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PubMed2026

Proteomics-based analysis of the defense mechanisms of disease-resistant grass carp against Aeromonas veronii.

Sustainable aquaculture of grass carp (Ctenopharyngodon idella, GC) is consistently threatened by bacterial diseases, particularly those caused by Aeromonas veronii. A disease-resistant grass carp (DR-GC) has been developed by backcrossing female gynogenetic GC with normal male GC, exhibiting improved resistance. However, the systemic molecular mechanisms of DR-GC defending against Aeromonas veronii infection remain largely unexplored. Here, a label-free quantitative proteomics approach was employed to systematically compare proteomic profiles across five tissues (intestine, liver, muscle, skin, and kidney) in DR-GC and GC under healthy and infected conditions. The intestine was identified as the central defense tissue, exhibiting the highest number of differentially abundant proteins (DAPs). In DR-GC, A0A3N0YEK7 (small ribosomal subunit protein eS28), A0A3N0YGT8 (ATP synthase-coupling factor 6) and A0A3N0YNS7 (apolipoprotein A-I) were significantly upregulated in intestine, while D5KZW6 (GCHV-induced protein), A0A3N0Z0A1 and Q8JH84 (hemoglobin subunit alpha) were significantly dysregulated across multiple tissues, which playing the critical roles in defense mechanisms at the protein level. Furthermore, cytochrome P450-associated pathways, cytosolic DNA-sensing and RIG-I-like receptor signaling pathways were identified as crucial coordinators mediating immune and metabolic responses. This study provides the first comprehensive proteomic view of multi-tissue defense mechanisms in DR-GC, and identifies key DAPs and pathways for subsequent functional validation.

Animals↗

PubMed2026

Long-term hormone therapy for perimenopausal and postmenopausal women.

