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PubMed2026

The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures: A Systematic Review and Meta-analysis.

BACKGROUND: Current endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopic-based diagnostic sampling for indeterminant biliary strictures remain suboptimal. Artificial intelligence (AI)-based algorithms by means of computer vision in machine learning have been applied to cholangioscopy in an effort to improve diagnostic yield. The aim of this study was to perform a systematic review and meta-analysis to evaluate the diagnostic performance of AI-based diagnostic performance of AI-associated cholangioscopic diagnosis of indeterminant or malignant biliary strictures. METHODS: Individualized searches were developed in accordance with PRISMA and MOOSE guidelines, and meta-analysis according to Cochrane Diagnostic Test Accuracy working group methodology. A bivariate model was used to compute pooled sensitivity and specificity, likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristics curve (SROC). RESULTS: Five studies (n=675 lesions; a total of 2,685,674 cholangioscopic images) were included. All but one study analyzed a deep learning AI-based system using a convoluted neural network (CNN) with an average image processing speed of 30 to 60 frames per second. The pooled sensitivity and specificity were 95% (95% CI: 85-98) and 88% (95% CI: 76-94), with a diagnostic accuracy (SROC) of 97% (95% CI: 95-98). Sensitivity analysis of CNN studies (4 studies, 538 patients) demonstrated a pooled sensitivity, specificity, and accuracy (SROC) of 95% (95% CI: 82-99), 88% (95% CI: 72-95), and 97% (95% CI: 95-98), respectively. CONCLUSIONS: Artificial intelligence-based machine learning of cholangioscopy images appears to be a promising modality for the diagnosis of indeterminant and malignant biliary strictures.

Humans↗

PubMed2026

Unacknowledged Burdens and Clinical Assets of BIPOC Genetic Counseling Students: Qualitative Evidence to Inform Supervision.

As the genetic counseling profession works to diversify its predominantly white workforce, understanding the experiences of Black, Indigenous, and People of Color (BIPOC) students is central to equity efforts. While BIPOC students bring invaluable cultural and linguistic diversity that improves patient care, they often navigate clinical training environments that lack diversity and psychological safety. This article draws on data from a longitudinal constructivist qualitative study to examine how racial and ethnic concordance (or lack thereof) with patients and clinical supervisors influenced the clinical training, professional development, and well-being of BIPOC genetic counseling students. Semi-structured interviews were conducted with 25 BIPOC genetic counseling students in the United States and Canada. Interviews were recorded using Zoom.us, transcribed using Rev.com, and analyzed in NVivo using reflexive thematic analysis. The analysis led to the construction of three themes: (1)Shared identity with patients is a clinical advantage: Participants leveraged their cultural and linguistic intuition to establish trust and rapport with patients; (2) Identity navigation involves cognitive and emotional labor: Participants shouldered an unacknowledged burden in managing stereotype threat, overcoming feelings of exclusion, and educating supervisors; and (3) Racial/ethnic identity shapes supervisory dynamics: Participants described BIPOC supervisors as providing identity-affirming support, while some white supervisors avoided discussions about identity or committed microaggressions. These results suggest that BIPOC genetic counseling students have clinical assets rooted in biculturalism, yet carry a burden that often goes unacknowledged of managing power imbalances and pressure to assimilate in predominantly white clinical supervision spaces. To promote equitable training, programs should implement supervisor training on culturally responsive identity broaching, establish independent, transparent mechanisms for students to report biases they encounter in clinic, and expand mentorship networks to provide additional support.

Humans↗

PubMed2026

Effectiveness of psychosocial and lifestyle interventions in promoting behaviour change and improving cognitive outcomes in older people with memory concerns: A systematic review.

