Metabolites[JOURNAL]
Sun
200 papers
Parishin B Attenuates PTZ-Induced Seizures in Zebrafish and Is Associated with Neurotransmitter Balance and ACLY-Related Metabolic Pathways.
Sun M, Liu H, Hou Z … +2 more , Wang Q, Zhong W
Metabolites · 2026 Apr · PMID 42042920 · Full text
Epilepsy is a chronic neurological disorder characterized by recurrent seizures, complex neurochemical, and metabolic disturbances. Parishin B, a major bioactive component of Gastrodia elata, has shown neuroprotective po...
Epilepsy is a chronic neurological disorder characterized by recurrent seizures, complex neurochemical, and metabolic disturbances. Parishin B, a major bioactive component of Gastrodia elata, has shown neuroprotective potential, but its systemic mechanisms remain unclear. A pentylenetetrazol (PTZ)-induced seizure model in zebrafish larvae was developed and used to evaluate the anti-seizure effects of Parishin B. Behavioral analysis, ELISA-based biochemical assays, integrated untargeted metabolomics with DIA-based proteomics, and qPCR were performed to decipher underlying molecular mechanisms. Parishin B (0.0625-0.25 mg/mL) significantly alleviated PTZ-induced hyperactivity without developmental toxicity. Parishin B restored neurotransmitter balance by increasing GABA, dopamine, and norepinephrine levels while reducing 5-HT. In addition, it suppressed neuroinflammation and enhanced antioxidant capacity. Integrated multi-omics analysis revealed that Parishin B modulated key metabolic pathways, particularly the TCA cycle and lipid metabolism, and reversed the downregulation of ATP-citrate lyase (ACLY). Parishin B was also associated with the regulation of ferroptosis-related pathways, supported by changes in acsl4a and fth1a expression. qPCR results further confirmed the regulation of aclya, unc13c, and GABAergic signaling genes. Parishin B exerts anti-seizure effects through coordinated regulation of neurotransmitter homeostasis, neuroinflammation, and ACLY-associated energy-lipid metabolism, with potential involvement in ferroptosis-related processes. These findings provide molecular insights supporting Parishin B as a promising candidate for epilepsy therapy.
Deep Learning-Based and Python-Driven Construction and Application of a Mass Spectrometry Data Analysis Workflow: Taking Glucosinolates as an Example.
Yang S, Jia S, Jia P … +2 more , Xie W, Wang X
Metabolites · 2026 Apr · PMID 42042919 · Full text
BACKGROUND: Radish seeds are our model on glucosinolates (GSLs), which is a class of secondary metabolites in medicinal plants of the Brassicaceae family. Multilayer perceptron (MLP) network is highly effective in the st...
BACKGROUND: Radish seeds are our model on glucosinolates (GSLs), which is a class of secondary metabolites in medicinal plants of the Brassicaceae family. Multilayer perceptron (MLP) network is highly effective in the study of complex plants. This study came up with a smart plan through the Python language. METHODS: First, we used the MLP network to pick out GSL precursor ions, running them through a deep learning filter. Next, we set up an automated screening system and looked at how standard chemicals break down. To speed things up, we created a scoring system that flagged promising compounds. After that, we built a tracer molecular network, basically connecting compounds according to how the plant makes them, which helped us label everything accurately. Finally, we brought in a math-based tool that pieces together different chemical parts to predict new GSL structures. RESULTS: With this workflow, we annotated 195 glucosinolate-related compounds in radish seeds. That includes 86 regular GSLs, 34 malonyl products, 40 sinapoyl compounds, and 35 diglycosides. Among them, eight compounds were confirmed by comparison with authentic standards (retention time and MS/MS data), whereas the remaining compounds were tentatively annotated based on accurate mass measurements, diagnostic fragment ions, Tracer Molecular , and literature/database matching. In addition, 36 compounds were considered putatively novel derivatives pending further structural confirmation. CONCLUSIONS: This new approach reduces the time spent on determining chemicals in complicated samples. This can be done with other vegetables and medicinal herbs by researchers. It assists us in knowing the chemistry of plants in a deeper manner.
Bile and Serum Metabolomics in Living Donor Liver Transplantation: Exploratory Insights into Acute Rejection Biomarkers.
Hirata Y, Sakuma Y, Ogiso H … +9 more , Wakiya T, Omameuda T, Horiuchi T, Okada N, Sanada Y, Onishi Y, Yamaguchi H, Nagai R, Aizawa K
Metabolites · 2026 Apr · PMID 42042918 · Full text
BACKGROUND: Acute rejection remains a major complication following liver transplantation, yet reliable noninvasive biomarkers for its early prediction and diagnosis remain unidentified. This exploratory study characteriz...
BACKGROUND: Acute rejection remains a major complication following liver transplantation, yet reliable noninvasive biomarkers for its early prediction and diagnosis remain unidentified. This exploratory study characterized bile and serum metabolites associated with acute rejection in living donor liver transplantation using comprehensive metabolomic profiling combined with machine learning. METHODS: Non-targeted metabolomics were performed on bile samples collected on post-operative day (POD) 1 ( = 38) and serum on POD 14 ( = 45) from liver transplant recipients. Partial least squares discriminant analysis-based variable selection was followed by logistic regression and least absolute shrinkage and selection operator models, which were evaluated via cross-validation in the discovery cohort to explore potential biomarkers for acute rejection. RESULTS: A three-variable, bile-based model for predicting acute rejection achieved a mean cross-validated AUC of 0.872 (95% confidence interval: 0.814-0.930). Glycohyocholic acid and sulfolithocholylglycine were the main contributors. A nine-variable serum model for the Rejection Activity Index, including the change in γ-glutamyl transferase, showed a mean cross-validated R of 0.728 (95% confidence interval: 0.609-0.846), with methionine, creatine, and oxidized fatty acids contributing prominently. CONCLUSIONS: These findings suggest that metabolomic profiling combined with machine learning may provide candidate biomarkers for acute rejection after liver transplantation. However, given the exploratory nature of the study and the lack of external validation, the clinical utility of these metabolite signatures remains to be determined. Therefore, external validation in larger, independent cohorts will be required.
