Persistent organosulfur compounds in mid‑distillate fuels sturdily resist hydrodesulfurization (HDS), prompting for biological routes that cleave C-S bonds while retaining the hydrocarbon backbone. This review surveys aerobic biodesulfurizationwith emphasis on the 4S pathway, integrating the latest advances across Rhodococcus (wild‑type performance, regulation, systems biology, and genetic engineering) and Gram‑negative platforms (especially Pseudomonas) where operon refactoring and chassis design have converged with process‑level constraints. We discuss regulatory logic (sulfur source repression, genetic regulators), operon architecture (gene order, translational tuning, chromosomal integration), cofactor logistics, transport and product inhibition (2-hydroxybiphenyl), and biphasic reactor operation (interfacial area, oxygen transfer, kinetics). We conclude with integration strategies with HDS and research priorities required to close the gap towardcommercial deployment.

Shaping Aspergillus niger into a next-generation cell factory for L-malic acid.

From toxin to biofuel: engineering microbes for methanol biomanufacturing.

Transcriptional and Pathway Level Heterogeneity in Luminal A Breast Cancer: A Framework for Precision Therapy.

Multi-omics biomarkers in psychiatric disorders diagnosis and stratification.

NRF2-KEAP1 as a Redox Signal-Resolution Circuit: Beyond the Antioxidant Switch.

Oxylipin profile data analysis: Current methodologies, challenges, and future directions.

Exercise-induced muscle damage (EIMD) has classically been attributed to localized mechanical disruption following eccentric contractions. Emerging evidence, however, indicates that EIMD represents a systems-level failure of stress integration within skeletal muscle rather than a purely mechanical lesion. Mechanical loading initiates disturbances in intracellular Ca2+ homeostasis, which interact with metabolic stress, redox imbalance, and immune activation to form self-reinforcing feedback loops. When compensatory capacity is exceeded, transient injury may shift toward maladaptive remodeling marked by mitochondrial dysfunction, ferroptosis, chronic inflammation, and impaired regeneration. Recent studies identify reactive oxygen species accumulation, iron-dependent lipid peroxidation, dysregulated energy sensing, and aberrant immune polarization as key molecular tipping points governing injury reversibility. Beyond their regenerative role, satellite cells act as integrators of metabolic history and epigenetic memory, linking repetitive injury to reduced muscle adaptability, age-related sarcopenia, and heightened metabolic disease risk. Here, we synthesize evidence from animal models, clinical studies, and multi-omics analyses to establish a systems biology framework for EIMD. We delineate the spatiotemporal interactions among mechanical, metabolic, oxidative, immune, and regenerative modules; identify regulatory nodes that determine adaptive repair versus pathological outcomes; and critically evaluate current nutritional, physical, pharmacological, and regenerative interventions from a mechanism-oriented perspective. Finally, we discuss how multi-omics, digital monitoring, and individualized rehabilitation may enable precision management of EIMD and advance understanding of muscle stress resilience and adaptive limits.

The plant holobiont comprises the host plant and its associated microbial communities functioning together as a single ecological and evolutionary unit that influences plant health, productivity, and environmental adaptability. Endophytes, formerly classified primarily as plant growth-promoting agents, are currently gaining traction as integral components of plant-associated microbiomes such as the rhizobiome and phytobiome. They can alter host-mediated root exudation patterns, microbial community structure, and nutrient dynamics within the rhizosphere. Endophytes play an important role in modulating host signaling pathways, thus influencing plant growth. Various mechanisms by which endophytes contribute to improved plant performance include soil microbiome dynamics, carbon sequestration, and strengthening the host's ability to tolerate abiotic stressors. Multi-omics, single-cell, and systems-level approaches integrated with CRISPR, metabolic engineering, and AI, together with systems biology, guided by in vitro and field studies, support predictive modeling and provide evidence for the evolution of system-driven strategies for developing effective bioinoculants. This review highlights the potential of endophytes to serve as a scalable and sustainable component of climate-resilient and regenerative agricultural systems, while acknowledging ecological variability and field-level constraints.

MT2A buffering exhaustion marks cuproptosis in severe COVID-19: Multi-omics integration, computational modeling, and experimental validation.

The production of Chinese Baijiu relies on the synergistic metabolism of multi-species microbial communities in an open environment. Its intricate microbial succession and flavor formation mechanisms have long been considered complex systems that are difficult to fully deconstruct. Traditional culture-dependent techniques inherently fail to comprehensively capture the actual functional roles and dynamic regulation of "viable but non-culturable" (VBNC) microorganisms within this complex system. In recent years, the rapid advancement of multi-omics technologies has offered a novel perspective for elucidating the underlying fermentation mechanisms of Baijiu. This paper systematically reviews the recent progress in the application of metagenomics, metatranscriptomics, metaproteomics, and metabolomics in Baijiu research. Specific focus is placed on the unique contributions of these tools to resolving microbial community structural diversity, mining key functional genes and enzymes, uncovering microbial stress response mechanisms under environmental fluctuations, identifying phages and spoilage microorganisms, and tracing the metabolic pathways of flavor substances. Furthermore, the pivotal role of multi-omics integration strategies in constructing "microbe-metabolite" regulatory networks is highlighted. Finally, current challenges regarding standardization and data integration are discussed, with an outlook on leveraging omics big data to promote digital monitoring and intelligent brewing in the Baijiu industry.

