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PubMed2026

A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals↗

PubMed2026

The tunica vaginalis flap as a rescue procedure in testicular torsion: Quantifying salvage rates with matched cohorts.

INTRODUCTION: Testicular torsion is the most common urological emergency in children, and the role of tunica albuginea fasciotomy with tunica vaginalis flap (TVF) in its treatment is controversial. The objective of this study was to evaluate the outcomes among patients undergoing TVF, standard orchiopexy (SO), and orchiectomy, with attention to symptom duration. METHODS: We performed a retrospective review of boys aged 1 month-18 years who underwent surgery for testicular torsion at a single centre from 2010 to 2024. Clinical, ultrasonographic, and operative variables were abstracted, and testicular salvage was defined as a follow-up volume ≥50% of the contralateral testis with blood flow. Propensity score matching for age, symptom duration, and parenchymal heterogeneity generated TVF-SO and TVF-orchiectomy cohorts. Salvage was further stratified by duration of symptoms (<6, 6-12, 12-24, >24 h). RESULTS: Among 157 patients, 31 (20%) underwent orchiectomy, 39 (25%) TVF, and 87 (55%) SO. Overall salvage was 54%, differing by procedure (SO 82%, TVF 36%, orchiectomy 0%; p < 0.001). In the TVF-SO matched cohort (n = 64), salvage was 38% for TVF and 59% for SO (p = 0.133). In the TVF-orchiectomy matched cohort (n = 38), salvage was 32% in the TVF group and 0% in the orchiectomy group (p = 0.02). Salvage after TVF declined steeply with ischemia time, with higher rates observed within 6 h of presentation. DISCUSSION: These findings suggest that TVF is used predominantly in high-risk torsion with adverse ultrasound features. When viewed descriptively, the TVF cohort showed lower follow-up viability than the SO cohort, but this difference must be interpreted in the context of the different intraoperative and preoperative risk profiles underlying procedure selection. We highlight TVF as a valuable additional consideration compared to outright orchiectomy. CONCLUSION: In this retrospective cohort, TVF was used in clinically severe torsion and was associated with follow-up viability in a subset of cases. These descriptive findings support further prospective study but should not be interpreted as evidence of equivalence or comparative benefit of TVF.

Humans↗

PubMed2026

PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.

BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.

Humans↗

PubMed2026

Comparative effectiveness of torsemide vs furosemide in the management of heart failure patients: Win-ratio reanalysis of the TRANSFORM-HF trial.

BACKGROUND: Loop diuretics are widely used for managing congestion in patients with heart failure (HF). The TRANSFORM-HF trial is a multicenter randomized study that enrolled heart failure patients, comparing a strategy of torsemide vs furosemide. The time-to-event analysis demonstrated neutral effects on all-cause death at 30 months and the composite of all-cause death and first rehospitalization at 12 months. We evaluated whether a hierarchical win-ratio (WR) framework integrating mortality, recurrent hospitalization, and patient-reported health status provides additional interpretive insight. METHODS: This study is a secondary analysis of the pragmatic, multicenter, open-label, randomized TRANSFORM-HF trial, conducted across 60 US hospitals that randomized 2,859 patients hospitalized with HF to torsemide or furosemide. The primary 12-month hierarchical composite outcome was defined as (1) all-cause mortality, (2) recurrent all-cause hospitalizations, and (3) lack of improvement in the Kansas City Cardiomyopathy Questionnaire Clinical Summary Score (KCCQ-CSS). The primary statistical method was a WR analysis adjusting covariates via inverse probability weighting. Subgroup analyses evaluated potential heterogeneity across patient demographics and clinical characteristics. RESULTS: In the primary 12-month intention-to-treat analysis, the adjusted WR was 1.07 (95% CI, 0.98-1.16; P = .13), indicating no significant difference between torsemide and furosemide. A supplementary 30-month analysis with extended mortality follow-up yielded a similar estimate (adjusted WR, 1.06; 95% CI, 0.98-1.16; P = .14); hospitalization and KCCQ-CSS components were assessed through 12 months. As-treated sensitivity analyses were consistent with the neutral primary findings. Exploratory subgroup analyses were not adjusted for multiplicity and should be considered hypothesis-generating. CONCLUSIONS: The overall WR comparison between torsemide and furosemide showed no statistically significant difference in the primary 12-month analysis. The WR framework provided an interpretive decomposition across outcome domains but did not establish superiority of either loop diuretic strategy. All findings should be considered exploratory. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03296813, https://clinicaltrials.gov/study/NCT03296813.

