F1000Research

Introduction: Aphasia is an acquired language disorder with a significant negative functional impact. Much of the research on aphasia has focused on word-level language comprehension and production. Further evaluation of discourse-level tasks, both at behavioral and neural levels, will allow for an ecologically valid understanding of the functional implications of language impairment in this population. Method: This study evaluated bilateral frontal, temporal, and parietal cortical activity during computer-based narrative production in 14 young neurotypical individuals, 17 individuals with post-stroke aphasia, and 15 age-matched neurotypical participants using functional near-infrared spectroscopy (fNIRS). Oxygenated hemoglobin (HbO) was measured during narrative production following short video clips and compared to HbO during counting aloud. In addition, behavioral measures quantifying in-task performance were correlated with averaged HbO values. Results: Young neurotypical individuals showed greater cortical activity in bilateral language regions for narrative production compared to counting aloud. In contrast, people with aphasia showed positive condition-related effects in the right frontal ROI and the age-matched group showed positive condition-related effects in the left frontal and right precentral ROIs. Each group showed different patterns in relationships between cortical activity and discourse performance measures. Conclusion: Overall, young participants showing more consistent condition-related effects for narrative discourse production than individuals with aphasia and age-matched controls. This study shows the potential for fNIRS to evaluate cortical activity for ecologically valid language tasks in individuals with post-stroke aphasia.

ImportanceChildren with Down syndrome (DS), a genetic condition associated with neuromotor impairments, walk [~]1 year later than typically developing peers. Treadmill training is the most successful known intervention for accelerating walking onset in DS. Overground stepping with mobility devices better mimics critical properties of real-world walking, but it is unknown how overground stepping develops in pre-walking infants with DS. ObjectiveWe aimed to characterize the developmental trajectory of stepping quantity and quality in supported overground stepping compared to supported treadmill stepping. We also measured infants ability to self-propel in the walker. Finally, we assessed caregivers perspectives on both devices. DesignWe tested infants at 10, 13, 16, and/or 19 months of age. SettingThis study occurred in a university laboratory in the United States. ParticipantsWe tested 31 pre-walking infants with Down syndrome across 69 sessions. ExposureAt each session, infants completed four trials per task (treadmill and walker) and a test of self-propulsion in the walker. Main Outcomes and MeasuresWe measured step quantity (overall step rate and alternating step rate), step quality (percentage of steps that were alternating, forward, and flat-landing), the ability to self-propel the walker, and caregiver perspectives on both devices. ResultsStep quantity increased with age and varied by task--infants took more steps per minute in the walker compared to the treadmill. Moreover, steps were of equal or higher quality in the walker. By 16 months, about half of infants could self-propel. Caregivers viewed both devices favorably, though the majority preferred the walker for home and/or community use. ConclusionsOverground walkers promote more stepping than a treadmill in pre-walking infants with DS, with stepping of similar or higher quality. Caregivers feel positively about overground walkers. RelevanceOverground stepping using a suspension walker shows promise as an intervention for pre-walking infants with Down syndrome.

Aim: Healthy Heart Actions Right Time (HHART) is a multi-phased research project that seeks to identify, implement and evaluate strategies to connect community and clinical activities to reduce the burden of heart disease for Aboriginal and Torres Strait Islander people. The aim in Phase One was to identify priority activities for two participating services. Background: The ongoing effects of colonisation drive a disproportionate burden of heart disease for Aboriginal and Torres Strait Islander people. Clinical and community groups both have established strengths in reducing the risk of heart disease, but these are not always well connected. Methods: Using a case study methodology in two locations we partnered in a 12-month co-design process to identify priority activities to connect clinical and community activities. Findings: Three priorities emerged from the Phase One co-design process: (i) community-led gardening as a strategy to promote heart health through connection and healthy lifestyles; (ii) community days to increase engagement in heart checks and strengthen community-clinic relationship; and (iii) clinic-led development of culturally relevant education resources to promote clinician confidence and community heart health knowledge.

