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PubMed2026

Baseline Computed Tomography Coronary Angiography and Polygenic Risk Profiles in Adults With Type 2 Diabetes: A Cross-Sectional Analysis From the VOLTAIRE Study.

AIMS: To characterise baseline clinical, anatomical, and genetic cardiovascular risk profiles in participants enrolled in the VOLTAIRE (Evaluation of Polygenic Scores and CT Imaging in Risk Factor Modification in Patients with Type 2 Diabetes) study and examine concordance across these domains. METHODS: This analysis included adults with T2D who completed baseline computed tomography coronary angiography (CTCA) and polygenic risk score (PRS) assessment prior to randomisation in the VOLTAIRE study. Coronary atherosclerosis was evaluated using coronary artery calcium (CAC) score and CTCA-derived stenosis severity. Clinical risk was assessed using the New Zealand Society for the Study of Diabetes 5-year cardiovascular risk calculator. Polygenic risk for coronary artery disease was assessed using a genome-wide PRS and categorised into tertiles. RESULTS: Among 126 participants with T2D (mean age 57.5 ± 8.7 years; 62.7% male), coronary atherosclerotic burden was highly heterogeneous: 34.9% had CAC = 0, whereas 19.8% had CAC ≥ 400. Moderate-to-severe coronary stenosis (≥ 50%) was present in 40.5% of participants overall, including 20.4% of those classified as low clinical risk. PRS distribution was variable (low 37.3%, intermediate 35.7%, high 27.0%). Overlap between anatomical, genetic, and clinical domains was limited, with only 8.7% of participants classified as high risk across all three. CONCLUSIONS: Substantial heterogeneity and limited overlap exist between anatomical, genetic, and clinical cardiovascular risk measures in T2D. These findings support a multimodal approach to risk assessment integrating imaging and genetic profiling. TRIAL REGISTRATION: https://www. CLINICALTRIALS: gov; ID: NCT07091162.

Aged↗

PubMed2026

Gastric carcinoma classification in the WHO 6th edition (2026): Updated framework and emerging entities.

The sixth edition of the WHO Classification of Digestive System Tumours (2026) represents an important step in the continuing evolution of gastric carcinoma classification. While preserving morphology as the foundation of diagnosis, it incorporates advances in molecular pathology, genotype-phenotype correlations, tumour evolution, and predictive biomarker assessment. This review summarizes the development of the WHO classification from the third edition (2000) to the sixth edition (2026) and highlights its relationship with other major classification systems, including those of Laurén, Nakamura, and the Japanese Gastric Carcinoma Association (JGCA). Major histological categories remain largely unchanged; however, several important conceptual and diagnostic refinements have been introduced. These include recognition of crawling-type adenocarcinoma as a distinctive variant of tubular adenocarcinoma, subclassification of poorly cohesive carcinoma into signet-ring cell and non-signet-ring cell subtypes, introduction of the concept of pure signet-ring cell carcinoma, and increased emphasis on tumour evolution. The sixth edition also expands and refines the spectrum of uncommon gastric carcinoma subtypes, including gastric carcinoma with lymphoid stroma, AFP-producing carcinoma, micropapillary adenocarcinoma, gastric adenocarcinoma of fundic-gland type, and gastric sarcomatoid carcinoma. Crucially, molecular subgroups originally proposed by The Cancer Genome Atlas (TCGA) and actionable biomarkers-including HER2 (ERBB2), Claudin 18.2, mismatch repair deficiency/microsatellite instability (dMMR/MSI), and programmed death-ligand 1 (PD-L1)-have transitioned from research-based categories into essential tools for precision oncology. Rather than providing exhaustive diagnostic criteria, this review offers a conceptual framework and encourages consultation of the original WHO text for full details. These advances illustrate the transition of gastric carcinoma classification from a predominantly morphology-based system toward an integrated histomolecular framework that more closely links pathological diagnosis with tumour biology, prognostication, and therapeutic stratification.

