Search Results (521)

Root-knot nematode (Meloidogyne incognita) is a globally destructive plant-parasitic nematode that severely impedes the sustainable production of horticultural crops. Metabolic reprogramming in plant roots represents the host response to M. incognita infection that can also be exploited by the nematode to facilitate its parasitism. In this study, untargeted metabolomics was employed to analyze metabolic changes in cucumber roots following nematode inoculation, with the goal of identifying differentially accumulated metabolites that may influence M. incognita behavior. Metabolomic analysis revealed that M. incognita significantly altered the cucumber root metabolome, triggering an accumulation of lipids and organic acids and enriching biotic stress-related pathways such as alkaloid biosynthesis and linoleic acid metabolism. Among differentially accumulated metabolites, myristic acid and hexadecanal were selected for further study due to their potential roles in nematode inhibition. In vitro assays demonstrated that both metabolites suppressed egg hatching and reduced infectivity of M. incognita, while pot experiments indicated a correlation between their application and reduced root gall formation. Chemotaxis assays further revealed that both metabolites exerted repellent effects on the chemotactic migration of M. incognita J2 and suppressed the transcriptional expression of two motility-and feeding-related neuropeptides, Mi-flp-1 and Mi-flp-18. In conclusion, this study demonstrates the significant potential of differentially accumulated metabolites induced by M. incognita infection for nematode disease control, achieved by interfering with nematode chemotaxis and subsequent infection. This work also provides deeper insights into the metabolomic mechanisms underlying the cucumber-M. incognita interaction. Full article

Legumes are vital sources of protein, dietary fibre and nutrients, making them crucial for global food security and sustainable agriculture. However, their widespread acceptance and consumption are often limited by undesirable sensory characteristics, such as “a beany flavour”, bitterness or variable textures. Addressing these challenges requires a comprehensive understanding of the complex molecular mechanisms governing appearance, aroma, taste, flavour, texture and palatability in legumes, aiming to enhance their sensory appeal. This review highlights the transformative power of multi-omics approaches in dissecting these intricate biological pathways and facilitating the targeted enhancement of legume sensory qualities. By integrating data from genomics, transcriptomics, proteomics and metabolomics, the genetic and biochemical networks that directly dictate sensory perception can be comprehensively unveiled. The insights gained from these integrated multi-omics studies are proving instrumental in developing strategies for sensory enhancement. They enable the identification of key biomarkers for desirable traits, facilitating more efficient marker-assisted selection (MAS) and genomic selection (GS) in breeding programs. Furthermore, a molecular understanding of sensory pathways opens avenues for precise gene editing (e.g., using CRISPR-Cas9) to modify specific genes, reduce off-flavour compounds or optimise texture. Beyond genetic improvements, multi-omics data also inform the optimisation of post-harvest handling and processing methods (e.g., germination and fermentation) to enhance desirable sensory profiles and mitigate undesirable ones. This holistic approach, spanning from the genetic blueprint to the final sensory experience, will accelerate the development of new legume cultivars and products with enhanced palatability, thereby fostering increased consumption and ultimately contributing to healthier diets and more resilient food systems worldwide. Full article

Vegetable oils are essential for human nutrition and industrial applications. With growing global demand, increasing oil content in oilseed crops has become a top priority. This review synthesizes recent progress in understanding the genetic, environmental, and molecular mechanisms regulating oil content, and presents biotechnological strategies to enhance oil accumulation in major oilseed crops. Oil biosynthesis is governed by intricate genetic–environmental interactions. Environmental factors and agronomic practices significantly impact oil accumulation dynamics. Quantitative trait loci (QTL) mapping and genome-wide association studies (GWAS) have identified key loci and candidate genes involved in lipid biosynthesis pathways. Transcription factors and epigenetic regulators further fine-tune oil accumulation. Biotechnological approaches, including marker-assisted selection (MAS) and CRISPR/Cas9-mediated genome editing, have successfully generated high-oil-content variants. Future research should integrate multi-omics data, leverage AI-based predictive breeding, and apply precision genome editing to optimize oil yield while maintaining seed quality. This review provides critical references for the genetic improvement and breeding of high- and ultra-high-oil-content varieties in oilseed crops. Full article