BACKGROUND: Older adults with mild cognitive impairment or subjective cognitive decline have a greater dementia risk, particularly those from minority ethnic and socioeconomically disadvantaged backgrounds. Psychosocial and lifestyle interventions targeting modifiable risk factors offer hope for reducing risk, yet behavioural mechanisms remain unclear. This systematic review examines these mechanisms and associated outcomes. METHOD: We searched PubMed, Embase (Ovid), PsycINFO (Ovid), Web of Science, and Scopus for randomised control trials testing interventions that aimed to improve lifestyle and cognition in older adults with memory concerns. We explored behavioural mechanisms using the COM-B model and synthesised intervention effectiveness, overall and within underserved groups. We prioritised lower risk of bias studies. RESULTS: 26 studies described 23 randomised controlled trials (14 multidomain, 9 single domain interventions). Certainty of evidence that behaviour change was associated with cognition was low. Moderate-certainty evidence indicated that interventions providing a socially supportive environment and combining nutritional education and counselling for 6 + months improved diet. Physical activity improved primarily in interventions incorporating education, structured training, and enablement strategies (e.g., tailored programmes, providing tools). Interventions simultaneously targeting capability, opportunity and motivation showed greater overall effectiveness. Few studies recorded ethnicity (13%) or sociodemographic status (9%), and none explored their impact. CONCLUSIONS: Non-pharmacological interventions can help this population improve their lifestyles if they feel capable, equipped and motivated, highlighting the value of careful design and implementation. There is scarce evidence on how these interventions work for underserved populations. Future research should explore this to inform tailored interventions and develop equitable dementia prevention strategies.

Humans↗

PubMed2026

The Animal Variant Classification Guidelines v2: An Update With New Criteria and Improved Clarifications.

The Animal Variant Classification Guidelines (AVCG) were developed to standardize and objectify the classification of putative disease-causing variants. These guidelines are sufficiently reproducible and are used to classify previously published and new disease-causing variants across species. Here, the guidelines are updated (AVCG.v2), based on a three-phase decision process. Overall, four new criteria and seven clarifying comments were added. The number of criteria has increased from 23 to 27, with three new criteria supporting pathogenicity and one new criterion supporting benign classification. Pharmacogenomic variants were determined to fall within the scope of the guidelines. These updated guidelines are being used by the Variant Pathogenicity Working Group (VPWG), part of the Animal Genetic Testing Standardization standing committee, which is a committee of elected members of the International Society for Animal Genetics (ISAG). Under the auspices of ISAG, the VPWG retrospectively classifies published putative disease-causing variants. The pathogenicity label for a variant will be presented in the variant tables of Online Mendelian Inheritance in Animals (OMIA; https://omia.org/). The AVCGv.2 criteria and recommendations were developed by the expertise of the animal genetics community and the ISAG Executive Committee through the Animal Genetics Testing Standardization Committee endorses and strongly encourages their use to evaluate the evidence supporting pathogenicity of putative disease-causing variants.

Animals↗

PubMed2026

Is ophthalmology a pain-free career? A systematic review and meta-analysis of musculoskeletal pain among ophthalmologists.

OBJECTIVE: To estimate the pooled prevalence, anatomical distribution, and occupational impact of work-related musculoskeletal (MSK) pain among ophthalmologists, and to identify modifiable ergonomic risk factors. DESIGN: A systematic review and meta-analysis of published data. The protocol was preregistered (PROSPERO CRD42023422368) and reported in accordance with PRISMA. PARTICIPANTS: The participants were 6691 ophthalmologists from 21 studies. METHODS: Electronic databases (MEDLINE, Embase, Cochrane, and PubMed) were searched for peer-reviewed quantitative studies reporting MSK pain prevalence in ophthalmologists. Pooled estimates with 95% CI were calculated using random-effects models; heterogeneity was quantified using I². MAIN OUTCOME MEASURES: Prevalence of overall and site-specific MSK pain; effects on workload and productivity; prevalence of treatment or mitigation strategies. RESULTS: The pooled prevalence of any MSK pain was 70% (95% CI: 65%-75%; I² = 92%); neck (41%; 95% CI: 35%-47%; I² = 95%), lower back (36%; 95% CI: 32%-39%; I² = 87%), and shoulder pain (28%; 95% CI: 22%-35%; I² = 91%) were most common. Pain led to workload modification in up to 44% and contributed to reduced clinical volume, sick leave, or contemplation of early retirement. Forty-six percent (95% CI: 22%-71%) pursued no treatment; 39% (95% CI: 30%-49%) used medical therapy; and 29% (95% CI: 20%-41%) sought physiotherapy. Heterogeneity was high across studies, reflecting differing case definitions and self-reported measures. CONCLUSIONS: MSK pain affects most ophthalmologists, particularly in the cervical and lumbar regions and frequently alters practice patterns. These findings underscore the need for early ergonomic training, structured micro-breaks, and workspace redesign. Prospective intervention trials are required to establish causality and quantify benefit.

