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PubMed2026

Quantitative susceptibility mapping in neurodegenerative diseases: An umbrella review of iron-related biomarkers and mechanisms.

Pathological iron accumulation is a common pathophysiological hallmark across multiple neurodegenerative diseases (NDDs), motivating the need for accurate, non-invasive quantification methods. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique that enables in vivo measurement of tissue magnetic susceptibility (χ), providing a sensitive proxy for iron content. This umbrella review systematically evaluates the diagnostic accuracy, clinical correlations, and distinct iron distribution patterns of QSM in major NDDs, such as Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and atypical Parkinsonism. We included 15 (13/15 were rated Low or Critically Low on AMSTAR 2) systematic reviews and meta-analyses (through July 15, 2026); however, the findings should be interpreted cautiously because of heterogeneity and the low methodological quality. A Corrected Covered Area (CCA) analysis demonstrated only slight overlap of primary studies across the included reviews (CCA = 5.42%). Collectively, the evidence indicates that QSM provides comparable or higher diagnostic sensitivity and reliability than conventional R2* and SWI techniques, particularly for deep gray matter structures. The findings support significant iron overload in the substantia nigra, particularly in the pars compacta, as a robust biomarker for PD that correlates with motor severity and disease duration. Furthermore, regional iron profiling in the basal ganglia is critical for differential diagnosis; specifically, elevated χ in the putamen and globus pallidus effectively distinguishes multiple system atrophy and progressive supranuclear palsy from idiopathic PD. Distinctively, AD and ALS exhibit specific χ alterations in the thalamus, motor cortex, and hippocampus, reflecting divergent iron-related pathophysiological mechanisms, which correlate with cognitive impairment and upper motor neuron signs. Overall, QSM shows diagnostic promise and offers mechanistic insights into iron-related neurodegenerative processes.

Humans↗

PubMed2026

Divergent evolutionary strategies in spider venoms: A comparative proteomic profiling of four sympatric species from Yunnan.

Spider venoms comprise complex cocktails of bioactive molecules evolved for predation and defense, representing a valuable resource for biological research and pharmaceutical discovery. In this study, we performed a systematic analysis of venom gland extracts from four common spider species indigenous to Yunnan, China: Agelena limbata, Hippasa lycosina, Lycosa grahami, and Sinopoda pengi. Using an integrated transcriptomic and proteomic targeted profiling approach, we successfully annotated 141 distinct toxins. Comparative analysis revealed significant interspecific heterogeneity, suggesting distinct evolutionary trajectories and "weapon system economics." Both A. limbata and L. grahami exhibited a "peptide-dominant" profile anchored by neurotoxic peptides and isomerases, optimized for rapid chemical paralysis. In contrast, S. pengi displayed a distinct "protein-dominant" signature enriched with high-molecular-weight enzymes and CAP superfamily proteins, likely functioning to facilitate tissue degradation and toxin diffusion. Occupying an intermediate position, H. lycosina demonstrated a hybrid composition. These findings suggest that although these species share the same geographical range, their venom systems have undergone divergent evolutionary adaptations driven by specific ecological niches and hunting strategies. This study represents the first systematic proteomic characterization of these venom components, providing a valuable reservoir of molecular candidates while highlighting the bioinformatic nuances of analyzing whole-gland homogenates.

Animals↗

PubMed2026

Artificial Intelligence for Diagnosing Meibomian Gland Dysfunction: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies.

PURPOSE: To identify, appraise, and synthesize the performance of artificial intelligence-based meibography reading as compared with human graders in diagnosing meibomian gland dysfunction. METHODS: We followed Cochrane methodology and reporting guidelines for diagnostic test accuracy reviews. To assess potential risk of bias and applicability, we used a modified Quality Assessment of Diagnostic Accuracy Studies-2 checklist. We applied bivariate logistic models to estimate summary sensitivity and specificity when appropriate and used the GRADE framework to rate the certainty of the evidence. RESULTS: We identified 14 eligible studies involving 5511 predominantly middle-aged participants (average age: 27-55 years) who were primarily female (≥54.5%). A total of 18,926 meibography images were obtained through noncontact infrared (11 studies) or in vivo confocal microscopy (three studies). Two studies reported external validation of deep learning models, 12 reported internally validated models, and one reported both. All but one study had high risk of bias in at least one domain; 12 studies raised high or intermediate concern about applicability. Based on three external evaluations, the summary sensitivity and specificity for diagnosing meibomian gland dysfunction from normal glands were 97.5% (95% confidence interval: 77.5%-99.8%) and 85.5% (95% confidence interval: 47.3%-97.5%). Sources of heterogeneity in internally validated models included study population, case mix, and others. The overall evidence was very low to low certainty because of imprecision, high risk of bias, and concerns about applicability. CONCLUSIONS: Artificial intelligence-based meibography grading appears less accurate than human graders. Future studies should adopt rigorous designs, including a more diverse participant pool (or image set), and external validation.