Untargeted GC-IMS Metabolomics of Wound Headspace for Bacterial Infection Biomarker Discovery.
Lu Y, Yan B, Zeng L … +4 more , Zhou B, Wu R, Zhong X, He Q
Metabolites · 2026 Apr · PMID 42042917 · Full text
Wound infections cause significant morbidity, yet current diagnostics rely on time-consuming microbial culture. Volatile organic compounds (VOCs) from bacterial metabolism offer potential for early diagnosis. This study...
Wound infections cause significant morbidity, yet current diagnostics rely on time-consuming microbial culture. Volatile organic compounds (VOCs) from bacterial metabolism offer potential for early diagnosis. This study aimed to validate the volatile metabolites profiled by gas chromatography-ion mobility spectrometry (GC-IMS) combined with machine learning for rapid identification of wound infections and certain bacterial infections. Headspace of clinical wound samples were analyzed using GC-IMS. Volatile metabolite profiles were compared between infected and non-infected groups and between ()-positive and negative samples. Partial least squares discriminant analysis (PLS-DA) and Mann-Whitney U test were used for preliminary screening with variable importance in projection (VIP) > 1 and -value < 0.05. Three machine learning algorithms, namely support vector machine (SVM), logistic regression (LR), and random forest (RF), were trained on the selected features for classification, using 5-fold cross-validation with 10 repeated runs. Model performance was assessed using key evaluation metrics, including accuracy, sensitivity, specificity, the area under the curve (AUC) and feature importance ranking to identify the most relevant biomarkers. A total of 19 volatile metabolites associated with clinical wound samples were identified. The RF model achieved 90.15% sensitivity and 0.91 AUC for bacterial infection detection. For identification, LR reached 85.35% sensitivity and 0.89 AUC. Potential volatile metabolic biomarkers including elevated 3-methyl-1-butanol, 2-methyl-1-butanol, and ethyl hexanoate for identifying bacterial infection were selected through the cross-validation results of the three algorithms. Untargeted metabolomics by GC-IMS effectively captures infection-specific volatile metabolic signatures in complex wound samples. Integration with machine learning enables rapid, high-accuracy diagnosis of bacterial infections and identification at point of care. This approach addresses clinical metabolomics translational challenges by providing a portable and cost-effective method, potentially reducing antibiotic misuse through more timely and targeted therapy.
Dynamic Role of Omega-3/Omega-6 Polyunsaturated Fatty Acid Ratio in Modulation of Adipogenicity, Lipid Metabolites, and Adipokines Associated with Platelet Hyperactivity.
Almolafikh ST, Subash-Babu P, Barhoumi T … +1 more , Alshatwi AA
Metabolites · 2026 Apr · PMID 42042916 · Full text
Unhealthy expansion of adipose tissue (AT) due to excessive dietary intake of omega-6 or overnutrition stimulates the overaccumulation of the extracellular matrix (ECM), resulting in AT metabolic dysregulation. Hypertrop...
Unhealthy expansion of adipose tissue (AT) due to excessive dietary intake of omega-6 or overnutrition stimulates the overaccumulation of the extracellular matrix (ECM), resulting in AT metabolic dysregulation. Hypertrophic conditions, excessive adipose depots, and hypoxia stimulate the overproduction of collagenous and non-collagenous proteins, which pathophysiologically initiate the pro-fibrotic signaling pathway associated with fibrosis progression, resulting in atherosclerosis and cardiovascular diseases. We aimed to investigate adipocyte plasticity in response to a varying ratio of omega-3 (ω3) to omega-6 (ω6) supplementation during the chemically induced adipogenic differentiation of human mesenchymal stem cells. Additionally, changes in lipid accumulation, adipocyte hypertrophy and hyperplasia, active lipid metabolites, and inflammatory cytokine profiles were evaluated. Furthermore, conditioned media from adipocytes treated with different ω3/ω6 ratios were applied to platelets to assess inflammatory responses through prostaglandin and thromboxane measurements. A 1:3 ratio of ω3/ω6 (20:60 µM) significantly reduced lipid accumulation, promoted brown-like adipocyte morphology, and decreased apoptosis and reactive oxygen species (ROS) generation, as confirmed via FACS analysis. Transcriptional control of adipose tissue expansion was confirmed by the downregulation of LIPIN1 and COL1A1 mRNA expression and -prostaglandin12-R protein levels in a 1:3 ratio when compared with 1:1, 1:2, 1:4, or 2:6 ratios of ω3/ω6. Notably, a 1:3 ratio of fatty-acid-treated adipocyte-conditioned media-treated platelets significantly reduced platelet activation and aggregation, as evidenced by lower -thromboxane A2 protein levels. Supplementation with a 1:3 (20:60 µM) ω3/ω6 ratio favored the development of lean adipocytes, evidenced by the decreased lipid storage achieved by mitochondrial thermogenesis, which attenuated minimal adipocyte expansion and metabolic inflammation.