Crawling-type adenocarcinoma↗

PubMed2026

Novel non-contrast computed tomography parameters for predicting spontaneous stone passage and surgical requirement in ureteral stones: The role of ureteral wall thickness and dilatation ratio.

We investigated the predictive value of standard non-contrast computed tomography (NCCT) measurements, the ureteral dilatation ratio (DDR) and intraluminal urine stasis markers, for spontaneous stone passage (SSP) versus surgical intervention in patients with ureteral stones. We also evaluated ureteral wall thickness (UWT) as a practical clinical marker. This retrospective study included 461 patients diagnosed with ureteral stones via NCCT. Patients were categorised into two groups based on clinical outcomes: the spontaneous passage group (MET; n = 229) and the endoscopic surgery group (URS; n = 232). Stone volume, stone density (HU), UWT, DDR and intraluminal urine attenuation values were measured for all patients. Independent risk factors were identified using a multivariate logistic regression model and clinical cut-off values were determined via ROC curve analysis. Stone volume, density, UWT and hydronephrosis grade were all significantly higher in the URS group. Multivariate regression analysis revealed that increased UWT (OR: 5.03, 95% CI: 3.66-6.90; p < 0.001) was the strongest independent predictor of surgery. Higher DDR (OR: 1.88; p = 0.003), advanced hydronephrosis, stone volume, and density also increased surgical risk. A UWT cut-off ≥ 2.97 mm predicted surgery with 84.8% sensitivity and 84.3% specificity (AUC: 0.872). A DDR cut-off > 1.79 yielded 81.7% specificity and 40.4% sensitivity. UWT weakly correlated with stone volume (r = 0.145), indicating wall thickening reflects an inflammatory response rather than a mere mechanical consequence. UWT is a superior predictor of SSP failure, supported by increased DDR as a highly specific complementary risk factor. These parameters could help clinicians to identify patients who would benefit from early surgical counselling and intervention rather than prolonged conservative management.

Humans↗

PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗

PubMed2026

Comprehensive assessment of vasospastic angina using coronary computed tomography angiography: synergistic value of the presence of myocardial bridge, perivascular inflammation, and myocardial extracellular volume fraction.

AIMS: Coronary computed tomography angiography (CCTA) has evolved beyond anatomical assessment to include sophisticated tissue characterization. While an elevated perivascular fat attenuation index around the right coronary artery (FAI-RCA) is known to reflect coronary inflammation in vasospastic angina (VSA), recurrent vasospasms may also induce chronic subclinical myocardial injury and subsequent remodelling, potentially associated with an increased myocardial extracellular volume fraction (ECV). However, the diagnostic integration of ECV and FAI-RCA for identifying VSA in patients with angina with non-obstructive coronary arteries (ANOCA) remains to be elucidated. METHODS AND RESULTS: This study included consecutive ANOCA patients who underwent CCTA with a dedicated ECV protocol, followed by an invasive spasm provocation test. Comprehensive CCTA analysis quantified both FAI-RCA and the transmural ECV gradient (the difference between endocardial and epicardial ECV: ECVEndo - ECVEpi). Of the 100 patients analysed (mean age: 65.3 ± 11.8 years; 55% male), 27 were diagnosed with VSA. Multivariable logistic regression analysis identified transmural ECV gradient [odds ratio (OR): 1.12, 95% confidence interval (CI): 1.01-1.25], presence of myocardial bridging (MB) (OR: 3.49, 95% CI: 1.25-9.74), and high FAI-RCA (> -70.95 Hounsfield units [HU]) (OR: 5.79, 95% CI: 2.06-16.30) as significant independent predictors of VSA (all P < 0.05). Notably, the integration of transmural ECV gradient provided incremental diagnostic value beyond FAI-RCA and MB, as assessed by the Net Reclassification Improvement and Integrated Discrimination Improvement. CONCLUSION: A multi-parametric CCTA approach potentially identifies patients at high risk for VSA. The significant association of the transmural ECV gradient with VSA suggests that myocardial remodelling imaging provides a novel diagnostic window into the cumulative myocardial impact of vasospasm, independent of active adipose tissue inflammation and the presence of MB.