Humans↗

PubMed2026

Performance of Automated Hematology Analyzer Criteria in Detecting Peripheral Blood Smear Abnormalities: A Systematic Literature Review.

OBJECTIVES: Criteria for visual examination of stained peripheral blood smear (PBS) differ among institutions in the United States and internationally. In an effort to standardize review criteria, the International Consensus Group for Hematology Review (ICGHR) proposed in 2005 a consensus list of rules for CBC findings that should trigger a review of automated cell counter results and potentially lead to further testing or blood smear review. The primary aim of this paper is to report on the published literature in the past 20 years regarding PBS review criteria and their ability to identify relevant peripheral blood abnormalities. METHODS: We performed a systematic review of the published literature from 2005 to 2025 to investigate and summarize PBS review criteria and performance in the context of automated hematology analyzers in clinical laboratories. RESULTS: Of 5351 citations, 68 studies met our search criteria. These studies included 22 countries and all major hematology analyzer manufacturers. Marked variability was observed in study populations, analyzer flagging criteria, details of PBS visual review, definitions of a "positive" smear, and approaches to statistical data analysis. Across studies, the blast flag sensitivity ranged from 18% to 100% while the blast flag specificity ranged from 17% to 100%. Wide ranges in sensitivity/specificity were also seen for atypical and/or abnormal lymphocyte flags across studies. For studies analyzing the same patient population, less striking variation was seen across instruments. CONCLUSIONS: This systematic review provides a 20-year overview of the literature, highlighting significant variability in PBS review criteria, dependence on study design and hematology analyzer, and the importance of developing harmonized evidence-based guidelines.

Humans↗

PubMed2026

The future of TCR-Treg therapies is renewables.

Cell therapy has longstanding roots in haematopoietic stem cell transplantation and early immune cell transfers in infectious disease and transplantation, where patient- or donor-derived cells have achieved therapeutic benefit in selected contexts. The modern era has been driven largely by oncology, with engineered modalities such as tumour-infiltrating lymphocytes, CAR-T cells and TCR-engineered T cells delivering transformative responses but requiring complex, costly manufacturing. These platforms are now being adapted for autoimmune diseases to induce durable, antigen-specific immune tolerance, yet broad application is limited by safety concerns, process complexity and access. Non-engineered cell therapies for autoimmunity, including mesenchymal stem cells, polyclonal regulatory T cells and tolerogenic dendritic cells, have shown acceptable safety and proof-of-principle for immune re-education, but clinical responses have been modest and inconsistent, with limited scalability. Engineered approaches such as CAR-T cells can induce reversible B cell depletion in B cell-mediated rheumatic diseases but only addresses antibody-driven pathology and not T cell-mediated autoimmunity. TCR-engineered Tregs have emerged as a promising antigen-specific strategy, offering localized, antigen-linked suppression with bystander tolerance. Preclinical and early clinical data suggest superior potency, stability and disease control compared with polyclonal Tregs at similar or lower doses, but translation is constrained by the rarity and fragility of Tregs and by labour-intensive, CAR-T-like manufacturing. This review highlights emerging solutions for closed, automated and decentralised production, and discusses allogeneic approaches using gene-edited or banked Tregs with HLA engineering or matching. Together, these advances support the development of scalable, "off-the-shelf" TCR-Treg products with potential to provide safe, affordable tolerance-restoring therapies for autoimmune disease.

Humans↗

PubMed2026

Evaluating the persistence of semen under controlled environmental conditions.