Humans↗

PubMed2026

Biomonitoring of industrial heavy metal pollution via enzymatic and metabolic responses in desert ants (Cataglyphis savignyi) and beetles (Tentyrum sp) as bioindicators.

The current work seeks to evaluate the effectiveness of Cataglyphis saviginyi and Tentyrum sp as indicators of pollution in the city's main industrial regions by analyzing their enzymatic activity and primary metabolites. Soil samples were collected at each site under investigation to analyze soil characteristics and heavy metal content. C. saviginyi and Tentyrum sp were collected across four consecutive seasons (2023-2024) to investigate enzymatic (GPT, GOT, ALP, ACP, LDH) and metabolic (lipid, protein, carbohydrate) biomarkers. The physicochemical properties of the soil differed substantially between the industrial areas and the control site. Soil heavy metal buildup was highest at industrial sites (1 and 4) compared to the control site, with the order being Zn > Cr > Cd > Cu. Heavy metal pollution indices were determined. Increased industrial activity from metal industries, ceramics, and chemical painting companies defines this area, as seen by the high Cdeg, mCd, PI, and PLI values derived for industrial sites 1 and 4. While C. saviginyi and Tentyrum sp deconcentrated and released Cr, Cd, and Zn into the soil via the biological accumulation factor (BAF), Cu acted as a macro-concentrator. Compared with the control site, industrial environments were shown to increase levels of GPT, GOT, LDH, ACP, protein, and carbohydrates in C. saviginyi. However, lipid and ALP activity was suppressed. at industrial sites, Tentyrum sp carbohydrate content was higher than at control sites, but GPT, GOT, ALP, ACP, LDH, protein, and lipid activities were all suppressed. Consequently, enzymatic and metabolic biomarkers proved to be sensitive indicators for assessing industrial heavy metal pollution in desert ecosystems.

Animals↗

PubMed2026

Can ChatGPT Replace Human Clinical Coders? A Comparative Study in Otology Billing.

OBJECTIVE: Evaluate the utility of the large language model (LLM), ChatGPT, for the analysis of operative notes and the generation of Current Procedural Terminology (CPT) codes in comparison to human clinical coders. STUDY DESIGN: CPT billing codes assigned by ChatGPT were compared to existing billing data. Otology practice within a tertiary academic center. METHODS: About 191 operative notes from a single surgeon (9/2022-10/2023) were analyzed. ChatGPT-3.5 and 4 models were prompted for CPT codes based on operative notes. Assessment included determining exact and partial match rates, sensitivity and specificity for targeted procedures, and work Relative Value Units (wRVU) differences between ChatGPT-generated and human-assigned codes. RESULTS: ChatGPT-3.5 achieved exact matches in 22% of cases and partial matches in 32%, while ChatGPT-4 achieved 14% exact and 33% partial matches. When cochlear implantation (CI) was excluded, performance dropped significantly. For CI, ChatGPT-3.5 demonstrated a sensitivity of 94% and specificity of 90%, while ChatGPT-4 showed a sensitivity of 96% and specificity of 92%. In contrast, performance on cartilage grafting was poor, with sensitivities of 4.2% for ChatGPT-3.5 and 0% for ChatGPT-4. ChatGPT-3.5 and 4 showed moderate CPT code matching accuracy among themselves, with slight agreement to human coders. Both models tended to underbill for wRVUs compared to human coders, with significant differences in the values generated. CONCLUSION: This study assessed ChatGPT's effectiveness in automating CPT code assignment for otologic surgeries. While the models achieved high sensitivity values for assigning codes related to cochlear implantation, both models struggled with complex cases, failed to apply modifiers, and often assigned fewer wRVUs. The findings highlight ChatGPT's potential in medical billing but indicate a need for further refinement.

Humans↗

PubMed2026

Genome mining of alkaliphilic cyanobacterial consortia: identification of biosynthetic gene clusters in Sodalinema and associated heterotrophs.