Abstract Objective. To determine the incidence and identify independent clinical predictors of emergence delirium (ED) in children aged 2-12 years. Material and methods. A prospective observational study included 56 children aged 2-12 years undergoing elective surgery under general anaesthesia. Preoperative anxiety (m-YPAS), induction behaviour (4 point scale), anaesthesia duration, opioid use, and postoperative pain (FLACC) were assessed. ED was diagnosed when the maximum PAED score was [≥]12. Results. The incidence of ED was 55.4% (31/56). Univariate analysis with false discovery rate (FDR) correction identified significant associations with ED for anaesthesia duration (q=0.002), induction behaviour (q=0.007), and surgery type (q=0.027). Multivariable logistic regression revealed three independent predictors: induction behaviour (category 3 vs 1) - odds ratio (OR) 14.2 (95% CI 2.6-78.1); anaesthesia duration (per minute) - OR 1.07 (95% CI 1.02-1.13); opioid use - OR 12.1 (95% CI 1.3-113.0). The model showed good discriminatory ability: area under the ROC curve (AUC) = 0.83 (95% CI 0.72-0.94). Conclusion. Emergence delirium in children aged 2-12 years without pharmacological premedication occurs in 55.4% of cases. The strongest independent predictors are adverse induction behaviour, longer anaesthesia duration, and intraoperative opioid use. The derived model can be used for personalised risk stratification of ED. Keywords: emergence delirium; children; risk factors; PAED; prediction model.

Abstract Purpose:Comparison of ocular parameters (ACD, AL, LT, VL, CCT, ASD, LC, LT/ACD) in preterm infants with retinopathy after treatment, those with spontaneous regression, and those without retinopathy, at postmenstrual (ages of 0 (40 weeks), 3 , and 6 months. Methods: Cross-sectional study. This research involved 297 premature infants assigned to three groups based on fundus results and intravitreal injection therapy: an ROP post-injection group, an ROP spontaneous regression group, and a non-ROP group. Axial length (AL), anterior chamber depth (ACD), l e n s t h i c kn e s s (LT), and vitreous length (VL) were assessed in all three groups using a corneal thickness meter at po st menstrual age s (PMA) of 0, 3, and 6 months. Derived parameters--ASD ((ACD + LT), LC ((ACD + LT/2), and LT/ACD--were subsequently calculated. A one-way ANOVA analysis revealed statistically significant differences in these ocular parameters among the groups (P < 0.05). Results: Significant differences e m e r g e d in anterior chamber depth (ACD) and l e n st h i c k n e s s ( LT) between the ROP post-injection group, ROP spontaneous regression group, and non-ROP group at 0, 3, and 6 (months postmenstrual age (PMA). At 0 months PMA: ACD(F=4.33, P=0.014), LT (F=5.45, P=0.005). At 3 months PMA: ACD (F=17.20, P<0.01), LT(F=15.23, P<0.01). At 6 months PMA: ACD (F=17.89, P<0.01), LT (F=17.21, P<0.01). Central corneal thickness (CCT) also differed significantly among the three groups at 0 months PMA(P <0 .0 1 ). All ocular parameters correlated significantly with Postmenstrual Age, with CCT and LT showing a negative correlation. Before 6 months PMA, axial length (AL) and vitreous length (VL) increased significantly, and ACD deepened significantly across all groups (P <0 .05 ). However , LT exhibited no significant change within the ROP group (post-injection group P=0.4; spontaneous regression group P=0 .33). No significant differences existed in any ocular parameters between the ROP post-injection group and the ROP spontaneous regression group (P>0.05). Conclusions: Before 6 months of postmenstrual age (PMA), axial length (AL), vitreous length (VL), and anterior chamber depth (ACD) were increased between the ROP group and non-ROP group; lens thickness (LT) remained unchanged in the ROP group but increased in the non-ROP group. The injection group and the spontaneous regression group showed no significant differences. The primary factors influencing anterior segment development were birth weight (BW), gestational age (GA), and postmenstrual age (PMA).