Aged↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2026

Whole-Exome Sequencing in a Consanguinity-Enriched South Indian Retinitis Pigmentosa Cohort: Diagnostic Yield and Molecular Spectrum.

PURPOSE: To determine the molecular diagnostic yield, variant spectrum, inheritance architecture, and influence of consanguinity on whole-exome sequencing outcomes in a South Indian retinitis pigmentosa (RP) cohort. DESIGN: Prospective, registry-based cohort study. SUBJECTS: A total of 113 affected participants were enrolled through the Aravind Registry for Inherited Diseases of the Eye, including 109 unrelated probands and 4 affected relatives from already represented families. Primary analyses were restricted to the 109 unrelated probands. METHODS: Whole-exome sequencing was performed using a clinical exome workflow. Variants were interpreted using American College of Medical Genetics and Genomics/Association for Molecular Pathology criteria and cases were categorized as solved, possibly solved, inconclusive, or unsolved using prespecified inheritance-aware rules. MAIN OUTCOME MEASURES: Molecular diagnostic yield, distribution of implicated genes and variant classes, inheritance architecture, and diagnostic yield stratified by consanguinity status. RESULTS: Among the 109 unrelated probands, mean age at testing was 39.3 ± 14.1 years and 58.7% were male. Whole-exome sequencing identified 186 distinct rare variants across 92 inherited retinal disease genes, including 26 pathogenic and 33 likely pathogenic variants. A molecular diagnosis was established in 50 of 109 probands (45.9%), including 42 solved and 8 possibly solved cases; 45 (41.3%) were inconclusive and 14 (12.8%) remained unsolved, including 4 (3.7%) in whom no candidate variant was identified. EYS, USH2A, and ADGRV1 were the most frequently implicated genes. Autosomal recessive (AR) disease predominated (44/50, 88.0%). Consanguineous AR cases were exclusively homozygous (17/17); notably, 68.0% of nonconsanguineous AR cases were also homozygous (P = 0.013). Diagnostic yield was higher in consanguineous probands (51.4% vs. 41.7%), without reaching significance. Recurrent alleles included an established South Asian founder variant (MFSD8 c.1361T>C) and candidate founder alleles in EYS (c.4321C>T) and ADGRV1 (c.14329C>T). CONCLUSIONS: Whole-exome sequencing established a molecular diagnosis in nearly half of this South Indian RP cohort and revealed a predominantly recessive, homozygosity-enriched architecture shaped by consanguinity. These findings define a region-specific variant landscape to support clinical interpretation, genetic counseling, and future trial enrollment in this underrepresented population. FINANCIAL DISCLOSURES: The authors have no proprietary or commercial interest in any materials discussed in this article.

Consanguinity↗

PubMed2026

Virtual Reality Mastoidectomy as Precadaver Training for Novices: A Randomized Crossover Study.

OBJECTIVES: To compare cognitive load during virtual reality (VR) simulation and cadaveric dissection (CD) mastoidectomy training in novice learners. To determine whether training order influences cognitive load, characterize cognitive load progression during the procedure, and assess whether VR training improves subsequent cadaveric performance. METHODS: In this randomized crossover study, 24 core surgical trainees with no prior mastoidectomy experience performed a cortical mastoidectomy in both VR and CD settings. Participants were randomized to either VR-first or CD-first training sequences. Cognitive load was measured using a bespoke auditory reaction-time device at baseline and 10, 30, and 50 min. Relative reaction time (RRT) served as an objective index of cognitive load. Cadaveric performance was assessed using the Modified Welling Scale by two blinded otologists. RESULTS: Cognitive load was significantly lower during VR than CD, with mean RRT rising 26% from baseline in VR versus 60% in CD (p < 0.001). Training order did not affect cognitive load in either modality, and RRT increased progressively throughout mastoidectomy in both VR and CD. Participants who began with VR achieved significantly higher cadaveric performance scores than those who began with CD (mean 9.50 vs. 4.96; p < 0.001), and inter-rater reliability for performance scoring was high. CONCLUSION: VR mastoidectomy reduces cognitive load and enhances subsequent cadaveric performance in novice trainees, supporting its role as a cognitively optimized precadaver training modality that complements, rather than replaces, cadaveric dissection. These findings suggest VR enhances early learning efficiency and resource utilization in novice otolaryngology training. LEVEL OF EVIDENCE: N/A.