Alkaline soda lakes are high-pH environments that host specialized microbial communities with potential for biotechnology and natural product discovery. We characterized three Sodalinema-dominated cyanobacterial consortia enriched from Canadian soda lakes over 510 days. Using hybrid metagenomic sequencing and metatranscriptomics across pH, alkalinity, and temperature gradients, we reconstructed high-quality metagenome-assembled genomes and assessed functional activity. All consortia converged toward cyanobacteria dominance and exhibited temperature optima between 21°C and 30°C. Phylogenetic analysis placed Sodalinema genomes within a distinct clade affiliated with Candidatus Sodalinema alkaliphilum. Genomic analysis indicated complete biosynthetic pathways for vitamin B5, vitamin B7, and the molybdenum cofactor, but incomplete pathways for vitamins B1, B9, and B12, consistent with patterns observed in Sodalinema yuhuli. Metatranscriptomic profiles showed increased expression of genes involved in phycocyanin and carotenoid biosynthesis at pH 10.2 relative to pH 8.5. Biosynthetic gene cluster analysis revealed that most secondary metabolic potential resided in heterotrophic community members. Roseinatronobacter encoded pathways for N-acyl homoserine lactones, osmoprotectants, betalactones, and prodigiosin, while Alkalimonas, Wenzhouxiangella, and members of the Kiloniellales encoded clusters for lanthipeptides, cyclodipeptides, hydrogen cyanide, and pyrroloquinoline quinone. These findings indicate functional partitioning within the consortia and highlight the contribution of heterotrophs to secondary metabolism.IMPORTANCEAlkaline soda lakes contain microbial communities adapted to high pH that remain underexplored for biotechnology. This study focuses on Sodalinema, a filamentous cyanobacterium that dominates enriched consortia from Canadian soda lakes, and its associated heterotrophic partners. We show that while Sodalinema drives primary productivity, heterotrophic bacteria encode most of the pathways for antimicrobial and signaling compounds. These interactions may support community stability and defense against competing microorganisms. By linking genomic potential with gene expression, this work identifies alkaline cyanobacterial consortia as a source of bioactive compounds and provides a framework for exploring extremophilic microbial communities for natural product discovery.

Sodalinema↗

PubMed2026

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans↗

PubMed2026

Effects of Dynamic Neck Sensorimotor Biofeedback Training in Individuals With Mechanical Neck Pain: A Pilot Randomized Controlled Trial.

Mechanical neck pain (MNP) is commonly accompanied by pain-related functional limitations, sensorimotor disturbances, and fear of movement, which together may contribute to persistent disability. This preliminary randomized controlled trial study investigated the short-term effects of dynamic neck sensorimotor-based biofeedback training in individuals with MNP. 20 MNP patients from outpatient clinics were assigned to a biofeedback training group or a control group. The training group underwent dynamic biofeedback exercises twice weekly for 2 weeks, whereas the control group performed repeated cervical movements without biofeedback. Outcomes included cervical kinematics as repositioning errors (RPE), movement units (MU), maximal range of motion (ROM), and subjective measures, including pain intensity, Neck Disability Index (NDI), and Fear-Avoidance Beliefs Questionnaire (FABQ). All participants completed post-intervention assessments; adherence in the training group was 100%, with no missing data and no adverse events reported. Within the biofeedback training group, participants receiving biofeedback training demonstrated greater improvements in cervical repositioning accuracy during flexion (51.95%, p = 0.04) and extension (46.67%, p = 0.02), along with reductions in fear-avoidance beliefs related to physical activity and work (p < 0.05); these changes were less apparent in the active control group. Exploratory regression analyses suggested associations between improvements in repositioning accuracy and pain reduction, and between increased cervical range of motion and improvements in fear-avoidance beliefs related to physical activity. These pilot findings suggest that dynamic sensorimotor biofeedback training may improve proprioceptive acuity and fear-avoidance beliefs in individuals with MNP, supporting further evaluation in an adequately powered randomized trial.

Humans↗

PubMed2026

Aflatoxins and their biosynthetic precursors in lotus seeds: simultaneous UPLC-MS/MS determination, contamination profiling, and matrix-specific accumulation during Aspergillus flavus infection.