INTRODUCTION In the multiple-risk approach of cardiovascular disease management, communication of cardiovascular disease risk and its prevention play a significant role. in Sri Lanka, this function is conducted via Healthy Lifestyle Centres. METHODOLOGY A clinical audit was conducted to describe communication quality in 79 healthy lifestyle centers. A checklist developed based on Patient-Centered Communication Tools with the support of an expert panel. Two trained observers independently conducted the observations while the healthcare provider at the Healthy Lifestyle Centre revealed details of cardiovascular disease risk communication and health education sessions. RESULTS: The majority of Healthy Lifestyle Centers involved patients in decision-making (n = 228, 92.0%), explained patient choices (n = 230, 92.8%) and responded to patients' interest in decision-making (n =2 35, 99.2%). Most patients received a summary (n =159,67.1%), a follow-up plan (n =212,89.5%) and were communicated in a jargon-free language (n =127,53.6%). The majority of sessions demonstrated satisfactory use of examples (95.7%, n = 22), and responsiveness to questions (73.9%, n =17). However, most sessions were unsatisfactory regarding provision of a follow-up plan (95.7%, n = 22), encouragement of questions (95.7%, n = 22), allowing clients to talk (87.0%, n = 20), and active listening (69.6%, n = 16). CONCLUSIONS: Strengthening healthcare worker training in patient-centred communication especially shared decision-making, active listening, and encouraging patient questions are essential to improve cardiovascular disease risk communication and patient adherence to preventive guidelines at Healthy Lifestyle Centres. Key words Communication, Cardiovascular disease risk, health communication, effective communication, paternalistic healthcare

Background: Black patients and individuals with low socioeconomic status (SES) face significant disparities in accessing curative therapies for hepatocellular carcinoma (HCC), including liver transplantation. This study aimed to develop provider-co-created intervention prototypes in response to patient-identified barriers and recommendations. Methods: A human-centered design session with hepatology and transplant providers at a large academic medical center was conducted. Prior to the session, participants were presented with barriers and preliminary solutions identified through an earlier human-centered design session with Black and low-SES patients. Using structured ideation methods, including brainwriting, challenge mapping, and concept voting, providers co-created intervention prototypes. Final concepts were synthesized from patient insights, provider input, and design methods using affinity diagramming and concept modeling. Results: Nine providers participated in the session. They focused on three key areas for intervention: inefficiencies in transplant pre-evaluation, inadequate social support, and information overload. Solutions included: (1) a structured triage pathway to standardize referrals and reduce delays; (2) a peer navigator model to guide patients through the transplant process; and (3) a multimodal transplant education roadmap to improve comprehension and engagement. These prototypes addressed both patient- and system-level barriers. Conclusions: Protypes developed through provider-led design, grounded in patient-identified barriers and co-created ideas, can yield actionable, scalable strategies to advance equity in HCC care. Future work will refine these prototypes through patient feedback and pilot them in clinical settings.

Background Informed consent depends on patients' understanding of anaesthesia risk, yet comprehension remains poor despite routine preoperative consultation. Conversational artificial intelligence (AI) could establish patient-reported understanding before clinician contact, but whether such systems can achieve patient-reported understanding comparable to clinician-delivered education remains unknown. Methods We conducted a randomised equivalence trial (n = 130) of PEAR (Preoperative Education of Anaesthesia Risks), a multilingual retrieval-augmented conversational AI grounded in institutional consent materials, versus standard preoperative consultation in adults undergoing elective surgery. Results A total of 130 adults (mean age 52.4 +/- 14.5 years) were enrolled. Post-consultation understanding scores in the PEAR group met the pre-specified equivalence criterion compared with standard consultation across all three primary measures. Patients who interacted with PEAR before clinician contact achieved understanding scores comparable to those receiving standard face-to-face consultation alone. PEAR reduced documentation and consultation time, corresponding to a projected annual net benefit of approximately SGD 0.99 million (USD 0.78 million) at a single tertiary centre. Conclusions A retrieval-augmented conversational AI achieved patient-reported understanding of anaesthesia risk equivalent to standard preoperative consultation while substantially improving workflow efficiency. These findings support supervised deployment of conversational AI within perioperative care pathways while preserving clinician oversight for verification and patient-specific decision-making.