Humans↗

PubMed2026

Response-adapted surgical de-escalation following neoadjuvant immunotherapy in resectable mucosal HNSCC A systematic review and meta-analysis.

INTRODUCTION: Recent encouraging outcomes with neoadjuvant immune checkpoint inhibitors (ICIs) in mucosal head and neck squamous cell carcinoma (HNSCC) have generated interest in surgical de-escalation. However, the oncologic safety of response-adapted surgery (RAS) and its ability to achieve survival outcomes comparable to baseline-planned surgery (BPS) remain uncertain. METHODS: A systematic search of the PubMed, EMBASE, Cochrane Library, and the Clinical Trials Registry for studies of neoadjuvant ICIs, with or without chemotherapy, in resectable mucosal HNSCC, that explicitly report surgical extent, between 2020-2025 was performed. Two independent reviewers extracted data following PRISMA guidelines. Main outcomes included major pathologic response (MPR), pathologic complete response (pCR), event-free survival (EFS), and overall survival (OS). Study-level proportions were pooled by random effects models. Heterogeneity was assessed by the I2 statistic. RESULTS: The comparative analysis consisted of 4 RAS studies (involving 202 patients) and 11 BPS studies (403 patients). The pooled overall EFS was 83.3% (76.9-88.2) for the former and 82% (75.2-87.2) for the latter (P=.751), and the respective pooled OS was 92.3% (87.5-95.3) and 91.4% (80.3-96.5) (P=.839). The pooled pCR rate was 41.7% (95% CI 5.4-48.4; I2=.0) for RAS and 19.8% (95%CI 13.3-29.6; I2=.62) for BPS (P=.001), while the MPR was not significantly different (59.6%, versus 48.5%, P=.245). RAS was associated with greater organ preservation and reduced need for mandibulectomy and free-flap reconstruction. CONCLUSIONS: RAS following neoadjuvant ICIs in mucosal HNSCC may enable surgical de-escalation with preserved oncologic outcomes and improved function in selected patients. Larger prospective studies are warranted.

Humans↗

PubMed2026

Linked-color imaging with computer-aided detection and the proximal adenoma miss rate: a randomized tandem trial.

BACKGROUND AND AIMS: Linked-color imaging (LCI) aids the detection and characterization of lesions. Computer-aided detection (CADe) systems have been introduced to improve lesion detection during colonoscopy. Although several studies have been reported regarding LCI, few have investigated the combination of LCI and CADe. This study aimed to evaluate the efficacy of LCI with CADe colonoscopy compared to conventional white-light colonoscopy. METHODS: A single-center, randomized tandem trial was conducted. Participants referred for first-time colonoscopy after fecal immunochemical test (FIT)-positive, asymptomatic screening, or surveillance colonoscopy were randomized (1:1) to undergo CADe-assisted colonoscopy of LCI or white-light imaging (WLI) in the right side of the colon. The primary outcome was adenoma miss rate (AMR) in the right side of the colon. Secondary outcomes included polyp miss rate (PMR), diminutive adenoma miss rate (dAMR), sessile serrated lesion miss rate (SSLMR), advanced adenoma miss rate, advanced neoplasia miss rate, flat-type lesion miss rate (FMR), and the differences in miss rates based on expertise. RESULTS: Among 232 randomized participants, 209 were analyzed (LCI/CADe: 102; WLI: 107). AMR (WLI: 39% vs LCI/CADe: 20%; P = .001), PMR (42% vs 18%; P < .001), and dAMR (42% vs 21%; P = .003) were significantly lower in the LCI/CADe arm, particularly among experts. SSLMR (46% vs 0%), advanced AMR (30% vs 0%), advanced neoplasia miss rate (25% vs 0%), and FMR (27% vs 5.6%) were lower in LCI/CADe, although without statistical significance. CONCLUSIONS: Compared to conventional colonoscopy, LCI with CADe colonoscopy resulted in a statistically significant decrease, especially in AMR. (UMIN 000050685).

