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PubMed2025

Mixed Methods Findings from a Stepped Wedge Hybrid Implementation Trial of ATTAIN NAV: A Mental Health Family Navigation Intervention for Autistic Youth.

ATTAIN NAV (Access to Tailored Autism Integrated Care through Family Navigation) was delivered by family navigators to promote access to and engagement with mental health services for school-age autistic youth. This study used a mixed method, stepped wedge design to test the effects of family navigation on service and clinical outcomes while gathering information on implementation. Primary care providers from six clinics in California and 56 caregiver-child dyads enrolled in and completed the study. Clinics were randomized to either a technology-enhanced or standard family navigation condition. Caregivers completed assessments at baseline and post about child, family and services outcomes, and a subset participated in a post qualitative interview. Quantitative findings demonstrated improvements in child challenging behavior and parent activation across conditions although these improvements were more pronounced for families in the standard FN condition. At post-intervention, families in the standard FN condition reported higher levels of navigation satisfaction, a shorter time to attend their first mental health appointment, and higher engagement with their navigator. Qualitative findings complemented and expanded the quantitative survey findings. The ATTAIN NAV model of family navigation for autistic children with co-occurring mental health needs demonstrates promising implementation, service, and clinical benefits. Clinical Trials Registration. NCT05344378.

Humans↗

PubMed2026

A hybrid effectiveness-implementation trial to integrate precision skin cancer risk feedback in federally qualified health centers.

BACKGROUND: Skin cancers are the most common type of cancer in the United States, occur in all segments of the population, and are preventable. Our previous research with primary care patients' demonstrated interest in and efficacy of a precision prevention intervention providing feedback on MC1R risk level (higher versus average) in combination with prevention education materials relative to a standard educational intervention. Our current study is a hybrid type 1 effectiveness-implementation trial deployed at six federally-qualified health centers. This paper presents the study protocol. METHODS: A community advisory panel will guide development of study materials and measures. Staff training at each clinic will be completed in-person. Patients will be approached and screened in-person. Those completing genetic testing and the baseline survey will be randomized to the precision versus standard intervention for each risk level with a target sample size of 286 for each combination. Primary outcomes of effectiveness, assessed at 6 and 12 months, include a tanning score (5 items assessing intentional and unintentional tanning), number of sunburns, conduct of a skin self-examination, and electronic health record documentation of clinician-patient communication about skin cancer prevention. Effectiveness comparisons will focus on the precision relative to the standard intervention among higher risk participants. Implementation data will be collected to identify barriers and facilitators. RESULTS: Effectiveness and implementation outcomes will be evaluated following study completion. CONCLUSIONS: Results will guide subsequent scale-up of the precision intervention, including modifications of the intervention as well as methods for implementation. CLINICAL TRIALS IDENTIFIER: NCT07222995.

Humans↗

PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗

PubMed2026

Multicenter randomized effectiveness/implementation trial of a digital self-management support tool to improve the quality of life during adjuvant hormonal therapy for patients with early breast cancer: The HOPE trial.

BACKGROUND: For patients with hormone receptor (HR) positive early breast cancer (BC), adjuvant endocrine therapy (ET) represents the cornerstone of treatment. However, 75% of patients experience ET-related symptoms that negatively affect their quality of life (QOL). Despite their high prevalence, these symptoms are often underestimated and under-addressed during consultations. As a result, non-adherence to ET is common and remains a major barrier for optimal disease and survival outcomes. METHODS: National, prospective, randomized, open-label hybrid type 1 effectiveness/implementation trial conducted in France comparing a personalized digital health pathway plus standard of care (SoC) vs. SoC alone in patients with HR+ early BC reporting ET-related symptoms. 180 patients will be randomized 1:1 to receive either 12 weeks of the digital health pathway or 12 weeks of SoC. The intervention is anchored by the Resilience© digital companion including remote symptom and needs assessment, an introductory nurse-navigator phone call, and access to personalized, symptom-specific online educational and self-management programs (physical activity, yoga, meditation or cognitive behavioral therapy). In both arms, patients will be invited to wear a wearable device to objectively monitor behavioral parameters. The primary endpoint is the ET symptoms scale of the European Organization for Research and Treatment of Cancer (EORTC) QLQ-BR45 over 12-weeks. Secondary endpoints include other QOL domains, self-reported ET adherence, eHealth literacy, self-efficacy, and evaluation of the implementation process. DISCUSSION: This study should provide evidence on the effectiveness and real-world implementation of a personalized digital health pathway to improve QOL in patients experiencing ET-related symptoms. TRIAL REGISTRATION: ClinicalTrials.gov NCT06781996; Protocol version 3.0.

