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PubMed2026

Umbilical Cord-Derived Cell-Based Interventions for Bronchopulmonary Dysplasia and Related Complications in Preterm Infants: A Bayesian Sparse-Data Meta-Analysis.

Bronchopulmonary dysplasia (BPD) is a major complication of prematurity with limited disease-modifying therapies. We evaluated umbilical cord-derived cell-based interventions for BPD and related complications in preterm infants. This Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020-based systematic review and meta-analysis were registered in PROSPERO. PubMed, Cochrane Library, Web of Science, CNKI, and Wanfang were searched from inception to June 14, 2026. Comparative clinical studies of umbilical cord-derived cell-based interventions in preterm infants at risk of or diagnosed with BPD were included. Outcomes included BPD, BPD severity, death, persistent pulmonary hypertension of the newborn (PPHN), patent ductus arteriosus (PDA), intraventricular hemorrhage (IVH), necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), late-onset sepsis (LOS), and adverse events (AEs). Bayesian random-effects meta-analysis used a binomial-normal hierarchical model to estimate pooled odds ratios (ORs), 95% credible intervals (CrIs), prediction intervals, and heterogeneity. Twelve studies were included. Umbilical cord-derived cell-based interventions showed a possible protective effect on overall BPD (OR, 0.48; 95% CrI, 0.14-1.20). Stronger associations were observed for severe BPD (OR, 0.17; 95% CrI, 0.01-0.85), moderate or severe BPD (OR, 0.28; 95% CrI, 0.09-0.70), and ROP stage ≥3 (OR, 0.17; 95% CrI, 0.02-0.65). No conclusive benefit or harm was observed for death, PPHN, PDA, IVH, NEC, or LOS. No treatment-related serious AEs were identified. However, prediction intervals were generally wide, and the certainty of evidence was low to very low for most outcomes. Umbilical cord-derived cell-based interventions may reduce the risk of moderate or severe BPD in preterm infants, with an additional potential benefit for ROP stage ≥3. Current evidence remains limited, and larger randomized trials with standardized outcomes and long-term follow-up are needed.

Humans↗

PubMed2026

Copper-Containing Surface Engineering for Soft-Tissue Biomedical Devices: Structure-Function Relationships and Ion Release-Driven Biological Performance, A Systematic Review.

Copper and copper-based materials have gained increasing attention for the functional modification of implantable medical devices intended for prolonged soft-tissue contact, including vascular stents, catheters, and intrauterine devices. Owing to their broad-spectrum antimicrobial activity, redox reactivity, and involvement in angiogenesis and cellular signaling, copper-based systems offer significant potential for multifunctional surface engineering. However, achieving a balance between antibacterial efficacy, corrosion behavior, controlled ion release, and cytocompatibility remains a critical challenge. This PRISMA-compliant systematic review analyzes copper-containing materials and surface modification strategies for soft-tissue biomedical applications. A structured search of Scopus, Web of Science, and PubMed (2015-2025) identified 65 eligible studies. The review encompasses bulk copper-containing alloys, electrochemical and chemical surface modification techniques, physical vapor deposition approaches, and advanced hybrid systems integrating copper with polymers, hydrogels, or metal-phenolic networks. Across the reviewed literature, antibacterial performance was strongly dependent on copper concentration, microstructural distribution, and spatiotemporal ion release profiles. Moderate, well-controlled copper incorporation frequently improved antibacterial efficacy while maintaining acceptable hemocompatibility and cytocompatibility, particularly in vascular and blood-contacting devices. In contrast, excessive copper loading often accelerated corrosion and induced adverse cellular responses. Emerging multifunctional architectures demonstrated improved regulation of biological interactions, enabling simultaneous antibacterial, antithrombotic, and proendothelial effects. Overall, copper-based surface technologies represent a versatile platform for soft-tissue implant modification. Future translational progress will require precise control of copper release kinetics and comprehensive long-term in vivo validation to ensure safety and sustained therapeutic performance. From the authors' perspective, the most promising future direction involves multifunctional copper-based hybrid coatings capable of dynamically regulating ion release, host tissue integration, and antibacterial performance simultaneously. Strategies integrating hierarchical architectures, stimulus-responsive release systems, and clinically scalable fabrication methods are expected to play a key role in translating copper-containing surfaces from experimental concepts toward commercially viable soft-tissue biomedical devices.