Association Between Vitamin D Deficiency and Glycemic, Lipid, and Adiposity Markers in Older Adults: A Nationally Representative Study.
Kim YJ, Jang K
Metabolites · 2026 Apr · PMID 42042915 · Full text
BACKGROUND/OBJECTIVES: Vitamin D plays an important role in glucose metabolism, lipid regulation, and inflammatory processes, and has been implicated in cardiometabolic health. However, its associations with specific met...
BACKGROUND/OBJECTIVES: Vitamin D plays an important role in glucose metabolism, lipid regulation, and inflammatory processes, and has been implicated in cardiometabolic health. However, its associations with specific metabolic biomarkers remain inconsistent, particularly in older adults. This study aimed to examine whether vitamin D deficiency is differentially associated with multiple metabolic biomarkers in a nationally representative sample of older adults. METHODS: This cross-sectional study used data from the 2024 Korea National Health and Nutrition Examination Survey, including 1806 adults aged ≥65 years. Vitamin D deficiency was defined as serum 25-hydroxyvitamin D levels < 20 ng/mL. Metabolic biomarkers included fasting glucose, glycated hemoglobin (HbA1c), triglycerides, C-reactive protein (CRP), high-density lipoprotein cholesterol (HDL-C), waist circumference, and body mass index (BMI). Complex sample linear regression analyses were performed with sequential adjustment for sociodemographic factors, health behaviors, and comorbidities. RESULTS: In unadjusted analyses, vitamin D deficiency was associated with adverse metabolic profiles, including higher fasting glucose, HbA1c, triglycerides, waist circumference, and CRP levels, and lower HDL-C levels. After adjustment for sociodemographic factors, health behaviors, and comorbidities, significant associations remained for HbA1c (β = 0.10, = 0.034), triglycerides (β = 0.10, = 0.003), and waist circumference (β = 1.21, = 0.040). No significant associations were observed for fasting glucose, HDL-C, CRP, or BMI. CONCLUSIONS: Vitamin D deficiency was independently associated with poorer long-term glycemic status, hypertriglyceridemia, and central adiposity in older adults, but not with other metabolic markers after adjustment. These findings suggest that the metabolic correlates of vitamin D deficiency may be domain-specific rather than generalized. Longitudinal and interventional studies are needed to clarify causality and underlying mechanisms.
Precision Exercise in Type 2 Diabetes Mellitus: Targeting Signaling Networks for Lipid Homeostasis.
Tian T, Yu F, Liu X … +3 more , Zeng X, Yue J, Bao S
Metabolites · 2026 Apr · PMID 42042914 · Full text
Type 2 diabetes mellitus (T2DM) is frequently complicated by dyslipidemia, which accelerates insulin resistance and the progression of cardiovascular and hepatic diseases. While exercise intervention is a cornerstone of...
Type 2 diabetes mellitus (T2DM) is frequently complicated by dyslipidemia, which accelerates insulin resistance and the progression of cardiovascular and hepatic diseases. While exercise intervention is a cornerstone of T2DM management, a systems-level understanding of its underlying molecular mechanisms remains incomplete. This article summarizes current evidence to propose that exercise functions as a signaling network regulator, concurrently modulating critical lipid metabolism-related signaling pathways: cyclic adenosine monophosphate (cAMP), phosphatidylinositol 3-kinase-protein kinase B (PI3K-AKT), forkhead box O (FOXO), and mitogen-activated protein kinase (MAPK) signaling pathways. We delineate how dysregulation of these signaling pathways contributes to lipid disorders in T2DM, highlighting their tissue-specific and often bidirectional roles. Subsequently, we detail the molecular adaptations induced by various exercise modalities-from aerobic training to high-intensity intervals-that restore homeostasis of this signaling network. By integrating these findings, we present a novel framework for precision exercise-defined as the tailoring of exercise modality, intensity, and volume based on an individual's predominant signaling pathway disturbance, assessed via circulating or tissue-specific biomarkers. This framework advocates for future exercise prescriptions to be guided by molecular profiling alongside traditional physiological indicators. This mechanistic insight not only deepens our comprehension of exercise physiology but also paves the way for more effective, personalized strategies to combat T2DM and its metabolic complications.
M-GNN: A Topology-Enhanced Multi-Modal Graph Neural Network for Cancer Driver Gene Prediction.
Qin L, Zhu W, Liao X … +1 more , Zhang Y
Metabolites · 2026 Apr · PMID 42042913 · Full text
Accurate identification of cancer driver genes is essential for understanding tumorigenesis and developing targeted therapies. Although graph neural networks (GNNs) have advanced multi-omics integration, existing methods...
Accurate identification of cancer driver genes is essential for understanding tumorigenesis and developing targeted therapies. Although graph neural networks (GNNs) have advanced multi-omics integration, existing methods often simply concatenate omics features and underutilize the topological information of biological networks. We propose M-GNN, a multi-modal GNN framework for cancer driver gene prediction. It employs separate Graph Convolutional Network (GCN) encoders to process four types of omics data (mutation, expression, methylation, copy number variation (CNV)), each represented as a 16-dimensional vector. We incorporate knowledge distillation by using soft labels from a pre-trained teacher model to enhance feature representation. An attention mechanism adaptively fuses the encoded omics features, and a dual-path classifier combining a GCN and a Multilayer Perceptron (MLP) preserves both intrinsic gene properties and network topology. Experiments on three public protein-protein interaction (PPI) networks show that M-GNN consistently achieves the highest or second-highest AUPRC compared to five state-of-the-art methods. Ablation studies confirm the contribution of each module, and biological interpretability analysis-including analysis of GO enrichment and drug sensitivity-validates the reliability of the predicted genes. M-GNN provides a robust and interpretable computational tool for systematic cancer driver gene identification, effectively integrating multi-omics and network data.
