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PubMed2026

Development of a new recombineering system for Edwardsiella species.

Edwardsiella species are important aquaculture pathogens that also cause opportunistic infections in humans, necessitating efficient genome editing tools to study their pathogenesis and develop control strategies. In this study, we identified and characterized six endogenous recombinases pairs from Edwardsiella and its phages. Among these, the BAS_MS17 system exhibited the highest recombination efficiency in E. piscicida EIB202Δp. Extending homology arms from 150 bp to 200 bp improved editing efficiency by 2-fold, while the addition of Redg or Plug further enhanced recombination by 3-fold and 2.5-fold, respectively, without compromising accuracy (100%). More importantly, when applied to E. piscicida sdu12S, Redg or Plug improved the editing efficiency by 8-fold and 7-fold, respectively. Deletion of the phage-derived single-strand binding protein (SSB) reduced efficiency to 25% of the BAS_MS17 level, whereas expression of the endogenous RecA-family SSB (rSSB) increased recombinant yield by 5-fold, highlighting functional conservation. Furthermore, SSB proteins from heterologous hosts failed to enhance recombination efficiency. Using the optimized system, we successfully knocked out ten distinct genes, including virulence-associated loci, with editing accuracy exceeding 85%. Phenotypic analysis revealed that luxR, but not the other tested genes, contributes to biofilm formation. Virulence evaluation results showed that aroA, fur, and hfq are critical virulence-associated factors. Collectively, this streamlined recombineering system provides a simple, rapid, and efficient genetic tool for Edwardsiella, supporting mechanistic studies of virulence and the development of live attenuated vaccine candidates.

Edwardsiella piscicida↗

PubMed2026

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence↗

PubMed2026

Quo vadis, BGA? A collaborative EDNAP exercise on the challenges and progress in forensic biogeographical ancestry inference.

There is a broad consensus that forensic tests for the prediction of externally visible characteristics (EVC) and analysis of biogeographic ancestry (BGA) of an individual are technically reliable. However, interpretation of the results and population-specific genotype distribution patterns remains challenging. EVC and BGA analyses provide valuable information for population genetics studies and as investigative leads for criminal cases, as well as for historical and contemporary identification tests. However, inaccurate or incorrect predictions, for example, from subjective bias in the interpretations made, have the potential to misdirect police investigations. The legal situation regarding EVC and BGA testing varies by country: ranging from countries where it is explicitly prohibited, to those without specific regulations on biogeographic ancestry prediction, and others that have already enacted laws governing its use. The reluctance to utilize these analyses is not only due to legal restrictions and data protection concerns, but also to initial limited sets of sufficiently comprehensive forensic DNA assays. Forensic BGA marker panels typically contain up to ∼300 SNPs. This relatively small number of genetic markers, along with limited reference population data, complicates the interpretation of results from donors of unknown origin. This paper presents the results of a collaborative EDNAP study, which, for the first time, evaluated the approach to reporting EVC and BGA data between international laboratories. For the study, DNA from nine individuals with self-reported ancestry was collected and analysed using various forensic panels differing in the number and composition of ancestry-informative markers genotyped, comprising: the Precision ID mtDNA Whole Genome Panel, the VISAGE Basic Tool and the VISAGE Enhanced Tool for Appearance and Ancestry Prediction, and the Ion AmpliSeq™ PhenoTrivium Panel. To ensure full data protection, all SNP genotypes and uniparental marker haplotypes obtained were not shared with third parties. Instead, the genetic data were analysed using a range of commonly used population analysis software packages. These analysis outcomes were then distributed to twelve European forensic laboratories (both academic and law enforcement institutions), who were asked to prepare reports based on their interpretation of the phenotypes and ancestry they inferred from the analysis data. A questionnaire sent alongside the genetic information, aimed to evaluate which difficulties were encountered by the participants in processing the BGA analysis data they were given.

Humans↗

PubMed2026

Systemic biomarkers of treatment response to methotrexate in people with painful knee osteoarthritis: A biological substudy of the PROMOTE randomised controlled clinical trial.