Humans↗

PubMed2026

Individual differences in brain dynamics across a social cognition network induced by cortico-cerebellar tDCS in adults with autism spectrum disorder (ASD).

Autism spectrum disorder (ASD) is a neurodevelopmental condition with core diagnostic domains of social communication impairments, restricted interests and repetitive behaviors. Idiosyncratic brain organization is a potential hallmark of ASD. Previous transcranial direct current stimulation (tDCS) studies often targeted dorsolateral prefrontal cortex, with changes oin brain dynamics averaged across the cohort. We utilized a magnetoencephalographic (MEG) array to characterize individual differences in brain dynamics induced by cortico-cerebellar tDCS across nodes of a social cognition network. A randomized, sham-controlled, double-blind, within-subject clinical trial was conducted in a cohort of 24 young adults with ASD or high autistic traits. Two separate sessions of computerized social learning activities were combined with verum/sham tDCS, with anodal electrode over right temporoparietal junction (TPJ) and cathode on right deltoid. Following stimulation, theta- and alpha-band activity were evaluated within nodes of a social cognition network: bilateral TPJ, fusiform, medial prefrontal cortex and Crus I/II of cerebellum. Idiosyncratic participant-specific up- and down-regulation of theta- and alpha-band activity occurred across the network. Activity in right Crus I/II, a region inundated by the stimulation current, strongly correlated with the change of activity summed across all cerebral cortical nodes in theta- but not alpha-band. Intrinsic theta-band activity is believed to mediate input/output relationships in cerebellar cortex and to drive synaptic plasticity. These results suggest that theta-band stimulation of cerebellar cortex might be an effective therapy for individuals on the autism spectrum who present with cerebellar hyperactivity.

Humans↗

PubMed2026

Spinal meningiomas: histopathological grading using a benchmark radiomics model with notes on disease control.

OBJECTIVE: Spinal meningiomas (SMs) are common primary spinal tumors for which surgery is considered the first-line treatment when safe and feasible. The ability to extrapolate the tumor grade from preoperative imaging may significantly inform early patient expectation-setting regarding recurrence. Building on radiomics studies in cranial meningiomas, the authors aimed to construct a benchmark radiomics model to preoperatively identify the histological grade of SMs. METHODS: Institutional surgical records from May 2012 to November 2025 were queried for pathology-confirmed meningiomas below the foramen magnum, with preoperative contrast-enhanced imaging available for segmentation. SMs were classified as low-grade (WHO grade 1) and high-grade (WHO grade 2 tumors and grade 1 tumors with atypia). Tumors were manually segmented, and features were extracted using the PyRadiomics software package. An ensemble model of k-nearest neighbors, random forest, and support vector machine classifiers was trained using nested cross-validation on a subset of 10 features to differentiate tumor grades. Clinical data for the cohort were also extracted, and disease control in an adjunctive clinical series was assessed. RESULTS: Seventy-four patients were included in radiomics analysis, with an area under the receiver operating characteristic curve of 0.879 and a mean F1 score of 0.748. The model's top 5 features were all texture features that differed significantly (p < 0.05) across low- and high-grade SMs. These included measures of tumor textural and contrast-enhancement heterogeneity, with overlap with features reported in radiomics models for histological grading of intracranial meningiomas. Fifty-five patients with a median radiographic follow-up of 22.2 (range 1.9-86.4) months remained for clinical analysis after exclusion of patients with less than 1 month of follow-up and syndromic meningiomas. Four recurrences occurred at a median of 20.8 (range 1.8-41.8) months. High-grade tumor pathology did not significantly impact progression-free survival (p = 0.682, log-rank test; Cox regression high vs low grade hazard ratio [HR] 0.62, 95% CI 0.06-6.11, p = 0.685). Subtotal resection was associated with poorer progression-free survival than gross-total resection (p = 0.004, log-rank test; Cox regression subtotal vs gross-total resection HR 10.62, 95% CI 1.46-77.05, p = 0.019). These findings remain contextualized within a relatively limited follow-up window and small recurrence event count, suggesting a need to characterize the interplay between tumor grade and extent of resection as drivers of local disease control in SMs. CONCLUSIONS: A preoperative radiomics model can stratify high-grade SMs using open-source tools applied to single-institution data.

Humans↗

PubMed2026

Clinical outcomes of Epstein-Barr virus infection/reactivation following CAR-T cell therapy: A systematic review.

