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Inside the black box: Refining programme theory in the PriDem dementia care study

Introduction Refining programme theory following feasibility testing is a critical but rarely reported step in the development of complex interventions, creating a ‘black box’ in implementation science. This lack of transparency limits understanding of how and why interventions work and constrains effective scale-up and adaptation. This challenge is particularly salient in post-diagnostic dementia support, which is often fragmented in primary care, with limited guidance on how system-level interventions can be implemented and adapted in real-world settings. The PriDem programme developed a flexible, primary care-led intervention to improve post-diagnostic dementia support, involving Clinical Dementia Leads (CDLs) working with general practices to strengthen care systems. Programme theory was articulated in a logic model, to guide a feasibility implementation study, which demonstrated intervention feasibility, acceptability, and potential for systems-level change. Understanding how the intervention operated in practice was critical to refining this theory and informing future scale-up. This paper presents a structured exemplar of theory refinement, addressing this recognised gap in implementation science. Methods A deductive thematic analysis was conducted, using the logic model as a coding framework. We synthesised previously reported findings with new qualitative insights from feasibility interviews, fieldnotes, supervision records and researcher reflections. Confirmed, refined, and newly emergent theoretical components were identified and the logic model updated. Results Many original theory elements were confirmed, including improved review processes leading to enhanced care plan personalisation and staff training increasing confidence in care delivery. New mechanisms were identified, such as mapping local services as a relational tool and dementia review templates as educational resources. Pre-implementation activities, such as specific CDL training and champion identification, emerged as critical to success. Role ambiguity and capacity concerns acted as negative mechanisms, impeding implementation. These insights informed a revised logic model to guide future scale-up. Conclusions This paper demonstrates the value of theory refinement following feasibility testing. By unpacking the ‘black box’ of implementation, we offer a transparent model for optimising complex interventions in primary care-led dementia support. Trial registration number ISRCTN11677384.

Bayesian variable selection for genome-wide association study of grain traits in rice

Rice (Oryza sativa) is a staple food crop for more than half of the world‘s population. Besides high gluten-free nutritional contents, it has high economic value supporting livelihood of millions of farmers. That is why a lot of research is being carried out to derive new varieties of rice and improve its yield, stress tolerance, and grain quality. It remains a central goal in agricultural research. Genome-wide association studies (GWAS) provide a powerful framework for linking genetic variation to complex phenotypic traits, but the high dimensionality of genomic data presents significant challenges for model selection and prediction. Using rice genotype and phenotype data, we compared the performance of several frequentist and Bayesian modeling approaches: multiple linear regression (OLS: Ordinary Least Squares), LASSO (Least Absolute Shrinkage and Selection Operator), Ridge, Bayesian LASSO, Bayesian Sparse Linear Mixed Model (BSLMM), and a Bayesian spike-and-slab prior model. Phenotypic traits were transformed where necessary to approximate normality, and predictive performance was evaluated through cross-validation using mean squared error and predictive correlation. The spike-and-slab prior model often outperformed the classical methods, yielding superior prediction and effective variable selection. Our findings demonstrate the value of Bayesian model selection frameworks for plant GWAS and trait prediction, and highlight the effectiveness of Bayesian methods in identifying informative markers in rice. Such approaches hold promise for accelerating genetic improvement and supporting marker-assisted selection in crop breeding programs. Rather than emphasizing biological interpretation of individual loci, our results highlight differences in predictive behavior, stability, and inferential characteristics across models.