Copper↗

PubMed2026

Micro- and nanoplastics-induced neurotoxicity: a CNS-centered, evidence-graded adverse outcome pathway framework based on systematic weight-of-evidence assessment.

Micro- and nanoplastics (MPs/NPs) are ubiquitous anthropogenic particulate pollutants posing emerging threats to human neurological health. Severe heterogeneity in particle physicochemical properties, environmental aging status, exposure paradigms and experimental platforms has created persistent mechanistic uncertainties in MP/NP neurotoxicology, hindering reliable hazard characterization and risk translation. Here, we systematically consolidate empirical toxicological evidence and construct a dedicated central nervous system (CNS)-targeted adverse outcome pathway (AOP) network integrated with rigorous weight-of-evidence (WoE) grading to elucidate the hierarchical, particle-specific toxic cascades underlying MP/NP-induced neural injury. Our synthesis overturns the conventional linear toxicity paradigm, demonstrating that MPs/NPs trigger neurotoxicity via a complex multi-input mechanistic network. We definitively establish oxidative stress as a robust early convergent key event-rather than a universal molecular initiating event-orchestrating ROS overproduction, lipid peroxidation, mitochondrial dysfunction, and neuroinflammation to propagate neuronal damage. This core module is driven by five distinct particulate upstream triggers: particle-biomolecule interfacial perturbation, corona-facilitated cellular internalization, plastic-associated chemical leaching, aging-derived free radical reactivity, and gut-borne systemic neurotoxic signaling. Downstream pathogenic outcomes encompass glial overactivation, neurotransmitter dyshomeostasis, autophagy-lysosome dysfunction, metabolic reprogramming, regulated neuronal cell death, and behavioral impairments. Tiered WoE analysis confirms strong validation for early oxidative/inflammatory cascades, moderate support for gut-brain axis crosstalk and intracellular trafficking disruption, and nascent evidence for synaptic dysfunction and neurodegeneration-linked proteostatic defects. Extrapolation to human health risk remains constrained by the frequent use of high-dose exposure paradigms, limited validated data on internal dosimetry in the human brain, discrepancies between effective concentrations in experimental models and environmentally relevant human tissue burdens, and insufficient causal validation of distal adverse outcomes. We highlight key research priorities including aged mixed-particle exposure systems, leachate-controlled assays, quantitative internal dose evaluation, and mechanistic intervention verification. This evidence-stratified AOP framework resolves longstanding mechanistic ambiguities in particulate neurotoxicity, providing a standardized, causality-based foundation for future mechanistic exploration and health risk assessment of global plastic pollution.

Adverse outcome pathway↗

PubMed2026

Evaluating a culturally adapted question prompt list to improve end-of-life communication among indonesian migrant caregivers: A randomized controlled trial with qualitative insights.

OBJECTIVE: Indonesian caregivers serve as essential providers of end-of-life (EOL) care in Taiwan. But often face communication challenges due to language, cultural, and hierarchical barriers. This study evaluated the effectiveness of a culturally adapted Question Prompt List (QPL). METHODS: This study employed a two-arm randomized controlled trial design supplemented with qualitative interviews. The study was conducted in a hospice ward and home care setting within a medical center in Taiwan. A total of sixty Indonesian caregivers were recruited and randomly assigned to either the intervention group (n = 30) or the control group (n = 30). The intervention group received routine end-of-life (EOL) education along with a culturally adapted Question Prompt List (QPL), which consisted of 37 items covering domains including the dying process, emotional support, communication, symptom management, and care decision-making. The control group received routine EOL education. Outcome measures included caregiving preparedness, communication self-efficacy, satisfaction, and question-asking behavior. In addition, semi-structured interviews were conducted with eight participants, and the data were analyzed using thematic content analysis. RESULTS: Analysis of covariance revealed no statistically significant between-group differences in caregiving preparedness (F = 1.58, p = .215 [-0.41, 0.44]) or communication selfefficacy (F = 0.83, p = .366 [-0.44, 0.79]). However, communication satisfaction was significantly higher in the intervention group (F = 4.19, p < .05 [0.04, 0.44]). The number of questions asked was also significantly higher in the intervention group (t = -4.35, p < .001 [-5.41, -1.98]). Thematic analysis of qualitative data identified 4 themes and 14 subthemes, illustrating how the QPL reduced anxiety, clarified care needs, and improved confidence. CONCLUSIONS: A culturally adapted QPL can enhance communication engagement and satisfaction among migrant caregivers. PRACTICE IMPLICATIONS: Integrating culturally tailored QPLs into caregiver education and palliative care practice may promote more inclusive and effective communication.