BACKGROUND: Hormone therapy is widely provided to control menopausal symptoms and has been used for the management and prevention of cardiovascular disease, osteoporosis and dementia in older women. This is an updated version of a Cochrane review first published in 2005. OBJECTIVES: To assess the long-term effects of prolonged use (at least one year) of hormone therapy on mortality, cardiovascular outcomes, cancer, gallbladder disease, fractures and cognition in perimenopausal and postmenopausal women. SEARCH METHODS: We used the Cochrane Gynaecology and Fertility Group Specialised Register, CENTRAL, MEDLINE, three other databases and two trial registers, together with reference checking, citation searching and contact with study authors to identify the studies included in the review. The latest search date was 26 September 2024. SELECTION CRITERIA: We included randomised, double-blind trials in which peri- or postmenopausal women took hormone therapy or placebo for at least one year. We included various oestrogen formulations, with or without progestogens. We focused on studies assessing hormone therapy's effects on long-term clinical outcomes, including death, coronary events and cancer. Hormone therapy's efficacy in managing menopausal symptoms was beyond the scope of this review, and is assessed in other Cochrane reviews. DATA COLLECTION AND ANALYSIS: Two review authors independently selected studies, assessed risk of bias and extracted data. We calculated risk ratios (RRs) for dichotomous data and mean differences (MDs) for continuous data, along with 95% confidence intervals (CIs). We assessed the certainty of the evidence using GRADE. MAIN RESULTS: We included 24 studies - with two newly added in this update - involving 45,660 participants. We derived nearly 70% of the data from two well-conducted studies: the Heart and Estrogen/progestin Replacement Study (HERS 1998) and the large, multi-component Women's Health Initiative research programme, which included two hormone therapy arms (WHI 1998). Across all the studies, most participants were postmenopausal American women with one or more comorbidities. The mean participant age in most studies was over 60 years. Only one included study focused on perimenopausal women. We present full results for all included studies with available data in the main review. The results presented below are drawn from WHI 1998, in which the combined hormone therapy arm and the oestrogen-only arm were run concurrently, with women assigned to the appropriate trial based on their uterus status. One study with 16,608 postmenopausal women with an intact uterus compared combined continuous hormone therapy (conjugated equine oestrogen and medroxyprogesterone acetate) to placebo, and measured outcomes at an average of 5.6 years of follow-up. Based on this study, combined continuous hormone therapy probably makes little to no difference to the risk of a coronary event (RR 1.17, 95% CI 0.95 to 1.44; moderate-certainty evidence). It may increase the risk of stroke (RR 1.39, 95% CI 1.09 to 2.09; low-certainty evidence) and venous thromboembolism (RR 2.03, 95% CI 1.55 to 6.64; low-certainty evidence). Compared to placebo, combined continuous hormone therapy probably increases the risk of breast cancer (RR 1.27, 95% CI 1.03 to 1.56; moderate-certainty evidence) and probably makes little to no difference to the risk of lung cancer (RR 1.06, 95% CI 0.77 to 1.46; moderate-certainty evidence). It may increase gallbladder disease requiring surgery (RR 1.64, 95% CI 1.30 to 2.06; 14,203 participants; low-certainty evidence), and probably reduces the risk of all clinical fractures (RR 0.78, 95% CI 0.71 to 0.86; moderate-certainty evidence). One study including 10,739 postmenopausal women who had undergone a hysterectomy compared oestrogen-only (conjugated equine oestrogen) hormone therapy to placebo, and measured outcomes at an average of seven years' follow-up. Based on this study, oestrogen-only hormone therapy probably makes little to no difference to the risk of coronary events (RR 0.94, 95% CI 0.78 to 1.13), venous thromboembolism (RR 1.32, 95% CI 1.00 to 1.74) and breast cancer (RR 0.79, 95% CI 0.61 to 1.01), all with moderate-certainty evidence. It may make little to no difference to the risk of lung cancer (RR 1.04, 95% CI 0.73 to 1.48; low-certainty evidence). Oestrogen-only hormone therapy probably increases the risk of stroke (RR 1.33, 95% CI 1.06 to 1.67) and gallbladder disease requiring surgery (RR 1.78, 95% CI 1.42 to 2.24), and probably reduces the risk of all clinical fractures (RR 0.73, 95% CI 0.65 to 0.80), all with moderate-certainty evidence. We judged most included studies to have a low risk of bias for most domains. The overall certainty of evidence for the main comparisons was moderate. The main limitation was that only about 30% of women were 50 to 59 years old at baseline, the age group most likely to consider hormone therapy for vasomotor symptoms. AUTHORS' CONCLUSIONS: Long-term follow-up of women using hormone therapy suggests that the risk profiles vary between combined hormone therapy and oestrogen-only therapy. Oestrogen-only hormone therapy probably makes little to no difference to coronary events, and probably increases the risk of stroke and gallbladder disease. It probably makes little to no difference in the risk of breast cancer, and probably reduces the risk of all fractures. Combined hormone therapy may increase the risk of thromboembolism and probably increases the risk of breast cancer. These results should be interpreted with caution as they are based on one study using oral hormone therapy, which may not represent the risks of the hormone therapy currently used in clinical practice.

Humans↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

The effects of visuomotor training and tDCS stimulation on visuomotor integration and visual processing: an electrophysiological approach.

BACKGROUND: Visuomotor integration coordinates visual and motor cortical activity to produce goal-directed responses and can be indexed by Rolandic Mu-rhythm suppression and visual evoked potential (VEP) P100 parameters. Perceptual-motor training improves visuomotor performance, and transcranial direct current stimulation (tDCS) over primary motor cortex (M1) has been reported to enhance motor learning when paired with training. This study examined whether anodal M1 tDCS augments the effects of Senaptec visuomotor training in healthy adults. METHODS: Sixty participants were randomized to active anodal tDCS (five 10-minute sessions, 1 mA; n = 31) or sham (n = 29) over M1 immediately before each Senaptec training session; 53 completed all sessions and post-testing. Outcomes were Mu-suppression ratios, VEP P100 latency and amplitude, and Senaptec measures of visual sensitivity and visuomotor control. RESULTS: Active tDCS produced no augmentation of any outcome, with no significant group × time interaction for any measure, consistent across composite and task-level analyses. Training alone produced no change in Mu suppression or visuomotor control. By contrast, both groups showed significant training-related gains in visual sensitivity, including near-far quickness and stereopsis, accompanied by shorter P100 latencies and larger amplitudes, indicating more efficient early visual processing. CONCLUSIONS: A clear dissociation emerged: training produced robust improvements in early visual processing, whereas neither tDCS nor training altered sensorimotor (Mu) or visuomotor-control measures. The tDCS results should be interpreted cautiously given the modest dose and limited power to detect small effects, rather than as evidence of inefficacy. Tablet-based perceptual training enhanced visual processing independent of neuromodulation.