OBJECTIVE: Stratification of therapeutic responses may help identify efficacious therapies for osteoarthritis (OA). In the PROMOTE randomised trial, participants with elevated baseline high-sensitivity C-reactive protein (hs-CRP) showed greater pain reduction after methotrexate treatment. We set out to interrogate a broader panel of serum/plasma inflammatory response markers relevant to methotrexate actions as potential biomarkers of therapeutic effect. Our objectives were to: (i) characterize changes in these systemic markers during methotrexate treatment; determine whether (ii) baseline levels or (iii) changes in any marker during treatment were associated with treatment response; and (iv) compare these findings with the more established clinical inflammatory marker, hs-CRP. DESIGN: Plasma/serum samples from participants in PROMOTE's biological substudy were analysed for 35 inflammatory markers at baseline (pre-treatment) and at 6-months (post-treatment), by MesoScale V-plex multiplex assay. Those with paired biological and clinical data at both baseline and 6-months were included in the substudy analysis set. Relationships between markers and overall data structure were assessed by Pearson correlation and Principal Component analysis. Associations between markers (baseline levels or change over time) and change in average knee pain severity in past week (numerical rating scale, NRS) were evaluated by univariable linear regression, adjusting for baseline age, sex, and body mass index. Least Absolute Shrinkage and Selection Operator (LASSO) regression with bootstrap resampling enabled marker selection. Benjamini-Hochberg correction adjusted for multiple testing (Padj). RESULTS: 87 participants with paired blood marker and clinical data were eligible for substudy analysis. 18/35 markers were quantifiable and analysed. Systemic IL-8 and TNF-α levels decreased (Padj=0.015, 0.048 respectively) while IL-15 increased (Padj=0.033) with methotrexate treatment over 6-months. Analysing within this active treatment randomised arm, higher baseline IFN-γ was associated with greater reduction in NRS pain change (0.66 [0.01, 1.31], P=0.047), as was decreasing TNF-α over 6-months (2.25 [0.00, 4.5], P=0.049). LASSO identified higher IFN-γ, lower plasma IL-15 and IL-16, and younger age as the most important baseline predictors of pain improvement. hs-CRP was highly selected by LASSO for treatment response in both arms. In a secondary univariate treatment arm-by-biomarker interaction analysis, of the 19 markers, only hs-CRP showed consistent effects in adjusted models (at baseline, coeffic. 2.34 [0.53, 4.15], P=0.001; change over 6-months, (0.36 [0.06, 0.66], P=0.018). CONCLUSIONS: Blood measurement of IFN-γ, TNF-α, IL-15 and IL-16 as well as hs-CRP could act as potential markers to stratify the treatment response by average knee pain to methotrexate in knee osteoarthritis.

Humans↗

PubMed2026

Strategy for enhanced production of A40926B0 in Nonomuraea gerenzanensis using an efficient CRISPR/AsCas12f1 system.

The global emergence of vancomycin-resistant Gram-positive pathogens underscores the urgent need for efficient production of novel lipoglycopeptide antibiotics. Dalbavancin, a last-resort therapeutic agent, relies on its key biosynthetic precursor A40926B0, whose industrial manufacture is severely limited by the low yield of wild-type Nonomuraea gerenzanensis and inefficient genetic tools for this rare actinomycete. Here, we developed a high-efficiency CRISPR/AsCas12f1 genome editing system and applied systematic metabolic engineering to boost A40926B0 biosynthesis. First, conjugation conditions were optimized to elevate the transfer efficiency in N. gerenzanensis D11. The hypercompact AsCas12f1 nuclease showed markedly lower cytotoxicity than SpCas9 and enabled 100% gene deletion efficiency with preferred PAMs (TTTG, CTTG, GTTG). Second, we strengthened the shikimate pathway via multiple genetic strategies: overexpressing feedback-resistant DAHP synthase (aroG fbr ) and chorismate mutase/prephenate dehydrogenase (tyrA fbr ), as well as knocking out pheA. This manipulation blocks the phenylalanine synthetic branch and redirects metabolic flux toward the l-tyrosine branch. Third, we engineered the branched-chain fatty acid (BCFA) pathway via promoter replacement of bkdA2B2C2, LipAB, fabF and deletion of acdH to enhance isododecanoyl side-chain supply. The combinatorial engineering yielded strain B-13, which produced 1740 mg/L A40926B0 in shake flasks. Finally, 50-L fed-batch fermentation with continuous maltodextrin feeding further increased the titer to 1817 mg/L, the highest reported titer to date. This work establishes a robust CRISPR editing tool for N. gerenzanensis and provides valuable engineering references for precursor-oriented strain improvement targeting lipoglycopeptide antibiotics, offering insights for the industrial scale production of A40926B0.

