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Intestinal content accelerates muscle protein degradation in red shrimp (Solenocera crassicornis) during refrigeration: Insights from metagenomics and metabolomics.

This study systematically explored the effects of intestinal components on muscle quality deterioration and protein degradation of red shrimp during refrigerated storage. The results demonstrated that refrigeration induced continuous quality degradation and muscle protein breakdown in red shrimp, whereas eliminating intestinal tissues effectively retarded muscle spoilage and protein degradation, and optimized muscle texture. The intestinal microorganisms could secrete extracellular proteases to promote muscle protein degradation were primarily Vibrio, Bacillus, Pseudomonas, Photobacterium, and Shewanella. These microorganisms promote protein degradation by secreting zinc proteases, serine proteases, and aspartyl proteases. This study elucidates the molecular mechanisms of intestinal microbial metabolism influences the muscle protein degradation of red shrimp during refrigeration. The findings provide a theoretical foundation for precise regulation of intestinal-targeted microorganisms, thereby maintaining optimal quality of shrimps during refrigeration.

Animals

Integrative genomic and transcriptomic analyses identify key regulators of skin pigmentation in Larimichthys crocea.

The yellow body coloration of large yellow croaker (Larimichthys crocea) constitutes a crucial economic trait, yet its underlying genetic regulatory mechanisms remain poorly understood. This study systematically elucidated the molecular basis of body color variation by integrating genome resequencing and skin transcriptome analyses, combined with the contextual analysis of key pigmentation-related genes and phenotypic histological validation. 200 phenotyped individuals (including yellow-selected lines, F1 progeny, and normal control groups, all derived from a well-characterized aquaculture stock) identified 39 significantly associated SNPs (-log₁₀(P) ≥ 6), mapping to multiple candidate genes. These genes were significantly enriched in pathways related to pigment deposition (GO:0033059), melanosome organization (GO:0032438), melanogenesis, and tyrosine metabolism. Cross-developmental stage transcriptome analysis revealed 2395 differentially expressed genes (DEGs). Multi-omics integration identified eight overlapping candidate genes, including tyrp1, slc45a2, oca2, and dgat2, among which tyrp1 was prioritized for in-depth validation based on its core regulatory role in eumelanin synthesis, significant SNP association signal, and consistent downregulation in transcriptomic data. Experimental validation demonstrated that the g.895C > T mutation in exon 2 of tyrp1b was strongly significantly associated with the yellow phenotype: the frequency of mutant genotypes (TT/CT) reached 92.86%in the yellow-selected group, whereas the control group exclusively exhibited the wild-type genotype (CC). qPCR confirmed significantly downregulated tyrp1b expression in the skin of yellow individuals, consistent with the transcriptome trend. Histological and stereomicroscopic observations of skin tissues further validated the physiological basis of the yellow phenotype, revealing a significant reduction in melanophore number and abnormal melanosome morphology in yellow-phenotype individuals, accompanied by increased xanthophore density. These results suggest that tyrp1b mutation is strongly associated with the yellow phenotype. However, the presence of a wild-type CC individual in the yellow group indicates that this mutation is not strictly required for yellow coloration, suggesting that other genetic or environmental factors may also contribute to the phenotype, Additionally, downregulation of the carotenoid metabolism gene bco2 coupled with upregulation of xdh, together with the functional changes of slc45a2 and oca2, may synergistically promote xanthophore pigment deposition, contributing to the yellow phenotype. As melanin synthesis in large yellow croaker relies on the conserved tyrosinase pathway and transporter proteins, mutations in associated genes (tyrp1b, slc45a2, oca2) represent a primary underlying cause for the loss of melanin-based coloration and transition to a yellow phenotype in L. crocea. These findings provide key molecular targets and a theoretical foundation for molecular breeding of body color in this species, and also enrich the understanding of xanthism regulatory mechanisms in teleosts.

Animals

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models

Retinoid dynamics in immune cells during age-related diseases.