When semen is deposited at a crime scene, it may be exposed to harmful environmental conditions. It is important to understand to what extent the different components of semen, specifically acid phosphatase (AP), prostate specific antigens (PSA), sperm and DNA, may become less detectable after exposure to high temperatures and varying levels of humidity. In this study, semen (50 μL) was deposited onto squares of black cotton and exposed to 45 °C and a relative humidity (RH) of 10 or 80% for 0, 7, 14, 21 or 28 days (n = 5 per day, per climate condition). Source testing included AP test reagent, ABAcard® p30 immunoassay kits, and hematoxylin and eosin staining. DNA was extracted using the DNA IQ™ System (Promega, Australia) and quantified using Quantfiler Trio™ (Thermo Fisher Scientific, Australia). Over the 28-day period under both RH conditions, the time taken for a positive AP test to develop increased significantly (p < 0.01) and the number of sperm observed decreased significantly (p < 0.01). All ABAcard® p30 tests were positive regardless of exposure time or conditions. No impact on the quantity of DNA recovered was observed when semen was exposed to 45 °C and 10% RH, with a higher median quantity of DNA recovered at day 28 compared to day 0. In contrast, when the RH was raised to 80%, the median quantity of DNA recovered was substantially less at day 28 (81.5 ng, IQR: 87.5 ng) compared to day 0 (181.5 ng, IQR: 1172.4 ng). This study highlights the impact that temperature and RH may have on the persistence of AP, PSA, sperm and DNA over time.

Humans↗

PubMed2026

Ancient DNA and Human Physiology.

Ancient DNA (aDNA) enables the reconstruction of chronologically sampled genomes from ancient humans, animals, plants, pathogens, and microorganisms, as well as environmental DNA, providing a record of biological changes through time. Improvements in short and degraded DNA extraction methods and low-cost sequencing now enable the generation of broad, cross-regional datasets that expand evolutionary analyses from past population demography to biological mechanisms. By tracking temporal shifts of allele frequencies, integrating functional genomics resources (e.g., gene expression, chromatin structure variation), modeling population demography to separate selection from genetic drift, and aligning genetic changes with archaeological, cultural, and climatic data, aDNA has the potential to link sequence variation to physiological function within their temporal and environmental contexts. In this review, we summarize illustrative case studies from aDNA research spanning complex traits, dietary adaptations, and responses to pathogens and other environmental changes, showing how human biology has evolved under multiple selective pressures through time. These dated signals help triage experimental work and expose mechanisms that are rare or absent in living cohorts. Although some challenges remain, such as geographic and temporal sampling disparities, limitations in data resolution and variant detection, and genotype-phenotype uncertainties, rapid methodological progress and stronger ethical frameworks are expanding what can be inferred, making aDNA a promising tool for refining physiological pathways, their timing, and their drivers.

Humans↗

PubMed2026

Review: The African turquoise killifish as a model for the integrative physiology of vertebrate aging.

With increasing emphasis on extending healthy lifespan, aging research requires vertebrate models that permit efficient mechanistic investigation and intervention testing within practical time and cost constraints. The African turquoise killifish (Nothobranchius furzeri) has attracted growing attention because it combines an exceptionally short life cycle with an intact vertebrate physiological context and an expanding genetic toolkit, enabling relatively rapid evaluation of candidate aging interventions and mechanistic analysis across molecular, tissue, and organismal levels. This review assesses N. furzeri from an integrative-physiology perspective, focusing on germline-soma interactions, gut microbiota-host crosstalk, nutrient sensing and metabolic remodeling, temperature responsiveness, and AMPK-mTOR-linked programs. It also examines expanding genome-engineering and reporter approaches that support mechanistic and tissue-resolved investigation of these physiological processes. Building on recent reviews of killifish biology, disease modeling, regeneration, and the hallmarks of aging, we synthesize evidence across major intervention domains, distinguish established phenotypic effects from incompletely resolved mechanisms, and highlight functional endpoints, methodological standardization, and the appropriate interpretation of the model's translational relevance. Together, these features position N. furzeri as a strategically useful vertebrate platform for rapid mechanistic testing, intervention evaluation, and prioritization of aging-related pathways. Future progress will require improved methodological standardization, tissue-resolved causal studies, and question-driven cross-species validation where appropriate.

Animals↗

PubMed2026

Targeted Nanoparticle Delivery CRISPR/Cas9: overcoming biological barriers, enhancing stability, and improving therapeutic precision.