Humans↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Pervasive hybridization and introgression in Diervilleae (Caprifoliaceae).

Diervilleae (Caprifoliaceae) is a horticulturally important lineage with striking floral diversity and a long history of interspecific crossing, suggesting reticulate evolution. We integrated nuclear SNPs and whole plastome data to reconstruct a phylogenomic backbone for the tribe and to identify hybrids, cultivated accessions, and introgression among lineages. Nuclear and plastid phylogenies consistently recover Weigela and Diervilla as reciprocally monophyletic and resolve four major lineages within Weigela, providing a reproducible framework for revising sectional limits and species boundaries. Cultivated accessions form a well supported clade sister to W. florida and show predominantly W. florida ancestry while retaining contributions from multiple wild lineages, consistent with recurrent crossing, backcrossing, and selection. Analyses of wild populations reveal recurrent hybrids and enable plausible parental combinations to be inferred. Tests across the genome further indicate strong evidence for historical introgression across Diervilleae, with the strongest signals involving W. middendorffiana, W. maximowiczii, and Diervilla. Fossil evidence, divergence time estimation, and paleodistribution modelling together suggest range expansion during the Miocene and Pliocene followed by climate driven contraction, providing a spatiotemporal context for episodic contact, introgression, and the East Asia-North America disjunction.

Hybridization, Genetic↗

PubMed2026

Complex evolutionary history of Rosales mediated by extensive incomplete lineage sorting and hybridization.

The angiosperm order Rosales still represents a major challenge for phylogenetic reconstruction. Although its circumscription is now well-defined, phylogenetic relationships among families are still uncertain. Here, we used nuclear, plastid, and mitochondrial genomic data from 33 species representing all nine families to further clarify interfamilial relationships and the group's evolutionary history. We detected significant phylogenetic conflict among the three datasets. Further analyses at the nuclear level identified incomplete lineage sorting (ILS) as the main cause of unstable phylogenetic positions among families. The discordant placements of Rhamnaceae and Elaeagnaceae based on plastid and mitochondrial data are caused by ancient hybridization events, potentially involving differences in organellar inheritance. Our molecular dating confirms earlier suggestions that the ancient rapid diversification of the three Rosaceae subfamilies could be the main reason for the difficulties in resolving their phylogenetic relationships. Our findings provide new insights into the interfamilial relationships of Rosales and demonstrate that the evolutionary history of this order was shaped by ancient and rapid radiation as well as extensive ILS and reticulate evolution. They also suggest that previous attempts to clarify interfamilial relationships in this order were hampered by combining nuclear and organellar sequence data, leading to inconsistent topologies observed across earlier studies.

Phylogeny↗

PubMed2026

Design of an innovative framework based hybrid catalyst for simultaneous and sensitive monitoring of food additive and preservative of vanillin and nitrite in direct samples.

As vanillin (VAN) and nitrite (NIT) contamination in the food chain poses substantial threats to environmental and public health, rapid and portable detection is essential. The present study presents the first electrochemical sensor report based on a hybrid composite of Ni-TPA-MOF and MoS2/Co3O4. The oxidation of VAN and NIT exhibited sharp peaks and less over-potential on Ni-TPA-MOF/MoS2/Co3O4/GCE than on control electrode surfaces. On modified composite electrode surfaces, pH and scan rate were investigated for VAN and NIT. Further, the oxidation current exhibited high linearity at VAN and NIT concentrations of 5 nM-1000 μM and 3 nM-1250 μM, with detection limits of 0.102 nM and 0.073 nM (S/N = 3). We also applied anti-interfering ability (five/ten-fold excess of co-interfering compounds) and practical tests to various food-based real samples, with high recoveries of 98.85-102.41%. This study highlights the catalytic properties of Ni-TPA-MOF/MoS2/Co3O4 and demonstrates the sensor as a promising tool for food safety.

Benzaldehydes↗

PubMed2026

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

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

Animals↗

PubMed2026

Proteomic insights into hepatic responses to high soybean meal inclusion with citric acid supplementation in hybrid grouper (Epinephelus fuscoguttatus × Epinephelus lanceolatus) juveniles.