A40926B0↗

PubMed2026

Emerging hantavirus risks in mass gatherings: epidemiology, diagnostic challenges, and outbreak preparedness.

Hantaviruses are emerging rodent borne zoonotic pathogens of increasing global public health concern because of their high mortality, expanding ecological distribution, and potential for international dissemination. Although traditionally associated with sporadic rural outbreaks, recent ecological disruption, climate variability, urbanization, and increased global mobility have heightened concerns regarding hantavirus risks in mass gathering settings. This review critically examines the epidemiology, transmission uncertainty, diagnostic and surveillance challenges, and preparedness strategies related to hantavirus infections in the context of mass gatherings, including religious events, refugee settlements, cruise tourism, sporting events, and temporary accommodations. Particular emphasis is placed on the 2026 multinational cruise ship associated outbreak linked to the MV Hondius, which highlighted vulnerabilities related to delayed diagnosis, international passenger dispersal, and uncertainties surrounding possible human to human transmission of Andes virus. Current evidence indicates that hantavirus transmission occurs primarily through inhalation of aerosolized rodent excreta; however, controversies regarding limited interpersonal transmission, environmental persistence, and asymptomatic infections continue to complicate risk assessment and outbreak preparedness. Diagnostic limitations, underreporting, insufficient environmental surveillance, and lack of mass gathering specific preparedness frameworks remain major public health challenges, especially in resource limited settings. Strengthening proactive preparedness through integrated One Health approaches, ecological surveillance, genomic monitoring, AI driven epidemic intelligence, and coordinated international response systems is essential for mitigating future risks. The review emphasizes the urgent need for multidisciplinary research and evidence based policy development to improve global preparedness against emerging hantavirus associated threats in increasingly interconnected mass gathering environments.

Humans↗

PubMed2026

From commensal to pathobiont: The emergence of virulence-enhanced Escherichia coli in China's food-animal systems - insights with future implications.

A fundamental shift in Escherichia coli epidemiology is being driven by convergence of virulence determinants and antimicrobial resistance within linked human-animal-environment systems. In China, the rapid growth of food-animal production, extensive antimicrobial use, and complex food networks are accelerating the emergence and dissemination of virulence-enhanced E. coli pathobionts. This review synthesizes recent epidemiological, genomics, and outbreak data to characterize China's evolving landscape of food-animal-associated E. coli. We highlight a significant shift from classical pathotypes to hybrid lineages that simultaneously carry virulence factors and last-resort antibiotic resistance determinants, including mcr-1, tet(X4), and blaNDM. These traits disseminate rapidly via plasmid-mediated horizontal gene transfer, facilitating rapid adaptation and enabling cross-sectoral One Health transmission. National surveillance, foodborne outbreak investigations, and whole-genome sequencing data show that food-animal reservoirs are active evolutionary niches that drive pathogen diversity and fitness, rather than serving merely as contamination sources. Whole-genome sequencing also pinpoints high-risk clones (e.g., ST394) and plasmid-mediated co-selection of virulence and AMR. The emergence of hybrid pathotypes (e.g., STEC/ETEC) and AMR-virulence co-selection challenges traditional classification and limits the effectiveness of conventional surveillance approaches. The 2017 colistin ban reduced mcr-1, yet ongoing resistance and emerging tet(X4) demand integrated surveillance. Collectively, these findings call for reconceptualizing E. coli as a dynamic genomic entity embedded within a unified ecological network. Addressing this threat requires an integrated One Health strategy including genomic surveillance, agricultural antimicrobial stewardship, and coordinated food-environment-clinical monitoring to prevent high-risk clone emergence and global spread.