Temporal Metabolic Reprogramming Reveals Stage-Specific Adaptations in Proso Millet Resistance Against Head Smut.
Fan W, Qi M, Li Z … +7 more , Zuo Y, Zhao M, Liu H, Wen Y, Wang X, Bian L, Zhang L
Metabolites · 2026 Apr · PMID 42042912 · Full text
BACKGROUND/OBJECTIVES: Proso millet ( L.), a drought-tolerant cereal vital to semi-arid agriculture, faces severe yield losses from head smut disease caused by the pathogen . Although partial resistance exists, the dynam...
BACKGROUND/OBJECTIVES: Proso millet ( L.), a drought-tolerant cereal vital to semi-arid agriculture, faces severe yield losses from head smut disease caused by the pathogen . Although partial resistance exists, the dynamic molecular mechanisms governing its defense response across developmental stages remain poorly understood. METHODS: Here, we performed untargeted metabolomics on leaf samples from Inoculated Asymptomatic (IA) and Inoculated Symptomatic (IS) plants of the partially resistant cultivar 'Chishu 13' at four key growth stages following pathogen inoculation, with group classification validated by qPCR. Using weighted metabolite co-expression network analysis (WGCNA) combined with differential metabolite screening, we identified 18 metabolites markedly enriched in the tricarboxylic acid (TCA) cycle, metabolite transport-related processes, and phenylpropanoid biosynthesis pathways. RESULTS: Notably, L-phenylalanine accumulated substantially in IA plants relative to IS plants and correlated closely with biosynthesis of key defensive phenylpropanoids, including cinnamic acid and -coumaric acid. Our results reveal distinct temporal patterns in metabolic reprogramming that correlate with resistance outcomes in Inoculated Asymptomatic plants: early stages are characterized by differential regulation of energy metabolism, while later stages show enhanced phenylpropanoid biosynthesis. These stage-specific metabolic adaptations are strongly associated with successful defense outcomes. CONCLUSIONS: These findings elucidate stage-specific metabolic adaptations that distinguish successful defense in IA plants from susceptibility in IS plants, providing robust biomarkers and stage-targeted strategies for breeding smut-resistant millet varieties.
The Thyroid-Metabolism Axis: Pathways of Dysregulation and the Effects of Treatment.
Curcio M, Vincent RP
Metabolites · 2026 Apr · PMID 42042911 · Full text
Thyroid hormones regulate a complex and interconnected network of metabolic signaling. Thyroid dysfunction is, at present, defined and monitored through circulating thyroid-stimulating hormone (TSH) and free thyroid horm...
Thyroid hormones regulate a complex and interconnected network of metabolic signaling. Thyroid dysfunction is, at present, defined and monitored through circulating thyroid-stimulating hormone (TSH) and free thyroid hormones. However, biochemical normalization does not entirely indicate restoration of metabolic homeostasis. This discrepancy highlights a critical limitation of the current TSH-centric paradigm, which also fails to explain the heterogeneity in cardiometabolic outcomes observed among patients with similar biochemical profiles. Metabolomics, through the analysis of tissue-specific biofluids, could aid in capturing the complex metabolic perturbations that characterize this disease. In this review, we summarize metabolomic signatures typical of thyroid dysfunction, perform a critical evaluation of limitations and variability across studies, and explore the clinical and translational implications of metabolomics in thyroid pathology. In addition, five metabolic hubs influenced by thyroid hormone activity are summarized: (i) lipid and lipoprotein remodeling; (ii) mitochondrial energetics and redox balance; (iii) amino acid metabolism and protein turnover; (iv) gut-liver-thyroid axis and (v) biological impact of subclinical thyroid diseases. Taken together, these findings challenge the sufficiency of a diagnostic model based on TSH measurement and pose metabolomics as a promising tool to refine risk stratification, uncover subclinical vulnerability and guide patient-centered management of thyroid disease. Despite its promise, clinical adoption of metabolomics is hindered by a lack of standardization and complex data interpretation. To overcome these limitations, coupling metabolomics with genomics and transcriptomics may allow its translation into practical application.
Ceramide in Type 2 Diabetes and Obesity: Modulation by Nutrients and Dietary Patterns and Opportunities to Prevent and/or Manage Metabolic-Related Conditions.
Gaggini M, Suman AF, Vassalle C
Metabolites · 2026 Apr · PMID 42042910 · Full text
Ceramides, sphingolipids produced from fatty acids linked to sphingosine and an amide, are structural elements of cellular membranes and lipoproteins. These molecules also retain biological effects in key cellular pathwa...