Background: Electrolyte replacement is ubiquitous in the acute care setting, but its familiarity cannot belie that even small dosing errors with potassium can cause lethal cardiac arrhythmias. Recently, MedAgentBench offered a benchmark for agentic artificial intelligence (AI) including the ability to correctly dose potassium based on a single rule; however, this does not adequately reflect the clinical complexity or safety concerns of an agent that has been used as the lethal injection. The purpose of this analysis was to a probe leaderboard large language model (LLM) capabilities to follow basic dosing rules to safely replace potassium in a series of clinician-annotated cases. Methods: Using a clinician panel, we developed a series of dosing principles and 20 clinical cases reflective of the complexity of potassium replacement. External clinicians were surveyed to assess practice variability and agreement to clinician panel answers. We tested GPT-5-chat with each case in triplicate, with and without the clinician curated dosing principles, and prompted the model to answer six questions involving potassium goals, dosing, route, lab frequency, concurrent interventions, and the model's perceived level of confidence for the output and complexity of the case. The primary outcome was the rate of appropriate recommendations in comparison to clinician answers. Results: A total of 54 clinicians reviewed the 20 hypokalemia cases and hypokalemia dosing guideline. Clinicians expressed "highly agree" or "somewhat agree" for 66.8% of the cases evaluated when asked if they agree with the guideline-recommended management. When given the potassium dosing guideline, total errors dropped from 165 to 104, and average accuracy improved from 45% to 65% with GPT-5-Chat. GPT-5-Chat conveyed a high level of confidence for 100% of responses, while labeling 80% and 76% of cases as highly complex with and without the criteria, respectively. Potential harm scores were considerable in both groups, however, a notable reduction in severity scores occurred with the dosing guidance document. Recommendations on concurrent interventions and dosing had the highest rate of errors in both groups. Conclusions: Benchmarks must appropriately reflect clinical complexity to be considered valuable for the deployment of agentic artificial intelligence tools in the healthcare domain. GPT-5-Chat assessment on a comprehensive medication management task for potassium replacement showed improvement with dosing guidance, yet unfit benchmarking performance.

Numbers of research articles studying circRNAs have increased rapidly since 2017. Previous analyses of human circRNA articles in two high impact factor cancer research journals identified papers with wrongly identified nucleotide sequence reagents and circRNAs whose identities could not be independently verified. In the present study, verification of human nucleotide sequence reagent and cell line identities in retracted circRNA articles published from 2017-2021 in high impact factor journals found wrongly identified nucleotide sequences and/or cell lines in all 13 retracted papers. Similar analyses of human circRNA papers published in high impact factor journals in 2022 found wrongly identified, non-verifiable and/or questionable reagents in 71% (84/118) papers, where 51% (60/118) papers described at least one wrongly identified reagent. When individual error types and features of concern were considered, 2022 circRNA papers described wrongly identified nucleotide sequence reagents (52/118, 44%), questionable circRNA probes that did not meet accepted targeting requirements (34/118, 29%), non-verifiable nucleotide sequences (25/118, 21%), wrongly identified cell lines (22/118, 19%), and/or non-verifiable cell line identifiers (6/118, 5%). In summary, wrongly identified, non-verifiable and/or questionable reagents were unexpectedly frequent in human circRNA papers in high impact journals, highlighting the need for critical engagement with the circRNA literature.