Animals↗

PubMed2026

From population to individual: advocating personalised digital tools for heat-health early warning in a changing climate.

Escalating heat extremes under climate change are imposing substantial health burdens, with 2023 and 2024 consecutively breaking global temperature records. Mounting evidence suggests that heatwaves elevate the risks of hospitalisation and mortality across multiple disease categories, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and acute kidney injury. Nonetheless, most existing heat-health warning systems remain primarily reliant on population-level predictions, and considering individual differences and disease-specific considerations when defining warning levels would benefit the effectiveness of early prevention for high-risk groups. In this Viewpoint, which is based on the framework of precision public health-delivering the right intervention to the right population at the right time-we propose a framework for personalised digital heat-health early warning tools comprising three dimensions: individualised, risk-stratified prediction models that generate tiered early warnings; personalised health prompts coupled with theory-informed behavioural interventions; and adaptive, equity-oriented alert delivery mechanisms tailored to diverse populations. Such tools have the potential to bridge precision disease prevention and climate adaptation, thereby helping to mitigate heat exposure risks and disease burdens, particularly among high-risk populations. Future implementation research will be essential to address substantial challenges related to feasibility, validation, and equity.

Journal Article↗

PubMed2026

Interface-dependent V. parahaemolyticus biofilm under varying temperatures, media, and oxygen conditions: implications for seafood safety.

Vibrio parahaemolyticus biofilms play a critical role in pathogen persistence in marine and seafood-processing environments, where oxygen availability, temperature, and surface interfaces vary widely. This study investigated biofilm development by three strains on partially submerged stainless-steel coupons under gas-liquid-wall (GLW) and fully submerged (SM) interfaces. Viable cell counts (log₁₀CFU/cm2) along with normalized protein concentration per viable cell (nProt) and normalized polysaccharide concentration per viable cell (nPol) were measured, under aerobic and anaerobic conditions across a temperature range of 15-30 °C, using tryptic soy broth with 3% NaCl (TSB) and seawater-based medium (SW). GLW biofilms consistently exhibited higher cell counts (6.4-7.3 log₁₀CFU/cm2) compared to SM biofilms (5.9-6.3 log₁₀CFU/cm2), suggesting that enhanced oxygen diffusion promotes bacterial proliferation. Conversely, SM biofilms exhibited significantly higher nProt and nPol levels (p < 0.001), indicating increased production of the extracellular polymeric substance (EPS) matrix under low-oxygen, high-nutrient conditions. Microscopy and three-dimensional surface plot analyses revealed relatively uniform biofilm layers at the GLW interface, whereas SM biofilms formed heterogeneous, tower-like structures. EPS production was further influenced by medium composition, oxygen, and temperature. SM biofilms grown in SW exhibited significantly higher nProt and nPol than those in TSB under aerobic conditions (p < 0.001), indicating enhanced matrix stabilization. Under anaerobic conditions at 15 °C, nProt and nPol were higher, whereas under aerobic conditions, peak nProt and nPol occurred at elevated temperatures. These findings highlight a trade-off between bacterial growth and matrix production and provide insight into biofilm adaptation and persistence in seafood-processing environments. These insights may help develop improved biofilm control and seafood safety management.

Biofilms↗

PubMed2026

Perioperative care for patients with opioid exposure and opioid use disorder: screening and treatment strategies.