Retinoids comprise vitamin A and its structurally related natural and synthetic derivatives. Retinoid dynamics involves multiple retinoid forms, carrier proteins, and enzymes that orchestrate the absorption, transport, storage and biotransformation of dietary vitamin A. Beyond their canonical metabolic functions, metabolites and proteins involved in retinoid metabolism also play distinct roles in signal transduction and transcriptome reprogramming, broadening the mechanisms that influence immune cell fate decisions. Age‑related changes in retinoid bioavailability and signaling intensity alter immune cell polarization and function, thereby contributing to the pathogenesis of chronic inflammation in neurodegenerative diseases, cardiovascular diseases, osteoarthritis, and other age-related diseases. In this review, we focus on age-related alterations in the retinoid metabolic pathway and their impact on inflammation and the progression of age-related diseases. This review highlights the pivotal role of retinoid metabolism in anti-ageing interventions and considers future directions and challenges in this field.

Humans

Trade-offs in avian parental care: a review of theory and meta-analysis of brood size manipulations.

The selective forces shaping parental care have been studied for over 50 years. While theoretical and experimental work has yielded qualitative progress, the large body of empirical work testing predictions about parental investment based on life-history trade-offs has yet to be synthesized. We first provide an overview of the core life-history theory exploring how selection might shape parental care. We then conduct a systematic review and meta-analysis on studies that experimentally manipulated brood size in birds, a widely used experimental approach to manipulate parental investment. We extracted 313 estimates from 62 studies representing 31 species of birds from 19 different families and tested key predictions on trade-offs in parental care derived from theory. Our analysis provides strong support for some predictions about life-history trade-offs in parental care, but weak or equivocal support for others. Specifically, we found that overall, avian parents respond to brood size manipulations as predicted by life-history theory: they increased care in response to brood enlargement, and decreased care in response to brood reductions. Furthermore, for the same relative manipulation size, responses to brood reductions were greater than responses to brood enlargements. This finding is consistent with predictions derived from life-history theory based on some types of non-linear utility curves. However, many predictions derived from theory are not well supported by our comparative analysis. Species' life-history traits such as clutch size (a measure of current reproduction), adult survival, and broods per year (two measures of future reproduction), explained little, if any, among-species variation in response to brood size manipulations. Several factors may explain this. We highlight that brood size manipulations may affect more than just perception of the value of current reproduction, such as altering parents' perception of predation risk. Importantly, these unintended consequences could lead to asymmetric responses like those we observed. Other common experimental approaches - such as hormone manipulations, altering a partner's effort, and food supplementation - often affect multiple traits or fitness components simultaneously, or may involve cues that poorly match the evolved mechanisms guiding parental behaviour. Our review of both theory and experimental approaches suggests that there are multiple opportunities for more precise experiments. We offer several recommendations for effective designs. One is improved understanding of the biology underlying the functions relating to costs and benefits, with careful consideration of not only how the manipulation will affect only one of those, but also the mechanisms that might alter how parents perceive the manipulation. We also emphasize general principles, such as assessing alternative hypotheses and devising multiple independent tests. Armed with these recommendations, we believe there are new opportunities to increase the strength of inference achieved from studies aimed at understanding the trade-offs affecting the evolution of parental care.

Animals

O'nyong-nyong virus adaptive mutations in non-structural protein 1 and 3 enhance RNA replication and overcome FHL1 requirement.

Arthritogenic alphaviruses, like o'nyong-nyong virus (ONNV), cause debilitating musculoskeletal diseases and are geographically expanding. To predict their emergence, we seek to better understand evolutionary mechanisms that enable changes in virus tropism. Here, we identify adaptive mutations in the ONNV non-structural proteins (nsPs) that arose during cellular serial passaging and enabled ONNV to infect non-permissive Lunet cells. Using shotgun proteomics, we show that this human hepatoma cell line lacks the four-and-a-half-LIM domain protein 1 (FHL1), an essential host factor in ONNV RNA replication. Individual single nucleotide mutations in the nsP1 ring-aperture membrane-binding and oligomerization domain, the nsP3 macrodomain, and the nsP3 opal stop codon overcome FHL1 deficiency in Lunet cells by enhanced RNA replication. These findings demonstrate how subtle genomic changes in nsPs can profoundly influence alphavirus replication and tropism.

LIM Domain Proteins

Liver transcriptome analysis revealed multiple immune processes and lipid metabolism pathways involved in the defense response of the turbot (Scophthalmus maximus) against Aeromonas salmonicida.