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

In silico identification of DNMT1 inhibitors from the PlantCyc database through computational approach to assess the anti-cancer potential of nutraceutical compounds in breast cancer.

Breast cancer accounts for a disproportionate share of global cancer-related deaths, with 670,000 fatalities and 2.3 million new diagnoses recorded in women during 2022 alone. Existing treatment modalities carry considerable toxicity burdens, and resistance to available agents remains an unresolved clinical problem. DNA methyltransferase 1 (DNMT1), the enzyme chiefly responsible for maintaining genome-wide methylation patterns during DNA replication, has been mapped out as a high-value target in breast cancer because its dysregulation silences tumour suppressor genes through promoter hypermethylation. The present work involves hierarchical in silico workflow to screen 4549 plant-derived compounds from the PlantCyc database (v16.0.3) against the human DNMT1 catalytic domain (PDB ID: 4WXX). Ten top-scoring compounds were taken forward for molecular docking via AutoDock Vina; Quercetin and Kaempferol both recorded the highest binding affinities at -9.5 kcal/mol, Wogonin (-9.3 kcal/mol) and Xanthohumol (-8.1 kcal/mol) also emerged as strong binders. Pharmacokinetic evaluation using ADMET-AI confirmed that all 10 compounds met Lipinski's rule of five, with human intestinal absorption values at or above 0.98. Wogonin and Xanthohumol were selected for a 100 ns all-atom molecular dynamics (MD) simulation in GROMACS due to their well-rounded ADMET profiles and limited existing data on their specific interactions with DNMT1 in breast cancer. Across all measured trajectory metrics, backbone RMSD, residue fluctuation, radius of gyration, solvent-accessible surface area, and intermolecular hydrogen bond count, Wogonin formed a more stable, compact complex. These findings suggest that Wogonin and Xanthohumol are non-toxic nutraceutical candidates suitable for DNMT1 targeted epigenetic therapy, with computational foundation strong enough to facilitate future in vitro and in vivo validation work.

Humans↗

PubMed2026

Photon-counting detector computed tomography (PCD-CT) in multiple myeloma: a systematic review and trial sequential meta-analysis on image quality and radiation dose.

OBJECTIVES: To systematically review and perform a meta-analysis comparing the effects of PCD-CT versus EID-CT on image quality (sharpness) and radiation dose (CTDIvol) in patients with bone lesions due to multiple myeloma (MM). METHODS: A comprehensive search of PubMed, Embase, Scopus, and Cochrane Central was conducted from inception to October 2025. Studies comparing PCD-CT and EID-CT in MM patients were included. Methodological quality was assessed using ROBINS-I, and the certainty of evidence was assessed using GRADE. RESULTS: A total of 41 studies were identified that matched our search criteria. After duplicate removal and screening, five studies (n = 170 patients) were included in the systematic review, with four contributing to the meta-analysis. PCD-CT showed a significant pooled mean difference in image sharpness (mean difference, + 0.99 points; 95% CI, 0.62-1.37; p < 0.001). PCD-CT also demonstrated a reduction in radiation dose (mean difference, -4.95 milligrays; 95% CI, -8.39 to -1.50; p = 0.005). Trial sequential analysis (TSA) confirmed stability of pooled estimates, with conclusive evidence for image sharpness improvement, and suggestive yet incomplete evidence for radiation dose reduction. CONCLUSION: Compared to EID-CT in MM, PCD-CT significantly improves subjective image sharpness as supported by trial sequential analysis. Conventional meta-analysis suggested a reduction in radiation dose with PCD-CT; however, trial sequential analysis indicated that the cumulative evidence remains inconclusive. Further large-scale studies are suggested to confirm the magnitude of the radiation dose reduction benefit.

