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• Overview of recent findings concerning ischemic stroke and the liver. • The liver contributes to post-stroke immunosuppression and stress-induced hyperglycemia. • Increased hepatic glutathione production could combat inflammation and oxidative stress after acute ischemic stroke. Focal brain damage and neurological deficits are the direct consequences of acute ischemic stroke (AIS). In addition, cerebral ischemia causes systemic alterations across peripheral organs. Dysregulation of the autonomic and endocrine systems as well as the release of brain-derived pro-inflammatory mediators trigger a peripheral immune response and systemic inflammation. As a key metabolic organ, the liver contributes not only to post-stroke immunosuppression but also to stress-induced hyperglycemia. At the same time, increased ketogenesis and glutathione production in the liver are likely to combat inflammation and oxidative stress after AIS. The closely linked lipid metabolism could regulate both glucose and glutathione homeostasis. In addition, increased hepatic very low-density lipoprotein (VLDL) secretion may improve the availability of phospholipids, polyunsaturated fatty acids (PUFAs) and glutathione after AIS. This review provides an overview of recent findings concerning ischemic stroke and the liver and discusses the therapeutic potential of targeting the hepatic metabolism to improve patient outcome after stroke. [ABSTRACT FROM AUTHOR]

Background: Hyperglycaemia is frequent in acute ischemic stroke and denotes a bad prognosis, even in the absence of pre-existing diabetes. However, in clinical trials treatment of elevated glucose levels with insulin did not improve stroke outcome, suggesting that collateral effects rather than hyperglycaemia itself aggravate ischemic brain damage. As reactive glucose metabolites, glyoxal and methylglyoxal are candidates for mediating the deleterious effects of hyperglycaemia in acute stroke. Methods: In 135 patients with acute stroke, we used liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) to measure glyoxal, methylglyoxal and several of their glycated amino acid derivatives in serum. Results were verified in a second cohort of 61 stroke patients. The association of serum concentrations with standard stroke outcome scales (NIHSS, mRS) was tested. Results: Glucose, glyoxal, methylglyoxal, and the glyoxal-derived glycated amino acid Nδ-(5-hydro-4-imidazolon-2-yl)ornithine (G-H1) were positively correlated with a bad stroke outcome at 3 months as measured by mRS90, at least in one of the two cohorts. However, the glycated amino acids Nε-carboxyethyllysine (CEL) and in one cohort pyrraline showed an inverse correlation with stroke outcome probably reflecting lower food intake in severe stroke. Patients with a poor outcome had higher serum concentrations of glyoxal and methylglyoxal. Conclusions: The glucose-derived α-dicarbonyl glyoxal and glycated amino acids arising from a reaction with glyoxal are associated with a poor outcome in ischemic stroke. Thus, lowering α-dicarbonyls or counteracting their action could be a therapeutic strategy for hyperglycaemic stroke. [ABSTRACT FROM AUTHOR]

The increasing prevalence of depression requires more effective therapy and the understanding of antidepressants' mode of action. We carried out untargeted metabolomics of the prefrontal cortex of rats exposed to chronic social isolation (CSIS), a rat model of depression, and/or fluoxetine treatment using liquid chromatography–high resolution mass spectrometry. The behavioral phenotype was assessed by the forced swim test. To analyze the metabolomics data, we employed univariate and multivariate analysis and biomarker capacity assessment using the receiver operating characteristic (ROC) curve. We also identified the most predictive biomarkers using a support vector machine with linear kernel (SVM-LK). Upregulated myo-inositol following CSIS may represent a potential marker of depressive phenotype. Effective fluoxetine treatment reversed depressive-like behavior and increased sedoheptulose 7-phosphate, hypotaurine, and acetyl-L-carnitine contents, which were identified as marker candidates for fluoxetine efficacy. ROC analysis revealed 4 significant marker candidates for CSIS group discrimination, and 10 for fluoxetine efficacy. SVM-LK with accuracies of 61.50% or 93.30% identified a panel of 7 or 25 predictive metabolites for depressive-like behavior or fluoxetine effectiveness, respectively. Overall, metabolic fingerprints combined with the ROC curve and SVM-LK may represent a new approach to identifying marker candidates or predictive metabolites for ongoing disease or disease risk and treatment outcome. [ABSTRACT FROM AUTHOR]