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has emerged as a promising gene-editing platform for genetic disorders; however, its in vivo application remains limited by low delivery efficiency and biological barriers. Many CRISPR payloads fail to reach target sites due to extracellular degradation, immune clearance, and intracellular trafficking limitations. This review examines the interplay between biological barriers and nanoparticle engineering strategies for CRISPR/Cas9 delivery. A barrier-oriented engineering approach is proposed as a central framework, encompassing ligand-based surface modification for enhanced targeting and uptake, improved circulation stability via PEGylation and biomimetic coatings, and optimized payload release through endosomal escape strategies. Stimulus-responsive nanoparticle systems further enable spatiotemporal control over payload release. Nuclear targeting strategies, including optimization of nuclear localization signals (NLS) and exploitation of endogenous trafficking pathways, are highlighted as key factors for improving genome-level editing efficiency. Despite these advances, major challenges-including limited intracellular delivery efficiency, insufficient targeting precision, and safety concerns-continue to hinder clinical translation. Future directions highlight artificial intelligence-driven nanoparticle design, personalized delivery systems, and next-generation CRISPR platforms. Overall, an integrated, barrier-oriented engineering strategy is essential for advancing CRISPR/Cas9 delivery toward clinical applications, ultimately advancing global good health and well-being.

CRISPR/Cas9↗

PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries↗

PubMed2026

Enhancing Hemoglobin Bart's hydrops fetalis syndrome prevention: a single-tube multiplex real-time PCR assay for the comprehensive detection of four significant α0-thalassemia deletions (--SEA, --THAI, --CR, and --SA) found in Thailand.

BACKGROUND: Hemoglobin (Hb) Bart's hydrops fetalis is a major public health concern in Southeast Asia, particularly in Thailand. Current screening strategies target the two most common α0 -thalassemia deletions (--SEA and --THAI). METHOD: In this study, we developed a single-tube multiplex real-time PCR assay for the simultaneous detection of four clinically relevant α0-thalassemia deletions (--SEA, --THAI, --CR, and --SA). The assay was validated using 538 clinical samples with diverse thalassemia genotypes and compared against conventional gap-PCR as the reference method. Analytical performance, including sensitivity, specificity, and limit of detection (LOD), was evaluated. In addition, clinical utility was assessed in 22 prenatal diagnosis cases at risk of Hb Bart's hydrops fetalis. RESULTS: The study cohort demonstrated substantial genetic heterogeneity, comprising 43 distinct genotypes. The developed assay achieved 100% sensitivity and specificity for all targeted deletions, with complete concordance with gap-PCR results. No cross-reactivity was observed with α+-thalassemia. The assay demonstrated a high analytical sensitivity with a LOD of 9.76 × 10-3 ng per reaction. Whereas in prenatal diagnosis, all 22 fetal genotypes were accurately identified, including five cases of homozygous --SEA and one rare compound heterozygous --SEA/--CR fetus. CONCLUSIONS: This study presents a rapid, accurate, and cost-effective multiplex real-time PCR assay capable of detecting both common and rare α0-thalassemia deletions in a single reaction. The assay demonstrates strong potential for implementation in routine clinical laboratories and large-scale population screening, contributing to improved prevention and control of severe thalassemia syndromes in high-prevalence regions.

Humans↗

PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2×2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I²=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans↗

PubMed2026

Efficacy of current approaches to non-invasive diagnosis of skin cancer and the potential impact of artificial intelligence: A systematic review and meta-analysis.

BACKGROUND: Skin cancer is one of the most prevalent malignancies worldwide, particularly within Caucasian populations. This systematic review and meta-analysis aimed to quantitatively review the current literature on non-invasive diagnosis of skin cancer and evaluate the current evidence to support the use of tools in addition to, or in replacement of clinician face-to-face assessment. METHODS: A literature search was conducted for publications in PubMed, Medline and Embase databases. Articles describing accuracy, sensitivity, specificity and outcomes of their mode of assessment were included. A total of 208 articles met the inclusion criteria. RESULTS AND CONCLUSION: This systematic review and meta-analysis showed that the diagnostic performance of artificial intelligence (AI) in the interpretation of dermatoscopic images was high for melanoma diagnosis, basal cell carcinoma or malignancy, in comparison to dermatoscopic assessment alone by clinicians and experts. Although AI interpretation of images demonstrated higher sensitivity for melanoma diagnosis in comparison to clinical assessment combined with dermatoscopic assessment, it is unclear if this is also the case for basal cell carcinoma and squamous cell carcinoma diagnosis. Reflectance confocal microscopy, a non-invasive high resolution imaging technique, is known to have a high sensitivity for diagnosing cutaneous malignancy, and this may have applications within secondary care. Therefore, AI could help reduce resource burden and aid in clinical assessment, particularly within primary care settings.

Humans↗

PubMed2026

ER proteostasis failure in HYOU1 deficiency alters B cells, neutrophils, and interferon signalling.