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

A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy.

To address the widespread adulteration of sweet potato starch and its vermicelli with cheaper starches and overcome conventional supervised learning's dependency on large labeled datasets, this study developed a few-shot discrimination method integrating Raman spectroscopy with meta-learning. We constructed a meta-learning framework using cassava- and wheat-adulterated sweet potato starch as the source domain for training, with potato-adulterated sweet potato starch and cassava-adulterated sweet potato vermicelli as two target domains for testing. Raman spectra showed high consistency between sweet potato vermicelli and its raw starch, laying the foundation for cross-domain detection. Testing yielded comprehensive classification accuracies of 95.33% and 98.00% for the two target domains, significantly outperforming SVM, RF, and CNN (max. 85.24%). This approach effectively identifies subtle starch variety differences in complex adulteration, providing novel food quality inspection solutions and verifying the feasibility of raw material-to-finished product cross-domain detection.

Ipomoea batatas↗

PubMed2026

Machine learning-assisted Mn-N-C nanozyme colorimetric sensor array for trace-level detection of biogenic amines in meat.

Accurate detection of biogenic amines (BAs) in meat remains challenging due to their high structural similarity and co-occurrence. Herein, an Mn-N-C nanozyme was synthesized via a metal-organic framework confined pyrolysis strategy, possessing excellent oxidase (OXD)- and peroxidase (POD)-like activities. The dual enzyme-like activity showed Km values of 0.1584 mM (OXD) and 0.1498 mM (POD), respectively, in detection system. Leveraging these properties, a colorimetric sensor array was constructed, enabling the detection of four representative BAs within a concentration range of 2-10 ppm with 100% classification accuracy. In addition, a concentration independent recognition model based on an artificial neural network was developed to address signal nonlinearity interference in meat. The integrated system achieved accurate trace-level identification of BAs in perishable fish, pork, and chicken, demonstrating its applicability for early-stage BAs monitoring and quality deterioration warning during storage and transportation.

Biogenic Amines↗

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

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

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans↗

PubMed2026

Obinutuzumab or Tacrolimus in Primary Membranous Nephropathy.

BACKGROUND: Studies of obinutuzumab, a type II anti-CD20 antibody, have shown efficacy in the treatment of hematologic cancers and autoimmune diseases. An evaluation of the efficacy and safety of obinutuzumab in patients with primary membranous nephropathy is needed. METHODS: In a phase 3 trial, we randomly assigned adults with primary membranous nephropathy in a 1:1 ratio to receive intravenous obinutuzumab or oral tacrolimus. The primary end point was complete remission (defined as a urinary protein-to-creatinine ratio of 0.3 or lower and a stable estimated glomerular filtration rate [eGFR]) at week 104. Key secondary end points were complete or partial remission at week 104, complete remission at week 76, a sustained reduction in the eGFR of at least 30%, duration of complete remission, and change in the Patient-Reported Outcomes Measurement Information System Fatigue T score from baseline to week 104. Fixed-sequence hierarchical testing was performed. Safety was assessed. RESULTS: A total of 142 patients underwent randomization. At week 104, complete remission was observed in 26 of 71 patients in the obinutuzumab group and in 4 of 70 patients in the tacrolimus group (37% vs. 6% with multiple imputation for missing data; adjusted difference, 31 percentage points; 95% CI, 18 to 44; P<0.001). The analyses of complete or partial remission at week 104 and complete remission at week 76 also showed a significant treatment effect. The analysis of a sustained eGFR reduction did not show a significant treatment effect; thus, subsequent end points in the hierarchy were not formally tested for significance. Adverse events of grade 3 or higher were reported in 16 patients (22%) in the obinutuzumab group and in 13 patients (19%) in the tacrolimus group; serious adverse events occurred in 12 (17%) and 10 (14%), respectively. There were 61 and 57 infections per 100 patient-years in the obinutuzumab and tacrolimus groups, respectively; 3 and 4 serious infections per 100 patient-years; and 11 and 14 serious adverse events per 100 patient-years. Adverse drug reactions with obinutuzumab included infusion-related reactions, respiratory tract infections, and neutropenia. One patient in each group died during escape therapy. CONCLUSIONS: Obinutuzumab was superior to tacrolimus in inducing complete remission in patients with primary membranous nephropathy. (Funded by F. Hoffmann-La Roche; MAJESTY ClinicalTrials.gov number, NCT04629248.).

