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Omics in hereditary optic neuropathies: A systematic review of clinical studies with an integrated point of view.

Hereditary optic neuropathies are characterized by bilateral visual loss due to the degeneration of retinal ganglion cells, resulting in optic nerve degeneration and atrophy. Although the genetic origin of the main isolated and syndromic hereditary optic neuropathies has been characterized, the clinical phenotypes exhibit significant and poorly understood variability in both penetrance and expressivity. Additionally, the genetic and environmental factors that influence the onset of these optic neuropathies remain poorly understood, with limited biomarkers to predict disease progression or as readouts for therapeutic trials. Data-driven omics strategies allow deep phenotyping to improve our understanding of pathophysiological mechanisms and to search for new biomarkers and therapeutic targets. We explore whether the omics strategies applied to patients with hereditary optic neuropathies have provided such new insights. MEDLINE, Web of Science and EMBASE databases were screened for studies with terms relating to hereditary optic neuropathies, transcriptomics, epigenomics, proteomics, metabolomics and lipidomics in clinical studies exploring patients' samples. Out of 1244 references identified, 22 articles were included after double-masked data curation. These articles focused only on the 3 main forms of hereditary optic neuropathies, namely, OPA1-related dominant optic atrophy (n = 4), Leber hereditary optic neuropathy (n = 13), and Wolfram syndrome (n = 5). While the methodological designs and results of these studies were highly heterogeneous, they revealed molecular alterations that we have attempted to discuss at the integrated multi-omics level. This data integration highlighted several common pathophysiological mechanisms such as energetic impairment, endoplasmic reticulum stress, proteotoxic and oxidative stresses, lipid remodeling and altered amino acid and purine metabolisms, while suggesting potential new biomarkers and therapeutic targets. These findings underscore the potential of integrated multi-omics approaches to deepen our understanding of the phenotypic complexity of hereditary optic neuropathies and to support the development of innovative diagnostic and therapeutic strategies.

Humans

Proteomic and phosphoproteomic profiles of time-dependent dynamic changes in LPS-induced macrophage polarization.

The temporal proteomic and phosphoproteomic reprogramming during early M1 macrophage polarization (0-6 h) remains poorly understood. We performed time-resolved proteomic and phosphoproteomic analyses of LPS-stimulated RAW264.7 macrophages at seven time points within 6 h. Time-clustering of differentially expressed molecules revealed two patterns: initial change with partial recovery, and sustained dysregulation. Upregulated proteins and phosphorylation sites were enriched in the Rho GTPase signaling pathway, T-cell receptor signaling pathway, NF-κB cascade, osteoclast differentiation pathway, and antiviral immune pathway. Downregulated pathways were associated with cell cycle regulation, chromatin remodeling, RNA metabolism, and mRNA processing, indicating resource reallocation to prioritize acute inflammatory responses. Kinase-substrate network analysis confirmed the mitogen-activated protein kinase (MAPK), cyclin-dependent kinase (CDK), protein kinase B (AKT), and ribosomal S6 kinase (RSK) families as core upstream phosphorylation regulators. Integrated analysis revealed synergistic and antagonistic relationships between proteomic and phosphoproteomic changes. This study provides a temporal molecular atlas of M1 polarization, delineating inflammatory signaling dynamics and offering a basis for therapeutic target discovery in inflammatory diseases. SIGNIFICANCE: Macrophage M1 polarization is a central event in innate immune defense against pathogenic invasion, yet its dysregulation is a pivotal driver of the onset and progression of a broad spectrum of inflammation-associated disorders, spanning autoimmune diseases, infectious conditions and inflammatory bone diseases, making the dissection of its molecular regulatory mechanisms an urgent research priority in immunology and translational medicine. Dynamic molecular events within 0-6 h after LPS stimulation are critical for initiating and shaping M1 inflammatory activation, yet systematic time-resolved proteomic and phosphoproteomic profiling remains insufficient.In this study, we comprehensively characterized temporal proteome and phosphoproteome changes at seven consecutive time points during macrophage polarization, clarified two distinct dynamic molecular patterns, identified core signaling pathways and key kinase regulators involved in inflammatory reprogramming, and uncovered the leading role of post-translational phosphorylation modifications in initiating polarization. This work delineates the time-series molecular atlas of early macrophage activation, provides novel insights into the temporal regulatory mechanism of inflammatory signaling networks, and lays a solid experimental foundation for exploring new intervention targets and regulatory nodes in clinical translational research.