Ceramides, sphingolipids produced from fatty acids linked to sphingosine and an amide, are structural elements of cellular membranes and lipoproteins. These molecules also retain biological effects in key cellular pathways such as oxidative stress and inflammation, apoptosis, and fibrosis, with a role in the onset and development of many pathophysiological conditions, including obesity, diabetes, and insulin resistance. Increasing evidence suggests that different nutrients and dietary patterns may affect ceramide levels, both negatively (e.g., fructose and the Western diet), whereas others improve the ceramide profile (e.g., ω-3 PUFAs, resveratrol, vitamin D, and the Mediterranean and the Nordic diets). Thus, ceramide nutritional modulation could represent a simple, additive, and reliable tool to improve metabolic health. This review focused on the role of ceramides in the pathophysiology of diabetes and obesity, as well as their pathogenetic mechanisms of action. Ceramides are increasingly recognized as "dynamic metabolic interfaces" linking nutrition and disease. This review aims to address a critical gap by synthesizing recent evidence on how dietary interventions, in addition to pharmacological approaches, can specifically target the enzymatic pathways involved in ceramide synthesis to enhance metabolic health. Thus, this review offers a concentrated analysis of the response of specific ceramide species, such as Cer16:0 and Cer18:0, to distinct dietary factors. Additionally, it incorporates emerging evidence on the role of gut microbiota in the biotransformation of sphingolipids, thereby adding a contemporary dimension to the established nutritional perspective.
Evidence That Oscillations in Glucose Metabolism Promote Optimal Islet Function.
List BP, Whitticar NB, Corbin KL … +1 more , Nunemaker CS
Metabolites · 2026 Apr · PMID 42042909 · Full text
Impairment in pulsatile insulin release contributes to insulin resistance and is one of the earliest markers of developing type 2 diabetes. Insulin delivered to the liver in pulses has a stronger glucose-lowering effect...
Impairment in pulsatile insulin release contributes to insulin resistance and is one of the earliest markers of developing type 2 diabetes. Insulin delivered to the liver in pulses has a stronger glucose-lowering effect than continuous insulin delivery. Whether pulsatility benefits the islet itself is an open question. We previously showed that reducing glucokinase activity with the glucokinase inhibitor D-mannoheptulose (MH) improves function in islets exposed to prolonged hyperglycemic conditions. In this study, we test whether pulsatile vs. continuous delivery impacts the effectiveness of MH in islets. Islets were exposed to high-glucose conditions (20 mM glucose) for 24 or 48 h to induce early adaptations to hyperglycemia. We then used a specially designed perifusion system to impose pulsatile activity by exposing mouse islets to 3 min of MH in 20 mM glucose and 3 min of only high levels of glucose. Islets given intermittent MH for 18 h were compared with continuous delivery of MH at a full (2.5 mM) or half (1.25 mM) dose. MH delivered by the forced oscillatory system reversed the effects of hyperglycemia and restored glucose sensing more effectively than continuous delivery. Specifically, fura-2AM imaging of intracellular calcium showed that islets given pulsatile MH had greater reductions in the elevated basal calcium caused by hyperglycemic conditions, improved the glucose stimulation index, and improved phase 0 response (indicating glucose-stimulated calcium uptake by the endoplasmic reticulum). These findings suggest that the loss of oscillatory glucose metabolism in islets contributes directly to beta-cell dysfunction.
Integrated Metabolomic and Transcriptomic Analyses Reveal Alterations in the Serotonergic Synapse Pathway and a Robust Diagnostic Model in Ulcerative Colitis.
Wang H, Wu H, Fu Y … +5 more , Lv X, Li C, Jin Y, Ge W, Wu Z
Metabolites · 2026 Apr · PMID 42042908 · Full text
OBJECTIVES: To overcome the limitations of invasive diagnostic approaches for ulcerative colitis (UC) diagnosis, this study integrates liquid chromatography-mass spectrometry (LC-MS)-based serum metabolomics with mucosal...
OBJECTIVES: To overcome the limitations of invasive diagnostic approaches for ulcerative colitis (UC) diagnosis, this study integrates liquid chromatography-mass spectrometry (LC-MS)-based serum metabolomics with mucosal transcriptomics to elucidate the interplay between systemic metabolic perturbations and neuroendocrine signaling in UC pathogenesis. METHODS: Serum metabolites and mucosal differentially expressed genes (DEGs) were identified through multi-omics profiling. Key neurotransmitter receptor-related genes (NRRGs) were prioritized using three machine learning algorithms: LASSO, Random Forest, and SVM-RFE. A three-gene diagnostic nomogram was developed and rigorously validated across multiple independent cohorts (GSE48958, GSE73661) using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). RESULTS: The integrated analysis revealed 334 dysregulated metabolites and 3093 DEGs, both converging on the serotonergic synapse pathway. Specific molecular alterations were uncovered, including tryptophan depletion linked to the downregulation of SLC6A4, concomitant with abnormal serotonin accumulation and PTGS2-mediated inflammatory responses. The three-gene signature, HTR3C, RPS6KA6, and NETO2, formed a highly robust diagnostic model, achieving an area under the ROC curve (AUC) exceeding 0.96 in both the training cohort and external validation sets. CONCLUSIONS: This multi-omics study delineates a neuroimmune mechanism in UC centered on dysregulation of the serotonergic synapse. The resulting three-gene nomogram identifies a candidate biomarker signature that demonstrates strong discriminative potential; however, given the exceptionally high performance metrics, these findings should be interpreted as a preliminary diagnostic framework rather than a clinically validated tool, and its efficacy relative to standard markers like CRP or fecal calprotectin requires further investigation in prospective real-world cohorts. Nonetheless, this study provides critical mechanistic insights into gut-brain axis dysfunction in UC.