Adult↗

PubMed2026

Endoscopic Ultrasound-Guided Franseen Fine-Needle Biopsy for Solid Pancreatic Lesions: A Systematic Review and Meta-Analysis.

INTRODUCTION: Accurate tissue acquisition (TA) of solid pancreatic lesions is essential for guiding treatment with endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) being the preferred method. Among FNB designs, the three-pronged Franseen-tip needle demonstrates strong diagnostic performance, though direct head-to-head comparisons with other FNB designs remain limited. METHODOLOGY: This meta-analysis was conducted in accordance with PRISMA guidelines (PROSPERO: CRD420251123856). Eligible studies enrolled patients with solid pancreatic lesions who underwent EUS-guided FNB, directly compared the Franseen-tip with other FNB needles. Six databases were systematically searched through July 2025, and study selection, data extraction, and risk of bias assessment (QUADAS-2 tool) were performed independently by two reviewers. Pooled estimates were generated using random-effects and bivariate hierarchical models. RESULTS: Sixteen studies (2,010 Franseen vs. 2,811 comparator) were included. Bivariate analysis showed that sensitivity and specificity of the Franseen needle were comparable to newer-generation comparator needles (sensitivity 91.3% vs. 94.0%; specificity 99.99% vs. 99.15%), whereas older-generation needles demonstrated lower sensitivity (80.8%) and inferior discriminatory performance (Negative Likelihood Ratio [LR⁻] 0.19 vs. 0.09). Diagnostic accuracy was higher with the Franseen needle (RR 1.07, 95% CI 1.01-1.14; I2 = 69%). Sample adequacy was similar overall (RR 1.04, 95% CI 0.95-1.14) but superior to older-generation needles (RR 1.19, 95% CI 1.02-1.41) and in lesions > 30 mm (RR 1.14, 95% CI 1.02-1.28, I2 = 81.2%). The Franseen needle achieved nominally strong diagnostic performance (DOR 116.6), although small-study effects were observed. Primary procedural outcomes were comparable between Franseen and comparator needles, including technical success (RR 1.00, 95% CI 0.98-1.02) and histological core procurement (RR 1.04, 95% CI 0.92-1.17). The Franseen needle had fewer low-cellularity samples (RR 0.56, 95% CI 0.45-0.69) and lower specimen bloodiness (RR 0.48, 95% CI 0.25-0.90) but a slightly higher overall adverse event rate (RR 1.29, 95% CI 1.06-1.57). CONCLUSION: The Franseen needle provides superior diagnostic accuracy and sample adequacy compared to older-generation FNB needles with comparable performance to newer-generation designs. It reduces low-cellularity samples and specimen bloodiness, although adverse events are slightly increased, with other primary procedural outcomes remaining comparable. TRIAL REGISTRATION: PROSPERO (Registration No. CRD420251123856).

Humans↗

PubMed2026

External load metrics and monitoring in women's football match play: A systematic review.