Humans↗

PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗

PubMed2026

Effectiveness of kinesiologic tape in the management of postoperative trismus, discomfort, and edema in mandibular fractures: a randomized controlled trial.

OBJECTIVE: This study compared kinesiologic taping (KT) with conventional elastic adhesive bandaging in managing postoperative morbidity following open reduction and internal fixation. STUDY DESIGN: In this prospective, randomized controlled trial conducted at KLE Dr Prabhakar Kore Hospital, 26 patients with unilateral mandibular fractures were allocated into two groups: Group 1 received an elastic adhesive bandage (n = 13) and Group 2 used KT (n = 13). Pain (Visual Analog Scale), facial swelling (standardized linear measurements), and maximum interincisal distance were recorded at baseline and on postoperative Days 2 and 5. Data were analyzed using repeated measures ANOVA and independent t tests (p < .05). RESULTS: The KT group showed significantly lower pain scores and reduced facial edema at Days 2 and 5 compared with controls (P < .05). Trismus improved in both groups without significant intergroup differences. No adverse effects were observed. CONCLUSIONS: KT is a safe and effective adjunct for reducing early postoperative pain and edema after mandibular fracture fixation.

Humans↗

PubMed2026

Physical Appearance Anxiety and Eating Disorders Symptomatology: A Systematic Review and Meta-Analysis.

The present study aimed to assess the link between physical appearance anxiety (PAA) and eating disorder (ED) symptomatology by a meta-analysis of existing literature. Eligible studies were searched across six electronic databases up until November 20, 2025. Pooled effect sizes (r) were calculated using random-effects models. Potential variables that influence effect heterogeneity were analyzed by univariable and multivariable meta-regressions. Influence analyses and a three-parameter selection model (3PSM) were used to assess robustness of the results and publication bias. Twenty-seven effect sizes from 21 studies (N = 5261) were obtained. The results indicated a strong association (i.e., r = 0.559) between the two variables under consideration, which was notably stronger (i) among females compared to males; and (ii) for overall eating disorder symptoms rather than bulimic symptoms. The results of this study advocate for further investigation into the effectiveness of addressing anxiety responses related to personal body traits, particularly among females, within the context of preventing and treating eating disorders.

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↗

PubMed2026

Feeding the disease: The impact of nutritional supplementation on Nosema (Vairimorpha) infection in honey bees (Apis mellifera).

Honey bees (Apis mellifera) experience variable colony losses across regions and years, with infectious diseases representing a key component of colony health challenges. Among the most prevalent pathogens are the microsporidian parasites Nosema apis and Nosema ceranae, whose impacts on host survival and transmission vary widely depending on context. While nutritional supplementation is commonly used to support honey bee health, its effects on Nosema infection outcomes remain unclear. Here, we experimentally tested whether dietary enrichment alters survival and infection intensity following exposure to a mixed Nosema inoculum. Newly emerged worker bees were challenged with Nosema spores and maintained on either a basic sucrose diet or the same diet supplemented with a commercial pollen substitute. Dietary enrichment significantly increased both mortality risk and infection intensity in Nosema-infected bees, while having no detectable effect on survival in uninfected controls. These results indicate that supplementation can, counter intuitively, exacerbate nosemosis by promoting parasite replication rather than enhancing host resistance. Our findings highlight the importance of distinguishing nutritional effects on host tolerance versus resistance, and caution that interventions intended to improve bee nutrition may inadvertently increase pathogen production and transmission potential under certain conditions.

Animals↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗

PubMed2026

Reinforcement learning-based dynamic ensemble for missense variant effect prediction and tiered prioritization of VUS.