BACKGROUND: Epstein-Barr virus (EBV) infection or reactivation is an emerging but underrecognized complication following chimeric antigen receptor T-cell (CAR-T) therapy and is likely associated with treatment-induced immune dysregulation. Data regarding its clinical impact remain limited. OBJECTIVE: To evaluate the reported occurrence, clinical manifestations, and outcomes of EBV infection or reactivation in adults undergoing CAR-T therapy. METHODS: A systematic review was conducted in accordance with the PRISMA 2020 guidelines. PubMed, Embase, and Cochrane CENTRAL were searched from inception to March 2025 for studies reporting EBV infection or reactivation after CAR-T therapy in adults. Due to limited and heterogeneous data, results were synthesized descriptively. RESULTS: Five studies comprising 80 patients were included (median age, 55 years; 52.6% male among patients with reported sex data [10/19]). Across the included studies, 11 EBV infection/reactivation events were identified among 80 described CAR-T recipients, representing 13.8% of the reported sample rather than a true incidence estimate. Among events with usable individualized timing data, the median interval from CAR-T infusion to EBV detection/reactivation was 9.8 months (approximate range, 1-44 months). Because EBV surveillance strategies and definitions were inconsistently reported across studies, this proportion should not be interpreted as a true incidence estimate. Four patients (36.4%) developed EBV-associated disease, including three cases of EBV-related lymphoproliferative disorder and one case of EBV-associated diffuse large B-cell lymphoma. Among seven patients with reported post-CAR-T treatment response, four achieved Complete Remission/ Continuous Complete Remission; treatment response should be interpreted separately from final survival status. Confirmed EBV-related mortality occurred in 2/11 patients with reported EBV infection/reactivation and in 2/4 patients with EBV-associated disease; all-cause mortality could not be reliably estimated because patient-level vital status could not be fully attributed to the EBV-reactivated subgroup. Reported toxicities predominantly consisted of low-grade cytokine-release syndrome; however, toxicity data were limited. CONCLUSION: Although infrequently reported, EBV infection or reactivation after CAR-T therapy may be associated with substantial morbidity and mortality among affected patients. However, the available evidence is limited by the small sample size, heterogeneous study designs, and inconsistent EBV surveillance practices.

Humans↗

PubMed2026

Psychotherapy training in psychiatry: a systematic review and narrative synthesis on the supervision experiences of early-career psychiatrists.

BACKGROUND: Supervision is a fundamental component of psychotherapy training, transforming theoretical knowledge into clinical skills through real-world practice. Psychotherapy training practices vary widely between countries, training programs, and over time, including supervision. Our systematic review aimed to investigate and describe the experiences of psychotherapy supervision through early-career psychiatrists' (ECPs) views. METHODS: We systematically searched PubMed/MEDLINE, Scopus, and PubPsych for survey-based studies on ECPs' experiences of psychotherapy supervision during or after their psychiatry training and reported our findings according to the PRISMA guidelines. Of 32,877 articles screened, 29 articles were included. Each article underwent quality assessment, and results were synthesized narratively. RESULTS: Included articles published between 2000 and 2025, were from Europe (N = 16, 55.1%), the Americas (N = 5, 17.2%), Western Pacific (N = 4, 13.7%), South-East Asia (N = 2, 7%), Eastern Mediterranean (N = 1, 3.5%), and Africa (N = 1, 3.5%), with a total of 4691 participants. Supervision access rates ranged from 26.2% in Nigeria to 85.5% in Russia, with significant variation across countries and psychotherapy modalities. Most ECPs received 50-100 total hours of supervision, frequently delivered in weekly sessions. While formats, individual, group, or mixed, varied by country and training scheme, supervision was generally provided by a psychiatrist-psychotherapist. Common learning techniques included oral consultations and case discussions, followed by audio recordings or transcripts. The need to self-fund psychotherapy supervision costs was identified as a prominent barrier. CONCLUSIONS: Psychotherapy supervision is inconsistent globally, with barriers including supervisor availability and cost. There is a large implementation gap between recommendations and evaluated practice. Digital tools and competency-based frameworks may improve access and quality.

Humans↗

PubMed2026

How AI-supported intelligent systems support infection prevention and control training in healthcare: A systematic review of educational functions and outcomes.