Aeromonas salmonicida is a significant pathogen causing notable economic losses in Scophthalmus maximus aquaculture. This study utilized Illumina sequencing technology to examine the transcriptional response characteristics of S. maximus liver at 24 h following A. salmonicida infection. A total of 2363 differentially expressed genes (DEGs) were identified when compared to the negative control group. The immunity-related Toll-like receptor signaling pathway, NOD-like receptor signaling pathway, as well as metabolism-related PPAR signaling pathway and insulin signaling pathway, were notably enriched. Significant differences exist in the expression of key genes within the PPAR pathway, particularly cd36, acsl4a, pparαa, and plin2, all of which mediate the interaction between lipid metabolism and the immune response. These results offer valuable insights into the immunometabolic regulatory mechanism of S. maximus response to A. salmonicida infection.

Animals

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves

Carboxyl group number and acidity of organic acids regulate structural reorganization and low glycemic index in cassava pyrodextrins via molecular interactions.

Transforming high-glycemic cassava starch into functional dietary fiber via pyrodextrinization is a promising way to valorize tuber crops, yet the molecular mechanisms catalyzed by organic acids with different carboxyl numbers and acidity remain unclear. This study investigates how carboxyl number and acidity of acetic acid (AA), tartaric acid (TA), and citric acid (CA) affect structural reorganization and low glycemic properties of cassava pyrodextrins. Compared with AA, TA, and CA with stronger acidity and more carboxyl groups promoted more extensive hydrolysis, transglycosylation, repolymerization, and esterification. These changes increased indigestible glycosidic linkages and the branching degree, while reducing molecular weight. Molecular docking confirmed stronger hydrogen-bonding interactions between TA/CA and starch chains. Furthermore, TA- and CA-catalyzed pyrodextrins exhibited superior anti-digestive properties with resistant starch up to 54.26% and an estimated glycemic index as low as 42.46, highlighting the critical role of carboxyl numbers and acidities in modulating the functionality of pyrodextrins.

Manihot

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

Single nucleus multiomics reveals an early inflammatory response to high-fat diet in mouse islets.

In periods of sustained hyper-nutrition, pancreatic β-cells undergo functional compensation through transcriptional upregulation of gene programs driving insulin secretion. This adaptation is essential for maintaining systemic glucose homeostasis and metabolic health. Using single nuclei multiomics, we have mapped the early transcriptional adaptive mechanisms in murine islets of Langerhans exposed to high-fat diet (HFD) for 1 and 3 wk. We show that β-cells exhibit the largest transcriptional response to HFD, characterized by early activation of pro-inflammatory eRegulons and down-regulation of β-cell identity genes, particularly in a distinct subset of β-cells. These observations extend to humans, where the prevalence of an β-cells with a high inflammatory signature is increased in diabetes. Collectively, these observations point to cellular crosstalk through pro-inflammatory signaling as a central and early driver of β-cell dysfunction that limits the compensatory capacity of β-cells, which is closely linked to the development of diabetes.

Animals

Furanic compounds in different coffee extraction systems: Analysis of the main influencing factors and correlation with acrylamide.

This study investigates how different coffee types representative of distinct roast profiles and brewing methods jointly affect the occurrence of furanic compounds and acrylamide in brewed coffee. Coffees were prepared using eight extraction methods (AeroPress, Clever, Chemex, French Press, Moka, Pure Brew, Turkish and V60). Five furanic compounds (furfural, furfuryl acetate, 5-methylfurfural, furfuryl alcohol and 5-hydroxymethylfurfural) were quantified in coffee powders and brews by HS-SPME-GC-MS, while acrylamide was determined by UHPLC-MS/MS. Moka and Turkish brews consistently exhibited the highest concentrations of furanic compounds, whereas paper-filtered pour-over methods (V60 and Chemex) showed the lowest levels. Pearson correlation analysis revealed coffee-dependent relationships between furanic compounds, acrylamide and extraction parameters with the strongest associations observed in dark-roasted coffee, reflecting advanced Maillard reaction chemistry. Overall, these results demonstrate that contaminant levels arise from the combined effects of intrinsic coffee chemistry and brewing mechanics and support targeted mitigation strategies: such as roast selection and brewing method optimization.

Acrylamide

Integrated metabolomic, transcriptomic, and proteomic analyses reveal changes in the non-volatile metabolite profile of LED light-withered oolong tea.