Precision neurosurgery is rapidly evolving as a medical specialty by merging genomic medicine, multi-omics technologies, and artificial intelligence (AI) technology, while at the same time, society is shifting away from the traditional, anatomic model of care to consider a more precise, molecular model of care. The general purpose of this review is to contemporaneously reflect on how these advances will impact neurosurgical care by providing us with more precise diagnostic and treatment pathways. We hope to provide a relevant review of the recent advances in genomics and multi-omics in the context of clinical practice and highlight their transformational opportunities in the existing models of care, where improved molecular insights can support improvements in clinical care. More specifically, we will highlight how genomic profiling, CRISPR-Cas9, and multi-omics platforms (genomics, transcriptomics, proteomics, and metabolomics) are increasing our understanding of central nervous system (CNS) disorders. Achievements obtained with transformational technologies such as single-cell RNA sequencing and intraoperative mass spectrometry are exemplary of the molecular diagnostic possibilities in real-time molecular diagnostics to enable a more directed approach in surgical options. We will also explore how identifying specific biomarkers (e.g., IDH mutations and MGMT promoter methylation) became a tipping point in the care of glioblastoma and allowed for the establishment of a new taxonomy of tumors that became applicable for surgeons, where a change in practice enjoined a different surgical resection approach and subsequently stratified the adjuvant therapies undertaken after surgery. Furthermore, we reflect on how the novel genomic characterization of mutations like DEPDC5 and SCN1A transformed the pre-surgery selection of surgical candidates for refractory epilepsy when conventional imaging did not define an epileptogenic zone, thus reducing resective surgery occurring in clinical practice. While we are atop the crest of an exciting wave of advances, we recognize that we also must be diligent about the challenges we must navigate to implement genomic medicine in neurosurgery—including ethical and technical challenges that could arise when genomic mutation-based therapies require the concurrent application of multi-omics data collection to be realized in practice for the benefit of patients, as well as the constraints from the blood–brain barrier. The primary challenges also relate to the possible gene privacy implications around genomic medicine and equitable access to technology-based alternative practice disrupting interventions. We hope the contribution from this review will not just be situational consolidation and integration of knowledge but also a stimulus for new lines of research and clinical practice. We also hope to stimulate mindful discussions about future possibilities for conscientious and sustainable progress in our evolution toward a genomic model of precision neurosurgery. In the spirit of providing a critical perspective, we hope that we are also adding to the larger opportunity to embed molecular precision into neuroscience care, striving to promote better practice and better outcomes for patients in a global sense. Full article

Huanglongbing (HLB), caused by Candidatus Liberibacter asiaticus (CLas), is the most devastating disease threatening global citrus production. Although no commercial citrus varieties exhibit complete HLB resistance, genotype-specific tolerance variations remain underexplored. This study conducted a comparative transcriptomic profiling of six commercially citrus cultivars in South China, four susceptible cultivars (C. reticulata cv. Tankan, Gongkan, Shatangju, and C. sinensis Osbeck cv. Newhall), and two tolerant cultivars (C. limon cv. Eureka; C. maxima cv Guanxi Yu) to dissect molecular mechanisms underlying HLB responses. Comparative transcriptomic analyses revealed extensive transcriptional reprogramming, with tolerant cultivars exhibiting fewer differentially expressed genes (DEGs) and targeted defense activation compared to susceptible genotypes. The key findings highlighted the genotype-specific regulation of starch metabolism, where β-amylase 3 (BAM3) was uniquely upregulated in tolerant varieties, potentially mitigating starch accumulation. Immune signaling diverged significantly: tolerant cultivars activated pattern-triggered immunity (PTI) via receptor-like kinases (FLS2) and suppressed ROS-associated RBOH genes, while susceptible genotypes showed the hyperactivation of ethylene signaling and oxidative stress pathways. Cell wall remodeling in susceptible cultivars involved upregulated xyloglucan endotransglucosylases (XTH), contrasting with pectin methylesterase induction in tolerant Eureka lemon for structural reinforcement. Phytohormonal dynamics revealed SA-mediated defense and NPR3/4 suppression in Eureka lemon, whereas susceptible cultivars prioritized ethylene/JA pathways. These findings delineate genotype-specific strategies in citrus–CLas interactions, identifying BAM3, FLS2, and cell wall modifiers as critical targets for breeding HLB-resistant cultivars through molecular-assisted selection. This study provides a foundational framework for understanding host–pathogen dynamics and advancing citrus immunity engineering. Full article