Reply to Chen: Methodological and analytical considerations in the study of H3-Dendra2 distribution

Long-text caption generation for surgical image with a concept retrieval augmented large multimodal model

Surgical image captioning is critical for automated reporting and education but is currently limited by a lack of long-text datasets and the tendency of generic Multimodal Large Language Models (MLLMs) to hallucinate medical details. To address this, we present a comprehensive framework for long-text surgical captioning. First, we construct a verified long-text benchmark extending the EndoVis2018 dataset, utilizing an automated pipeline with expert-in-the-loop validation to transform brief triplets into rich narratives. Second, we investigate domain-specific adaptation strategies for MLLMs. We implement a surgical concept retrieval-augmented generation (RAG) mechanism that dynamically injects specialized knowledge (instruments, actions) into the visual encoder, effectively mitigating domain-specific hallucinations common in generic models. Finally, recognizing the inadequacy of n-gram metrics for long medical text, we establish a robust evaluation protocol using clinically-aligned metrics. Extensive experiments demonstrate that our data-centric and retrieval-enhanced approach significantly outperforms baselines in producing clinically accurate, coherent long descriptions.

The relationship between the perceived personalities of dating partners and dating violence victimization: A three-month longitudinal cross-lagged panel study

Dating violence is a significant social issue with serious psychological consequences. Victims’ perceptions of perpetrators’ traits may both influence and be influenced by abuse. However, most existing studies are cross-sectional, providing limited insight into the temporal and reciprocal relationships between these variables. Therefore, this study aimed to examine the directional and reciprocal associations between victims’ perceptions of perpetrators’ personalities and their experiences of dating violence. A three-month longitudinal survey was conducted with 206 young adults (aged 18–29 years) who were currently in romantic relationships. Three personality characteristics previously linked to dating violence perpetration were assessed: the basic Big Five personality traits, aggression, and attachment style. We used a cross-lagged panel model (i.e., a statistical approach that estimates directional and reciprocal influences over time) and found three key results. First, among the Big Five personality traits, perceived “agreeableness” exhibited a cross-sectional relationship with dating violence victimization. Second, perceived aggression had a bidirectional effect: viewing partners as more aggressive predicted later victimization, and dating violence victimization predicted higher subsequent perceptions of partner aggression. Third, perceptions of partners’ “fear of abandonment” were shaped through experiences of dating violence. Among these findings, the bidirectional link between perceived aggression and victimization was the most robust and theoretically novel. These results suggest that victims’ perceptions of their partners’ anger-related traits predict and reflect abuse, underscoring the need for interventions that target mutual perception dynamics in violent relationships.

Enhancing recommendation diversity and accuracy with product paths and time decay mechanisms

The recommendation algorithm suggests products to users, improving their experience, however, it encounters a challenge of insufficient diversity in the recommended results. This paper proposes Product Path and Time decay enhanced Product-based Neural Network recommendation algorithm. Firstly, establishes three types of product paths: User Purchase History Path, Product Similarity Calculation Path, and Product Bundles Path, integrates them to form a comprehensive product relation network, thereby enhancing the diversity of the recommended results. Then, a time decay function is introduced to further improve recommendation accuracy of the recommended products. Finally, fuses the product path and time decay function as a new R component to the Product layer of the PNN model. Experimental results show that the Product Path and Time decay enhanced PNN model improves the AUC from 0.8605 to 0.8772 and reduces the cross-entropy loss from 0.2228 to 0.2155. Meanwhile, the intra-list diversity (ILD) increases from 0.8581 to 0.8832, and the entropy rises from 4.15 to 4.74, demonstrating superiority over the standard PNN model in both accuracy and recommendation diversity.

Correction for Potapova et al., <i>Vibrio cholerae</i> biofilm matrix assembly and growth are shaped by a glutamate-specific TAXI/TRAP protein

Summative evaluation of the rural surgical obstetrical networks initiative: Findings from a five year retrospective qualitative study