Humans↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗

PubMed2026

Identification of molecular subtypes in clear cell renal cell carcinoma based on chromatin regulators and tumor immune microenvironment profiling.

In the histological classification of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) accounts for the highest proportion and is the most common subtype. Despite advances in management, it continues to be associated with considerable incidence and mortality. Although surgery and systemic therapies are available, their efficacy is constrained by pronounced intratumoral heterogeneity and treatment resistance. Identifying robust biomarkers and clarifying the underlying biological mechanisms are therefore essential to improving diagnosis, risk stratification and therapeutic decision-making. In this work, we identified two ccRCC molecular subtypes displaying divergent chromatin regulator (CR) profiles and different clinical prognoses. Using the genes differentially expressed between these subgroups, we constructed a CR-related score (CRS) that effectively stratified patients according to survival. More analysis concluded that the low expression of CR was more linked with the immune-activated tumors, which encompassed the immune pathway enrichment, as well as the elevation of numerous immune cell subtypes. Moreover, elevated CRS was associated with improved immunotherapy responsiveness. Drug-sensitivity analyses nominated several candidate agents, and SMARCD3 knockdown in 786-O cells inhibited proliferation and migration and reduced sensitivity to masitinib. Collectively, these findings support the prognostic and therapeutic relevance of CR-related states in ccRCC and provide a framework for future experimental validation of chromatin-regulated tumor-immune interactions.

Humans↗

PubMed2026

Pedagogical Efficacy of LLM-Generated Synthetic Data Versus Real-World Clinical Records: A Randomized Controlled Non-Inferiority Trial.

BACKGROUND: Expert-reviewed clinical cases generated by large language models (LLMs) may supplement case resources in medical education, but their short-term educational performance relative to real-case-derived teaching materials remains uncertain. We compared immediate post-training test performance after teaching with the two types of case materials and assessed non-inferiority against a prespecified margin. METHODS: We conducted a prospective, parallel-group, randomized non-inferiority trial. Through the Wenjuanxing online platform, participants were randomized 1:1 to learn with either real-case-derived teaching cases compiled by clinicians and reviewed by experts or AI-generated clinical cases produced by Gemini 3.0 Pro from fully de-identified matched real cases and reviewed by three senior general surgery specialists with full-professor rank. The primary outcome was the total score on an independent 10-item immediate post-training test (0-10 points), with a prespecified non-inferiority margin of -0.5 points. Secondary outcomes included the training-phase performance score, learning efficiency index, single-item mental effort rating, case realism, and case-source judgment. RESULTS: A total of 403 participants were randomized, of whom 386 were included in the modified intention-to-treat analysis: 192 in the real-case group and 194 in the AI-generated case group. The mean post-training test score was 4.95 (SD, 3.35) in the real-case group and 4.61 (SD, 3.35) in the AI-generated case group. The mean difference (AI-generated minus real-case group) was -0.335 points (95% CI, -1.006 to 0.337). Because the lower bound of the confidence interval was below the prespecified non-inferiority margin of -0.5 points, non-inferiority was not demonstrated (one-sided P = 0.314). No significant between-group differences were observed in the training-phase performance score, learning efficiency index, or single-item mental effort rating. AI-generated cases received lower realism ratings for Level 3 cases. The proportion of participants with at least one high-confidence completely incorrect response was 1.6% in the real-case group and 2.1% in the AI-generated case group. CONCLUSIONS: In this short-term, text-based online case-learning setting, no statistically significant between-group difference was observed in immediate post-training test performance; however, non-inferiority of AI-generated clinical cases relative to real-case-derived teaching materials was not demonstrated.