Hypoxia upregulated 1 (HYOU1) is a stress-inducible ER chaperone. We investigated 2 unrelated patients carrying biallelic HYOU1 variants and presenting with primary immunodeficiency. Patient 1, homozygous for p.Pro444His, displayed failure to thrive, hypoglycemia, B cell lymphopenia, and neutropenia. Patient 2, compound heterozygous for p.Arg262Gln and p.Pro757_Glu758insAla, exhibited recurrent infections, enteropathy, and hypogammaglobulinemia. In Patient 1, while HYOU1 transcription was preserved, the protein was severely reduced. Tunicamycin treatment of dermal fibroblasts showed a blunted unfolded protein response and defective induction of ER stress-responsive genes. Immunophenotyping showed near-absence of circulating B cells, and single-cell RNA sequencing of bone marrow identified an arrest at the pro-B cell stage. Neutrophils displayed hypogranulation and dysregulated IFN- and apoptosis-associated transcriptional signatures, unresponsive to G-CSF. HYOU1 deficiency hence results in ER stress-induced proteostasis failure that simultaneously impairs adaptive immunity through B cell developmental arrest and innate immunity through neutrophil dysfunction and IFN pathway imbalance. This work expands the spectrum of HYOU1 deficiency and further identifies ER proteostasis as a central determinant of immune homeostasis.

Journal Article↗

PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗

PubMed2026

A conserved distal-tail helical extension defines a tailspike attachment architecture in Gram-negative siphophages.

Rapid growth of bacteriophage genome collections has outpaced functional annotation of tail-tip proteins, limiting comparative analysis of host-recognition structures. Starting from a shared distal-tail gene organization in the Salmonella phages 9NA and Jersey, I developed a morphogenetic bioinformatic framework integrating gene synteny, sequence comparison, profile hidden Markov model (HMM) screening, structural evidence, structure-aware searching, and AlphaFold modeling. Comparison with the experimentally characterized lambda and Sf11 tail assemblies identified a predominantly alpha-helical C-terminal extension of the distal-tail (DT) protein associated with tailspike attachment, termed the distal-tail helical extension (DT-helix). Screening 541,986 proteins from 5167 complete NCBI RefSeq tailed-phage genomes, followed by evidence-based evaluation of sequence, genomic context, and structural architecture, identified 165 curated DT-helical-extension-associated phages. Their DT proteins segregated into six sequence groups. In the four principal multi-member groups, cognate tailspikes showed group-specific conservation in proximal N-terminal regions but substantially greater downstream diversity, consistent with sequence constraint at the DT-tailspike attachment boundary. A complementary ProstT5/Foldseek search supported the established groups but revealed no convincing additional highly divergent family. Together with the experimentally characterized Sf11 attachment interface, these findings define a recurrent morphogenetic architecture linking conserved distal-tail scaffolds to more variable receptor-binding proteins across siphophages infecting Gram-negative bacteria. Although universal exchangeability is not established, the identified scaffold-receptor-binding boundaries provide a framework for molecular characterization and rational phage engineering. Accession-level information for the 165 curated phages is available through PhageTailDB.

Viral Tail Proteins↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

Comparative analysis of histological and transcriptomic characteristics in caudal muscles of nile crocodiles (Crocodylus niloticus), siamese crocodiles (Crocodylus siamensis), and their hybrids.

Crocodylus niloticus and Crocodylus siamensis are high-value aquaculture species. C. niloticus is large-bodied but less abundant, while C. siamensis grows fast but is small-sized. Their hybrids combine parental advantages, yet relevant research is scarce. This study compared the histological and transcriptomic characteristics of the caudal muscle across the three taxa. HE staining indicated that C. niloticus had significantly larger myofiber diameters (p < 0.05); C. siamensis had the smallest, and the myofiber density of hybrids was much closer to that of C. siamensis. Masson's trichrome staining indicated that C. niloticus had the thickest collagen fibers (p < 0.05), C. siamensis the thinnest, and hybrids exhibited highly similar histological traits to C. siamensis. C. niloticus had higher LDH and SDH activities in caudal muscles, whereas the hybrid crocodile indicated the highest CK activity. Transcriptomic analysis identified numerous differentially expressed genes (DEGs), which were enriched in growth, muscle metabolism, and energy allocation pathways via GO/KEGG annotations. PPI analysis screened 24 hub genes related to energy metabolism. This study systematically reveals caudal muscle differences, providing insights into growth-related molecular mechanisms and theoretical support for crocodile artificial breeding.

Animals↗