AIMS: Artificial intelligence (AI)-supported intelligent systems have been increasingly incorporated into infection prevention and control (IPC) education and training, primarily to support the monitoring of observable behaviors and the provision of feedback. However, existing evidence has focused largely on short-term compliance outcomes, with limited synthesis of the educational role of AI-supported intelligent systems in supporting sustained IPC competence. This systematic review examined how AI-supported intelligent systems have been designed and used to support IPC education and training, with a focus on system characteristics, educational functions, and reported outcomes. DESIGN: A systematic literature search was conducted across the PubMed/MEDLINE, Embase, Cochrane, and CINAHL databases. DATA SOURCES: A total of 18 studies met the inclusion criteria. Findings were qualitatively synthesized according to system design characteristics, educational functions, and outcome domains. REVIEW METHODS: Methodological quality was appraised using the Mixed Methods Appraisal Tool. RESULTS: Most AI-supported intelligent systems focused on hand hygiene and relied on fully automated monitoring systems to capture behaviors and provide performance feedback. Educational functions were predominantly limited to performance assessment, automated feedback, and reminders. Outcomes were mainly measured using compliance or performance metrics, whereas sustained behavioral change and decision quality were rarely assessed. CONCLUSIONS: AI-supported intelligent systems have been used primarily to reinforce short-term IPC performance and compliance. However, their current applications for supporting sustained competence over time remain limited. The findings of this review suggest that AI-supported intelligent systems may serve as maintenance-oriented educational support by extending learning beyond initial instruction through repeated practice and feedback. Future research should prioritize outcome measures that capture the durability of performance and decision-making processes to better align AI-supported intelligent systems used in IPC education and training with the educational demands of clinical practice.

Humans↗

PubMed2026

Identifying stakeholder behaviors for competency-based pharmacy education: A stage 1 behavior change wheel analysis.

INTRODUCTION/OBJECTIVES: Competency-Based Pharmacy Education (CBPE) is a strategic priority for preparing graduates to meet evolving healthcare needs. However, efforts to implement CBPE can stall due to behavioral challenges among faculty, administrators, preceptors, and learners. This study aimed to apply Stage 1 of the Behavior Change Wheel (BCW) to identify stakeholder-specific behaviors and associated determinants needed to implement the five core components of CBPE. METHODS: A multi-method approach grounded in the BCW, the Capability, Opportunity, Motivation - Behavior (COM-B) model, and the Theoretical Domains Framework (TDF) was used. Data were gathered through (1) targeted literature review; (2) structured focus groups with competency-based education experts and pharmacy education stakeholders; and (3) an iterative consensus process. Behaviors were mapped to the five CBPE components: (1) defined competencies, (2) developmental progression, (3) tailored instruction, (4) authentic experiential learning, and (5) programmatic assessment, and then mapped to COM-B and TDF constructs. RESULTS: Over fifty stakeholder-specific behaviors were identified and specified across the CBPE framework. This revealed shared barriers such as limited instructional design knowledge (psychological capability), insufficient assessment of infrastructure (physical opportunity), and misaligned professional identity (reflective motivation). Key TDF domains included knowledge, environmental context, beliefs about capabilities, and professional roles. The behavioral problem statements, specifications, and determinants were identified to support future intervention planning. CONCLUSION: This Stage 1 analysis provides a behaviorally grounded foundation for CBPE implementation by identifying stakeholder behaviors and conditions that enable change. These findings will inform the development of readiness-to-change assessments and targeted interventions (BCW Stages 2 and 3), supporting scalable and sustainable CBPE transformation in pharmacy education.

Education, Pharmacy↗

PubMed2026

Comparative phylogenomics and transcriptional regulatory networks of AQPs, HSPs, and LEA proteins in salt-stressed Portulaca oleracea.