This study evaluated the growth performance and hepatic proteomic responses of juvenile hybrid grouper (Epinephelus fuscoguttatus × Epinephelus lanceolatus) juveniles fed diets containing 30% or 40% soybean meal (SBM), with or without 3% citric acid supplementation, and compared with a fishmeal (FM) control diet over a 10-week feeding trial. Fish fed 30% SBM (LSBM) showed a final body weight comparable to the FM group, whereas fish fed 40% SBM (HSBM) recorded significantly reduced growth and net protein utilization (NPU) (p < 0.05). Supplementation of citric acid in the 40% SBM diet (HSBM + CA) significantly improved NPU and partially restored growth relative to HSBM. LC-MS/MS based quantitative proteomics identified 1544 hepatic proteins and showed clear dietary segregation. Differentially expressed proteins were predominantly associated with reduced abundance of proteins involved in lipid metabolism, amino acid metabolism, pyruvate metabolism, and the tricarboxylic cycle across all SBM diets, suggesting a shift in oxidative metabolic capacity. In contrast, LSBM induced upregulation of spliceosome-associated proteins and RNA processing components, suggesting adaptive post-transcriptional regulation under moderate SBM inclusion. In contrast, HSBM exhibited greater reduction in metabolic protein abundance without comparable upregulation of adaptive regulatory components, coinciding with reduced nutrient retention. Protein-protein interaction analysis further confirms the correlation between the regulation of spliceosomal clusters and mitochondrial lipid-catabolic modules. Citric acid supplementation did not markedly reverse hepatic metabolic protein changes but improved protein retention. Data are available via ProteomeXchange with identifier PXD081994. These findings suggest a tolerance limit between 30% and 40% SBM inclusion, with 30% inducing adaptive hepatic proteomic responses compatible with maintained growth performance.

Animals↗

PubMed2026

Spatially confined electrochemical strategy with DNA-assembled nanogaps for SNP detection.

Accurate detection of low-abundance single nucleotide polymorphisms (SNPs) against a large excess of homologous wild-type sequences requires both selective molecular recognition and effective transduction of small sequence differences into measurable signals. Here, we report a spatially confined electrochemical strategy that couples sequence-selective recognition with size-dependent mass-transport gating. DNA-hybridization-driven self-assembly of gold nanoparticles (AuNPs) forms a three-dimensional self-assembled electrode (3D-SAE) with a DNA-defined interparticle architecture. Competitive probes (SP/WP) convert single-base recognition into distinct molecular-size states: the SNP-associated pathway preferentially triggers a hybridization chain reaction (HCR), generating bulky AuNP-anchored HCR/methylene blue complexes (Au@HCR/MB) with reduced electrochemical accessibility through the porous 3D-SAE, whereas the wild-type pathway does not trigger HCR and maintains a high-current response from more readily accessible MB-containing species. Thus, sequence recognition is translated into a molecular-size difference and subsequently into an electrochemical signal through differential mass transport. Under buffer conditions, the platform achieved a statistically estimated detection limit of ∼0.47 fM and a quantitative range of 1 fM-100 pM. It discriminated a 0.1% mutant abundance in a fragmented genomic-DNA background. The downstream signal-transduction chemistry is enzyme-free and isothermal. This work establishes a mechanistical recognition-size-conversion-mass-transport-gating architecture for electrochemical nucleic acid analysis.

Polymorphism, Single Nucleotide↗

PubMed2026

Solutions for engaging priority populations in HIV cure research: a hybrid Delphi consensus-building process.

BACKGROUND: To achieve consensus on barriers and strategies to improve the engagement of three priority populations - Black and Latino/a/x individuals, cisgender women, and transgender women in HIV cure research. METHODS: We assembled a panel of 54 experts assigned to six groups in a hybrid Delphi process: (1) HIV community members, (2) biomedical researchers, (3) medical providers, (4) funders and private industry members, (5) bioethicists and regulators, and (6) social scientists. Over 18 months, we conducted four iterative survey rounds and three group discussions to identify barriers and strategies to arrive at a consensus on how to engage these priority populations in HIV cure research. RESULTS: For Black and Latino/a/x populations, the panellists identified inadequate outreach and a lack of accessible educational information as primary barriers and emphasised community-driven engagement and partnerships with trusted leaders as key strategies. For cisgender women, logistical hurdles, caregiving responsibilities and time constraints were identified as major barriers, with flexible trial designs and equitable compensation proposed as solutions. For transgender women, the lack of transgender-focused research design, including misrepresentation and exclusion, was identified as a key barrier, while centring transgender-specific needs in study design achieved consensus as the most effective strategy. CONCLUSION: Among all four priority populations, investment in outreach, engagement along the research process, better integration of health needs with research, and enhanced incentives are not novel ideas, but remain obviously ignored in a way that has led to underrepresentation of people in HIV cure research, who carry the greatest burden of HIV in the U.S. SUMMARY: This paper uses a hybrid Delphi process to identify and reach consensus on key barriers and strategies to engage underrepresented groups: Black and Latino/a/x individuals, cisgender women, and transgender women in HIV cure research across the United States.

Humans↗

PubMed2026

Beyond Glycaemia: Fear of Hypoglycaemia, Cognition and Functional Mobility After Advanced Hybrid Closed-Loop Therapy in Older Adults With Type 1 Diabetes: A Prespecified Secondary Analysis of a Randomised, Single-Centre Study.

BACKGROUND: Evidence on psychological, cognitive and functional outcomes of advanced diabetes technologies in older adults with long-standing type 1 diabetes (T1D) remains limited. We evaluated whether initiation of advanced hybrid closed-loop (AHCL) therapy was associated with changes in fear of hypoglycaemia, diabetes distress, psychological well-being, cognition, frailty-related measures and mobility-related function in adults aged ≥ 65 years with T1D. METHODS: This prespecified, exploratory secondary analysis was conducted within a single-centre, open-label, randomised, controlled, parallel-group trial including adults aged ≥ 65 years with long-standing T1D. Participants were randomly assigned (1:1) to initiate AHCL therapy using the MiniMed 780G system or to continue standard diabetes treatment. The secondary outcomes included WHO-5, the 17-item Diabetes Distress Scale (DDS), Hypoglycemia Fear Survey-II (HFS-II), Montreal Cognitive Assessment, Digit Symbol Substitution Test, Fried frailty phenotype and performance-based functional measures. No formal sample-size calculation was performed for these secondary outcomes. RESULTS: Thirty-one participants were randomised and 29 completed 12 months of follow-up and were included in the treatment-effect analyses. In the baseline-adjusted primary analysis, AHCL therapy was associated with a lower HFS-II score than standard treatment (adjusted mean difference -18.9; 95% CI: -32.4 to -5.4; nominal p = 0.008), although this finding did not remain statistically significant after Holm correction (adjusted p = 0.104) or in an exploratory model additionally adjusted for sex (difference -13.6; 95% CI: -32.2 to 5.0; p = 0.145). Diabetes distress, psychological well-being, global cognition and processing speed did not differ between groups. In sex-adjusted sensitivity analyses, the between-group differences remained statistically significant for 6-min walk distance (92.6 m; 95% CI: 36.8 to 148.3; p = 0.002) and Timed Up and Go performance (-2.27 s; 95% CI: -4.28 to -0.27; p = 0.028), but not for gait speed (0.27 m/s; 95% CI: -0.05 to 0.59; p = 0.099). At 12 months, 12 of 14 AHCL participants were robust and 2 were pre-frail; in the control group, 11 of 15 were robust and 4 were pre-frail. No participant was classified as frail at follow-up. CONCLUSIONS: In this small, selected cohort, AHCL therapy was associated with a nominally lower fear-of-hypoglycaemia score and better performance on selected mobility-related tests over 12 months. The fear-of-hypoglycaemia finding did not remain statistically significant after correction for multiple comparisons or additional adjustment for sex. Six-minute walk distance and Timed Up and Go remained statistically significant in the exploratory sex-adjusted sensitivity analyses, whereas the gait-speed difference did not. No measurable between-group deterioration in global cognition or processing speed was observed. These exploratory findings require confirmation in larger studies with balanced representation by sex and direct measurement of physical activity. These findings also support a person-centred clinical message: older age alone should not be regarded as a barrier to AHCL when treatment is introduced with individualised education and appropriate ongoing support.

Humans↗

PubMed2026

Early Worsening of Diabetic Retinopathy Following Initiation of Hybrid Closed-Loop/Automated Insulin Delivery Systems in Type 1 Diabetes: A Systematic Review and Structured Study-Level Synthesis.

