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[Optical genome mapping analysis of a Chinese pedigree with a complex balanced translocation involving four chromosomes].

OBJECTIVE: To explore the genetic characteristics of a complex balanced translocation involving four non-homologous chromosomes in a Chinese pedigree using optical genomic mapping (OGM). METHODS: A woman with primary infertility and her family members who presented at the Prenatal Diagnosis Center of the Sixth Affiliated Hospital of Sun Yat-sen University in October 2021 were selected as study subjects. Comprehensive analysis and verification of chromosomal abnormalities were conducted through conventional G-band karyotyping analysis, single nucleotide polymorphism microarray (SNP array) and OGM. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: E2022210). RESULTS: G-band karyotyping analysis indicated that the proband, her father, and younger brother have all carried a complex translocation involving four chromosomes. SNP array analysis revealed a duplication of approximately 21.63 Mb in the 9p24.1-p21.1 region in the proband's younger brother, while no abnormality was detected in other family members. OGM confirmed that the complex balanced translocation has involved chromosomes 5, 8, 9, and 10. CONCLUSION: The proband has harbored a complex balanced translocation. OGM has demonstrated certain advantages in characterization of complex chromosomal structural abnormalities.

Humans

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

Whole cell inactivated poly-bacterial preparation MV130 effect on nasal mucosal immunity and experimental human pneumococcal carriage: double-blind randomised controlled trial with controlled human infection model.

BACKGROUND: Bacterial mucosal immunotherapy has shown protection of children and adults from both viral and bacterial respiratory infections, offering the potential to reduce antimicrobial use, and hence also control antimicrobial resistance (AMR). Pneumococcal carriage of vaccine type Streptococcus pneumoniae remains high in Malawi despite infant conjugate vaccination and AMR is increasing. We compared nasal inflammation following sublingual bacterial immunotherapy including S. pneumoniae (MV130, Inmunotek, Spain) or placebo and determined the effect in an experimental human pneumococcal carriage model. METHODS: A double-blind, randomised, placebo-controlled trial in healthy adult volunteers was conducted at Queen Elizabeth Central Hospital in Blantyre, Malawi. Participants were randomly allocated to receive MV130 or placebo sublingually once daily for 42 days. Mucosal inflammation (neutrophil to T cell ratio, NTR) was measured in nasal micro-biopsies. Post-treatment, participants were challenged with 160,000 CFU/naris S. pneumoniae 6B (Spn6b). Experimental pneumococcal carriage rates post inoculation were compared between the two arms. All participants completing the study were included in the analysis. Prospective trial registration: PACTR202403820001276. FINDINGS: 107 participants were enrolled and randomised to MV130/placebo between May and December 2024. There were no serious adverse events, complete compliance was good (72%) and all adverse events were mild. 96 participants (53 male, 43 female) completed the study with 52 participants randomised to MV130 and 44 to placebo. There was no difference in mucosal inflammation (neutrophil to T cell ratio) at day 14 of the intervention MV130 NTR median = 0.737 (IQR 0.294, 2.059) and placebo NTR = 0.831 (IQR 0.450, 2.073), p = 0.64. Secondary analyses showed a rise in mucosal neutrophils after MV130 treatment and after experimental pneumococcal inoculation. There was no difference in nasal or serum anti-pneumococcal immunoglobulin or in experimental pneumococcal carriage proportion between MV130 (12/52, 23%) and placebo (10/44, 23%) groups (unadjusted risk ratio 1.02 (CI 0.49-2.12) p = 1.0). INTERPRETATION: MV130 induced non-specific mild neutrophil inflammation of the nasal mucosa but had no protective effect against experimental human pneumococcal carriage. FUNDING: Wellcome Trust.

Humans

Pre-clinical evaluation of the anticaries effect of an experimental Malva sylvestris extract mouthwash using a cariogenic model in situ.