Effects of Probiotic Supplementation on Gut Microbiota and Fecal Metabolome in Autism Spectrum Disorders: A Secondary Analysis of a Randomized Clinical Trial in Preschoolers.
Guiducci L, Laghi L, Dellarosa N … +4 more , Mastromarino P, Prosperi M, Muratori F, Calderoni S
Metabolites · 2026 Apr · PMID 42042907 · Full text
BACKGROUND/OBJECTIVES: Recently, a randomized clinical trial evaluated whether a six-month probiotic administration could reduce symptom severity in preschool children with Autism Spectrum Disorders (ASD), with (GI) or w...
BACKGROUND/OBJECTIVES: Recently, a randomized clinical trial evaluated whether a six-month probiotic administration could reduce symptom severity in preschool children with Autism Spectrum Disorders (ASD), with (GI) or without (NGI) gastrointestinal symptoms. Significant positive changes were observed only in NGI children. A second explorative study on children prior to intervention identified a fecal metabolome fingerprint associated with ASD severity. Building on these findings, the present study aimed to assess whether metabolomics could monitor changes in ASD severity following probiotic administration using a subset of samples from the same trial. Second, this study aimed to identify fecal metabolites to be monitored in children to predict whether their autism severity may decrease after probiotic or placebo treatment. METHODS: Evaluations of the fecal metabolome and microbiota could be completed on 57 children before and after a double-blind administration of a probiotic mixture or a placebo. RESULTS: In NGI children the probiotic was found to influence the concentration of the amino acids aspartate, leucine, tryptophan, and valine, together with nicotinate and the short chain fatty acids acetate, butyrate, isobutyrate, and propionate. Lactobacilli and showed significant changes in response to probiotic administration ( < 0.05). Acetate, 4-hydroxyphenyl, galactose, proline, and tyramine were identified as key fecal metabolites for prediction purposes. CONCLUSIONS: The present exploratory analysis, despite the small sample size, suggests that fecal metabolomics may provide a useful approach for monitoring and potentially for predicting changes in ASD severity following probiotics administration.
Finishing Barrow Skeletal Muscle Performance and Fatigue Response to Large-Dose Nicotinamide Riboside Supplementation.
Alambarrio DA, Li X, Zedonek SS … +7 more , Willis SE, Proctor JN, Mozafari F, Call JA, Delgado LE, Doran MS, Gonzalez JM
Metabolites · 2026 Apr · PMID 42042906 · Full text
Delaying muscle fatigue could alleviate economic and food security, and welfare concerns associated with transporting market-weight pigs to harvest. Previous research demonstrates barrow nicotinamide riboside () suppleme...
Delaying muscle fatigue could alleviate economic and food security, and welfare concerns associated with transporting market-weight pigs to harvest. Previous research demonstrates barrow nicotinamide riboside () supplementation at varying doses during the last 10 d of finishing shows to be a countermeasure to muscle fatigue by reducing muscle fiber recruitment and increasing mitochondrial DNA expression in a dose-dependent manner. Therefore, this study aims to determine if a greater NR dose further enhances barrow fatigue resistance and characterize muscle mitochondria content and efficiency. Barrows ( = 87) were assigned to one of two dietary NR supplementation doses (): 0 () or 150 () mg/kg body weigh NR administered during the last 14 d of finishing. Muscle () biopsies were collected on supplementation d () 0, 7 and 14 from three hind-leg muscles for NAD+ quantification and mitochondrial DNA expression and efficiency. On days 15 and 16, barrows were subjected to a performance test until they were subjectively exhausted. Electromyography data collection during the performance test were divided into five periods () and included normalized root mean square () from the same muscles. There were no three-way interaction for nRMS ( > 0.83), but there were MUS × TRT and PER × TRT interactions ( < 0.05). During performance testing, 150NR had greater nRMS than 0NR in the () and (; < 0.01), but there were no differences in the semitendinosus (; = 0.77). Treatments did not differ during PER 1 and 2 ( > 0.14) but 150NR had greater nRMS than 0NR during PER 3, 4 and 5 ( < 0.01) across all muscles. There was no three-way interaction for normalized (; = 0.14), but there was a DAY × TRT interaction ( < 0.05). There were no differences between 0NR and 150NR at d 0 ( = 0.95); however, by d 7 and 14, 150NR muscles had greater nNAD+ than 0NR muscles ( < 0.01). There tended to be a three-way interaction for mitochondrial DNA expression ( = 0.09). At supplementation d 14, all 150NR muscles had greater mitochondrial DNA expression and electron transport chain complex I and II activities ( < 0.01). When normalized to citrate synthase activity, electron transport chain complex I and II activity did not differ ( > 0.05). Large-dose NR supplementation appears to support sustained muscle fiber recruitment during prolonged activity and enhance fatigue resilience, primarily through increased NAD+ and mitochondrial biomarkers abundance and not through mitochondrial efficiency.
LC-MS/MS Quantification and Comparative Profiling of Stratum Corneum Ceramides in Human Normal and Dry Skin Subtypes.
Xie A, Zhao Y, Zhao Y … +3 more , Zhao X, Zhu X, Wang J
Metabolites · 2026 Apr · PMID 42042905 · Full text
: Ceramide (Cer) dysregulation in content and composition is linked to various skin conditions, particularly sensitive and dry skin. Existing ceramide quantification methods often lack efficiency, sensitivity, or compreh...
