criteria for early DAPT initiation. Phase 3 comprised a prospective cohort analysis comparing outcomes between 939 propensity-matched pairs receiving early/new SOP (< 6 h) and late/old SOP (> 6 h) DAPT.

Results
The clinical audit revealed a mean DAPT administration time of 18.3 h post-CABG, highlighting variability in practice. The pilot study demonstrated that early DAPT was associated with a significantly lower chest reopening rate (0.8% vs. 21.6%) under stringent selection criteria. In the follow-up study, early DAPT was linked to reduced rates of postoperative stroke (1.0% vs. 2.5%, p = 0.013), dialysis (5.5% vs. 7.0%, p < 0.001), and chest reoperation (6.5% vs. 9.0%, p = 0.045). Despite a higher transfusion rate in the early DAPT group (76.0% vs. 43.6%, p < 0.001), ICU stays and hospitalization durations were not prolonged. Mortality rates were lower in the early DAPT group (3.2% vs. 4.6%), although the difference was not statistically significant (p = 0.123).

Conclusions
Guided by stringent clinical criteria, early DAPT administration within 6 h post-CABG is a feasible and effective strategy for reducing adverse outcomes, such as stroke and dialysis requirements, while maintaining manageable bleeding risks. Future research should explore long-term graft patency, refine transfusion protocols, and assess the broader applicability of this approach.
Burden of psychiatric and somatic comorbidities in individuals with suicidal behavior: a nationwide Danish registry-based, observational study
Authors: Reilev Mette , Møller Jens-Jakob Kjer , Stenager Elsebeth , Christiansen Erik 
Published: January 2025

Abstract

Background
Many psychiatric and somatic comorbidities increase the risk of suicidal behavior, but the effect of co-existing comorbidities is sparsely elucidated. We described co-existence of psychiatric and somatic comorbidities and the influence of the combined comorbidity burden on the risk of suicidal behavior.

Methods
We defined two case populations above 10 years in the Danish health registries: those who 1) died by suicide (2010–2020) and 2) had an incident suicide attempt (2010–2021). Co-existing somatic and psychiatric comorbidities and relative odds of suicidal behavior at increasing comorbidity burden were assessed.

Results
Among 5.9 million Danish citizens (2021), 6,257 individuals died by suicide whereas 30,570 had an incident suicide attempt. More than half had ≥2 co-existing psychiatric and/or somatic comorbidities. Of those who died by suicide, 18% had co-existing mood disorders and stress disorders, while 5% had both mood disorders and cancer. An 88-fold increase of odds for attempting suicide and a 35-fold increase of odds for suicide were observed among those with the highest combined burden of somatic and psychiatric comorbidities relative to those without. The presence of somatic comorbidities seemed to protect against suicide in older individuals.

Conclusions
Psychiatric and somatic comorbidities commonly co-exist in individuals with suicidal behavior. Higher combined burden of psychiatric and somatic comorbidities increased the odds of suicidal behavior, though the presence of somatic diseases had a potential protective effect on the risk of suicide in older individuals. This warrants collaboration and enhanced awareness of suicidal behavior risks across somatic and psychiatric departments.