LED light withering is a crucial method for overcoming weather limitations and enhancing the quality of oolong tea. To elucidate the underlying molecular mechanisms, this study simulated solar spectra using multiwavelength LED light and compared the resulting metabolic, transcriptomic, and proteomic profiles during the enzymatic-catalysis process (ECP) in oolong tea processing. Results indicated that LED light withering altered gene expression and protein regulation of secondary metabolism, particularly in the flavonoid biosynthesis pathway. These shifts encompassed key quality-related compounds, including flavonoids (quercetin-3-O-rhamnoside, dihydroquercetin), amino acids (L-asparagine, L-histidine), guanosine 5'-monophosphate (GMP), and carbohydrates. Furthermore, LED light withering accelerated tea leaf water loss, influenced gene expression involved in photosynthetic cellular components (chloroplasts, thylakoids), increased ascorbate peroxidase regulation under stress, and subsequently modulated energy metabolism and signal transduction in tea leaves. This study offers molecular theoretical framework for the controlled light-withering of oolong tea under bad weather and the associated improvements in its quality.

Camellia sinensis

Integrated widely targeted metabolomics and GC-IMS reveal dynamic flavor, nutritional, functional, and metabolic profiles in macadamia kernels during processing.

Different processing stages influence the color, flavor, and antioxidant activities of macadamia kernels. However, the biochemical mechanisms that occur during processing are not well known. This study integrated widely targeted metabolomics (UPLC-MS/MS) with GC-IMS to systematically characterize non-volatile and volatile compounds in macadamia kernels across key three sample groups: fresh kernels (FMN), low-temperature-dried kernels (DMN), and roasted kernels (BMN). A total of 622 non-volatile metabolites and 52 volatile compounds were identified. Low-temperature drying promoted the accumulation of phenolic acids and flavonoids, enhancing antioxidant capacity. Roasting degraded heat-sensitive nutrients but generated flavor compounds via Maillard reaction and lipid oxidation, shifting aroma from green to nutty notes. Nutritional assessment confirmed that roasting significantly reduced antioxidant activities and bile acid binding capacity. Pearson correlation analysis verified the key metabolite-antioxidant relationships. These findings provide critical insights into metabolic dynamics during nut processing and establish a scientific basis for optimizing thermal processing strategies.

Metabolomics

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

Enhancement flavor quality in Zhao'an Baxian oolong tea through enhanced turning-over process.

A systematical investigation on the effects of turning-over intensity on the flavor formation of Zhao'an Baxian oolong tea (ZBT) was performed, through a comparative analysis of heavy turning-over (HT) and light turning-over (LT) treatments in this study. The tea samples were subjected to proteomic and metabolomic analyses, combined with quantitative descriptive analysis (QDA) and electronic sensory (E-tongue/E-nose) evaluation. The results demonstrate that HT significantly reduced the content of bitter and astringent compounds, such as catechins and flavonol glycosides, while promoting the accumulation of umami-related amino acids. Concurrently, HT enhanced the biosynthesis of key floral and fruity volatiles, such as β-ocimene, geraniol, benzaldehyde, jasmone by activating stress-responsive metabolic pathways. These coordinated biochemical changes, driven by enzyme-catalyzed reactions in response to prolonged mechanical wounding and environmental stress, collectively improved the overall sensory profile of ZBT. These findings provide a mechanistic foundation for improving ZBT production, with clear implications for quality control and flavor-oriented product development.

Tea

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

Molecular adaptation of caspase genes to salinity stress in the tropical sea cucumber Stichopus monotuberculatus: A comparative analysis across echinoderms.

Apoptosis is an essential physiological process that plays a critical role in development and tissue homeostasis. Caspases, as central regulators of apoptosis, are crucial in controlling inflammation and cell death. In this study, we investigated the caspase gene family in Stichopus monotuberculatus to explore their potential roles in salinity stress adaptation. Five caspase genes were identified from the genome of S. monotuberculatus, including Smcaspase3, Smcaspase6, Smcaspase8a, Smcaspase8b, and Smcaspase8c. Phylogenetic analysis revealed that these Smcaspase genes clustered into distinct caspase subfamilies and showed high conservation with homologs from other echinoderms and representative vertebrates. Conserved motif and gene structure analyses showed relatively similar structural patterns within each clade, whereas divergence was observed among different subfamilies. Promoter analysis identified numerous cis-acting elements related to gene regulation, immune response, and growth and development. Expression profiling under salinity stress showed that Smcaspase8a was significantly upregulated, particularly under prolonged stress, whereas the other genes exhibited limited transcriptional responses. Our findings highlight caspase function in salinity stress and provide the foundation of molecular salinity adaptation mechanisms in S. monotuberculatus.

Animals