Humans↗

PubMed2026

'Sawa Aqwa' (Stronger Together): A multi-site randomized controlled trial of a brief family systemic intervention for adolescent mental health in Lebanon.

BACKGROUND: There are no evaluated family-based mental health and psychosocial support (MHPSS) interventions for adolescents in Southwest Asia (known as the Middle East), and few whole-family interventions in low- and middle-income countries, despite consistent evidence for the impact of family support on mental health and well-being. This study aims to evaluate the effectiveness of a brief family systemic mental health intervention, deliverable by non-specialists in mental health. METHODS: We conducted an assessor-blind type I hybrid effectiveness-implementation multi-site randomized controlled trial comparing the locally developed family intervention to a waitlist control group for randomly allocated families residing in North Lebanon and Beqa'a governorates. Eligible families presented with medium-to-high risk for child protection concerns (abuse, neglect, child labor, early marriage) and had at least one adolescent aged 12-17 who demonstrated psychological distress. Outcomes at the family, caregiver, and adolescent level were measured pre- and post-intervention, and at 3-month follow-up. RESULTS: Intent-to-treat analyses found a significant between-group effect of the intervention on adolescent-reported family functioning, caregiver mental health, and parenting. No change was found for adolescent psychological distress. Further analyses found effects on adolescent well-being for those who completed the intervention, and that father attendance was associated with better outcomes for adolescent well-being in the intervention group. No other significant moderators were found. At the 3-month follow-up for the intervention condition, family functioning and caregiver well-being significantly dropped from endline. CONCLUSIONS: The study demonstrates mixed results for a non-specialist-delivered family-systemic intervention developed in the context of humanitarian crises in Lebanon. While the intervention did not result in benefits in adolescent-reported symptoms of psychological distress, the intervention group did show greater improvements than the control group on a number of other outcomes, showing the potential impact of working with the wider family system to support adolescents in humanitarian settings.

Humans↗

PubMed2026

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers↗

PubMed2026

A black soybean yoghurt fermented with a reusable probiotic cellulose gel: beneficial effects and metabolic characteristics.

The demand for plant-based yoghurts is continuously increasing. However, achieving stable physicochemical properties and acceptable flavor of the plant-based yoghurts remains challenging. In our previous work, we encapsulated Lactiplantibacillus plantarum (L. plantarum) LCC-605 biofilm into bacterial cellulose (BC), obtaining a LP605@BC gel. LP605@BC gel exhibited excellent harsh-environment resistance abilities and storage stability, and is very suitable as a starter culture. In this work, we used LP605@BC as a starter culture to prepare the fermented plant-based yoghurt (e.g., black soybean yoghurt, BSY-LP605@BC). After fermentation, the inverted nonflowing yoghurt was formed due to the strong interaction between protein and exopolysaccharide (EPS) produced by LCC-605 during fermentation. In addition, the water holding capacity (67.2%) of BSY-LP605@BC was also greatly improved. The viable bacterial counts in BSY-LP605@BC reached 11.2 log CFU/mL after 21 days of storage. BSY-LP605@BC showed increased antioxidant, cholesterol-lowering abilities, and hypoglycemic potential compared with the unfermented black soybean milk. Interestingly, LP605@BC could be reused at least 5 times, demonstrating excellent sustainability. Significant metabolomic differences between BSY-LP605@BC and the black soybean milk were observed via untargeted metabolomic analysis, further proving the beneficial effects of BSY-LP605@BC. Overall, our work developed an effective reusable starter culture for preparing the plant-based yoghurt in a sustainable manner, providing a new design direction and form of starter culture.