Antimicrobial resistance (AMR) has emerged as a planetary health emergency, driven not only by the clinical misuse of antibiotics but also by diverse environmental dissemination pathways. This review critically examines the role of environmental compartments—water, soil, and air—as dynamic reservoirs and transmission routes for antibiotic-resistant bacteria (ARB) and resistance genes (ARGs). Recent metagenomic, epidemiological, and mechanistic evidence demonstrates that anthropogenic pressures—including pharmaceutical effluents, agricultural runoff, untreated sewage, and airborne emissions—amplify resistance evolution and interspecies gene transfer via horizontal gene transfer mechanisms, biofilms, and mobile genetic elements. Importantly, it is not only highly polluted rivers such as the Ganges that contribute to the spread of AMR; even low concentrations of antibiotics and their metabolites, formed during or after treatment, can significantly promote the selection and dissemination of resistance. Environmental hotspots such as European agricultural soils and airborne particulate zones near wastewater treatment plants further illustrate the complexity and global scope of pollution-driven AMR. The synergistic roles of co-selective agents, including heavy metals, disinfectants, and microplastics, are highlighted for their impact in exacerbating resistance gene propagation across ecological and geographical boundaries. The efficacy and limitations of current mitigation strategies, including advanced wastewater treatments, thermophilic composting, biosensor-based surveillance, and emerging regulatory frameworks, are evaluated. By integrating a One Health perspective, this review underscores the imperative of including environmental considerations in global AMR containment policies and proposes a multidisciplinary roadmap to mitigate resistance spread across interconnected human, animal, and environmental domains. Full article

Background/Objectives: Gastric cancer (GC) remains a significant global health burden due to its high mortality rate and frequent diagnosis at advanced stages. This study aimed to identify reliable diagnostic biomarkers and elucidate molecular mechanisms underlying GC by integrating transcriptomic data from independent platforms and applying machine learning techniques. Methods: Two transcriptomic datasets from the Gene Expression Omnibus were analyzed: GSE26899 (microarray, n = 108) as the discovery dataset and GSE248612 (RNA-seq, n = 12) for validation. Differential expression analysis was conducted using limma and DESeq2, selecting genes with |log2FC| > 1 and adjusted p < 0.05. The top 200 differentially expressed genes (DEGs) were used to develop machine learning models (random forest, logistic regression, neural networks). Functional enrichment analyses (GO, KEGG, Hallmark) were applied to explore relevant biological pathways. Results: In GSE26899, 627 DEGs were identified (201 upregulated, 426 downregulated), with key genes including CST1, KIAA1199, TIMP1, MSLN, and ATP4A. The random forest model demonstrated excellent classification performance (AUC = 0.952). GSE248612 validation yielded 738 DEGs. Cross-platform comparison confirmed 55.6% concordance among core genes, highlighting CST1, TIMP1, KRT17, ATP4A, CHIA, KRT16, and CRABP2. Enrichment analyses revealed involvement in ECM–receptor interaction, PI3K-Akt signaling, EMT, and cell cycle. Conclusions: This integrative transcriptomic and machine learning framework effectively identified high-confidence biomarkers for GC. Notably, CST1, TIMP1, KRT16, and ATP4A emerged as consistent, biologically relevant candidates with strong diagnostic performance and potential clinical utility. These findings may aid early detection strategies and guide future therapeutic developments in gastric cancer. Full article

Livestock farming is a vital component of global food security, yet it remains a major contributor to greenhouse gas (GHG) emissions, particularly methane (CH₄), which has a global warming potential 28 times greater than carbon dioxide (CO₂). This review provides a comprehensive synthesis of current knowledge surrounding the sources, biological mechanisms, and mitigation strategies related to CH₄ emissions from ruminant livestock. We first explore the process of methanogenesis within the rumen, detailing the role of methanogenic archaea and the environmental factors influencing CH₄ production. A thorough assessment of both direct and indirect methods used to quantify CH₄ emissions is presented, including in vitro techniques (e.g., syringe method, batch culture, RUSITEC), in vivo techniques (e.g., respiration chambers, Greenfeed, laser CH₄ detectors), and statistical modeling approaches. The advantages and limitations of each method are critically analyzed in terms of accuracy, cost, feasibility, and applicability to different farming systems. We then examine a wide range of mitigation strategies, organized into four core pillars: (1) animal and feed management (e.g., genetic selection, pasture quality improvement), (2) diet formulation (e.g., feed additives such as oils, tannins, saponins, and seaweed), (3) rumen manipulation (e.g., probiotics, ionophores, defaunation, vaccination), and (4) manure management practices and policy-level interventions. These strategies are evaluated not only for their environmental impact but also for their economic and practical viability in diverse livestock systems. By integrating technological innovations with sustainable agricultural practices, this review highlights pathways to reduce CH₄ emissions while maintaining animal productivity. It aims to support decision-makers, researchers, and livestock producers in the global effort to transition toward climate-smart, low-emission livestock farming. Full article