Background Unplanned hospital admissions in Inflammatory Bowel Diseases (IBD) account for nearly three-quarters of IBD inpatient stays in the United Kingdom. Although costly to services and distressing for patients, research exploring experiences and potential drivers of admissions is limited. We undertook a qualitative study to explore the healthcare experiences and access needs of people with IBD who had unplanned admissions, along with their caregivers and clinicians. Methods Semi-structured interviews with 25 participants from a single tertiary IBD service in England (17 people with IBD, 3 informal caregivers, 5 clinicians) were conducted. We applied thematic framework analysis, guided by the Candidacy Framework, and worked with 2 patient and public contributors to generate final themes. Results We identified four themes: 1) Difficulties in Identifying flares and asserting severity before admission, summarised the prevailing uncertainty in identifying a flare and access to timely IBD care. 2) Navigating a disjointed healthcare system, highlighted how lack of care plans and systemic barriers can delay access. 2) Emergency care access challenges highlighted the gaps in emergency and inpatient care during flares. Whilst 4) fighting for care and individual advocacy needs, described the persistent assertion for care that may disproportionally impact access to vulnerable groups, also highlighting the importance of positive interpersonal relationships. Conclusions Individual, interpersonal and healthcare factors across the patient pathway were perceived to shape access to care in unplanned IBD admissions. Potentially reducing admissions requires proactive strategies, including the integration of patient education, monitoring tools, establishment of specialist rapid-access pathways, and formal psychological support to address barriers to access.

Background/Aims: Neovascular glaucoma (NVG) is an aggressive secondary glaucoma with limited longitudinal data. This study reports the aetiologies, treatments, and longitudinal outcomes in NVG. Methods: Patients with NVG were identified through electronic medical record review. Inclusion required documented rubeosis of the iris and/or anterior chamber angle, intraocular pressure (IOP) [&ge;]25 mmHg, diagnosis during 2008-2024, and follow-up at Helsinki University Hospital. Baseline data and all follow-up visits were included. Results: Of 919 patients identified, 626 met inclusion criteria, with a median follow-up of 24 months. The estimated NVG incidence was 2.2/100,000/year. The most common aetiology was central retinal vein occlusion (CRVO; 45%), followed by diabetic retinopathy (DR; 14%), central retinal artery occlusion (CRAO; 11%), and ocular ischaemic syndrome (8%). Half of patients had hand motion vision or worse at baseline, with 18% at no light perception (NLP). At 5 years, 13% of patients had Snellen 6/60 vision or better. Visual outcomes differed by aetiology, with median time to NLP ranging from 1.6 (CRAO) to 9.1 (DR) years (log-rank p=0.002). Median baseline IOP was 40 mmHg, decreasing to 21 mmHg by 1 year. Ocular pain fell from 43% at baseline to 11% at last follow-up. Structural eye loss (e.g., enucleation or phthisis) occurred in 3% by 5 years. Conclusion: The estimated incidence was lower than previously reported elsewhere. Unlike other cohorts where DR predominates, CRVO was the most common aetiology, and visual prognosis was strongly aetiology-dependent. Glaucoma drainage device surgery reached 7.6% at 3 years, despite the severity and refractory nature of NVG.

