Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex.

Background: Major depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation. Methods: We systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls. Results: Differential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power. Conclusions: The biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Alterations of the gut microbiota in patients with schizophrenia.

Introduction: Schizophrenia is a complex psychiatric disorder, of which molecular pathogenesis remains largely unknown. Accumulating evidence suggest that gut microbiota may affect brain function via the complex gut-brain axis, which may be a potential contributor to schizophrenia. However, the alteration of gut microbiota showed high heterogeneity across different studies. Therefore, this study aims to identify the consistently altered gut microbial taxa associated with schizophrenia. Methods: We conducted a systematic search and synthesis of the up-to-date human gut microbiome studies on schizophrenia, and performed vote counting analyses to identify consistently changed microbiota. Further, we investigated the effects of potential confounders on the alteration of gut microbiota. Results: We obtained 30 available clinical studies, and found that there was no strong evidence to support significant differences in α-diversity and ß-diversity between schizophrenic patients and healthy controls. Among 428 differential gut microbial taxa collected from original studies, we found that 8 gut microbial taxa were consistently up-regulated in schizophrenic patients, including Proteobacteria, Gammaproteobacteria, Lactobacillaceae, Enterobacteriaceae, Lactobacillus, Succinivibrio, Prevotella and Acidaminococcus. While 5 taxa were consistently down-regulated in schizophrenia, including Fusicatenibacter, Faecalibacterium, Roseburia, Coprococcus and Anaerostipes. Discussion: These findings suggested that gut microbial changes in patients with schizophrenia were characterized by the depletion of anti-inflammatory butyrate-producing genera, and the enrichment of certain opportunistic bacteria genera and probiotics. This study contributes to further understanding the role of gut microbiota in schizophrenia, and developing microbiota-based diagnosis and therapy for schizophrenia.

Combined Experimental and Density Functional Theory Study on the Mechanism of the Selective Catalytic Reduction of NO with NH3 over Metal-Free Carbon-Based Catalysts.

Metal-free carbon-based catalysts are attracting much attention in the low-temperature selective catalytic reduction of NOx with NH3 (NH3-SCR). However, the mechanism of the NH3-SCR reaction on carbon-based catalysts is still controversial, which severely limits the development of carbon-based SCR catalysts. Herein, we successfully reconstructed carbon-based catalysts through oxidation treatment with nitric acid, thereby enhancing their low-temperature activity in NH3-SCR. Combining experimental results and density functional theory (DFT) calculations, we proposed a previously unreported NH3-SCR reaction mechanism over carbon-based catalysts. We demonstrated that C-OH and C-O-C groups not only effectively activate NH3 but also remarkedly promote the decomposition of intermediate NH2NO. This study enhances the understanding of the NH3-SCR mechanism on carbon-based catalysts and paves the way to develop low-temperature metal-free SCR catalysts.

Uncovering the Dinuclear Mechanism of NO2-Involved NH3-SCR over Supported V2O5/TiO2 Catalysts.

Commercial vanadium oxide catalysts exhibit high efficiency for the selective catalytic reduction (SCR) of NO with NH3, especially in the presence of NO2 (i.e., occurrence of fast NH3-SCR). The high-activity sites and their working principle for the fast NH3-SCR reaction, however, remain elusive. Here, by combining in situ spectroscopy, isotopic labeling experiments, and density functional theory (DFT) calculations, we demonstrate that polymeric vanadyl species act as the main active sites in the fast SCR reaction because the coupling effect of the polymeric structure alters the elementary reaction step and effectively avoids the high energy barrier of the rate-determining step over monomeric vanadyl species. This study unveils the high-activity dinuclear mechanism of the NO2-involved SCR reaction over vanadia-based catalysts and provides a fundamental basis for developing high-efficiency and low V2O5-loading SCR catalysts.

Integrated pathway and network analyses of metabolomic alterations in peripheral blood of patients with depression.

Depression is a serious mental illness, but the molecular mechanisms of depression remain unclear. Previous research has reported metabolomic changes in the blood of patients with depression, while integrated analysis based on these altered metabolites was still lacking. The objective of this study was to integrate metabolomic changes to reveal the underlying molecular alternations of depression. We retrieved altered metabolites in the blood of patients with depression from the MENDA database. Pathway analysis was conducted to explore enriched pathways based on candidate metabolites. Pathway crosstalk analysis was performed to explore potential correlations of these enriched pathways, based on their shared candidate metabolites. Moreover, potential interactions of candidate metabolites with other biomolecules such as proteins were assessed by network analysis. A total of 854 differential metabolite entries were retrieved in peripheral blood of patients with depression, including 555 unique candidate metabolites. Pathway analysis identified 215 significantly enriched pathways, then pathway crosstalk analysis revealed that these pathways were clustered into four modules, including amino acid metabolism, nucleotide metabolism, energy metabolism and others. Additionally, eight molecular networks were identified in the molecular network analysis. The main functions of these networks involved amino acid metabolism, molecular transport, inflammatory responses and others. Based on integrated analysis, our study revealed pathway-based modules and molecular networks associated with depression. These results will contribute to the underlying knowledge of the molecular mechanisms in depression.

Unveiling the Origin of Selectivity in the Selective Catalytic Reduction of NO with NH3 over Oxide Catalysts.

The trade-off between activity and selectivity is a century-old puzzle in catalysis. In the selective catalytic reduction of NO with NH3 (NH3-SCR), various typical oxide catalysts exhibit distinct characteristics of activity and selectivity: Mn-based catalysts show outstanding low-temperature activity and poor N2 selectivity, mainly caused by N2O formation, while Fe- and V-based catalysts possess inverse characteristics. The underlying mechanism, however, has remained elusive. In this study, by combining experimental measurements and density functional theory calculations, we demonstrate that the distinct difference in the selectivity of oxide catalysts is determined by the gap in the energy barriers between N2 formation and N2O formation from the consumption of the key intermediate NH2NO. The gaps in the energy barriers follow the order of α-MnO2 < α-Fe2O3 < V2O5/TiO2, in correspondence with the order of N2 selectivity of the catalysts. This work discloses the intrinsic link between the target reaction and side reactions in the selective catalytic reduction of NO, providing fundamental insights into the origin of selectivity.