PURPOSE OF REVIEW: The prevalence of opioid tolerance, dependence, and use disorder is increasing among patients presenting for surgical care, yet perioperative management strategies for these patients remain inconsistent. This review examines the impact of preoperative opioid exposure on surgical outcomes, the scope of untreated opioid use disorder (OUD) among surgical patients, and advances in clinical and systems-level approaches to perioperative care. RECENT FINDINGS: Preoperative opioid exposure independently predicts worse surgical outcomes, including higher opioid consumption, readmissions, complications, and mortality, in a dose-dependent manner. Perioperative opioid exposure predicts persistent opioid use after surgery, with the duration of exposure a stronger predictor of subsequent OUD than daily dose. Data-driven prescribing guidelines and structured opioid tapering reduce overprescribing without compromising pain control. Among surgical patients with diagnosed OUD, approximately two-thirds do not receive medications for opioid use disorder (MOUD), though treatment engagement and maintenance substantially improve outcomes. Evidence now clearly supports perioperative buprenorphine continuation over interruption. SUMMARY: Effective perioperative management of opioid-complex surgical patients requires systematic screening, evidence-based prescribing, MOUD continuation, and institutional infrastructure. The primary barrier is shifting from evidence generation to implementation.

Humans↗

PubMed2026

Beyond Photometric Consistency: Addressing Loss Insensitivity to Depth Noise in Endoscopic Estimation via Error Calibration.

Self-supervised monocular depth estimation in endoscopy is fundamentally constrained by the ill-posed nature of photometric supervision. In this work, we identify a critical yet overlooked cause of this ambiguity: the inherent insensitivity of photometric loss to depth noise. To overcome this intrinsic limitation, we propose Depth Error Calibration Learning (DECL), a two-stage framework that suppresses prediction variance and mitigates residual errors in self-supervised depth estimation. In Stage I (Variance Reduction), a cyclic depth generation strategy produces multiple depth hypotheses for the input image. The per-pixel empirical variance is quantified and integrated into a dedicated variance loss term, which penalizes inconsistent predictions and encourages the network to generate more stable and reliable depth estimates. In Stage II (Bias Calibration), an image-conditioned diffusion model refines the Stage-I depth prior and mitigates structured residuals through iterative denoising, thereby improving geometric accuracy and global consistency. Extensive experiments on three public endoscopic datasets demonstrate that DECL achieves consistent improvements over representative self-supervised monocular depth estimation methods under the evaluated protocols. Moreover, ablation studies on two representative backbones indicate that DECL is not restricted to a single network implementation, while broader validation on additional backbone families remains necessary. The source code is publicly available at https://github.com/DavidLuBit/EndoDenoising.

Journal Article↗

PubMed2026

Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.

Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P = 0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3 °C; +4.5 °C relative to CK_M), and its group-mean temperature remained ≥ 60 °C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.

Bacillus↗

PubMed2026

Cross-kingdom dynamics of the subgingival bacteriome and mycobiome: A pilot study on the effects of a novel HA-H₂O₂-Glycine formulation to treat periodontitis.

OBJECTIVES: Traditional periodontal therapy primarily focuses on bacterial biofilm control; however, recent evidence also suggests a critical role for the oral mycobiome. This study evaluated the clinical and ecological impact of a novel mouthwash formulation containing hyaluronic acid (HA), hydrogen peroxide (H2O2), and glycine on periodontal patients METHODS: This prospective, randomized split-mouth trial included 13 adult participants with periodontitis treated with HA-H2O2-glycine formula (BMG0703A) used twice a day for seven days. Subgingival plaque samples were collected from periodontal pocket and healthy control sites at baseline (T0) and one-week post-treatment (T1). Microbial and fungal communities were characterized using Next-Generation Sequencing (NGS) of the 16S rRNA and ITS2 regions. Linear Mixed Models (LMM) and Spearman correlation were used to assess taxonomic shifts and cross-kingdom relationships. RESULTS: Sequencing revealed a promising ecological shift: the bacteriome shifted from anaerobic dominance (Olsenella, Peptostreptococcus) toward a health-associated aerobic profile, with Rothia near-doubling (11.91% to 22.68%). The mycobiome underwent a "normalization" effect: Candida abundance decreased significantly (22.8% to 9.1%), while fungal Shannon diversity in pockets returned to healthy-site levels. Inter-kingdom analysis identified antagonistic relationships between expanding commensal bacteria and opportunistic fungi, suggesting that the intervention may help re-establish a protective bacterial niche. CONCLUSIONS: The HA-H2O2-glycine formulation seems to facilitate a rapid, cross-kingdom modulation of the subgingival niche. By reducing anaerobic pathogens and normalizing the mycobiome it appear to induce short-term changes, suggesting potential as adjunctive strategy in periodontal management. CLINICAL SIGNIFICANCE: The present work underlines the possible cross-Kingdom effects of a novel compound.