Soil salinization severely threatens global food security, necessitating systematic investigations of halophytes like Portulaca oleracea to decode the molecular mechanisms of environmental resilience. Utilizing an integrated framework of deep learning-based genome annotation (58,817 predicted genes; 96.5% BUSCO completeness), multi-tissue RNA-Seq, phylogenomics, and gene regulatory network (GRN) inference, the synergistic orchestration of 78 aquaporins (AQPs), 525 heat shock proteins (HSPs), and 119 late embryogenesis abundant (LEA) proteins was elucidated. The active transcriptome, encompassing 39,065 expressed loci, revealed a systemic growth-defense trade-off. Tissues displayed distinct adaptive mechanisms: leaves modulated intracellular water balance via specialized AQPs, whereas adult roots maintained proteostasis through robust HSP20/HSP70 induction. Phylogenomic clustering across 154 species demonstrated that salinity tolerance constitutes an evolutionary mosaic, identifying 81 halophyte-exclusive orthogroups and 1129 species-specific clusters. Comparative topology across six independent GRNs (4.2M-5.3 M edges) unmasked a highly modular transcriptional reprogramming strategy governed by a core apparatus of 22 stress-exclusive regulators, with functional enrichment heavily prioritizing protein dimerization and chromatin remodeling. Theoretically, the distinct convergence of Trihelix transcription factors with guard cell differentiation pathways offers a candidate transcriptomic framework to explain the plant's characteristic C4-CAM photosynthetic plasticity under severe osmotic pressure. Practically, these evolutionary blueprints and specific master switches transcend single-gene transgenic limitations. Utilizing these root-sustained and stress-inducible targets under localized promoters provides a naturally optimized, network-level precision engineering roadmap to transfer robust, compartmentalized halotolerance to sensitive glycophytic crops.

Gene Regulatory Networks↗

PubMed2026

Development, feasibility, acceptability, and preliminary impact of NutriSOS®: A behavioral mobile app to promote sustainable diets.

The primary objective of this study was to describe the development of the NutriSOS® app and to evaluate its feasibility and acceptability for its use in the NutriSOS® Randomized Controlled Trial (RCT) to promote sustainable diets. A secondary objective was to explore preliminary changes in dietary and physical activity behaviors and environmental impact following app use. The NutriSOS® app integrates personalized dietary advice, educational content, self-monitoring, and social interaction features. A single-arm, pre-post pilot study was conducted in 37 young Mexican adults over four weeks. Feasibility, acceptability, quality, and usability were assessed using online surveys, alongside exploratory changes in dietary and physical activity behaviors, environmental indicators, and their association with perceived behavioral determinants. Feasibility and acceptability were high overall, with favorable responses reaching up to 100% in key components such as the nutritional guide and learning modules, and above 90% for messaging, registration, and design. Greater variability was observed in some sections, particularly the 24-h recall (41-86%). Reductions in red and processed meat and ultra-processed food consumption were observed (from 3 to 1 times/week, p < 0.01), with ∼60% decreases in their related environmental footprints (p < 0.01) and favorable self-reported behavioral determinants (p < 0.0001). Physical activity type and intensity changed (p < 0.05). These findings support NutriSOS® as a feasible and acceptable tool, while highlighting areas for refinement, particularly those related to the time and effort required for data entry, prior to its implementation in the NutriSOS® RCT, in which its effectiveness will be formally evaluated.

Humans↗

PubMed2026

Post-intervention effectiveness of a computerized personalized cognitive stimulation program adapted according to cognitive reserve in older adults without cognitive impairment in Primary Care: A randomized clinical trial.

BACKGROUND: Cognitive reserve may influence responsiveness to cognitive interventions, yet it is rarely used to tailor computerized stimulation. OBJECTIVE: To evaluate the effectiveness of a computerized cognitive stimulation program personalized according to cognitive reserve on cognition, reserve-related activities, and digital competence in community-dwelling older adults without cognitive impairment in Primary Care. METHODS: In this randomized clinical trial, 102 adults aged ≥65 years with normal cognitive performance were recruited from three primary care centers in Zaragoza, Spain, and stratified by cognitive reserve level before random allocation to intervention or control. The intervention comprised digital literacy sessions followed by 8 weeks of home-based computerized cognitive stimulation tailored to participants' cognitive reserve profiles and life history. Controls received a single group-based health education session focused on maintaining everyday cognitive activity. Outcomes were assessed at baseline and post-intervention using global cognition (MEC-35), the Cognitive Reserve Questionnaire, the Mobile Device Proficiency Questionnaire-16, and domain-specific neuropsychological tests. A total of 100 participants completed the final evaluation and were included in complete-case analyses. RESULTS: Compared with controls, the intervention group showed greater adjusted post-intervention improvements in global cognition (MEC-35 between-group difference: 1.8 points) and several cognitive measures, including temporal orientation, calculation, attention, praxis, verbal fluency, processing speed, executive functions, and verbal learning. CRQ scores and digital competence also improved, with small-to-large effect sizes. CONCLUSIONS: A computerized cognitive stimulation program adapted according to cognitive reserve appears feasible in Primary Care and may improve cognition, engagement in reserve-related activities, and digital competence in older adults without cognitive impairment.

Humans↗

PubMed2026

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models↗