BACKGROUND: Accurate classification of missense variants remains a challenging task despite major advances in genomics. Numerous computational models have been developed to assist in variant classification, but often require repeated integration and benchmarking efforts. Ensemble methods have been proposed to overcome the limitations of single predictors, but mostly rely on fixed, predefined weights that constrain their ability to capture interactions among predictive signals. METHODS: We present GenixRL, a dynamic ensemble framework that reformulates model fusion as a reinforcement learning optimization problem. GenixRL uses a Q-learning agent to learn a policy that dynamically weights the probabilistic outputs of complementary predictors, including BayesDel (addAF and noAF), ClinPred, and MetaRNN. Replacing static weighting with policy learning allows GenixRL to adaptively identify optimal weightings and substantially improve classification accuracy. RESULTS: In benchmark evaluation against 25 state-of-the-art predictors, GenixRL achieved an AUROC of 0.9644 on an independent ClinVar dataset. On saturation genome editing assays for BRCA1 and BRCA2, GenixRL achieved the best performance and ranked highest on 14 of 17 clinically significant genes in a zero-shot evaluation. Applied to uncertain and conflicting ClinVar variants, GenixRL enabled tiered, evidence-based prioritization of hundreds of thousands of variants as likely pathogenic or pathogenic with high confidence, supported by orthogonal population evidence from gnomAD. CONCLUSION: GenixRL advances pathogenicity prediction for missense variants and provides an adaptive ensemble that sorts variants of uncertain significance into tiered candidates for expert curation and functional validation.

Mutation, Missense↗

PubMed2026

Robotic-assisted transbronchial biopsy versus computed tomography-guided transthoracic needle biopsy for peripheral pulmonary lesions: a systematic review and meta-analysis of direct comparative studies.

Robotic-assisted bronchoscopy (RAB) and computed tomography-guided transthoracic biopsy (CTTB) are competing strategies for sampling peripheral pulmonary lesions (PPLs). Whether they differ in yield or safety is uncertain. To our knowledge, this is the first systematic review restricted to direct comparisons. We searched MEDLINE, Europe PMC, Scopus, Web of Science and ClinicalTrials.gov from inception to 7 July 2026 for studies directly comparing RAB with CTTB in adults with PPLs. The primary outcome was strict 2024 American Thoracic Society/American College of Chest Physicians diagnostic yield. Risk of bias was assessed with ROBINS-I and certainty with GRADE. A cohort-genealogy step identified, per outcome, the largest set of cohorts sharing no patients; only that set was pooled, with Hartung-Knapp and Mantel-Haenszel sensitivity analyses. Five retrospective studies from one US health system were eligible. Four share patients; at most three cohorts are mutually independent. Across those three, diagnostic yield was comparable (risk ratio [RR] 0.99, 95% confidence interval [CI] 0.93-1.06; I²=24%; Hartung-Knapp 0.87-1.13), with an identical relative effect under strict and intermediate definitions although absolute yields fell from 88% to 74-84% under strict criteria. Pneumothorax requiring a chest tube and/or admission was about three-quarters less frequent with RAB across all three cohorts (RR 0.25, 95% CI 0.14-0.46; I²=0%; Hartung-Knapp 0.07-0.96). Strict yield (RR 0.99) and any pneumothorax (RR 0.06) were reported by two cohorts each and neither survives the few-studies correction. RAB took about 50 min longer than CTTB where same-session staging endobronchial ultrasound was counted in the robotic time, but only about 8 min longer than CTTB where it was not. Only one cohort reported yield by lesion size category and none reported yield by bronchus sign or lung zone, so lesion-level subgroups could not be pooled. Certainty was low for pleural complications and very low elsewhere. Low-certainty evidence indicates that RAB is associated with fewer pleural complications, with no statistically detectable difference in diagnostic yield; equivalence was not formally established. Because all evidence is retrospective, confined to one health system, and almost never stratified by lesion size or accessibility, these findings are hypothesis-generating and require a multicenter randomized trial.

Humans↗