Aflatoxin (AF) contamination poses a severe global threat to food and medicinal material safety, yet existing research focuses on terminal AF metabolites while neglecting residual biosynthetic precursors, leading to potential underestimation of contamination risks. In this study, a UPLC-MS/MS method was established for the simultaneous quantification of six AFs and their five precursors in lotus seeds, with optimization of mass spectrum parameters, chromatographic separation conditions, and sample pretreatment. Method validation confirmed linearity (R2 > 0.99), LODs (0.03-0.36 μg/kg), and recoveries (76.53%-120.0%, RSD < 15%). Analysis of 41 natural lotus seed samples revealed a 63.4% AF contamination rate, dominated by B-group AFs, while O-methylsterigmatocystin (OMST) and versicolorin hemiacetal (VOH) were identified as the primary co-residual precursors with co-occurrence rates ≥ 50%. Notably, AFM1 was predominantly detected in natural samples with AFB1 concentrations exceeding 100 μg/kg. Artificial inoculation experiments further demonstrated that sterilization and sealing conditions modulated AF biosynthesis in lotus seeds, with non-sterilized and non-sealed groups showing delayed fungal metabolism and lower toxin accumulation. A significant linear correlation was observed between AFM1 and AFB1 levels (r = 0.94) in infected samples, demonstrating their accumulation levels are coupled with fungal overall metabolic flux. Given the high co-occurrence rate of OMST/VOH with AFB1 in natural samples, their individual and combined toxicities require in-depth investigation. This work deciphers matrix-specific AF dynamics in lotus seeds, supporting regulatory standard refinement (e.g., precursor inclusion) and targeted control (e.g., time-sensitive drying after harvest). Further studies will focus on exploring the molecular mechanisms of substrate-dependent AF synthesis.

Aflatoxins↗

PubMed2026

Cross-kingdom dynamics of the subgingival bacteriome and mycobiome: A pilot study on the effects of a novel HA-H₂O₂-Glycine formulation to treat periodontitis.

OBJECTIVES: Traditional periodontal therapy primarily focuses on bacterial biofilm control; however, recent evidence also suggests a critical role for the oral mycobiome. This study evaluated the clinical and ecological impact of a novel mouthwash formulation containing hyaluronic acid (HA), hydrogen peroxide (H2O2), and glycine on periodontal patients METHODS: This prospective, randomized split-mouth trial included 13 adult participants with periodontitis treated with HA-H2O2-glycine formula (BMG0703A) used twice a day for seven days. Subgingival plaque samples were collected from periodontal pocket and healthy control sites at baseline (T0) and one-week post-treatment (T1). Microbial and fungal communities were characterized using Next-Generation Sequencing (NGS) of the 16S rRNA and ITS2 regions. Linear Mixed Models (LMM) and Spearman correlation were used to assess taxonomic shifts and cross-kingdom relationships. RESULTS: Sequencing revealed a promising ecological shift: the bacteriome shifted from anaerobic dominance (Olsenella, Peptostreptococcus) toward a health-associated aerobic profile, with Rothia near-doubling (11.91% to 22.68%). The mycobiome underwent a "normalization" effect: Candida abundance decreased significantly (22.8% to 9.1%), while fungal Shannon diversity in pockets returned to healthy-site levels. Inter-kingdom analysis identified antagonistic relationships between expanding commensal bacteria and opportunistic fungi, suggesting that the intervention may help re-establish a protective bacterial niche. CONCLUSIONS: The HA-H2O2-glycine formulation seems to facilitate a rapid, cross-kingdom modulation of the subgingival niche. By reducing anaerobic pathogens and normalizing the mycobiome it appear to induce short-term changes, suggesting potential as adjunctive strategy in periodontal management. CLINICAL SIGNIFICANCE: The present work underlines the possible cross-Kingdom effects of a novel compound.

Humans↗

PubMed2026

A narrative review of what cohorts have taught us and how they have laid the foundation for much of our understanding of type 2 diabetes.