Open educational resources (OERs) contain authentic materials that benefit students, but few studies have focused on the benefits to authors of OERs. This gap needs attention considering the challenges that OER authors face, given their commitments to multiple professional activities while also being motivated to take part in OER development. It is critical to understand what benefits authors receive, to help in the continued development of these valuable educational tools. To this end, we investigated what benefits a specific group of researcher-educators perceived from investing their limited time and energy to design, create, and share authentic OERs in the OCELOTS (Online Content for Experiential Learning of Tropical Systems) Research Coordination Network in Undergraduate Biology Education. Our study was based on conceptual frameworks for teaching and learning, communities of practice, and self-determination theory. We used qualitative data from a survey specifically designed to address the question of benefits perceived by OER authors, complemented with quantitative and qualitative data from existing internal evaluations of this network. In a content-analysis framework, we analyzed the open-ended responses to identify broader themes emerging about author benefits. OER authors reported improved pedagogical practice, increased visibility of research and outreach efforts, professional rewards, and increased collaborations. Authors reported gains in pedagogical knowledge and personal fulfillment as benefits that they received, along with satisfaction from contributing to their discipline and society in general. While benefits around improving pedagogical practice was the richest theme, creation of modules also generated new collaborations and helped strengthen and broaden authors professional networks. In particular, the sense of belonging to and building the community was a significant benefit, providing implications for how to support future OER development and the critical role of peer networks. We discuss connections across these themes and compare our results with related previous studies. These results indicate that sustained investment in intentionally designed, interdisciplinary networks can generate substantial and diverse benefits for the educators and researchers who create these resources. Open Research StatementThe de-identified data associated with this manuscript will be permanently archived in Zenodo, upon the acceptance of the manuscript.

IntroductionCellular differentiation and lineage commitment are known to be associated with differences in DNA methylation. Leiomyosarcoma (LMS) is a tumor thought to originate from smooth muscle cells in the walls of vessels in the soft tissue (STLMS) or from the uterine myometrium (ULMS). Here, we identify the methylation signatures of normal smooth muscle cells from blood vessels and the uterine wall and compare these with those found in STLMS and ULMS. We hypothesized that these methylation signatures could be used to assign a smooth muscle subtype of origin to individual leiomyosarcomas, and that tumors of different origin would show biological differences with potential therapeutic relevance. MethodsTo define methylation profiles for smooth muscle from vessel walls versus those found in myometrium, EPIC methylation profiling was performed on DNA from 49 formalin-fixed paraffin-embedded (FFPE) normal smooth muscle samples. A supervised machine learning algorithm (Random Forest) was used to distinguish the methylation patterns of normal smooth muscle cells in vessel walls from those in the myometrium. The resulting classifier was applied to methylation data on 67 cases of LMS with corresponding bulk RNAseq data to identify which tumors showed a methylation signature most consistent with either blood vessel wall (LMSvessel) or myometrial smooth muscle (LMSwall). A custom signature matrix derived from scRNAseq data from 6 samples of LMS was used in CIBERSORTx analysis to compare the cellular composition of LMS cases with a vessel or uterine wall methylation signature. ResultsA high degree of correlation was found between the known site of origin for LMS (STLMS vs ULMS) and the methylation signature derived from different types of normal smooth muscle. LMSwall tumors compared to LMSvessel tumors had significantly higher activation of the PD-1 checkpoint pathway in RNAseq analysis. Digital flow cytometry by CIBERSORTx analysis showed an increased expression of transcriptomic signatures of several immune cell subtypes in LMSvessel tumors. ConclusionUsing a supervised machine learning approach we classified LMS samples as either showing a high similarity in methylation patterns to normal smooth muscle cells of either the vessel wall or the myometrium. We found a correlation between LMS showing either a "vessel" or "muscle wall" methylation signature and their site of origin, but notably we also identified some exceptions. When classified based on their methylation signature LMSwall and LMSvessel differed in their PD-1 pathway activation and in their predicted immune cell populations, suggesting potential implications for immunotherapeutic approaches.

Perioperative patient monitoring requires clinicians to integrate multiple physiological data streams under time pressure and frequent interruptions. Conventional monitors predominantly present vital signs as separate numerical values and waveforms, which must be sequentially interpreted and mentally integrated, imposing substantial cognitive demands. Audible alarms are intended to enhance safety but contribute to alarm fatigue and increased workload. Time spent outside predefined safe ranges for key physiological variables and excessive alarm burden are associated with adverse outcomes, motivating approaches that support earlier detection and improved situation awareness without increasing cognitive load. The Philips Visual Patient Avatar is an avatar-based visualisation technology displayed on the patient monitor that supports clinicians' situation awareness by integrating multiple vital signs and sensor states into a single animated virtual patient, while retaining conventional numerical displays. Although laboratory, simulation and qualitative studies suggest benefits of avatar-based monitoring, its impact on objective monitoring outcomes has not been systematically quantified.