OBJECTIVE: The aim of this study was to evaluate the antimicrobial and anticariogenic potential of Malva sylvestris extract on enamel and dentin in situ. METHODS: A double-blind crossover in situ study was conducted with 12 participants wearing palatal appliances containing two bovine enamel and two dentin specimens per 3 phases, a total of 72 enamel and dentin specimens. Biofilm formation and daily sucrose exposure were allowed. Treatments were applied twice daily in three phases: Malva sylvestris (2.5%, MS); fluoride (225 ppm, F); and placebo (P). After seven days, biofilm was collected from the bovine specimens for analysis of Lactobacillus spp. and mutans streptococci by Colony Forming Unit counts (CFU log₁₀/mL). Dental demineralization of the bovine specimens was assessed by transverse microradiography (TMR). RESULTS: MS did not reduce Lactobacillus spp. counts (CFU log₁₀/mL: enamel 6.63±0.81; dentin 6.68±0.92) compared to P (6.63±0.70; 6.62±0.51). F also did not differ (6.29±0.75; 6.32±0.41; ANOVA/Tukey, p>0.38). Mutans streptococci data were inconclusive. In enamel, both MS (2320.8±768.2 %vol·µm; 101.6±27.0 µm) and F (1777.3±733.3 %vol·µm; 95.8±23.5 µm) significantly reduced integrated mineral loss and lesion depth compared to P (3517.2±1119.9 %vol·µm; 138.6±19.5 µm; ANOVA/Tukey, p≤0.0003). In dentin, MS significantly reduced integrated mineral loss (322.5 [250-580] %vol·µm) and lesion depth (30.1 [15-42.2] µm) compared to P (880 [580-1705]; 58.3 [32.2-88.6] µm; Kruskal-Wallis/Dunn, p≤0.001), while F (587.5 [305-720]; 25.2 [16.5-38.8] µm) did not differ significantly (p>0.05). CONCLUSIONS: Malva sylvestris extract had no antimicrobial effect on Lactobacillus spp. counts, but significantly reduced enamel and dentin demineralization, showing anticaries effect comparable to fluoride. CLINICAL RELEVANCE: Malva sylvestris has demonstrated promising biological activity. This study investigates the antimicrobial efficacy of Malva sylvestris against cariogenic microorganisms in situ. Our findings provide relevant evidence that M. sylvestris exert significant anticaries effects using an in situ model.

Biofilms

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

Humans

Mendelian randomisation for rheumatology: beyond hype-what it's good for, what it can't do, and how to read it critically.

Mendelian randomisation (MR) has become abundant in the literature, with variation in quality and frequent overinterpretation of causality. This creates a problem for clinical readers, reviewers, and editors: some MR studies can sharpen causal thinking, prioritise drug targets, and challenge misleading observational claims, whereas others are little more than automated exposure-outcome scans with causal claims disproportionate to the evidence. MR can strengthen causal inference when randomised trials are impractical and conventional observational studies are vulnerable to confounding, reverse causation, or selection bias. In rheumatology, credible MR can contribute to questions about disease aetiology, modifiable risk factors, therapeutic target validation, adverse-effect anticipation, and phenotype validation. However, its interpretation depends on whether the exposure is plausibly instrumentable, whether the genetic instruments are biologically defensible, whether assumptions are interrogated in ways appropriate to the design, and whether findings are triangulated with clinical, observational, experimental, and mechanistic evidence. Instead of recapitulating all methodological issues of MR, this review aims to help rheumatologists distinguish robust MR from weak or overinterpreted analyses quickly. We provide an accessible framework for reading and triaging MR studies in rheumatology. Papers that use poorly justified instruments, treat medication use as drug-target evidence, interpret genetic liability as diagnosis, rely on mechanical sensitivity analyses, ignore prior evidence or ask no clinically meaningful question can often be passed over by readers. The goal is not to discourage MR in rheumatology, but to raise the standard; useful MR should clarify causal reasoning rather than simply generate another statistically significant association.

Journal Article

Pangenome-wide identification and expression analysis of the chalcone synthase (CHS) gene family in five yellowhorn spp.

Chalcone synthase (CHS) is a pivotal enzyme in flavonoid biosynthesis involved in plant development, defense, and secondary metabolism. Xanthoceras sorbifolium (yellowhorn) is a medicinal and ornamental species with high resistance to environmental stresses, but its CHS gene family remains uncharacterized. We performed a pangenome-wide identification of CHS genes across five yellowhorn genomes (Xzs4, Xwf8, Xjg, Xg11, and Xzg2). Across the five yellowhorn genomes, 27 CHS genes were identified and classified into four core pangenes, present in all five genomes, and two dispensable genes, present only in a subset of genomes. Phylogenetic analysis grouped these genes into three major clades, and chromosomal mapping and duplication analyses identified four tandemly duplicated gene pairs under purifying selection. The analyses of conserved structural features, including protein motifs and exon-intron organization, together with promoter cis-regulatory elements and gene ontology annotation, further indicated the potential involvement of CHS genes in flavonoid biosynthesis and stress-responsive mechanisms. Gene expression profiling identified significant upregulation of Xg11_CHS1 and Xg11_CHS3 under cold and drought stress, with tissue-specific expression patterns. These findings provide valuable insights into the evolution, functional diversification, and stress-responsive roles of the CHS gene family, identifying candidate genes for future studies targeting stress tolerance and flavonoid biosynthesis in yellowhorn.