: Ceramide (Cer) dysregulation in content and composition is linked to various skin conditions, particularly sensitive and dry skin. Existing ceramide quantification methods often lack efficiency, sensitivity, or comprehensive analytical capabilities. This study aimed to adopt an optimized LC-MS/MS platform to ensure the acquisition of reliable and accurate ceramide quantitative data, thereby providing robust methodological support for an in-depth investigation of the differences in ceramide profiles among different dry skin subtypes. : Stratum corneum samples were collected via tape stripping from 93 adult female volunteers, who were stratified into sensitive dry skin, non-sensitive dry skin, and normal skin groups based on clinical assessments. Cer metabolomics was analyzed via targeted metabolomics using liquid chromatography-tandem mass spectrometry (LC-MS/MS). : Quantitative analysis of ceramide content in different groups revealed significantly elevated levels of ultra-long-chain ceramides and the atypical Cer (d17:1/24:0) in the SD group, alongside relatively lower levels of shorter-chain ceramides. The NSD group, in contrast, was predominantly enriched in shorter-chain ceramides. Statistical analysis showed statistically significant differences in the levels of Cer (d18:1/24:0), Cer (d18:1/24:1), and Cer (d17:1/24:0) between the SD group and the N group. The UPLC-MS/MS method exhibits a wide linear range and high recovery. : This method offers a reliable tool for the quantitative analysis of ceramides in dermatological, physiological, and pathological research. The findings not only underscore the profound heterogeneity in lipid metabolism underlying different dry skin subtypes but also provide a molecular rationale linking aberrant ceramide chain lengths to compromised barrier integrity and heightened inflammatory susceptibility. The partially validated analytical platform and the specific ceramide signatures revealed herein offer valuable tools and insights for advancing the mechanistic understanding, diagnosis, and targeted intervention of sensitive dry skin.
A Dual-Target Microbial Therapeutic Strategy for Treating Metabolic Diseases: Complementary Mechanisms and Clinical Prospects of and .
Liu S, Wang M, Sun X … +2 more , Jia Z, Huang K
Metabolites · 2026 Apr · PMID 42042904 · Full text
Metabolic diseases, including obesity, type 2 diabetes, and their related complications, have emerged as major global public health challenges. Increasing evidence indicates that gut microbiota dysbiosis contributes to d...
Metabolic diseases, including obesity, type 2 diabetes, and their related complications, have emerged as major global public health challenges. Increasing evidence indicates that gut microbiota dysbiosis contributes to disrupted metabolic homeostasis, chronic low-grade inflammation, and progression of metabolic disorders. Among candidate microbiome-based interventions, () and () have attracted particular attention because they regulate host metabolism through partially distinct yet potentially complementary mechanisms. has been associated with modulation of appetite-related hormones, adipose tissue remodeling, reinforcement of intestinal barrier function, and attenuation of inflammatory signaling. has been linked to strengthening of the mucus barrier, production of beneficial metabolites, and improvement in immune and metabolic homeostasis. However, current evidence remains fragmented across strain-specific studies, heterogeneous formulations, and predominantly single-strain experimental designs, and direct comparative evidence for combined administration is still limited. This review synthesizes current epidemiological, mechanistic, preclinical, and clinical evidence on and , with emphasis on their physiological traits, gut ecological adaptability, pathway-based metabolic effects, and translational challenges in obesity, type 2 diabetes, and related complications. We further highlight the ecological rationale for their functional complementarity and discuss priorities for future combination studies and precision implementation. Overall, the available literature supports functional complementarity and possible additive metabolic benefits, but synergistic effects in humans remain unconfirmed. A clearer understanding of strain identity, active therapeutic entities, delivery strategies, and host context will be essential for advancing this dual-target microbial strategy toward clinically meaningful applications.
A Novel Topology-Based Candidate Reaction Prediction Approach for Gap-Fillings of Genome-Scale Metabolic Models.
Qu J, Wang K
Metabolites · 2026 Apr · PMID 42042903 · Full text
: It is significant to predict and fill metabolic reaction gaps (gap-fillings) for reconstructions of high-quality genome-scale metabolic models (GEMs). Currently, many existing optimization-based gap-filling methods hav...
: It is significant to predict and fill metabolic reaction gaps (gap-fillings) for reconstructions of high-quality genome-scale metabolic models (GEMs). Currently, many existing optimization-based gap-filling methods have to rely on phenotypic data, while performances of topology-based approaches by deep learning algorithms need to be further improved. : This paper proposes a novel topology-based approach (GHCN-SE) of predicting confidence scores of candidate reactions, which can be used for gap-fillings of GEMs. The topological features of GEMs are fully extracted by simultaneously using graph and hypergraph convolutional networks, such that both associations of metabolites in the same reaction and higher-order interactions of metabolites within reactions can be captured. After the feature fusion, we further employ the squeeze-and-excitation network to enhance features. : The reaction prediction and reaction recovery experiments through 5-fold cross validations on 108 high-quality BiGG GEMs show that the proposed GHCN-SE is superior to other related methods. The ablation study further demonstrates the contributions of the graph convolutional network, hypergraph convolutional network, and squeeze-and-excitation network in GHCN-SE. In addition, the visualization study interprets the effectiveness of GHCN-SE. : For potential applications in metabolic engineering, biomedicine, etc., this proposed GHCN-SE can be used to further improve the phenotypic prediction accuracy of the draft GEM generated from automated reconstruction tools.