This systematic review aimed to identify the most commonly used variables for monitoring external load during elite women's football matches and to compare reporting practices internationally and in Brazil. Searches were conducted in Web of Science, PubMed, and SciELO using the PICOS framework between February and March 2026, resulting in the inclusion of 35 studies. The main outcomes analysed were total distance covered (TD), distance covered across speed zones (HSR, VHSR, sprint), number of accelerations and decelerations, and maximum speed. TD and distance covered across speed zones were the most frequently reported indicators (94.3%), followed by HSR (82.8%) and sprint distance (68.5%). Considerable variability was observed in the classification of speed zones and thresholds used to define accelerations and decelerations, limiting comparisons between studies. External load values varied according to playing position and competition level, with international matches generally imposing greater demands than national competitions. Brazilian research remains limited and demonstrates notable methodological variability. This review proposes standardised speed and acceleration/deceleration thresholds based on the most recurrent ranges reported in the literature, supporting improved consistency in monitoring practices across elite women's football contexts.

Humans↗

PubMed2026

Genetic diversity and recombination of NA-PRRSV field strains in Vietnam: Implications for vaccine efficacy.

Porcine reproductive and respiratory syndrome (PRRS) causes severe reproductive losses in pregnant sows and piglets, resulting in substantial economic impact on the swine industry worldwide. However, due to the significant genetic diversity and rapid evolutionary changes of the pathogen, continuous surveillance and detailed genetic analysis of circulating strains are essential. The current study aimed to evaluate the genetic diversity of the hypervariable (HV) region of non-structural protein 2 (nsp2) among North American PRRSV strains isolated from swine farms in Vietnam. Phylogenetic analysis and multiple sequence alignment were conducted to determine subtype classification and assess genetic variability. A total of 48 field isolates were obtained, of which 12.5% belonged to classical NA-PRRSV, 16.6% to NADC30-like and 70.9% to HP-PRRSV, primarily distributed across sublineages 1.4, 5.1, 8.7 and 8.9. Amino acid comparisons found multiple insertions, deletions and substitutions at various positions within the hypervariable region of nsp2. The study revealed substantial genetic variation in the HV region of nsp2 among NA-PRRSV field strains, largely associated with recombination and immune escape. These findings highlight epidemiological risks to vaccine efficacy and underscore the need for continuous molecular surveillance to support effective PRRSV control in Vietnam.

PRRSV↗

PubMed2026

Genomic and Phenotypic Characterization of Two Novel Enterobacter Phages With EDTA-Enhanced Antibiofilm Activity.

Multidrug-resistant members of the Enterobacter cloacae complex (ECC) are increasingly linked to difficult-to-treat infections and biofilm-mediated antimicrobial tolerance. Here, two lytic phages, vB_EhoIP_HHH and vB_EluM_RZH, displaying podovirus-like and myovirus-like morphology, respectively, were isolated from the River Chelt. HHH has a 39,582 bp genome (51.2% GC, 63 ORFs), while RZH has a 174,197 bp genome (39.4% GC, 314 ORFs), with neither genome carrying antimicrobial resistance, virulence or lysogeny-associated genes. VIRIDIC and VICTOR analyses placed HHH within Kayfunavirus and RZH within Karamvirus, supporting their classification as distinct species. Both phages demonstrated rapid adsorption, short latent periods and stability across physiological pH and temperature ranges. A phage cocktail targeting MDR ECC strain was evaluated with EDTA against established biofilms. Crystal violet assays showed the greatest biomass reduction at MOI 10 with 0.5-0.75 mM EDTA. Bliss independence analysis revealed localized synergy within this window but significant overall antagonism at higher EDTA concentrations. CFU enumeration confirmed greater activity against 24 h than 48 h biofilms. The optimized combination also reduced recoverable bacteria in a fibroblast infection model while maintaining low LDH release. These findings identify two novel lytic Enterobacter phages and support a narrow EDTA concentration window for enhanced phage-mediated antibiofilm activity.

Biofilms↗

PubMed2025

Online Risk Behavior in Adolescents: A Systematic Review.