AI-driven multiscale virtual plant cell modeling represents a paradigm shift in plant systems biology, enabling predictive simulation from molecular mechanisms to tissue functions and accelerating the engineering of climate-resilient crops. AI-driven multiscale virtual plant cell modeling is emerging as a pivotal paradigm for deciphering complex biological processes in plants. By integrating dynamic processes across molecular, subcellular, and tissue scales, this framework enables systematic simulation from protein interaction prediction to emergent tissue functions, significantly enhancing our understanding of plant environmental responses and developmental mechanisms. This review comprehensively summarizes key technological advances in multiscale modeling, including neural network-assisted molecular interaction prediction, virtual plant tissue simulator construction, deep vision-based 3D reconstruction techniques, and cross-scale dynamic coupling algorithms. It highlights the application value of generative adversarial networks (GANs), transfer learning, and multi-omics integration strategies in addressing data scarcity and cross-species modeling challenges. The review also discusses validation methodologies such asin vitroexperimental verification, evolutionary conservation analysis, and uncertainty quantification. In applied contexts, multiscale modeling offers novel insights for plant metabolic engineering, developmental programming simulation, and stress response prediction, while identifying current bottlenecks in parameter transfer accuracy, model interpretability, and computational efficiency. Future directions, including quantum computing-enabled real-time simulation, agricultural digital twin systems, and brain-inspired autonomous models, are explored. The central role of AI technologies in transitioning plant systems biology from descriptive to predictive and engineering-oriented paradigms is emphasized.

Mapping the causal circuits that shape the phenotypic and functional landscape of immune cells remains a formidable challenge. Recent advances in pooled CRISPR-based screens, coupled with multiplexed single-cell profiling and imaging-based spatial readouts, make this goal increasingly attainable. In this Perspective, we discuss how CRISPR-based genetic screens will fundamentally transform our understanding of immunobiology. We highlight the applications of state-of-the-art, high-throughput pooled perturbation approaches, including emerging methodologies for bulk, single-cell, and spatial CRISPR screens, to advance our understanding of immunity and in vivo biology. Additionally, we summarize new strategies to address the complexity of combinatorial perturbations to uncover genetic interactions and mechanistic drivers of immunity at unprecedented scale and resolution. By integrating CRISPR screening data with experimental insights, we advocate a new framework in immunology research that leverages perturbation-driven regulatory effects and networks to discover new therapeutic targets and establish causal systems biology and immunology for advancing immunological knowledge and therapeutic application.

NAD⁺ as a central metabolic hub Regulating the hallmarks of aging: Mechanisms and therapeutic implications.

ABSTRACT Naphthalene, a widely detected polycyclic aromatic hydrocarbon (PAH), is among the 16 priority PAHs identified as major environmental hazards due to its persistence, ubiquity, and toxicity to ecosystems and human health. Its occurrence in crude oil, combustion residues, vehicle emissions, and household products highlights the urgent need for sustainable remediation strategies. Microbial‐based bioremediation stands out as an eco‐friendly and cost‐effective approach that harnesses the metabolic versatility of diverse microorganisms, their genes, and enzymes responsible for naphthalene degradation. Recent advances in omics technologies and high‐throughput sequencing have expanded our understanding of novel microbial taxa, metabolic pathways, and stress responses under naphthalene exposure. Complementarily, computational modelling, in silico tools, machine learning, and systems biology have enabled the prediction of degradation dynamics and the design of synthetic microbial consortia optimised for field use. Despite these advances, challenges such as environmental fluctuations, co‐contaminant effects, and the gap between laboratory and field outcomes remain. Overcoming these requires an integrative framework that connects microbial ecology, omics insights, and computational modelling. This review consolidates current knowledge on microbial degradation of naphthalene, emphasising key taxa, genes, and pathways, and highlights how omics, in silico tools and systems biology can drive sustainable remediation in the Anthropocene.

Integrative omics approaches for bioactive metabolite discovery in marine macroalgae: Recent advances and future perspectives.

Toward A Pre-disease State-centered New Paradigm in Multi-omics Research.

A 3-hit metabolic signaling model of the causes of autism spectrum disorder (ASD) is described. The 3-hits required for ASD are: 1) inheritance of a genotype that sensitizes mitochondria and/or eATP-stimulated, intracellular calcium signaling to environmental change, 2) early exposure to environmental triggers that activate the metabolic features of the cell danger response (CDR), and 3) recurrent or persistent exposure to CDR-activating triggers for at least 3-6months during the critical neurodevelopmental window from the late 1st trimester of pregnancy to the first 18-36months of life. The three hits associated with an increased risk of ASD can be functionally classified as primers, triggers, and amplifiers of the CDR, respectively. Since the CDR is maintained by metabolic signaling, this new model creates a unified intellectual framework for understanding how the diverse features of ASD are connected. The example of phenylketonuria (PKU) is given to show that even disorders with very strong genetic predispositions can follow this 3-hit developmental paradigm and still be treatable using the principles of metabolic signaling. Since the 2nd and 3rd hits are modifiable, this model predicts that if the children at greatest risk can be diagnosed and treated before symptoms occur, some of these children may never develop ASD, and if diagnosed after symptoms occur, the core symptoms that are most disabling can be decreased significantly.

DMDGRN: A data augmentation-based multilayer directed graph convolutional network for gene regulatory network inference.

Lipid metabolism: a molecular switch to control inflammation.