Acyltransferases

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine

Ibuprofen versus acetaminophen for acute mild-to-moderate pain management in pediatric populations: a systematic review and meta-analysis of their efficacy.

UNLABELLED: Ibuprofen and acetaminophen are the most widely used analgesics in pediatric practice for the management of acute mild-to-moderate pain. Despite their widespread use, the comparative analgesic efficacy of these two agents in children remains a subject of ongoing debate, with existing evidence largely derived from heterogeneous clinical settings and small individual trials. Therefore, this study aimed to systematically review and meta-analyze randomized controlled trials comparing the analgesic efficacy of ibuprofen versus acetaminophen in pediatric populations with acute mild-to-moderate pain. A systematic literature search was conducted up to May 2026 in PubMed, Scopus, and Web of Science. The review was conducted and reported in accordance with the PRISMA-Children and Adolescents (PRISMA-C) 2026 reporting guideline. Eligible studies were randomized controlled trials comparing ibuprofen with acetaminophen in children and adolescents (defined as individuals aged 0 to&#x2009;<&#x2009;18&#xa0;years) with acute pain, reporting at least one extractable efficacy outcome. Continuous outcomes were synthesized as standardized mean differences (Hedges' g) using random-effects models; dichotomous outcomes were pooled as risk ratios (RRs) with 95% confidence intervals. Risk of bias was assessed using the Cochrane RoB 2 tool and certainty of evidence was evaluated using the GRADE framework. Eight randomized controlled trials enrolling 1325 participants were included. Three pediatric trials contributed to the primary continuous pain outcome meta-analysis (n&#x2009;=&#x2009;196 analyzable participants), yielding a pooled SMD of&#x2009;-&#x2009;0.28 (95% CI&#x2009;-&#x2009;0.57 to 0.00; p&#x2009;=&#x2009;0.052; I2&#x2009;=&#x2009;0%), indicating a small effect favoring ibuprofen that did not reach conventional statistical significance. Given the small number of contributing studies (k&#x2009;=&#x2009;3), the I2 statistic should be interpreted with caution as it has limited power to detect heterogeneity in this context. For the dichotomous pain freedom outcome (2 trials, n&#x2009;=&#x2009;114), no significant difference was observed (pooled RR 1.03, 95% CI 0.53-1.99; p&#x2009;=&#x2009;0.93; I2&#x2009;=&#x2009;0%). A prespecified sensitivity analysis including an adult soft-tissue injury trial attenuated the pooled effect toward the null (SMD&#x2009;-&#x2009;0.15, 95% CI&#x2009;-&#x2009;0.38 to 0.09; p&#x2009;=&#x2009;0.23; I2&#x2009;=&#x2009;36.6%). Narrative synthesis of additional studies generally demonstrated comparable analgesic efficacy between the two agents across postoperative and outpatient pediatric settings. The overall certainty of evidence was rated as low for both primary outcomes, primarily due to imprecision and indirectness. CONCLUSION: Current evidence from randomized controlled trials does not demonstrate a superiority of ibuprofen over acetaminophen for acute mild-to-moderate pain management in children. Both agents appear to provide clinically meaningful analgesia across heterogeneous pediatric pain settings. The clinical choice between agents should be guided by individual patient factors, including contraindications to NSAIDs, the inflammatory nature of the pain etiology, and patient-specific characteristics. The low certainty of evidence underscores the need for adequately powered, methodologically rigorous trials to definitively establish the comparative efficacy of these two analgesics in the pediatric population. WHAT IS KNOWN: &#x2022; Ibuprofen and acetaminophen are the two most widely used non-opioid analgesics for acute mild-to-moderate pain in children, and both are recommended as first-line agents by major international guidelines. &#x2022; Prior meta-analyses in mixed pediatric-adult populations have suggested a modest analgesic advantage of ibuprofen over acetaminophen, but pediatric-specific evidence has remained limited and methodologically heterogeneous. WHAT IS NEW: &#x2022; This systematic review and meta-analysis, restricted to randomized controlled trials in pediatric populations, found that ibuprofen showed a small effect favoring pain reduction compared with acetaminophen (SMD&#x2009;-&#x2009;0.28, p&#x2009;=&#x2009;0.052), although this did not reach conventional statistical significance. &#x2022; The analgesic advantage of ibuprofen may be more pronounced in pain etiologies with a significant inflammatory component (e.g., fractures). At the same time, both agents appear broadly equivalent in most other acute pediatric pain settings, supporting individualized analgesic selection based on clinical context and patient-specific factors.

