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Oxaliplatin (L‐OHP), a third‐generation platinum‐based anti‐tumor drug, finds widespread application in the first‐line treatment of metastatic colorectal cancer. Despite its efficacy, the drug's usage is curtailed by a litany of side effects, with L‐OHP‐induced peripheral neuropathy (OIPN) being the most debilitating. This condition can be classified into varying degrees of severity. Employing serum metabolomics, a high‐sensitivity, high‐throughput technique, holds promise as a method to identify biomarkers for clinical assessment and monitoring of OIPN patients across different severity levels. In our study, we analyzed serum metabolites in patients with different OIPN levels using ultra‐performance liquid chromatography‐high resolution mass spectrometry. By employing statistical analyses and pathway enrichment studies, we aimed to identify potential biomarkers and metabolic pathways. Our findings characterized the serum metabolic profiles of patients with varying OIPN levels. Notably, pathway analysis revealed a significant correlation with lipid metabolism, amino acid metabolism, and energy metabolism. Multivariate statistical analysis and receiver operator characteristic curve evaluation pointed to anhalamine and glycochenodeoxycholic acid as potential biomarkers for OIPN C and A, which suggest that serum metabolomics may serve as a potent tool for exploring the metabolic status of patients suffering from diverse diseases and for discovering novel biomarkers. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to discover differential metabolites and pathways underlying infrequent gout flares (InGF) and frequent gout flares (FrGF) using metabolomics and to establish a predictive model by machine learning (ML) algorithms. Methods: Serum samples from a discovery cohort of 163 patients with InGF and 239 patients with FrGF were analyzed by mass spectrometry–based untargeted metabolomics to profile differential metabolites and explore dysregulated metabolic pathways using pathway enrichment analysis and network propagation–based algorithms. ML algorithms were performed to establish a predictive model based on selected metabolites, which was further optimized by a quantitative targeted metabolomics method and validated in an independent validation cohort with 97 participants with InGF and 139 participants with FrGF. Results: A total of 439 differential metabolites between InGF and FrGF groups were identified. Top dysregulated pathways included carbohydrates, amino acids, bile acids, and nucleotide metabolism. Subnetworks with maximum disturbances in the global metabolic networks featured cross‐talk between purine metabolism and caffeine metabolism, as well as interactions among pathways involving primary bile acid biosynthesis, taurine and hypotaurine metabolism, alanine, aspartate, and glutamate metabolism, suggesting epigenetic modifications and gut microbiome in metabolic alterations underlying InGF and FrGF. Potential metabolite biomarkers were identified using ML‐based multivariable selection and further validated by targeted metabolomics. Area under receiver operating characteristics curve for differentiating InGF and FrGF achieved 0.88 and 0.67 for the discovery and validation cohorts, respectively. Conclusion: Systematic metabolic alterations underlie InGF and FrGF, and distinct profiles are associated with differences in gout flare frequencies. Predictive modeling based on selected metabolites from metabolomics can differentiate InGF and FrGF. [ABSTRACT FROM AUTHOR]

Background: Agitation is common in subarachnoid hemorrhage (SAH), and sedation with midazolam, propofol and dexmedetomidine is essential in agitation management. Previous research shows the tendency of dexmedetomidine and propofol in improving long-term outcome of SAH patients, whereas midazolam might be detrimental. Brain metabolism derangement after SAH might be interfered by sedatives. However, how sedatives work and whether the drugs interfere with patient outcome by altering cerebral metabolism is unclear, and the comprehensive view of how sedatives regulate brain metabolism remains to be elucidated. Methods: For cerebrospinal fluid (CSF) and extracellular space of the brain exchange instantly, we performed a cohort study, applying CSF of SAH patients utilizing different sedatives or no sedation to metabolomics. Baseline CSF metabolome was corrected by selecting patients of the same SAH and agitation severity. CSF components were analyzed to identify the most affected metabolic pathways and sensitive biomarkers of each sedative. Markers might represent the outcome of the patients were also investigated. Results: Pentose phosphate pathway was the most significantly interfered (upregulated) pathway in midazolam (p = 0.0000107, impact = 0.35348) and propofol (p = 0.00000000000746, impact = 0.41604) groups. On the contrary, dexmedetomidine decreased levels of sedoheptulose 7-phosphate (p = 0.002) and NADP (p = 0.024), and NADP is the key metabolite and regulator in pentose phosphate pathway. Midazolam additionally augmented purine synthesis (p = 0.00175, impact = 0.13481) and propofol enhanced pyrimidine synthesis (p = 0.000203, impact = 0.20046), whereas dexmedetomidine weakened pyrimidine synthesis (p = 0.000000000594, impact = 0.24922). Reduced guanosine diphosphate (AUC of ROC 0.857, 95%CI 0.617–1, p = 0.00506) was the significant CSF biomarker for midazolam, and uridine diphosphate glucose (AUC of ROC 0.877, 95%CI 0.631–1, p = 0.00980) for propofol, and succinyl-CoA (AUC of ROC 0.923, 95%CI 0.785–1, p = 0.000810) plus adenosine triphosphate (AUC of ROC 0.908, 95%CI 0.6921, p = 0.00315) for dexmedetomidine. Down-regulated CSF succinyl-CoA was also associated with favorable outcome (AUC of ROC 0.708, 95% CI: 0.524–0.865, p = 0.029333). Conclusion: Pentose phosphate pathway was a crucial target for sedatives which alter brain metabolism. Midazolam and propofol enhanced the pentose phosphate pathway and nucleotide synthesis in poor-grade SAH patients, as presented in the CSF. The situation of dexmedetomidine was the opposite. The divergent modulation of cerebral metabolism might further explain sedative pharmacology and how sedatives affect the outcome of SAH patients. [ABSTRACT FROM AUTHOR]

Saposhnikovia divaricata (SD), a Chinese crude drug, has long been recognized for therapeutic effect to rheumatoid arthritis (RA). At present, the mechanisms of SD treatment in RA have not been fully understood especially on the perspective of metabolomics. Aim of the study : To study the pharmacodynamic effects of Saposhnikovia divaricata decoction on CIA rats, and explore the therapeutic mechanism by metabolomics methods. Wistar rats were randomly divided into normal group, CIA model group, dexamethasone group and SD decoction groups (10 g crude drug/kg, 5 g crude drug/kg and 2.5 g crude drug/kg of SDD). Body weight, arthritis scores, serum cytokine levels and histopathological parameters of rats were assessed. A metabolomics method based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOFMS) was established to collect the metabolic profiles of rats and explore the metabolic changes that occurred after SDD treatment. SDD showed its protective effect on the affected joints, especially in the middle dosage group of SDD. Eighteen and 13 potential biomarkers for the SDD treatment of CIA rats were identified in the plasma and urine, respectively. SDD could regulate the disturbed metabolic pathways including tryptophan metabolism, glycerophospholipid catabolism, primary bile acid biosynthesis and fatty acid metabolism. In summary, SDD treatment could effectively alleviate symptoms of RA and regulate metabolic disorders in CIA rats. Image 1 • Saposhnikovia divaricata decoction could effectively alleviate symptoms of CIA rats. • Differentially biomarkers were identified for the SDD treatment of CIA. • Saposhnikovia divaricata decoction could regulate the disturbed metabolic pathways. [ABSTRACT FROM AUTHOR]