Circadian Reprogramming by Combined Time-Restricted Feeding and Exercise Improves Metabolic Homeostasis in Diabetes.
Li Q, Zhang G, Zhou S … +1 more , Xie Y
Metabolites · 2026 Apr · PMID 42042902 · Full text
BACKGROUND: Circadian disruption exacerbates type 2 diabetes mellitus (T2DM). Time-restricted feeding (TRF) and exercise (EX) improve metabolic health, but their combinatory effect remains unclear. This study investigate...
BACKGROUND: Circadian disruption exacerbates type 2 diabetes mellitus (T2DM). Time-restricted feeding (TRF) and exercise (EX) improve metabolic health, but their combinatory effect remains unclear. This study investigated whether combined TRF and EX additively ameliorates metabolism via circadian reprogramming in db/db mice. METHODS: Eight-week-old male db/db mice were assigned to control (Con), diabetic model (DM), TRF (8 h feeding window), EX (treadmill, 60 min/day, 5 days/week), or combined TRF + EX groups for 8 weeks ( = 8/group). Body weight, glucose/insulin tolerance, and 24 h energy metabolism (CLAMS) were assessed. Mitochondrial function, oxidative stress, inflammation, and expression of mitophagy (Pink1, Park2, Bnip3, Fundc1) and thermogenic (Ucp1, Pgc1a, Prdm16, Cidea) genes were measured. RESULTS: Compared with the con group, DM mice showed obesity, hyperglycemia and blunted circadian metabolic rhythm. The TRF and EX groups improved these defects. Specifically, combined TRF + EX reduced fasting blood glucose from 25.3 ± 3.1 mmol/L (DM) to 13.2 ± 1.8 mmol/L ( < 0.05), body weight from 49.8 ± 2.5 g to 39.5 ± 1.7 g ( < 0.05), and body fat percentage from 45.6 ± 3.2% to 32.1 ± 2.2% ( < 0.05). GTT area under the curve (AUC) decreased from 3711.0 ± 186.5 (DM) to 2118.0 ± 112.4 ( < 0.05), and ITT AUC decreased from 2617.5 ± 135.8 to 1260.0 ± 68.9 ( < 0.05). Notably, the combination of TRF + EX produced greater effects than either intervention alone: body weight, fasting blood glucose, and glucose/insulin tolerance were greatly improved ( < 0.05). In addition, compared with the DM group, the diurnal metabolic amplitude and phase were improved in the TRF or EX group; the combination group showed further improvements in these parameters. Furthermore, TRF and EX each resulted in significantly higher expression of key thermogenic genes (Ucp1, Pgc1a, Prdm16, Cidea) in white adipose tissue (WAT) and brown adipose tissue (BAT) ( < 0.05), and the TRF + EX group showed the highest expression levels. Combined intervention also restored skeletal muscle SOD activity (31.2 ± 2.9 U/mg prot vs. DM 20.1 ± 2.5 U/mg prot, < 0.05) and reduced serum TNF-α (28.5 ± 4.5 pg/mL vs. DM 65.8 ± 8.5 pg/mL, < 0.05) and IL-6 (21.6 ± 3.8 pg/mL vs. DM 50.3 ± 7.1 pg/mL, < 0.05). CONCLUSIONS: TRF + EX additively restores metabolic homeostasis in diabetes by re-entraining circadian energy rhythms, improving mitochondrial quality, and activating adipose thermogenesis, supporting further investigation of integrated lifestyle timing as a potential therapeutic strategy.
Early Cytokine Profiles in Critically Ill Patients with COVID-19 and Their Association with Mortality.
Gamarra-Morales Y, Molina-López J, Machado-Casas JF … +4 more , Herrera-Quintana L, Vázquez-Lorente H, Pérez-Villares JM, Planells E
Metabolites · 2026 Apr · PMID 42042901 · Full text
BACKGROUND/OBJECTIVES: The purpose of this study was to (i) determine the levels of interleukins in patients with COVID-19 admitted to the Intensive Care Unit (ICU) and (ii) evaluate their early dynamics, as well as (iii...
BACKGROUND/OBJECTIVES: The purpose of this study was to (i) determine the levels of interleukins in patients with COVID-19 admitted to the Intensive Care Unit (ICU) and (ii) evaluate their early dynamics, as well as (iii) assess their relationships with morbidity and mortality. METHODS: This was a prospective analytical study of critically ill patients with COVID-19 who were monitored from admission to three days of stay in the ICU. Circulating levels of IL-1β, IL-2, IL-6, IL-7, IL-8, IL-10, and tumour necrosis factor-alpha (TNF-α) were measured. Cytokine levels were analysed in relation to clinical severity parameters and 28-day mortality. RESULTS: A dynamic cytokine response was observed during the first 72 h, with a significant increase in TNF-α levels and a decrease in IL-10 and IL-1β. Non-survivors showed higher TNF-α levels than survivors. In the multivariable analysis adjusted for clinical severity, TNF-α remained independently associated with 28-day mortality, whereas other cytokines did not retain statistical significance. The overall predictive performance of cytokines was moderate. CONCLUSIONS: Early cytokine dynamics reflect the evolving inflammatory response in critically ill COVID-19 patients. TNF-α emerges as an independent predictor of mortality, supporting its role as a relevant biomarker of adverse outcomes. Although its predictive capacity is moderate, TNF-α may provide clinically meaningful information for risk stratification when integrated with established clinical and laboratory parameters.
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