Background The Rural Surgical and Obstetrical Network (RSON) initiative was originally funded for five years to support, enhance, and sustain rural surgical and obstetrical services in British Columbia (Canada). Interviews and focus groups with healthcare providers and administrators from 10 rural communities were conducted annually, to document the implementation of RSON, understand challenges and gains, and to inform network improvements. To supplement this information and enable participants to reflect on the project’s full duration, we conducted a summative evaluation of RSON to understand the extent to which the program achieved its objectives. Methods Data were collected in two phases: annual interviews and focus groups with rural healthcare providers and administrators in the final project year and through a real-time interactive, anonymous platform, ThoughtExchange, in the context of a day-long, annual virtual meeting. Data from both sources were analysed using a process of thematic analysis. Findings Across both data sources, common themes highlighted the benefits of RSON, including the stabilization of local procedural care through increased local scope and volume, support for clinical coaching and other ongoing educational initiatives, quality improvement efforts, team-oriented care, increased administrative support, and appropriate staffing levels. Themes unique to the summative interviews included those addressing the limitations of RSON funding, particularly constraints on funding and contextual factors limiting participation. Conclusion Findings underscore the importance of a wrap-around approach to health service interventions to reflect the complexity of healthcare delivery and the importance of coordinated, context sensitive efforts that work in synergy with other initiatives. The RSON initiative precipitated a cultural change in key determinants of stability at individual site levels, a necessary precursor to long-lasting change. The combination of this retrospective assessment of RSON and the program evaluation findings suggest the need for long-term funding to support rural surgical and obstetrical services.

Genomic characterisation of extensively drug-resistant Acinetobacter baumannii isolates from a tertiary hospital in Ghana

Acinetobacter baumannii ( A. baumannii ) is an emerging “superbug” whose infections have become extremely difficult to treat due to its diverse antimicrobial resistance mechanisms and resistance to last-resort antibiotics including carbapenems. Despite this, data on genetic determinants and genomic context of carbapenemase genes in A. baumannii are scarce in Ghana. This study investigated the genetic determinants of carbapenem resistance in clinical isolates of A. baumannii ( Ab ) and explored the genetic contexts of carbapenemase-encoding genes in extensively drug-resistant A. baumannii (XDR- Ab ). We analysed 65 archived clinical A. baumannii isolates. Identification and antimicrobial susceptibility profiles of the isolates were determined using a MALDI-TOF-MS and the Microscan device, respectively. Carbapenem resistant A. baumannii (CR- Ab ) isolates were screened for carbapenemase-encoding genes ( bla NDM-1 , bla KPC , bla VIM , bla OXA-48 , bla OXA-23 , bla OXA-58 , and bla IMP ) using loop-mediated isothermal amplification (LAMP). Six XDR- Ab isolates were whole-genome sequenced (WGS) using Nanopore MinION. Carbapenem resistance was observed in 18/65 (27.7%) isolates. All CR isolates were resistant to penicillins, cephalosporins, fluroquinolones, aminoglycosides, sulfonamides and carbapenems (minimum inhibitory concentrations, MICs, &gt; 2µg/ml - &gt; 8µg/ml). The most predominant resistance gene, bla NDM-1 (33.3% ) , was found to co-exist with bla OXA-23 (27.8%) or bla OXA-58 (16.7%), while bla OXA-420 (12.5%) was the least prevalent gene detected. The sequence types identified among the isolates were ST2 (33.3%), ST164 (16.7%), ST214 (16.7%), ST52 (16.7%), and ST16 (16.7%) according to MLST-Pasteur scheme. The study highlights the carriage of multiple carbapenemase genes, other AMR-encoding genes and efflux pumps in XDR clinical A. baumannii isolates. To the best of our knowledge, the study reports for the first time, the detection of ST2 OXA-23, NDM-1 and ST164 OXA-58, NDM-1-producing A. baumannii strains at the Korle Bu Teaching Hospital. These strains belong to high-risk clones and continuous surveillance through molecular epidemiological studies and public health interventions are urgently needed to control their spread in Ghana.