Background: High blood pressure (BP) is an often treatable cause of cardiovascular disease. We developed an intervention, featuring a cardiovascular expert team and a toolbox, to support healthcare professionals (HCPs) in hypertension management and enhance patient self-management. Aim: This study evaluates the adoption and feasibility of this intervention. Design and Setting: A mixed-methods study in general practices in the Netherlands. Methods: HCPs could consult a cardiovascular expert team and use a self-management toolbox for their patients as preferred. We interviewed HCPs guided by the Consolidated Framework of Implementation Research (CFIR), and HCPs completed the Determinants of Implementation Behaviour Questionnaire (DIBQ). Using CFIR-ERIC matching tool, we matched implementation strategies to identified barriers. Adults with elevated BP, who were prescribed at least two blood pressure lowering medications were eligible to participate. Patient and disease characteristics were extracted from the electronical medical record. Results: Of 591 eligible patients at thirteen general practices, 176 participated. The cardiovascular expert team was well-received, with 33 unique consultations, although nurse practitioners (NPs) might need the expertise of the expert team more frequently than general practitioners (GP) (adoption). The toolbox was perceived as challenging to use (feasibility). We subsequently identified three key strategies to improve implementation. Mean systolic and diastolic BP were 158/87 mmHg at baseline and 148/85 mmHg after 12 months, although this change cannot be conclusively linked to the intervention. Conclusions: Structured implementation strategies may be helpful in hypertension management. The cardiovascular expert team was considered valuable, but might be better targeted to NPs rather than GPs.

Seismic shifts within academia over the last several decades have seen the growth of biomedical PhD recipients alongside the relative stagnation of tenure-track research-intensive faculty careers (RIFCs). This hypercompetitive academic job market has prompted interest in the paths of those who attain RIFCs. Understanding what drives recent biomedical PhDs to make their career decisions and persist toward them requires a clear picture of how career perceptions, motivations, and intentions develop and crystallize over time. Using annual in-depth interviews across nearly two decades, this report explores the evolution of career thinking and differentiation among 40 who attained a RIFC from diverse starting points to their attainment of a RIFC. Participants strategies for navigating early scientific experiences were patterned by their varied educational and socioeconomic backgrounds. Nearly half of participants did not start with or maintain stable interest in RIFCs, exhibiting changes in both PhD and postdoctoral phases. Participants highlighted six drivers toward RIFCs including desire for independence/autonomy and contributing to knowledge/health. Our results are instructive for trainees and mentors guiding career exploration and differentiation.

Background: Occupational therapists can improve stroke survivors hand and arm movement and participation in daily activities through action observation (AO). AO involves watching another persons hand or arm complete a movement or task. While research generally supports the use of AO with stroke survivors, there are limited AO videos are available to occupational therapists which makes applying AO challenging. Objective: The purpose of this work is to develop structured and widely accessible tool to support access to AO for stroke survivors, occupational therapists, and researchers. Methods: To develop an AO video library for stroke rehabilitation, functional and non-functional upper limb task deficits were first identified through clinical observations and clinician interviews to establish a prioritized list of daily activities. In collaboration with media production specialists, healthy adult volunteers were recruited and filmed performing these tasks from both first- and third-person perspectives. The recorded videos were then systematically edited, enhanced with instructional title slides, and distributed via a public YouTube channel for clinical application and a categorized digital repository for research purposes. Results: Initial assessments revealed a complete lack of familiarity, awareness, and utilization of AO resources among local occupational therapists, despite high perceived clinical utility. To address this gap, a final library of 150 tasks was established, resulting in the production of 419 finalized, standardized videos featuring six healthy volunteers. For clinical application, these videos were hosted on a free, public YouTube channel organized into 18 functional playlists, while a parallel set was structured into distinct movement categories for research repository storage. Conclusion: By providing a structured and highly accessible tool, this repository enables clinicians, researchers, and caregivers to readily implement evidence-based action observation interventions in both clinical and home settings.