Leukemias and lymphomas are hematologic malignancies characterized by complex pathophysiological mechanisms and increasing global incidence. Despite advances in chemotherapy, immunotherapy, and targeted therapies, challenges such as drug resistance and relapse persist, necessitating novel therapeutic strategies. This review explores the cytotoxic potential of venoms derived from snakes, bees, and scorpions against leukemia and lymphoma cells. Numerous venom-derived components, such as L-amino acid oxidases (LAAOs), phospholipases A₂ (PLA₂s), and peptides like melittin, demonstrate selective antitumor activity through mechanisms involving oxidative stress, apoptosis induction, cell cycle arrest, and immunomodulation. These molecules exert their effects via mitochondrial pathways, caspase activation, and inhibition of pro-survival signaling cascades such as NF-κB and PI3K/Akt. Despite promising preclinical results, the clinical translation of these bioactive compounds remains limited due to challenges in standardization, delivery, and safety profiling. This review highlights recent advances in venom research, summarizes key molecular targets, and discusses future directions to harness venom-derived molecules as innovative therapies for hematological cancers. Full article

Quinoa (Chenopodium quinoa Willd) is a tetraploid crop that has provided vital subsistence, nutrition, and medicine for Andean indigenous cultures. In recent years, quinoa has gained global importance all over the world. However, variations in fertility have been frequently observed during the flower development of quinoa, severely affecting quinoa production. To comprehend the fundamental causes of fertility variation in quinoa, this research examined hormonal metabolism and gene expression across three ecotypes: normal fertility (F), absent stamens (S1), and abnormal stamens (S3). S1 and S3 presented absent and abnormal stamens, respectively, compared with F. Phytohormone profiling yielded 60 metabolites and revealed the clear separation between different ecotypes at different developmental stages according to principal component analysis (PCA). The results of transcriptomics showed more DEGs (differentially expressed genes) identified between F and S1 ecotypes (8002 and 10,716 for earlier and later stages, respectively) than F vs. S3 (4500 and 9882 for earlier and later stages, respectively) and S1 vs. S3 (4203 and 5052 for earlier and later stages, respectively). Zeatin biosynthesis and hormone signal transduction pathways were enriched among 19 KEGG (Kyoto Encyclopedia of Genes and Genomes) terms, indicating their potential roles in quinoa flower fertility regulation. The correlation-based network presented the associations between selected hormones and genes, possibly regulating fertile ecotypes. Furthermore, we explored the expression of flower development-related genes in three ecotypes using RT-PCR, showing the higher expressions of AP1, AP3, and FLS in sterile ecotypes than fertile ecotypes at both stages. These findings reveal new insights into the hormonal and genetic regulations of floral fertility in quinoa, which may have consequences for developing high-yielding cultivars. Full article