Yogurt↗

PubMed2026

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗

PubMed2026

Effects of Exergame Balance Training with Variable Cognitive Motor Challenges on Serum BDNF, p-tau181, and Cognitive Functions in Adults with Mild Cognitive Impairment: A Randomized Trial.

INTRODUCTION: Cognitive-motor exergame balance training may increase attentional demands and neuronal processing, potentially affecting serum levels of brain-derived neurotrophic factor (BDNF), Aβ1-42, and p-tau181, as well as train cognitive abilities in adults with mild cognitive impairment (MCI). This study aimed to compare the effects of exergame balance training of mild, moderate, high-difficulty, and Wii Fit™ groups on blood serum levels of BDNF, Aβ1-42, p-tau181, and cognition function in adults with MCI. METHODS: In this four-arm, parallel group randomized clinical trial, 97 adults with MCI were randomly assigned to exergame balance training groups of mild, moderate, high-difficulty, and Wii Fit exergame as a control group. All participants received 40 min/session, 3 times/week for 8 weeks. Assessment of serum levels of p-tau181, Aβ1-42, BDNF, and cognitive functions was conducted at baseline, after weeks 4 and 8. A mixed-model analysis of covariance was used, with post-baseline measurements (weeks 4 and 8) specified as the within-subject factor and the corresponding baseline value entered as a covariate to adjust for initial between-group variability. RESULTS: A significant group × time interaction was found for BDNF, F(3,92) = 6.413, P = 0.017, ηp2 = 0.181; p-tau181, F(3,92) = 4.640, P = 0.040, ηp2 = 0.138; attention, F(3,92) = 4.171, P = 0.045, ηp2 = 0.057; abstraction, F(3,92) = 4.263, P = 0.043, ηp2 = 0.058; and visuospatial skills, F(3,92) = 6.931, P < 0.001, ηp2 = 0.234. CONCLUSION: Cognitive-motor challenge-based exergame balance training was associated with an increase in serum BDNF, a reduction in p-tau181. In contrast, the Aβ1-42 levels remained stable. These changes were accompanied by improvement in selective cognitive functions (attention, abstraction, and visuospatial skills) in individuals with MCI. Greater effects were observed in moderate and high-difficulty groups, suggesting the importance of intervention intensity in promoting cognitive and neurobiological outcomes in MCI.

Humans↗

PubMed2026

Comparative analyses of olfactory receptor repertoires in Schizothorax fish based on the chromosome-level genomes: Implications for regulatory roles of dietary differentiation and ploidy variation.

The olfactory receptor (OR) genes constitute the molecular basis of fish olfaction, mediating survival behaviors and environmental adaptation while coevolving with habitat-driven evolution. Schizothorax, a cyprinid genus endemic to the Qinghai-Tibetan Plateau, exhibits remarkable dietary divergence and ploidy variation in response to plateau environmental changes, which presumably facilitates the adaptive evolution of OR genes. However, the evolutionary patterns of OR genes associated with trophic divergence and ploidy variation in this genus remain unclear. In this study, three species were selected: the herbivorous diploid S. macropogon, the carnivorous diploid S. lantsangensis, and the herbivorous tetraploid S. curvilabiatus. S. macropogon possessed 142 OR genes (92.25% functional), primarily located on chromosomes 14 and 24, with the fewest sequence clusters. Such compact gene repertoire and highly overlapping chromosomal clusters indicated specialization for a herbivorous olfactory niche. S. lantsangensis contained 127 OR genes (93.70% functional), concentrated on chromosomes 4 and 5, with fewer sequence clusters and a scattered distribution, reflecting evolution of OR genes under carnivorous feeding habits. The herbivorous tetraploid S. curvilabiatus exhibited striking features: 316 OR genes (94.30% functional), the most subfamilies, unique ε and κ OR subfamilies, and species-specific motifs. These characteristics revealed that ploidy, rather than herbivory, dominated OR gene evolution. In conclusion, dietary differentiation and ploidy variation together drove olfactory adaptive evolution in Schizothorax, providing new insights into vertebrate OR gene ecological adaptation.