Humans↗

PubMed2026

Diagnostic value of plasma cell-free DNA metagenomic next-generation sequencing in patients with suspected infections and exploration of clinical scenarios-a retrospective study from a single center.

BACKGROUND: Plasma cell-free DNA metagenomic next-generation sequencing (mNGS) is a non-invasive comprehensive method for the etiological diagnosis of various infectious diseases. However, research on the early diagnosis and real-world clinical impact of plasma mNGS in patients with suspected infection are still limited. MATERIALS AND METHODS: This study retrospectively included 140 patients with suspected infections who underwent early plasma mNGS and conventional culture testing. Referring to the clinical diagnosis of infectious diseases, the diagnostic performance of plasma mNGS and culture tests was compared, and the application scenarios and clinical effects of plasma mNGS were evaluated. RESULTS: The positive rate of plasma mNGS was significantly higher than that of culture methods (55.71% vs 25.10%, p < 0.001) and blood cultures (55.71% vs 12.86%, p < 0.001). Regarding clinical diagnosis, the sensitivity of plasma mNGS was significantly higher than that of culture (58.27% vs 37.80%, p = 0.002). The combination of mNGS and culture achieved a higher detection sensitivity (69.29%), especially in patients with multi-site co-infections (73.68%) and blood infections (73.17%). Plasma mNGS demonstrated higher sensitivity in patients with procalcitonin (PCT) index > 5 ng/ml or human neutrophil lipocalin (HNL) index > 200 ng/ml. In terms of treatment, a total of 69 patients (54.33%) benefited from plasma mNGS. CONCLUSION: This study highlights the significant improvement in pathogen detection performance by combining conventional culture with plasma mNGS detection, especially in patients with multi-site co-infections and blood infections. Early use of plasma mNGS as an adjunct to culture can better guide clinicians to initiate appropriate anti-infective therapy.

Humans↗

PubMed2026

Comparative genomic epidemiology of food- and patient-derived diarrheagenic Escherichia coli from sentinel surveillance in Southeast China.

Diarrheagenic Escherichia coli (DEC) remains an important foodborne pathogen, yet long-term comparative genomic surveillance data jointly characterizing food-derived and patient-derived isolates remain limited. This surveillance-based comparative study integrated antimicrobial susceptibility testing and whole-genome sequencing to characterize diarrheagenic Escherichia coli isolates recovered from food and patient sources in Lishui, Southeast China, during 2018-2025, with emphasis on occurrence, resistance profiles, genomic backgrounds, and plasmid replicon-associated features. Antimicrobial susceptibility testing was performed for 258 selected isolates, and whole-genome sequencing was conducted for a curated analytical subset of 204 isolates. The sequenced subset was used for diversity-oriented comparative genomic analysis rather than for unbiased prevalence estimation of the entire DEC collection. EAEC predominated in both sources, although food-associated occurrence was heterogeneous across categories, with the highest recovery rate observed in raw meat. Patient-derived isolates showed a broader overall resistance burden, whereas food-derived isolates retained substantial resistance to tetracycline, chloramphenicol, and florfenicol. Phylogenetic analysis showed partial overlap in genomic backgrounds between food-derived and patient-derived isolates, while representative resistance determinants displayed both broadly distributed and lineage-enriched patterns. Replicon-based plasmid profiling identified 42 plasmid types, including 12 detected in both sources, with IncF-related replicons predominating among these shared profiles. Several food-derived isolates carried multiple plasmid replicon types that were also observed in patient-derived isolates. Overall, food-derived and patient-derived DEC showed partial overlap in genomic backgrounds, resistance determinants, and replicon-defined plasmid profiles within this surveillance setting, while retaining source-associated heterogeneity. These findings should be interpreted as surveillance-based comparative evidence rather than as evidence of direct source attribution or transmission.