Background: Prehabilitation programs improve postoperative outcomes in vulnerable patients undergoing major surgery. However, current screening tools such as the Malnutrition Universal Screening Tool (MUST) may lack the sensitivity needed to identify those who would benefit most. Muscle quality assessed by Computed Tomography (CT), specifically muscle radiodensity in Hounsfield Units (HUs), has emerged as a promising alternative for risk stratification. Objective: To evaluate the prognostic performance of CT-derived muscle radiodensity in predicting adverse postoperative outcomes in colorectal cancer patients, and to compare it with the performance of the MUST score. Methods: This single-center cross-sectional study included 201 patients with non-metastatic colon cancer undergoing elective laparoscopic resection. Patients were stratified based on enrollment in a multimodal prehabilitation program, either within an Enhanced Recovery After Surgery (ERAS) protocol or a non-ERAS pathway. Nutritional status was assessed using MUST, SARC-F questionnaire (strength, assistance with walking, rise from a chair, climb stairs, and falls), and the Global Leadership Initiative on Malnutrition (GLIM) criteria. CT scans at the L3 level were analyzed using automated segmentation to extract muscle area and radiodensity. Postoperative complications and hospital stay were compared across nutritional screening tools and CT-derived metrics. Results: MUST shows limited sensitivity (<27%) for predicting complications and prolonged hospitalization. In contrast, CT-derived muscle radiodensity demonstrates higher discriminative power (AUC 0.62–0.69), especially using a 37 HU threshold. In the non-ERAS group, patients with HU ≤ 37 had significantly more complications (33% vs. 15%, p = 0.036), longer surgeries, and more severe events (Clavien–Dindo ≥ 3). Conclusions: Opportunistic CT-based assessment of muscle radiodensity outperforms traditional screening tools in identifying patients at risk of poor postoperative outcomes, and may enhance patient selection for prehabilitation strategies like the ERAS program. Full article

Zeugodacus cucuribitae (Coquillett) (Z. cucuribitae) is a global extremely invasive quarantine pest which has a wide host range of fruits and vegetables. At present, there are a few control measures for Z. cucuribitae, and deltamethrin and avermectin are commonly used. Among the hosts of Z. cucuribitae, Luffa acutangular, Luffa cylindrica, Sechium edule, Brassica oleracea var. botrytis, Musa nana, and Fragaria × ananassa are non-favored hosts. However, it is still not clear why these hosts are non-favored and whether there are any repellent components of Z. cucuribitae in these hosts. In this study, the components of these six hosts were collected from the literature, and the genes of odor and chemical sensation were determined from the genome of Z. cucuribitae. After the potential relationships between these components and genes were determined by molecular docking methods, the KEGG and GO enrichment analysis of these genes was conducted, and a complex network of genes vs. components vs. Kegg pathway vs. GO terms was constructed and used to select the key components for experiments. The results show that oleanolic acid (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL), rotenone (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL), and beta-caryophyllene oxide (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL) had a significant repellent effect on Z. cucuribitae, and three components, rotenone (1 mg/mL and 0.1 mg/mL), echinocystic acid (1 mg/mL, 0.1 mg/mL, and 0.01 mg/mL), and beta-caryophyllene oxide (1 mg/mL, and 0.1 mg/mL) had significant stomach toxicity in Z. cucuribitae. Furthermore, a complex signaling pathway was built and used to predict the effect of these components on Z. cucuribitae. These components probably play roles in the neuroactive ligand–receptor interaction (ko04080) and calcium signaling (ko04020) pathways. This study provides a reference for the prevention and control of Z. cucuribitae and a scientific reference for the rapid screening and development of new pest control drugs. Full article

The global fish industry faces persistent challenges due to the inherent perishability of fish, driven by enzymatic autolysis, lipid oxidation, and microbial proliferation. Although numerous studies have characterized these individual spoilage pathways and evaluated discrete preservation techniques, practitioners still lack a unified, mechanism-based framework that links spoilage chemistry to targeted interventions. This gap prevents the rational selection and optimization of preservation methods. In this review, we first synthesize recent multi-omics and microbiological findings to delineate the molecular drivers of post-harvest fish spoilage. We then critically map a suite of preservation approaches—including low-temperature treatments (refrigeration, super-chilling, freezing), high-pressure processing, modified atmosphere packaging, nanoemulsion and essential-oil coatings, pulsed electric fields, and ozonation—onto the specific mechanisms they mitigate. By comparing efficacy metrics, practical constraints, and emerging innovations, our mechanism-driven roadmap clearly defines the problems we address and offers actionable guidance for developing more effective and sustainable fish preservation strategies. Full article