Animals↗

PubMed2026

Six weeks of isometric resistance training led to evidence of corticospinal but not reticulospinal adaptation in previously untrained adult males.

The latest hypothesis regarding the source of enhanced neural activation from resistance training is the reticulospinal rather than the corticospinal tract, based on invasive animal and emerging human data. The present study employed a six-week isometric resistance training intervention in a randomized controlled design to address this knowledge gap. Thirty-nine healthy, untrained males (age ~23 y, sustained contraction group n = 13, explosive contraction group n = 9, control group n = 17) underwent neuromuscular and electrophysiological testing and completed all study requirements. Maximal isometric torque (MVC) and rate of torque development (RTD) were measured during a familiarization session as well as before and after the six-week period. Transcranial magnetic stimulation was used to assess motor-evoked potential (MEP) area and silent period duration while subjects contracted to 10% of MVC. Loud sound (120 dB) was used to modulate MEP area and reaction time to visual stimuli during the StartReact test. Only the intervention groups demonstrated significant improvements in MVC (27%) and RTD (60%) (both P < 0.01), along with reduced MEP area (- 21%) and silent period duration (- 23%) (both P < 0.01). The sustained contraction group showed reduced modulation of reaction time and increased MEP suppression due to loud sound. Short-term resistance training seemed to reduce cortical inhibition and corticospinal excitability in both training groups. The study showed conflicting changes in measures purported to evaluate reticulospinal functioning. It is recommended to examine different forms of resistance training and longer training exposure in future.

Humans↗

PubMed2026

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans↗

PubMed2026

Artificial intelligence-derived myocardial fibrosis on cardiac magnetic resonance for prognosis in cardiomyopathy: A systematic review of a sparse evidence base.

BACKGROUND: Myocardial fibrosis on cardiovascular magnetic resonance (CMR), assessed by late gadolinium enhancement (LGE) and parametric mapping, is an established predictor of adverse events in cardiomyopathy. We assessed whether artificial intelligence (AI) quantification of fibrosis adds independent prognostic value. METHODS: We searched six databases, a clinical-trials register, and a preprint server from inception to 13 June 2026. Eligible studies used AI to generate a fibrosis marker in adults with ischemic or nonischemic cardiomyopathy, with covariate-adjusted outcomes over ≥12 months. Risk of bias was assessed using PROBAST, PROBAST+AI, and QUIPS. Fewer than three comparable studies precluded meta-analysis; certainty was rated using GRADE. RESULTS: Of 448 records (381 after de-duplication), 18 full texts were reviewed and two included, one peer-reviewed and one preprint. In an ischemic-cardiomyopathy registry (Ghanbari et al.; n = 216 analytic, 26 events), AI-derived dense LGE scar predicted arrhythmic events (univariable hazard ratio [HR] 2.35, 95% CI 1.33-4.15), and AI-derived but not manual scar improved discrimination beyond guideline criteria (area under the curve 0.63 to 0.68; p = 0.02). In a nonischemic dilated-cardiomyopathy preprint (Kim et al.; n = 347, 119 events), automated extracellular volume ≥30% predicted cardiovascular death or heart-failure hospitalization (adjusted HR 2.00, 95% CI 1.32-3.03). Both were at high risk of bias, with data-derived thresholds and no external validation. CONCLUSIONS: Across only two studies, AI-derived fibrosis was independently associated with adverse cardiovascular events, but its added value over manual quantification remains unproven. Certainty was very low. The evidence base is sparse and not yet ready for clinical use.

Humans↗

PubMed2026

Effects of faba bean-based crisping culture on phenotypic characteristics, muscle quality, and serum metabolome in Nile tilapia: Screening biomarkers to assess the degree of crisping.