This narrative review provides a historical perspective on how observational research on type 2 diabetes has been developed and consolidated over the last 50 years and how well-designed cohort studies will provide us with knowledge for research and practice in the future and aid guideline development. We have included data from a large number of cohorts from every continent that have been used to study the development and/or progression of type 2 diabetes, including cohorts that are general population-based, disease-based, intervention-based and registry-based. We have structured the results from the past 50 years based on the following themes: diagnosis and screening, complications, risk factors and pathophysiology. We also discuss the strengths and weaknesses of observational research when compared with other research designs. Finally, we discuss the emerging and future directions for type 2 diabetes research using cohorts, which include novel developments, such as artificial intelligence, precision health and the exposome. We conclude that cohort research has significantly advanced our understanding of type 2 diabetes and aided guideline development, and complements experimental work, such as human randomised controlled trials and animal studies. Both approaches are essential and complementary in our pursuit to provide a more comprehensive understanding of the development and progression of type 2 diabetes, and to change dogma, practice and policies for better outcomes.

Humans↗

PubMed2026

Estrone disrupts early reproductive development in juvenile male Siniperca chuatsi and is associated with brain and gonadal responses.

Whether estrone (E1)-associated disruption of early reproductive development in fish is accompanied by brain responses in addition to direct gonadal effects remains unclear. Here, juvenile Siniperca chuatsi, a non-model but economically important freshwater species, were exposed for 60 d to 0, 0.01, 0.1, and 1.0 μg/L E1, spanning environmentally reported and elevated concentrations. By integrating waterborne concentration monitoring, histopathology, transcriptomics, and quantitative real-time PCR (qPCR) validation, we evaluated E1-associated changes in brain and gonadal tissues during early reproductive development. Waterborne E1 concentrations remained generally stable throughout the exposure period. At the highest tested concentration (1.0 μg/L), E1 caused neuronal vacuolation and pyknosis in the hypothalamic region and induced distinct ovarian-like structures in the gonads of genetic males. In the brain, cyp19a1, crhr1, and adcy2a were significantly upregulated, whereas egr1 was significantly downregulated, indicating transcriptional changes in genes associated with local estrogen conversion, stress-response/cAMP signaling, and neuronal activity-related regulation within a broader injury/stress-response background. In the gonad, RNA-seq analysis showed significant downregulation of star2, hsd3b1, cyp17a1, and cyp11b and significant upregulation of hsd17b1, suggesting alterations in steroidogenesis-related gene expression at the transcriptomic level. qPCR analysis of selected gonadal candidate genes showed expression directions generally consistent with the RNA-seq results, and these molecular patterns were consistent with the feminized histological phenotype. Together, these results indicate that E1 can disrupt early reproductive development in juvenile S. chuatsi and support a cautious working model in which E1 exposure is accompanied by concurrent brain and gonadal responses. This study provides new evidence for understanding the toxic effects and ecological risk implications of natural estrogen E1 during early fish development.

Animals↗

PubMed2026

Effects of acute inflammatory challenge on anhedonia and social reward processing: A randomized controlled trial of endotoxin.

Anhedonia is a core feature of depression that reflects reward system dysfunction. Acute inflammatory challenge has been shown to induce transient anhedonia and reward processing deficits, but its effects on distinct components of social reward processes remain poorly understood. This randomized, double-blind, placebo-controlled study evaluated anhedonia and social reward responsivity following acute inflammatory challenge. Low-dose endotoxin (0.8 ng/kg body weight; n = 18) or placebo (same volume of 0.9% saline; n = 22) was administered to female adults (ages 25-44). Anhedonia (Snaith-Hamilton Pleasure Questionnaire) and blood samples for cytokine assessment were collected pre-infusion and 2 and 4 h post-infusion. Social reward motivation (wanting to engage in a social task) was assessed at a baseline eligibility visit and 2 h post-infusion. Sensitivity to positive social cues (attentional bias toward and recognition of happy faces) was assessed pre-infusion and 2 h post-infusion. Results showed that endotoxin increased anhedonic symptoms (p = .005) and decreased social motivation by 2 h post-infusion (p = .001); within the endotoxin condition, changes in both outcomes were associated with increases in TNF-α (p's < .04). A significant condition-by-time interaction for happy-face recognition (p = .011) was driven by increased accuracy in the placebo (p = .04) but not endotoxin (p = .43) condition. Endotoxin administration did not affect attentional bias toward happy faces. Findings suggest that acute inflammatory challenge induces anhedonia and reduces social motivation, with more limited effects on sensitivity to positive social cues, highlighting specific reward-related pathways through which immune activation may contribute to inflammation-associated depression. Future work could examine whether immune-related changes in social motivation contribute to motivational deficits in depression.