Humans

Molecular evaluation of residual disease following neoadjuvant chemotherapy in triple-negative breast cancer CALGB 40603 (Alliance).

BACKGROUNDDespite therapeutic advances in early-stage triple-negative breast cancer (TNBC), residual disease (RD) following neoadjuvant therapy remains a key predictor of a worse prognosis and obstacle to improving patient outcomes.METHODSTo better characterize RD and identify survival-associated features, we performed comprehensive transcriptomic profiling of 340 pretreatment stage II/III TNBCs and 70 matched posttreatment RD samples from the randomized CALGB 40603 (Alliance) phase II clinical trial. To explore preclinical treatment strategies for RD, patient-derived xenograft (PDX) mouse models mimicking RD were treated with antibody-drug conjugates (ADCs).RESULTSOur study shows prognostic genomic features measured pretreatment may differ from prognostic features measured posttreatment from RD specimens. Patients with a genomic PAM50 subtype of basal-like in RD specimens had a poor survival outcome, and their matching pretreatment tumors were characterized by elevated chromosomal amplifications of oncogenic drivers and significantly reduced B and T cell expression features. Paired analyses of basal-like RD and matched pretreatment tumors revealed further lymphocyte depletion in RD, along with lower expression of MHC class I and interferon signaling, indicating an immune-cold RD microenvironment. Treatment of a basal-like and conventional chemotherapy-resistant PDX model, resembling basal-like RD, with sacituzumab govitecan or trastuzumab deruxtecan produced a marked antitumor response.CONCLUSIONRD biology differs from pretreatment tumors, with basal-like subtype RD following neoadjuvant chemotherapy being immune cold and associated with poor survival. Preclinical modeling suggests this high-risk group may benefit from adjuvant ADC therapy.TRIAL REGISTRATIONClinicalTrials.gov NCT00861705.FUNDINGNIH NCI U10CA180821 (Alliance for Clinical Trials in Oncology), NCI U24CA176171 (Alliance for Clinical Trials in Oncology), NCI UG1CA233373 (Alliance for Clinical Trials in Oncology), NCI Breast SPORE program P50-CA058223; Susan G. Komen SAC-160074; Breast Cancer Research Foundation BCRF-23-127; NIH NCI R01-CA229409; UNC LCCC Triple Negative Breast Cancer Center.

Humans

Age- and sex-adjusted genomic differences between Korean and Beat AML cohorts.

Genomic profiling plays a central role in risk stratification and therapeutic decision-making in acute myeloid leukemia (AML), yet the clinical implications of population-specific genomic architectures remain incompletely defined. We conducted a prospective, multicenter study of 603 adults with newly diagnosed AML in Korea, integrating targeted sequencing of 83 recurrently mutated genes with comprehensive clinical annotation across treatment intensities, including allogeneic hematopoietic stem cell transplantation (allo-HSCT). For contextual comparison, genomic profiles were evaluated against the Beat AML cohort. The overall genomic landscape was broadly conserved, supporting shared core disease biology across populations. However, RUNX1::RUNX1T1, CEBPA, GATA2, KIT, and DDX41 mutations were more frequent in the Korean cohort, whereas FLT3 and NPM1 mutations were less common. These differences translated into a distinct distribution of European LeukemiaNet (ELN) 2022 risk categories, with implications for therapeutic stratification. Notably, most DDX41 alterations were germline (3.2%), highlighting the need for systematic germline evaluation with implications for genetic counseling and donor selection. Although unadjusted overall survival appeared longer in the Korean cohort, this difference was not significant after adjustment for key clinical variables. These findings indicate that population-specific genomic distributions reshape the clinical application of risk stratification and support population-aware precision medicine strategies in AML.

Journal Article

Genome-wide characterization of the TGF-&#x3b2; superfamily identifies bmp15, gdf9, and gsdf as sex-biased candidate regulators of gonadal differentiation in the synchronous hermaphrodite Plectropomus leopardus.