Identifying and categorizing online risk behaviors is crucial for assessing their impact on adolescents. Despite extensive research, previous studies have not provided a clear classification of these behaviors. This systematic review synthesizes the quantitative literature on adolescent online risk behaviors from the inception of research to September 2023, aiming to: (a) offer a comprehensive overview of the types of online risk behaviors and the specific actions encompassed within each category among adolescents; (b) summarize the adverse outcomes associated with these behaviors; and (c) discuss the implications and future research directions. Utilizing key terms, this study sourced studies from four electronic databases (Scopus, PubMed, Web of Science, and EMBASE), ultimately including 22 English-language quantitative studies. The review reveals that online risk behaviors are primarily categorized into content risk behaviors, contact risk behaviors, and conduct risk behaviors. Adolescents engaging in these behaviors are at an increased risk of experiencing physical health issues, mental health problems, externalizing behaviors, and even self-harm and suicidal thoughts or actions. Further research is needed to develop and validate an online risk behavior scale and conduct longitudinal and experimental studies to establish causal relationships and examine the long-term effects of these behaviors on adolescent well-being. The review concludes with implications for future research and potential prevention, intervention, and policy strategies to mitigate online risk behaviors in adolescents.

Humans↗

PubMed2026

Comparative genomic and proteomic analysis reveals orthogroup structured evolution of tick protease inhibitors.

Protease inhibitors (PIs) play central roles in regulating endogenous proteolysis and host-parasite interactions in ticks. However, the evolutionary architecture underlying their diversification across tick lineages remains insufficiently resolved. Here, we performed a genome-wide comparative analysis of predicted proteomes from 14 tick species to systematically characterize PI repertoires. In total, 4931 putative PIs were identified and grouped into 20 families using the MEROPS classification system. Further, PI families such as Antistasin, WAP-type, and Pacifastin, which have not previously been systematically reported in tick genomes, were classified. Orthogroup inference demonstrated that PI expansion is structured at the level of evolutionary lineages rather than uniformly across families. By stratifying orthogroups according to duplication burden and taxonomic conservation, we identified a broadly conserved single-copy core under strong purifying selection. Motif level analysis of serpin reactive center loops further revealed conservation of inhibitory specificity within single copy orthogroups and diversification of key functional residues in duplication-associated lineages. Integration of secretion prediction and tissue-resolved proteomics from Hyalomma anatolicum and Rhipicephalus microplus demonstrated that evolutionary stratification is reflected at the protein level. Together, these findings provide an orthogroup-resolved evolutionary framework linking duplication dynamics, molecular evolution, and tissue-level protein deployment. This integrative approach offers a systematic basis for prioritizing conserved and diversified PI lineages for future functional and anti-tick intervention studies.

Animals↗

PubMed2026

Complicated urinary tract infections: evolving definitions, clinical burden, and treatment landscape amid antimicrobial resistance.

INTRODUCTION: Complicated urinary tract infection (cUTI) is a common and heterogeneous infection associated with substantial morbidity, high healthcare utilization, and increasing antimicrobial resistance. Evolving definitions, increasing device use, and changing patient populations have altered its epidemiology and management. Marked variability in diagnostic criteria, clinical trial endpoints within and outside registrational settings, and treatment strategies complicates clinical decision-making and interpretation of therapeutic advances. AREAS COVERED: This review examines contemporary cUTI epidemiology, classification frameworks, and drivers of disease burden. It evaluates resistance trends and their therapeutic implications, alongside stewardship-based management strategies, including empiric antibiotic selection, intravenous-to-oral transition, treatment duration, and source control. Challenges in catheter-associated infection, recurrence, and regulatory endpoint design are discussed, together with the emerging role of novel agents targeting resistant Gram-negative pathogens. EXPERT OPINION: Rising multidrug resistance and limited oral options are reshaping cUTI management, necessitating individualized, stewardship-aligned therapy guided by illness severity and local epidemiology. Current regulatory endpoints inadequately reflect patient-centered outcomes, particularly in the context of asymptomatic bacteriuria. Expanding availability of effective oral agents may enable earlier discharge and outpatient care. Integration of rapid diagnostics and risk stratification will be essential to optimize therapy, limit resistance, and improve outcomes.

Humans↗