An analysis of neutrophil-to-lymphocyte ratios and monocyte-to-lymphocyte ratios with six-month prognosis after cerebral contusions.

Background and purpose: Neutrophil-to-lymphocyte ratio (NLR) and monocyte-to-lymphocyte ratio (MLR) have been identified as potential prognostic markers in various conditions, including cancer, cardiovascular disease, and stroke. This study aims to investigate the dynamic changes of NLR and MLR following cerebral contusion and their associations with six-month outcomes. Methods: Retrospective data were collected from January 2016 to April 2020, including patients diagnosed with cerebral contusion and discharged from two teaching-oriented tertiary hospitals in Southern China. Patient demographics, clinical manifestations, laboratory test results (neutrophil, monocyte, and lymphocyte counts) obtained at admission, 24 hours, and one week after cerebral contusion, as well as outcomes, were analyzed. An unfavorable outcome was defined as a Glasgow Outcome Score (GOS) of 0-3 at six months. Logistic regression analysis was performed to identify independent predictors of prognosis, while receiver characteristic curve analysis was used to determine the optimal cutoff values for NLR and MLR. Results: A total of 552 patients (mean age 47.40, SD 17.09) were included, with 73.19% being male. Higher NLR at one-week post-cerebral contusion (adjusted OR = 4.19, 95%CI, 1.16 - 15.16, P = 0.029) and higher MLR at admission and at 24 h (5.80, 1.40 - 24.02, P = 0.015; 9.06, 1.45 - 56.54, P = 0.018, respectively) were significantly associated with a 6-month unfavorable prognosis after adjustment for other risk factors by multiple logistic regression. The NLR at admission and 24 hours, as well as the MLR at one week, were not significant predictors for a 6-month unfavorable prognosis. Based on receiver operating characteristic curve analysis, the optimal thresholds of NLR at 1 week and MLR at admission after cerebral contusion that best discriminated a unfavorable outcome at 6-month were 6.39 (81.60% sensitivity and 70.73% specificity) and 0.76 (55.47% sensitivity and 78.26% specificity), respectively. Conclusion: NLR measured one week after cerebral contusion and MLR measured at admission may serve as predictive markers for a 6-month unfavorable prognosis. These ratios hold potential as parameters for risk stratification in patients with cerebral contusion, complementing established biomarkers in diagnosis and treatment. However, further prospective studies with larger cohorts are needed to validate these findings.

Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents.

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are classified as major mental disorders and together account for the second-highest global disease burden, and half of these patients experience symptom onset in adolescence. Several studies have reported both similar and unique features regarding the risk factors and clinical symptoms of these three disorders. However, it is still unclear whether these disorders have similar or unique metabolic characteristics in adolescents. We conducted a metabolomics analysis of plasma samples from adolescent healthy controls (HCs) and patients with MDD, BD, and SCZ. We identified differentially expressed metabolites between patients and HCs. Based on the differentially expressed metabolites, correlation analysis, metabolic pathway analysis, and potential diagnostic biomarker identification were conducted for disorders and HCs. Our results showed significant changes in plasma metabolism between patients with these mental disorders and HCs; the most distinct changes were observed in SCZ patients. Moreover, the metabolic differences in BD patients shared features with those in both MDD and SCZ, although the BD metabolic profile was closer to that of MDD than to SCZ. Additionally, we identified the metabolites responsible for the similar and unique metabolic characteristics in multiple metabolic pathways. The similar significant differences among the three disorders were found in fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, and proline metabolism. Interestingly, we found unique characteristics of significantly altered glycolysis, glycerophospholipid, and sphingolipid metabolism in SCZ; lysine, cysteine, and methionine metabolism in MDD and BD; and phenylalanine, tyrosine, and aspartate metabolism in SCZ and BD. Finally, we identified five panels of potential diagnostic biomarkers for MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, and BD-SCZ comparisons. Our findings suggest that metabolic characteristics in plasma vary across psychiatric disorders and that critical metabolites provide new clues regarding molecular mechanisms in these three psychiatric disorders.

AKT and MAPK signaling pathways in hippocampus reveals the pathogenesis of depression in four stress-induced models.

Major depressive disorder (MDD) is a highly heterogeneous psychiatric disorder. The pathogenesis of MDD remained unclear, and it may be associated with exposure to different stressors. Most previous studies have focused on molecular changes in a single stress-induced depression model, which limited the identification of the pathogenesis of MDD. The depressive-like behaviors were induced by four well-validated stress models in rats, including chronic unpredictable mild stress, learned helplessness stress, chronic restraint stress and social defeat stress. We applied proteomic and metabolomic to investigate molecular changes in the hippocampus of those four models and revealed 529 proteins and 98 metabolites. Ingenuity Pathways Analysis (IPA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified differentially regulated canonical pathways, and then we presented a schematic model that simulates AKT and MAPK signaling pathways network and their interactions and revealed the cascade reactions. Further, the western blot confirmed that p-AKT, p-ERK12, GluA1, p-MEK1, p-MEK2, p-P38, Syn1, and TrkB, which were changed in at least one depression model. Importantly, p-AKT, p-ERK12, p-MEK1 and p-P38 were identified as common alterations in four depression models. The molecular level changes caused by different stressors may be dramatically different, and even opposite, between four depression models. However, the different molecular alterations converge on a common AKT and MAPK molecular pathway. Further studies of these pathways could contribute to a better understanding of the pathogenesis of depression, with the ultimate goal of helping to develop or select more effective treatment strategies for MDD.