Lipopolysaccharides

Congenital Laryngomalacia: Pathophysiology, Clinical Spectrum, and Holistic Management.

Congenital laryngomalacia is the most common cause of infant stridor and arises from interacting structural, neuromuscular, and inflammatory mechanisms that produce dynamic supraglottic collapse. Disease severity spans mild stridor to significant obstruction, aspiration, and failure to thrive, often influenced by comorbid medical conditions. Diagnosis relies on flexible laryngoscopy supported by instrumental swallowing studies and microdirect laryngoscopy and bronchoscopy when indicated. Most infants respond to conservative management, particularly targeted feeding modifications, while acid suppression offers benefit in selective cases. Supraglottoplasty provides effective, durable improvement for severe disease and significantly enhances infant outcomes and family quality of life.

Humans

Evaluation of the clinical and mechanistic role of MCM2 expression in the prediction of meningioma recurrence after radiotherapy.

OBJECTIVE: Postoperative radiotherapy is an effective treatment for meningiomas; however, treatment response varies among patients. In addition, practical methods for predicting tumor recurrence after radiotherapy have not been well established. Minichromosome maintenance protein 2 (MCM2), a key regulator of DNA replication licensing, was recently implicated in highly proliferative molecular subtypes of meningioma. In this study, the authors evaluated whether MCM2 immunohistochemical expression predicts response to radiotherapy in patients with meningiomas. METHODS: The authors retrospectively analyzed the records of patients with WHO grade 1-3 meningiomas treated with resection followed by radiotherapy at a single institution between July 2003 and November 2023. The MCM2 labeling index was assessed immunohistochemically, and patients were stratified into MCM2-high and -low groups using a cutoff of 35%. Progression-free survival (PFS) was defined as the interval from the completion of radiation therapy to postoperative radiological tumor recurrence or regrowth. Patients who showed no progression were censored at their last follow-up. PFS was estimated using Kaplan-Meier analysis and subsequently evaluated with Cox proportional hazards models. To further investigate the biological mechanisms associated with MCM2 expression, comprehensive transcriptomic analyses, including gene set enrichment analysis, was performed to elucidate the molecular processes that occur within MCM2-high tumors. RESULTS: The study population included 15 men (42%) and 21 women (58%), with a mean age of 63 years. Ten tumors (28%) were classified as MCM2-high meningiomas and 26 (72%) as MCM2-low meningiomas. High MCM2 expression was significantly associated with WHO grades 2-3 histology and higher Ki-67 labeling indices. During a median follow-up of 2.52 years, tumor progression after radiotherapy occurred in 47% of the patients. High MCM2 expression (HR 8.34, p = 0.03) was significantly associated with shorter PFS and remained an independent predictor of recurrence after adjustment for WHO grade, tumor size, and Ki-67 labeling index. Transcriptomic analyses of MCM2-high tumors revealed upregulation of cell proliferation-related pathways, accompanied by increased signaling through the E2F8-CHEK1 axis associated with radiation resistance and suppression of the TNF-α signaling pathway implicated in radiosensitivity. CONCLUSIONS: In meningiomas, high MCM2 expression is associated with early recurrence following radiotherapy. The study findings suggest that this association is driven by diverse biological mechanisms related to cell cycle regulation and radioresistance. Immunohistochemical assessment of MCM2 expression may serve as a practical and accessible biomarker for risk stratification and may support the future development of individualized postoperative radiotherapy strategies.

Humans

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

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

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 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