Reply to Roske and Yeeles: Mismatch correction by a replicative polymerase constrained on DNA by a ring

Prevalence and risk factors of gross neurologic deficits in children after severe malaria: A systematic review and meta-analysis

Background Children with severe malaria may develop gross neurologic deficit(s). We conducted a systematic review on the prevalence and risk factors of gross neurologic deficits after childhood severe malaria. Methods The systematic review was conducted following PRISMA guidelines. Article search was conducted in MEDLINE, EMBASE, Web of Science, and Global Index Medicus. Studies included reported on prevalence and/or risk factors of gross neurologic deficits after severe malaria in children. Risk of bias analysis and heterogeneity assessment were performed using ROBINS tool and I 2 -statistic, respectively. Data analysis was done using quantitative synthesis in R ver 4.5.0 software, and narrative synthesis. Results 41 studies from 16 countries in Sub-Saharan Africa and Asia comprising 11,635 children were included in the analysis. Gross neurologic deficits included motor, movement, sensory, and speech impairments. 31 studies included prevalence of gross neurologic deficits at hospital discharge (cerebral malaria (CM), n = 26, broader forms of severe malaria, n = 5). Prevalence of deficits at hospital discharge in children with CM was 15.2% (95%CI: 11.5–18.8) (I 2  = 89.1%), compared to 2.4% (95%CI: 2.0–2.8) (I 2  = 36.6%) in children with broader forms of severe malaria. Prevalence of deficits in CM decreased from 15.2% to 5.7% (95%CI: 1.2–10.2) (I 2  = 79.2%) after 12 months follow-up. At regional level, Sub-Saharan Africa had a prevalence of 14.2% (95%CI: 10.5–17.9) (I 2  = 94.9%) compared to East Asia &amp; Pacific at 2.3% (95%CI: 0.8–3.8) (I 2  = 0.0%) and South Asia at 6.1% (95%CI: 0.0–14.8) (I 2  = 0.0%). Risk factors for gross neurologic deficits included profound coma, coma lasting ≥48 hours, multiple convulsions, hypoglycaemia, and acute kidney injury. Conclusions Gross neurologic deficits are more prevalent in children in Sub-Saharan Africa with CM compared to severe malaria in general, and a number of clinical factors in children with CM increase the risk. Interventions by clinicians should target children with CM at highest risk during admission.

A. James Hudspeth (1945–2025): A pioneer in the biology and physics of hearing

A. James (Jim) Hudspeth, who devoted five decades to studying how hair cells—the mechanoreceptor cells of the inner ear—mediate the senses of hearing and balance, passed away on August 16, 2025, at his home in New York City. He was 79. Among his many achievements, Jim elucidated how mechanical vibrations of the hair cell’s antenna—the hair bundle—evoke electrical signals that convey information to the brain and discovered that hair bundles not only serve as sensors but also act as active mechanical amplifiers of their own inputs. Through the groundbreaking nature and the breadth of his findings, the elegance of his experimental approaches and publications, his transformative mentorship of generations of students and postdoctoral fellows, and his ability to work and communicate across disciplinary boundaries, he has secured his legacy as one of the premier neuroscientists of our time.

Correction: Neural tube defects: Sex ratio changes after fortification with folic acid

Correction: Does C-reactive protein exhibit high prognostic information value in acute pulmonary embolism? A novel structural pathway for disease progression beyond classical statistical associations

Therapeutic communication in nursing students: A cross-sectional study of personal, educational, and contextual factors

Background Therapeutic communication is a key competency in nursing education and a central component of person-centred care. However, evidence regarding its association with personal, educational, and contextual factors among nursing students remains heterogeneous. Objective To describe therapeutic communication scores in nursing students and to examine their association with personal, educational, and contextual variables using the Therapeutic Communication Scale in Nursing Students. Methods A cross-sectional study was conducted among second-, third-, and fourth-year undergraduate nursing students at a Spanish university. Participants completed a questionnaire including sociodemographic and academic variables, self-perceived communication ability, factors related to stress and the clinical practice context, and the Therapeutic Communication Scale in Nursing Students, which provides a total score and two dimensions: Relation Building and Problem Solving. Descriptive statistics were calculated, and bivariate analyses were performed using non-parametric tests. Results A total of 450 students participated. Mean scores indicated a generally high level of therapeutic communication. Female students obtained significantly higher scores than male students in both dimensions and in the total scale score. No significant differences were observed according to academic shift, employment status, volunteering experience, or academic stress level. Higher self-perceived communication ability and greater motivation towards nursing studies were associated with higher therapeutic communication scores. In addition, students who reported frequent use of communicative behaviours such as active listening, verbal empathy, and open-ended questions showed significantly higher scores. Perceived support from clinical tutors and clinical accompaniment was not associated with communication scores, whereas a favourable clinical climate was associated with slightly higher total scores. Conclusions Therapeutic communication in nursing students appears to be more strongly associated with self-perceived competence, academic motivation, and specific communicative behaviours than with sociodemographic characteristics or stress levels. These findings highlight the importance of strengthening training in concrete communication skills during undergraduate nursing education.