The transforming growth factor-&#x3b2; (TGF-&#x3b2;) superfamily plays conserved roles in vertebrate reproduction and gonadal sex differentiation. However, its genomic repertoire and sex-biased expression patterns remain unclear in the leopard coral grouper (Plectropomus leopardus), a species with synchronous hermaphroditism. Here, we performed a genome-wide identification of the TGF-&#x3b2; superfamily, identifying 42 genes from the chromosome-level genome. Phylogenetic and synteny analyses indicated that segmental duplication under purifying selection contributed to family expansion. Expression profiling across multiple tissues and four gonadal developmental stages (undifferentiated, 120 dph; early differentiated, 15&#xa0;months; mature testis, 3&#xa0;years; mature ovary, 3&#xa0;years) identified eight gonad-enriched genes, among which bmp15 and gdf9 exhibited pronounced female-biased expression, with transcripts localized exclusively to the oocyte cytoplasm, particularly in stage II-III oocytes. In contrast, gsdf showed male-biased expression and was localized in spermatogenic cells of the testis. These reciprocal expression patterns indicate that bmp15/gdf9 and gsdf are candidate factors associated with gonadal sex differentiation. Our study provides the first comprehensive characterization of the TGF-&#x3b2; superfamily in P. leopardus and highlights bmp15, gdf9, and gsdf as candidate sex-differentiation factors in this hermaphroditic species.

Animals

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

Comprehensive source-risk assessment of organophosphate esters in surface water of the Dianchi Lake Basin, Yunnan, China.

Organophosphate esters (OPEs), widely used as flame retardants and plasticizers, have been increasingly detected in aquatic environments. However, investigations of their distribution in high-altitude plateau lakes remain scarce. Identifying and quantifying the sources and associated risks of OPEs are crucial for subsequent water environment management. In this study, an integrated source-risk analysis approach was employed by combining the Positive Matrix Factorization (PMF) model, the Geodetector (GD) model, and risk quotient (RQ). Analysis of 14 OPEs in surface waters of the Dianchi Lake Basin (DLB) revealed 12 detectable compounds, with total OPEs concentrations (&#x3a3;OPEs) ranging from not detected (ND)-64.6 ng/L during the wet season and ND-35.8 ng/L during the dry season. Elevated &#x3a3;OPEs were primarily observed at inflow sites in the northern part of the lake and in urban rivers. Source apportionment indicated four major contributing sources: agricultural films containing flame-retardant and plasticizer additives, traffic-related particulate emissions, releases from household and personal care products, and industrial production and applications of flame retardants in plastics, electronics, and related products (the predominant source). The ecological impact caused by OPEs ranges from no risk to low risk, with tris(2-chloroethyl) phosphate emitted from industrial source being the primary driver of potential environmental risk. These findings highlight the necessity of prioritizing industrial sources in future management strategies. Overall, this study provides a methodological framework for source apportionment and risk assessment of OPEs and offers scientific evidence to support environmental management of OPEs in the DLB.

Environmental Monitoring

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics

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

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

Biomarkers

Synaptic vesicle glycoprotein 2A PET imaging in parkinsonian &#x3b1;-synucleinopathies: a systematic review.

Synaptic dysfunction is increasingly recognized as an early and biologically relevant component of &#x3b1;-synucleinopathies. However, conventional imaging biomarkers mainly assess dopaminergic dysfunction, glucose metabolism, or structural damage rather than presynaptic density itself. Synaptic vesicle glycoprotein 2A (SV2A) PET enables in vivo assessment of presynaptic terminal integrity and may provide complementary information in Parkinson's disease (PD), Parkinson's disease dementia/dementia with Lewy bodies (PDD/DLB), and multiple system atrophy (MSA). This systematic review synthesized the available evidence on SV2A-targeted PET in parkinsonian &#x3b1;-synucleinopathies, focusing on regional imaging patterns, clinical associations, longitudinal findings, and methodological determinants of interpretation. Seventeen reports were included. In PD, the most recurrent finding was reduced SV2A binding in the substantia nigra, although additional involvement of brainstem, caudate, striatal, thalamic, raphe, or cortical regions was reported in selected cohorts. In PDD/DLB, abnormalities appeared broader and more cortical, with evidence of association between cortical SV2A binding and cognitive performance. In MSA, one study suggested a distinct infratentorial and cerebellar pattern with potential relevance for phenotypic stratification. SV2A PET is a promising research biomarker for biological characterization of synucleinopathies. However, the field remains limited by small cohorts, methodological heterogeneity, variable quantification strategies, limited longitudinal evidence, and potential cohort overlap. Multicentre validation and harmonized protocols are required before clinical translation.

Humans

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence