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

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

Biogenic Amines

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans

Transcriptomic insights into the molecular mechanism of antifouling agent-induced settlement inhibition in the Pacific oyster Crassostrea gigas.

Marine biofouling remains a persistent challenge to maritime industries and marine ecosystems worldwide. In this study, we systematically evaluated the acute toxicity, settlement inhibitory efficacy, and underlying molecular mechanisms of an N-oleyl-1,3-propanediamine-based antifouling agent using pediveliger larvae of the Pacific oyster Crassostrea gigas. The 96 h-LC50 of the agent was determined to be 0.81 mg/L, and exposure to 1.68 mg/L achieved complete larval settlement inhibition without inducing significant acute toxicity. Transcriptomic analysis identified 791 differentially expressed genes, dominated by downregulated genes associated with ribosomal function, translation, cell adhesion, and cytoskeletal organization. The agent exerts its inhibitory effect primarily through the global suppression of protein synthesis, disruption of cell-substrate adhesion and cytoskeletal integrity, and induction of proteotoxic stress responses. These findings reveal a multi-pathway molecular mechanism underlying antifouling agent-induced settlement inhibition in oyster larvae and provide key molecular biomarkers to support the development of eco-friendly antifouling technologies.

Animals

Strategies for mosaic variant calling in brain disorders.

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

Humans

The Factors That Contribute to Dysfunctional Behavior in Active Military Personnel: An Umbrella Review.

Dysfunctional behavior in active military personnel is a complex and challenging issue for military forces worldwide. Effective management of this issue requires a comprehensive understanding of the factors that contribute to dysfunctional behavior in military populations. The current study presents an umbrella review that synthesized and analyzed the existing literature on contributory factors to dysfunctional behavior in active military personnel using a systems thinking-based framework. Eleven systematic reviews were identified as eligible for inclusion in the umbrella review. The synthesis identified 14 contributory factors to the following types of dysfunctional behavior: suicidal behavior, substance misuse, domestic violence perpetration, and destructive leadership. The analysis indicated that existing literature focuses on contributory factors relating to the military personnel themselves and not influences in the broader military system or wider society. Additionally, few studies have sought to understand how factors interact to create dysfunctional behavior. Future research would benefit from the use of systems thinking-based frameworks and methods to investigate the factors, across the broader military system and society, that contribute to dysfunctional behavior in active military personnel.

Humans

The present and future of nonviral delivery-based genome editing for hereditary hearing loss.

PURPOSE OF REVIEW: This review summarizes nonviral genome-editing delivery platforms for hereditary hearing loss, focusing on lipid nanoparticles (LNPs) and engineered virus-like particles (eVLPs), and discusses their advantages over adeno-associated virus-based delivery, as well as the barriers to clinical translation. RECENT FINDINGS: Recent advances have established LNPs as a clinically advanced nonviral platform, although challenges related to inner ear biodistribution, cell type specificity, endosomal escape, and immunogenicity remain to be addressed. In parallel, eVLPs have undergone substantial technical evolution, progressing from early low efficiency systems to advanced base editor- and prime editor-eVLP architectures that enhance cargo loading and editing efficiency. Extracellular vesicle-based genome editing has also emerged as an additional platform, although issues related to reproducibility, loading efficiency, and scalability remain major hurdles. SUMMARY: Nonviral genome editing platforms expand the therapeutic toolkit for hereditary hearing loss by enabling transient delivery of genome editors with potential safety advantages. Future efforts should focus on characterizing biodistribution and immunogenicity, refining cell type-specific tropism, and establishing scalable manufacturing processes to enable successful clinical translation.

Humans

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon sources, particularly for hydrophobic carbon sources, coupled with robust growth and diverse biosynthetic capacities, making them promising hosts for sustainable production of chemicals, fuels, and proteins. Despite these advantages, industrial deployment of Candida species has been hindered by concerns regarding opportunistic pathogenicity and the historical lack of efficient genetic manipulation tools, leading to a substantial gap between metabolic potential and practical utilization. Recent advances in functional genomics, genome editing, and systems metabolic engineering are rapidly overcoming these barriers, enabling more precise and efficient strain development. In this review, we systematically summarize recent progress in the metabolic engineering of Candida species as microbial cell factories, with particular emphasis on expanding genetic toolkits, utilizting renewable and non-conventional carbon sources, and biosynthesizing high-value compounds. In addition, we propose a biosafety-oriented classification framework to support their safe industrial deployment. Finally, we discuss current challenges and emerging opportunities, emphasizing that the synergy of synthetic biology and artificial intelligence-driven design holds the key to unlocking the biotechnological potential of Candida yeasts.

Candida

Cationic porphyrin covalent organic framework reinforced hydroxypropyl methylcellulose films for photodynamic-photothermal sterilization and food preservation.

Microbial contamination in food necessitates effective antimicrobial packaging. While cellulose-based packaging materials suffer from limited antimicrobial efficacy, lack of active functionality, and susceptibility to inducing microbial resistance. To address these challenges, this study synthesized a cationic porphyrin-based covalent organic framework (Por-ICOF) as a multimodal photosensitizer. Por-ICOF was uniformly dispersed via non-covalent interaction within hydroxypropyl methylcellulose (HPMC), creating an HPMC/Por-ICOF composite film. This integration enhanced mechanical strength (increased by 26%), hydrophobicity (WCA 71°), and gas barrier properties (OP reduced by 42%, WVP reduced by 36%). Under visible light, the HPMC/Por ICOF film superior absorption generated reactive oxygen species (ROS) and photothermal effects, inactivating 99.2% of Escherichia coli and 99.95% of Staphylococcus aureus within 20 min. The composite film exhibited excellent biocompatibility and effectively extended the shelf life of strawberries. This cationic modification strategy for cellulose-based films offers a novel avenue for the design of high-performance antimicrobial food packaging materials.

Food Preservation

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

Self-healing materials for food packaging: Design principles, activation mechanisms and implications for food safety.

Self-healing materials (SHMs), originally developed to restore mechanical integrity, have recently attracted growing interest in food packaging. By autonomously repairing physical damage, SHMs help preserve packaging integrity, barrier performance, food safety, and shelf-life during storage and transportation. This review summarizes recent advances in the design principles, activation mechanisms, material systems and food packaging applications of SHMs. Key healing strategies, including microencapsulation, dynamic covalent bond exchange, reversible non-covalent interactions and responsiveness to external stimuli such as temperature, pH, and humidity, are discussed. Representative material systems, including biopolymer-based films, hydrogels, nanocomposites, and stimuli-responsive polymers are evaluated with respect to their relevance to packaging animal-derived foods, fruits, and vegetables. Performance evaluation methods, sustainability implications, and food-contact safety concerns are addressed. Despite promising healing efficiency and mechanical resilience, challenges remain regarding production cost, food-grade safety, migration risks, trigger compatibility and stability under fluctuating environmental conditions. Future research should focus on scalable manufacturing, standardized evaluation protocols, repeated damage-healing safety assessment, regulatory compliance, and integration with intelligent packaging technologies.

Food Packaging

PGPR inoculation and growth enhancement of crops cultivated in hydroponic systems.

Plant growth-promoting rhizobacteria (PGPR) are ubiquitous rhizosphere microorganisms that promote plant health through various mechanisms. Although the study of PGPR inoculants in soil has been done for ages, their application in hydroponic systems has received relatively limited attention. This review identifies PGPR inoculants that are commonly used in hydroponics, methods of application, and their effects on plant growth and nutrient use efficiency. Literature shows that PGPR inoculants improve plant performance in controlled hydroponic systems through the production of growth-stimulating substances, nitrogen fixation, and improved nutrient acquisition. However, the plant growth responses are highly variable depending on the composition of nutrient solutions, environmental factors, crop and microbe species, and the type of hydroponic system. The review identifies various challenges of PGPR inoculation in hydroponic systems and future research directions to address the current gaps. Generally, the productivity of hydroponic systems can be enhanced through advanced inoculation strategies and the development of suitable carrier materials to improve inoculant survival, viability, and functions. Emphasis should also be placed on designing system-specific microbial consortia and Synthetic communities that are tailored to the unique ecological conditions of hydroponic systems.

Hydroponics

Exploring determinants of vaccine hesitancy among healthcare professionals: a systematic literature review.

INTRODUCTION: This systematic review aims to assess determinants of vaccine hesitancy (VH) among healthcare professionals, to identify knowledge gaps and inform targeted training programs. RESEARCH DESIGN AND METHODS: A systematic search of PubMed and Scopus was conducted in February 2024. PRISMA criteria were applied, and methodological quality was assessed using a cross-sectional study evaluation tool. Studies addressing HCWs' VH determinants, including knowledge, attitudes, communication, and organizational factors, were included. RESULTS: Out of 1394 records, 221 articles were included. Reported prevalence of VH among HCWs varied across studies, reflecting differences in professional roles, settings, and vaccines studied. Key determinants included gaps in knowledge, personal beliefs, organizational barriers, and communication skills. The review highlights the importance of evidence-based information, continuing education, and effective communication in addressing VH among HCWs. CONCLUSIONS: Educational and organizational interventions are essential to improve HCWs' knowledge, attitudes, and practices regarding vaccination. Strengthening vaccine education, fostering effective communication, and addressing organizational challenges can reduce hesitancy and support HCWs in promoting vaccination among patients. Future initiatives should consider the diversity of educational settings, professional roles, and training requirements across healthcare systems.

Humans

Oxidative potential of fresh vs. O₃-aged PM2.5 across urban and rural sources in China.

Fine particulate matter (PM2.5) is a major health risk, yet its impacts are still largely assessed using mass concentration, which does not capture toxicity. Recently, oxidative potential (OP) has emerged as a more relevant metric, reflecting the ability of particles to generate reactive oxygen species. A current challenge, especially in China, is understanding how emission sources and ozone (O3) aging affect PM2.5 toxicity, given that O3 is an increasingly important pollutant there. A work by Ma and co-workers published in J. Environ. Sci. (doi.org/10.1016/j.jes.2024.04.023) addressed this by evaluating the OP of fresh and O3-aged PM2.5 from multiple sources in China using the dithiothreitol (DTT) assay. Biomass burning particles exhibited the highest OP, up to 35 times greater than suburban PM2.5, driven by water-soluble organics and transition metals. While O3 aging generally reduced OP, it also induced complex chemical transformations. These findings highlight that PM2.5 toxicity is dynamic and source-dependent, underscoring the need to move beyond mass-based air quality metrics.

Particulate Matter

A chromosome-level, haplotype-resolved genome assembly for the barn owl, Tyto alba.

Recent advances in long-read sequencing have enabled near telomere-to-telomere (T2T) assemblies across diverse taxa. However, avian genomes remain challenging due to numerous microchromosomes, small, typically < 20Mb, DNA molecules that are gene-, GC-, and repeat-rich. As a consequence, microchromosomes are often missing from genome assemblies. Here, we present a chromosome-level, haplotype-resolved genome assembly for the Western barn owl (Tyto alba). Using a trio-binning strategy with Illumina parental reads combined with PacBio HiFi and Oxford Nanopore Technologies data, we generated two phased contig sets. These were scaffolded into 40 linkage groups using a linkage map. Comparative analyses identified unplaced HiFi scaffolds corresponding to microchromosomes, which we integrated into six additional microchromosomes using long reads information. The two assemblies present 46 chromosomes, matching the karyotype of the species. They exhibit strong synteny between parental haplotypes, except for a &#x223c;38 Mb complex region on chromosome 7 containing nested inversions. This high-quality reference provides a haplotype-resolved and chromosome-level genome for Strigiformes, enabling fine-scale studies of structural variation and avian genome evolution.

Tyto alba

The hidden threat from food-derived carbon dots: Formation, biodistribution, and potential health risks.

Food-derived carbon dots (CDs) are a new class of carbon-based nanoparticles generated during the thermal processing of food matrices. These nanomaterials have been extensively studied for their unique fluorescence, good biocompatibility, and tunable surface chemistry in food detection, intelligent packaging, and biomedical applications. However, their nanoscale size and high surface activity have raised safety concerns regarding biological interactions, in vivo biodistribution, and potential long-term health hazards. Although CDs have traditionally been regarded as low-toxicity materials due to their favorable biocompatibility, the potential hidden risks of CDs have not received sufficient attention. CDs exhibit dose-dependent toxicity, not only accumulating in various tissues and organs but also potentially inducing oxidative stress and interfering with cellular metabolic functions. Therefore, this review summarizes the advances in sources, synthetic strategies, and core properties of CDs, with a special focus on in vivo biological interactions, fates, and potential safety challenges. In addition, it is proposed that the standardized detection and risk assessment system should be established to further explore the long-term health effects of CDs under real dietary exposure, thereby ensuring their safety and sustainable application.

Carbon Quantum Dots

Emerging techniques of CRISPR/Cas system in antiviral therapy and diagnostics: Applications, limitations, and translational perspectives.

The CRISPR/Cas (clustered regularly interspaced short palindromic repeats) system is a versatile technology for developing antiviral medicines and editing viral genomes in both diagnostics and vaccine synthesis. Emerging insights into class 2 effectors, such as Cas9, Cas12, and Cas13, which target viral DNA and RNA, have revolutionized vaccines against viruses such as HIV, HPV, HBV, and EBV. Innovative diagnostic techniques such as SHERLOCK, DETECTR, and FELUDA have demonstrated system's diversity and accuracy in detecting the virus markers, supporting clinical decision-making, indicating adaptability and precision of CRISPR. This review critically evaluates CRISPR's role in RNA editing, emphasizing its importance for functional genomics and development of recombinant vaccines. Translational challenges are critically discussed, including off-target effects, delivery limitations, and ethical issues, for which unique approaches such as high-fidelity Cas variants, non-viral delivery systems, and bioethical frameworks are evaluated to address these limitations. This review also covers other social implications, such as accessibility and biosecurity risks, associated with CRISPR technologies Collectively, these advances underscore the transformative potential of CRISPR technologies in shaping next-generation antiviral diagnostics and therapeutics.

CRISPR-Cas Systems