Humans↗

PubMed2026

What do we know about medical invalidation and related concepts? - A scoping review and thematic analysis about the definitions, measurements, causes, consequences and potential solutions for medical invalidation.

BACKGROUND: Medical invalidation, medical gaslighting, and related constructs have gained visibility in public discourse but remain inconsistently defined in scientific literature. Despite growing research-often focused on specific diseases- to date, no single review has comprehensively synthesized their definitions, causes, consequences, or methods of measurement. This scoping review addresses this gap by examining medical invalidation and related constructs. METHODS: Using a preregistered protocol, we systematically searched PubMed, CINAHL, Web of Science, Google Scholar, and ProQuest (dissertations) without year restrictions. Eligible sources included peer-reviewed empirical, theoretical, and conceptual work in English addressing invalidation, gaslighting, or closely related notions within healthcare. A total of 158 studies were identified through database searches and citation tracking. Data extraction followed a standardized schema, and findings were synthesized descriptively and through thematic analysis to clarify terminology, map determinants and outcomes, and identify existing measurement approaches. RESULTS: The results showed substantial inconsistency in how "invalidation," "not being taken seriously," and "gaslighting" were defined. Medical invalidation emerged as a multifactorial phenomenon driven by diagnostic challenges, structural and societal factors, provider and patient characteristics, stigma, misattribution, interactional dynamics, academic knowledge gaps, and disease-related complexity. Invalidation was associated with wide-ranging behavioural, emotional, cognitive, physical, relational, and systemic harms, while validation had consistently beneficial effects. Proposed solutions in the summarized studies included communication improvements, clinician training, patient support, targeted research, and structural and systemic changes. DISCUSSIONS: Medical invalidation represents a complex, systemic issue with significant implications for patient safety. The discussion highlights its multifactorial origins, its potential to cause both psychological and physical harm, and the need for clearer conceptualisation within the field. Advancing research requires validated instruments and longitudinal designs to examine underlying mechanisms and consequences. Addressing medical invalidation will demand multi-level interventions to improve communication, reduce structural barriers, and promote equitable, patient-centred care. OSF PREREGISTRATION: https://doi.org/10.17605/OSF.IO/MPE6U.

Humans↗

PubMed2026

BRAIN-Diabetes: Acceptability of an adapted FINGER multidomain intervention among adults living with type 2 diabetes in rural border regions across the island of Ireland.

BackgroundIndividuals with type 2 diabetes mellitus (T2DM) face increased risk of cognitive decline and dementia. Multidomain lifestyle interventions offer a non-pharmacological strategy to support brain health in this high-risk group.ObjectiveThis study examined the acceptability of a culturally adapted FINGER-based intervention among adults living with T2DM in rural border regions of Ireland (BRAIN-Diabetes Trial).MethodsA 6-month pilot randomized controlled trial was conducted. The intervention group received a multidomain program targeting diet, physical activity, and computerized cognitive training (CCT). The control group received standard care. Acceptability was assessed using questionnaires (all participants) and semi-structured interviews (intervention participants). Quantitative data were analyzed descriptively and qualitative data using template analysis, guided by four a-priori themes: trial participation and engagement, dietary behavior change, exercise behavior change, and CCT behavior change.ResultsQuestionnaire data (intervention: n = 28; control: n = 36) indicated high overall acceptability. Dietary and exercise components were rated most positively, while CCT component was less well received. Interviews (n = 25) highlighted facilitators to trial engagement, including perceived health improvements, and social connection, with time constraints and limited personalization as barriers. Dietary change was supported by tailored guidance but hindered by cost and availability. Facilitators for exercise included accessible resources and perceived benefits, with barriers including competing priorities. CCT engagement was mixed, with challenges including digital access and repetitiveness.ConclusionsThe Brain-Diabetes intervention was acceptable and feasible among adults with T2DM. Personalized support and accessible resources were key to engagement. Future work should refine delivery to enhance scalability and long-term adherence among high-risk groups.

Humans↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