Utility of three-dimensional echocardiography for evaluating right ventricular size and function and ventricular myocardial deformation in repaired tetralogy of fallot

Purpose Right ventricular (RV) dysfunction remains a major long-term complication in patients with repaired Tetralogy of Fallot (rTOF). While cardiac magnetic resonance (CMR) is the gold standard for right ventricular (RV) assessment, it is limited by accessibility and cost. Three-dimensional echocardiography (3DE), with its strain imaging capabilities, offers a promising alternative for the serial evaluation of right ventricular (RV) size and function. This study aims to compare RV volumetric and myocardial deformation parameters obtained by 2D and 3D echocardiography (2DE, 3DE) with RV function measured by CMR in patients with rTOF. Materials and Methods We retrospectively analyzed 43 patients with rTOF who underwent same day 2D, 3D echocardiography, and CMR between November 2023 and December 2024. RV volumes, ejection fraction (RVEF), and global longitudinal strain (GLS) were measured across modalities. Correlation, Bland-Altman analysis, and area under receiver operating characteristic (AUC) curves were used to evaluate the agreement and diagnostic accuracy for detecting right ventricular (RV) systolic dysfunction. Results Three-DE demonstrated a strong correlation with CMR for RVEDV (r = 0.95) and RVEDVi (r = 0.91), with a mild underestimation. RVEF by 3DE was significantly lower than CMR (46.4 ± 8.8% vs. 50.3 ± 7.3%, p = 0.002). RV-GLS values differed across modalities, with 3DE yielding more negative values than 2DE (−20.3 ± 4.4% vs. −18.5 ± 4.7%, p = 0.009). Among patients with CMR-RVEF &lt;48%, both 2D and 3D Echo-derived RV-GLS were significantly reduced. Conclusion Three-dimensional echocardiography demonstrates a consistent association with CMR for the assessment of right ventricular volumes but modest underestimation of volumetric and functional parameters. Abnormal right ventricular strain was observed in patients with CMR-defined systolic dysfunction, supporting the clinical relevance of strain analysis. Overall, 3DE may serve as a feasible complementary tool for longitudinal right ventricular assessment in patients with rTOF, alongside CMR as the reference standard.

From challenge to growth: A qualitative study of parental adaptation to Autism Spectrum Disorder

Raising a child with Autism Spectrum Disorder (ASD) profoundly affects family dynamics and parental well-being. While research has often focused on stress and negative outcomes, less is known about the processes and resources that foster adaptation and growth in parents. This qualitative study explored the adaptation process among parents of children with ASD, examining both challenges and transformative experiences, and identifying key personal and contextual factors that support or hinder adjustment. Thirty-six parents (19 mothers, 17 fathers) of children aged 5–11 years with ASD (severity level 2 or 3, DSM-5) were recruited from two health care centres for ASD in Northern Italy. Semi-structured interviews were conducted using a guide developed according to an established methodological framework for qualitative interviews and analysed following Braun and Clarke’s framework. Themes were organised into three conceptual domains (i.e., Outcomes, Resources, and Challenges) reflecting the main research aims. Parents reported both emotional distress and personal growth, including improvements in family functioning and child development (Outcomes). Facilitating factors included social support, access to information, professional interventions, and parental self-efficacy (Resources). Barriers included difficulties with services, family conflicts, social stigma, and maladaptive coping strategies (Challenges). Parental adaptation to ASD emerged as a dynamic, ongoing process of negotiation between challenges and resources, often leading to transformative experiences and personal growth. The findings support the implementation of systematic intervention strategies aimed not only at reducing parental stress, but also at empowering parents and promoting the development of adaptive resources.