Introduction: Early hospital presentation after stroke onset is necessary for rapid assessment and access to time-dependent acute management. This study examined the correlates of late presentation for stroke care among patients recorded at a tertiary hospital in Ondo State, Nigeria. Methods: A retrospective records review was conducted using secondary data from the Stroke Registry of the University of Medical Sciences Teaching Hospital, radiology department records, referral notes, and ambulance records. Records of stroke cases documented within the preceding 24 months were reviewed. Late presentation was defined as hospital presentation more than four hours after symptom onset. Frequencies, chi-square tests, and modified Poisson regression with robust standard errors were used to estimate adjusted prevalence ratios. Results: The analysis included 371 stroke cases. Of these, 317 (85.4%) presented after four hours, and the median time to presentation was 24 hours (interquartile range: 9-72 hours). Late presentation differed significantly by employment status, first-contact route, and pathway complexity at bivariate analysis. After adjustment, non-hospital first contact remained strongly associated with late presentation: patients whose first documented contact was non-hospital-based had almost 3 times the prevalence of delay compared with those whose first contact was hospital-based (adjusted prevalence ratio = 2.89; 95% confidence interval: 2.15-3.90; p < 0.001). Conclusion: Late presentation was pervasive in this tertiary hospital record cohort and was primarily associated with the initial direction of care-seeking. Stroke response interventions should emphasise immediate hospital presentation and strengthen urgent referral from non-hospital first-contact points.

Predicting protein-protein interactions is a fundamental problem in molecular biology. Experimental approaches for identifying protein-protein interactions are time-consuming and labor-intensive, motivating the development of efficient computational alternatives, including machine learning-based methods. However, conventional machine learning methods often rely on manually engineered features that require substantial domain expertise. In this study, we propose a two-stage framework to address these limitations. In the first stage, a one-dimensional convolutional neural network autoencoder is used to automatically learn latent representations from protein sequences. The quality of these features is evaluated through reconstruction error, reflecting how accurately the model reconstructs the original sequence. In the second stage, these learned features are combined with amino acid frequency-based features to form a hybrid feature set for predicting protein-protein interactions. A systematic comparison is performed between models trained on frequency features alone and those using a hybrid representation. The comparison showed that incorporating one-dimensional convolutional neural network-derived latent features improved the models performance of predicting protein-protein interactions. The dataset was split into training, validation, and test sets. Nested cross-validation was employed, with inner loops for hyperparameter tuning and outer loops for model selection. The random forest classifier achieved the best performance, with a mean receiver operating characteristic-area under curve of 0.91 and a test F1-score of 0.87. These results highlight the effectiveness of integrating deep feature learning with ensemble methods for predicting protein-protein interactions and build upon previous work focused on this fundamental problem. Author SummaryProtein-protein interactions are fundamental in all biological processes. However, predicting these interactions is a key problem in molecular biology. Computational approaches have been tested to address this problem. We applied a mix of machine learning and deep learning to gain insight into the qualities of proteins that engage in interaction. First, we trained a deep learning model, which automatically learned the primary sequence and characters related thereto, reducing bias in the actual prediction process. We combined these features, or latent representations, with amino acid frequency features of protein sequences, and called the two together "hybrid features." Then we performed a systematic comparison of amino acid frequency features-only with hybrid features, among four different machine learning classifiers. Our results suggest that the random forest classifier performed best among all four classifiers at predicting interactions between proteins. We propose that this approach could be used to improve efficiency in testing protein-protein interactions at the bench and may have applications to other biologically relevant molecular interactions.