Microelement deficiencies, often termed “hidden hunger”, represent a significant global health challenge. Optimal human health relies on adequate dietary intake of essential microelements, including selenium (Se), zinc (Zn), copper (Cu), boron (B), manganese (Mn), molybdenum (Mo), iron (Fe), nickel (Ni), and chlorine (Cl). In recent years, there has been a growing focus on vitality and longevity, which are closely associated with the sufficient intake of essential microelements. This review focuses on these nine elements, whose bioavailability in the food chain is critically determined by their geochemical behavior in soils. There is a necessity for an understanding of the sources, soil–plant transfer, and plant uptake mechanisms of these microelements, with particular emphasis on the influence of key soil properties, including pH, redox potential, organic matter content, and mineral composition. There is a dual challenge of microelement deficiencies in agricultural soils, leading to inadequate crop accumulation, and the potential for localized toxicities arising from anthropogenic inputs or geogenic enrichment. A promising solution to microelement deficiencies in crops is biofortification, which enhances nutrient content in food by improving soil and plant uptake. This strategy includes agronomic methods (e.g., fertilization, soil amendments) and genetic approaches (e.g., marker-assisted selection, genetic engineering) to boost microelement density in edible tissues. Moreover, emphasizing the need for advanced predictive modeling techniques, such as ensemble learning-based digital soil mapping, enhances regional soil microelement management. Integrating machine learning with digital covariates improves spatial prediction accuracy, optimizes soil fertility management, and supports sustainable agriculture. Given the rising global population and the consequent pressures on agricultural production, a comprehensive understanding of microelement dynamics in the soil–plant system is essential for developing sustainable strategies to mitigate deficiencies and ensure food and nutritional security. This review specifically focuses on the bioavailability of these nine essential microelements (Se, Zn, Cu, B, Mn, Mo, Fe, Ni, and Cl), examining the soil–plant transfer mechanisms and their ultimate implications for human health within the soil–plant–human system. The selection of these nine microelements for this review is based on their recognized dual importance: they are not only essential for various plant metabolic functions, but also play a critical role in human nutrition, with widespread deficiencies reported globally in diverse populations and agricultural systems. While other elements, such as cobalt (Co) and iodine (I), are vital for health, Co is primarily required by nitrogen-fixing microorganisms rather than directly by all plants, and the main pathway for iodine intake is often marine-based rather than soil-to-crop. Full article

Background/Objectives: Long non-coding RNAs (lncRNAs) play significant roles in tissue development and disease progression and have emerged as crucial regulators of gene expression. The hepatocyte nuclear factor alpha antisense RNA 1 (HNF1A-AS1) lncRNA is a particularly intriguing regulatory molecule in liver biology that is involved in the regulation of cytochrome P450 enzymes via epigenetic mechanisms. Despite the growing recognition of lncRNAs in liver disease, the comprehensive role of HNF1A-AS1 in liver function remains unclear. This study aimed to investigate the roles of the mouse homolog of the human HNF1A-AS1 lncRNA HNF1A opposite strand 1 (Hnf1aos1) in liver function, gene expression, and cellular processes using a mouse model to identify potential therapeutic targets for liver disorders. Methods: The knockdown of Hnf1aos1 was performed in in vitro mouse liver cell lines using siRNA and in vivo livers of AAV-shRNA complexes. Changes in the global expression landscapes of mRNA and proteins were revealed using RNA-seq and proteomics, respectively. Changes in the selected genes were further validated via real-time quantitative polymerase chain reaction (RT-qPCR). Phenotypic changes were assessed via histological and absorbance-based assays. Results: After the knockdown of Hnf1aos1, RNA-seq and proteomics analysis revealed the differential gene expression of the mRNAs and proteins involved in the processes of molecular transport, liver regeneration, and immune signaling pathways. The downregulation of ABCA1 and SREBF1 indicates their role in cholesterol transport and fatty acid and triglyceride synthesis. Additionally, significant reductions in hepatic triglyceride levels were observed in the Hnf1aos1-knockdown group, underscoring the impact on lipid regulation. Notably, the knockdown of Hnf1aos1 also led to an almost complete depletion of CYP7A1, the rate-limiting enzyme in bile acid synthesis, highlighting its role in cholesterol homeostasis and hepatotoxicity. Histological assessments confirmed these molecular findings, with increased hepatic inflammation, hepatocyte swelling, and disrupted liver architecture observed in the Hnf1aos1-knockdown mice. Conclusions: This study illustrated that Hnf1aos1 is a critical regulator of liver health, influencing both lipid metabolism and immune pathways. It maintains hepatic lipid homeostasis, modulates lipid-induced inflammatory responses, and contributes to viral immunity, indirectly affecting glucose and lipid metabolic balance. Full article