Development and internal validation of a risk stratification scoring system for identifying gram-negative ESBL-positive acute cholangitis: A retrospective cohort study

Background Acute cholangitis, a severe biliary infection that is frequently caused by gram-negative pathogens, presents health challenges owing to the increasing prevalence of antimicrobial resistance, particularly among extended-spectrum beta–lactamase (ESBL)-producing bacteria. Accurate risk stratification of patients with extended-spectrum beta-lactamase–producing bacteria is crucial for optimizing antimicrobial therapies. Aims This study aimed to develop and internally validate a risk stratification scoring system for identifying ESBL-producing bacteria in patients with acute cholangitis, with the goal of supporting clinical risk stratification. Methods This retrospective cohort analysis included adult patients with acute cholangitis admitted between 2019 and 2023. Patients were excluded if they had incomplete medical records, missing microbiological data, or non-adherence to the Tokyo Guidelines 2018 diagnostic criteria. Predictors of positivity for ESBL-producing bacteria were identified using multivariate logistic regression and integrated into a scoring system, and the performance metrics were evaluated. Results A total of 303 patients with positive blood or bile cultures were included in the analysis, of whom 111 (36.6%) had ESBL-positive cholangitis. Independent predictors of positivity for ESBL-producing bacteria included prior antibiotic treatment (3.5 points), chills with rigors (2.5 points), alanine aminotransferase levels &lt;400 U/L (3.5 points), hematocrit levels &lt;27% (2.5 points), and alkaline phosphatase levels &gt;300 U/L (2.0 point). At cutoff scores of 7.5 and 11, the scoring system demonstrated sensitivity of 56% and 16%, specificity of 75% and 98%, positive predictive values of 56% and 82%, and overall accuracy of 68% and 70%, respectively. Conclusions This preliminary scoring system demonstrated high specificity at higher cutoffs, supporting its use as a rule-in tool for identifying patients at high risk of ESBL-producing bacteria in acute cholangitis. However, its moderate sensitivity limits its role as a rule-out strategy. This preliminary internally validated model should not be used to guide routine clinical decision-making without external multicenter validation, and any application must consider local resistance patterns and patient context.

Correction: Gut microbiota signatures of the three Mexican primate species, including hybrid populations

Dirichlet-Swing: understanding spatio-temporal aspects of political elections in heterogeneous societies through agent-based simulation

Many countries have a system of electing members to their governing bodies through district-based elections. In each district, the party with maximum votes wins the corresponding “seat” in the governing body. However, the final seat distribution is strongly dependent on the geographical distribution of voters of different parties, and the party with most (or least) voters may not win the most (or least) number of seats if their voters are non-homogeneously distributed over the districts. This is further complicated in heterogeneous societies, where political preference of voters depends on their social identities, which is also related to their districts of residence. Projections of outcomes by sample surveys tend to fail in such situations. The aim of this paper is to explore how electoral outcomes are influenced by the geographical distribution of voters and community-centric voting preferences. We consider agent-based modeling of voters along with their locations, community memberships and voting preference. Our models represent the relations between these factors with their uncertainties through conditional probability distributions involving latent variables with Dirichlet Processes. Our models also represent spatio-temporal factors in elections – how geographical proximity between districts influence the voting preferences, and swing of votes across successive elections. We propose two novel models for vote swing between successive elections based on Dirichlet Processes, which is far more powerful than the existing models of Uniform Swing and Proportional Swing. For any choice of parameters, our models can be used to simulate a full election by Monte Carlo Sampling, and such simulations provide us a range of possible outcomes. We can also simulate surveys and study how their projections can deviate from the actual results. We discuss inference approaches to estimate the parameters to fit the model to actual district-based elections held in India.