Humans↗

PubMed2025

Application of causal discovery of factors driving dissolved oxygen in estuarine environments.

Dissolved oxygen (DO) concentrations in estuarine bottom waters are a manifestation of multiple, interacting physical and biogeochemical processes, yet identifying their independent contributions remains challenging. Here, we analyze monthly water quality monitoring data from eight stations across Long Island Sound from 1994 to 2022 using a causal discovery framework (PCMCI+) and transformation of forcing variables. Our goal is to identify and isolate variables that causally influence bottom DO and improve predictive models by minimizing overfitting and multicollinearity. PCMCI+ reveals surface-layer temperature as the most important and consistent negative driver of bottom DO, followed by stratification. Wind events exhibit only brief relief by advection and mixing, while river discharge shows no direct causal link to DO, making it less influential than previously thought. Biogeochemical variables, including chlorophyll-a (Chl-a), nitrate and nitrite, and particulate carbon, influence DO through both contemporaneous and time-lagged pathways, often with signs that shift depending on the process. The derived models were evaluated by comparing skill scores, mean squared error, and Akaike Information Criterion. Both model types perform well, with coefficient of determination values exceeding 0.90 at multiple stations using only 3-5 predictors. Our analysis reveals that the best causal predictors are surface-layer temperature, stratification, Chl-a, and particle carbon. This approach provides a scalable framework for improving prediction models and understanding the mechanistic links that control the seasonal variability of DO in estuarine systems.

Estuaries↗

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

Endocrine Phenotypes and Hormonal Treatment in Meier-Gorlin Syndrome: Report of Two Cases and a Systematic Review of Literature.

BACKGROUND: Meier-Gorlin-syndrome (MGORS) is a rare cause of primordial dwarfism stemming from pathogenic variants in genes involved in DNA replication. The classic clinical triad is microtia, absent patella and short stature. MGORS can mimic endocrine causes of short stature or delayed/atypical pubertal development. METHODS: We report two new cases of MGORS. A systematic literature search of all cases published up to 31 March 2026 was done to identify the cases reporting any endocrinopathy or hormonal therapy, focussing on growth-hormone-deficiency (GHD) and response to growth hormone (GH). RESULTS: We describe a 14 year-old girl, the first MGORS case with CDC6 variant and mammary hypoplasia. Another 11-year old boy with GMNN variant had severe short-stature with GHD and had significant height improvement with GH. Among 29 cases (out of ~150 published), the classic triad was absent in 18.5%. Short stature was almost universal (median height-Z-score -4.4), with 70% exhibiting delayed bone age, 42.9% low IGF-1 and 35.3% GHD. Among 10 GH-treated cases with response data, 6 had reported improvement in height-SDS/growth-velocity. Those with GHD and delayed bone age were more likely to benefit from GH. Among females, all post-pubertal cases had mammary hypoplasia, while 23.5% had clitoromegaly with hypoplastic labia. Among males, cryptorchidism, hypoplastic scrotum and micropenis were common. However, gonadal hormones and gonadotrophins were normal. Data on the effect of estrogen on hypoplastic mammary glands or labia was variable. CONCLUSION: MGORS should be kept in mind as a differential of multiple endocrinopathies. Cases of MGORS should undergo screening for GHD. Available data, mostly from case-reports or small series, suggest that response to GH has been reported in some individuals, particularly where GHD or delayed bone age was present, but evidence remains very limited.

Humans↗