BACKGROUND: Hybrid closed-loop (HCL) systems achieve rapid, algorithm-driven improvements in glycaemia in type 1 diabetes (T1D). Paradoxically, rapid improvement in glycaemic control is associated with early worsening of diabetic retinopathy (EWDR), a phenomenon established in the intensive insulin therapy era. Whether HCL initiation carries a clinically meaningful EWDR risk is unknown. No systematic review has previously addressed this question. METHODS: A systematic review and structured quantitative synthesis was performed using study-level estimates only (PROSPERO CRD:420261391951). MEDLINE, SCOPUS and Web of Science were searched to 14th May 2026. Studies reporting retinal outcomes in people with T1D initiating any HCL system were eligible. Two reviewers independently screened studies and extracted data. Risk of bias was assessed using ROBINS-I and certainty of evidence using the GRADE framework. EWDR incidence was summarised using study-level proportions, and comparative studies were summarised using study-specific risk ratios for HCL versus control therapy. Given substantial heterogeneity in EWDR definitions, retinal assessment timing, follow-up duration, and comparator groups, no pooled or meta-analytic estimates were derived. RESULTS: Eight studies (n = 1487 participants; 860 HCL users) were included; all were observational and six were retrospective. EWDR varied markedly with the timing of retinal assessment. In studies assessing the retina within ≤ 12 months of HCL initiation, EWDR rates ranged from 8.9% to 26.5%. Studies with longer follow-up reported lower rates of retinal worsening or incident DR, 6.7% at 24 months and 6.1% over a mean follow-up of 4.9 years, suggesting that these studies may capture background DR progression rather than true early worsening. Three comparative studies included 177 HCL users and 315 controls; EWDR study-specific risk ratios were directionally inconsistent, ranging from 0.32 to 1.51, and were therefore not pooled. The most consistently identified risk factors were higher baseline HbA1c and older age. The magnitude of HbA1c reduction was not a consistent predictor of EWDR in the HCL context, in contrast to pre-HCL era evidence. Risk of bias ranged from moderate to critical and certainty of evidence was very low for all outcomes. CONCLUSIONS: Study-defined retinal worsening was reported in a minority of participants. The current evidence base is dominated by retrospective studies, variable retinal assessment timing, and inconsistent EWDR definitions. Well-designed prospective studies with protocol-specified retinal surveillance anchored to HCL initiation are required to generate reliable incidence estimates, identify risk factors, determine visual consequences, and inform standardised screening guidance.

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

Functional characterization of the MdFLZ2 gene in drought and salt stress tolerance in apple.

Drought and salt stress are significant environmental limitations that severely constrain plant growth and productivity, therefore, enhancing stress tolerance is a key goal in crop improvement. The plant-specific FCS-like zinc finger (FLZ) proteins have been identified as important regulators of stress adaptation. In this study, we conducted a genome-wide characterization of the FLZ gene family in apple and functionally characterized MdFLZ2. qRT-PCR analysis revealed that MdFLZ2 was differentially expressed across various tissues and transcriptionally induced by both drought and salt stress. Subcellular localization assays demonstrated that the MdFLZ2 protein is localized to both the nucleus and the cytoplasm. The overexpression of MdFLZ2 in apple calli, Arabidopsis and tomato conferred increased resistance to drought and salt stress. In addition, yeast two-hybrid (Y2H) assays confirmed that MdFLZ2 interacted with MdSnRK1.1, and similar interactions were also detected between other MdFLZ family members and MdSnRK1.1. Collectively, our findings suggest MdFLZ2 as a positive regulator of drought and salt tolerance and highlight its potential to serve as a genetic resource for abiotic stress improvement.

Malus↗

PubMed2026

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Introgression shapes the genomic conflict landscape of Malus, providing evidence for a reticulate backbone in a woody crop lineage.

Phylogenomic discordance is widespread across plants, but its evolutionary significance is often obscured when conflict is treated primarily as analytical noise rather than as evidence of underlying processes. In woody lineages in particular, incomplete lineage sorting, introgression, and genome duplication can interact over long timescales to produce complex genomic histories that are not adequately summarized by a strictly bifurcating tree. Here, we use Malus as a model woody genus to investigate how these processes structure conflict across a genus-scale, accession-based phylogenomic framework. Using broad taxon sampling, hundreds of nuclear loci, plastid genomes, and genome-wide SNP summaries, we reconstruct a robust nuclear backbone for sampled Malus lineages and evaluate where discordance is concentrated and which processes best explain it. Nuclear analyses resolve eight major clades, whereas conflict is non-random and localized to recurrent hotspots rather than evenly distributed across the tree. Cytonuclear discordance is similarly concentrated, especially around Clade H, represented by sampled accessions of M. tschonoskii, where localized plastid-nuclear disagreement is consistent with candidate plastid capture or organellar introgression. Multiple complementary analyses further indicate that the strongest conflict is not explained by ILS alone, but instead reflects lineage-structured introgression, while polyploid complexes represent additional localized sources of evolutionary complexity. Together, these results provide evidence for a reticulate genomic backbone in Malus and show how integrating nuclear, plastid, and genome-wide conflict analyses can help distinguish background discordance from process-specific signals in woody plant radiations. Several lineage-level reticulation hypotheses identified here should now be tested with broader population-level sampling and curated reference accessions.

Malus↗