Feeding Nile tilapia (Oreochromis niloticus) a faba bean-based crisping diet enhances muscle hardness (crispness) and overall flesh quality. However, the underlying mechanisms and reliable biomarkers remain insufficiently defined. This study integrated phenotypic traits, muscle texture, collagen content, serum antioxidant enzyme activities (SOD, CAT, and GSH-Px), MDA levels, and serum metabolomics to understand the determinants of muscle crisping. Fish were assigned to a crisping diet or a control group for 90 days. Individuals in the crisping group were implanted with passive integrated transponder (PIT) tags to enable correlation analyses among phenotypic traits (body weight/length/frame changes), serum indicators (NAM, FAD, and GSH-Px) and muscle hardness. Compared with controls, the crisping diet significantly increased muscle hardness, gumminess, and chewiness, accompanied by elevated collagen content. Antioxidant profiles were altered, with higher activities of serum SOD and CAT, together with elevated MDA levels and reduced GSH-Px activity (P < 0.05). Metabolomic analysis identified 830 differential metabolites (682 upregulated and 148 downregulated), predominantly comprising carboxylic acids and derivatives, glycerophospholipids, and benzene derivatives. Enrichment analysis indicated significant involvement in general metabolic pathways, ATP-binding cassette (ABC) transporters, amino acid biosynthesis, and glycine, serine, and threonine metabolism (P < 0.05). Notably, acetylpyruvate was upregulated in glutathione metabolism, nicotinate and nicotinamide metabolism, and galactose metabolism; pantothenic acid was upregulated in glycine, serine, and threonine metabolism; whereas δ-tocotrienol was downregulated. Correlation analysis revealed weak negative associations between muscle hardness and phenotypic traits (body weight/length/frame changes D5-7, D5-10, D7-8) (P < 0.05). In contrast, serum NAM and FAD were weakly positively correlated with muscle hardness, whereas GSH-Px showed a weak negative correlation (P < 0.05). Collectively, these findings suggest that body weight, body length, frame measurements (D5-7, D5-10, and D7-8), and serum NAM, FAD, and GSH-Px are associated with the degree of muscle crispness in Nile tilapia fed a faba bean-based crisping diet and may serve as candidate biomarkers under these culture conditions.

Animals↗

PubMed2026

Alginate-based edible coating incorporating green tea extract for preserving postharvest quality and safety of white mushrooms (Agaricus bisporus).

This study aimed to evaluate the effects of a sodium alginate based edible coating incorporated with green tea extract (GTE) (Camellia sinensis) on the postharvest quality attributes and antimicrobial activity against Listeria monocytogenes in white mushrooms during refrigerated storage. The phenolic profile of GTE was characterized, and its minimum inhibitory concentration (MIC) against L. monocytogenes (1.6 mg/mL) was determined. Sodium alginate coatings, with (ALG-GTE) or without GTE (ALG) at MIC (1.6 mg/mL), were characterized (functional groups, solubility in water, moisture, thickness, water contact angle and color) for their chemical and physical properties. The effects of ALG-GTE coatings on quality parameters (firmness, weight loss, color, pH, sugars and organic acids), enzymatic activity [polyphenol oxidase (PPO), peroxidase (POD) and pectin methylesterase (PME)], antimicrobial activity against L. monocytogenes (5 log CFU/g), and surface characteristics (3D optical profilometry) were assessed in white mushrooms (Agaricus bisporus) during refrigerated storage (8 days, 4 ± 1 °C, 90-95% RH). The ALG-GTE coatings preserved sugar composition, particularly rhamnose, reduced organic acids accumulation and delayed weight and firmness loss, reduced color changes, and decreased PME activity in coated white mushrooms. L. monocytogenes counts decreased by 1.4 log CFU/g after 1 day, and no viable cells were detected after 2 days (< 1.5 log CFU/g) in ALG-GTE coated white mushrooms. In addition, ALG-GTE coated white mushrooms exhibited smoother surfaces than uncoated samples. These findings highlight the potential of ALG-GTE coatings as a sustainable alternative capable of improving the microbiological safety and delaying the postharvest changes in fresh mushrooms.

Agaricus↗