Independent component analysis based gene co-expression network inference (ICAnet) to decipher functional modules for better single-cell clustering and batch integration.

With the tremendous increase of publicly available single-cell RNA-sequencing (scRNA-seq) datasets, bioinformatics methods based on gene co-expression network are becoming efficient tools for analyzing scRNA-seq data, improving cell type prediction accuracy and in turn facilitating biological discovery. However, the current methods are mainly based on overall co-expression correlation and overlook co-expression that exists in only a subset of cells, thus fail to discover certain rare cell types and sensitive to batch effect. Here, we developed independent component analysis-based gene co-expression network inference (ICAnet) that decomposed scRNA-seq data into a series of independent gene expression components and inferred co-expression modules, which improved cell clustering and rare cell-type discovery. ICAnet showed efficient performance for cell clustering and batch integration using scRNA-seq datasets spanning multiple cells/tissues/donors/library types. It works stably on datasets produced by different library construction strategies and with different sequencing depths and cell numbers. We demonstrated the capability of ICAnet to discover rare cell types in multiple independent scRNA-seq datasets from different sources. Importantly, the identified modules activated in acute myeloid leukemia scRNA-seq datasets have the potential to serve as new diagnostic markers. Thus, ICAnet is a competitive tool for cell clustering and biological interpretations of single-cell RNA-seq data analysis.

The systemic inflammatory response syndrome in acute antipsychotic poisoning.

The purpose of this study was to investigate the mutual effect of systemic inflammatory response syndrome (SIRS) accompanied with fibrinolysis, endotoxemia, and coagulation in severe cases of antipsychotic poisoning. A total of 199 patients were examined, of which 71 were men and 128 were women. The age of the patients was from 22 to 63 years, (45.3 ± 6.1 years on average). According to the results of the course of therapy, the patients were divided into two groups. In the blood plasma, the content of C-reactive protein, fibrinogen and its proteolysis products (oligopeptides, D-dimers), interleukin-6 were determined. In the first 1 to 3 days, in group 1, the level of interleukin-6 decreased and approached the normal level (P ≤ .05). The opposite trend continued throughout the observation of patients from group 2-their levels of interleukin-6 increased day by day (P ≤ .05). The concentration of D-dimer already in 1 day after admission to intensive care in patients from group 2 exceeded the norm by 14 times (P ≤ .05). The level of D-dimer correlated with the level of oligopeptides in blood plasma upon admission, as well as for 3 and 5 days after admission to intensive care: 0.36, 0.76 at P ≤ .05, 0.94 at P ≤ .01, respectively. Similar correlations were obtained for the content of oligopeptides in urine and the level of D-dimer: 0.55, 0.85 at P ≤ .05, 0.93 at P ≤ .01. In this regard, the most pronounced correlation is that between the SIRS score, plasma D-dimer level, and the plasma level of the D-dimer derivatives, oligopeptides.

Research on the Mechanism of HMGB1 Regulating Autoimmune Encephalomyelitis by Regulating NF-κB.

Background: Autoimmune encephalomyelitis is a clinical condition in which memory and cognition is affected badly and is also associated with lower levels of consciousness or even coma in worse scenarios. It is a noninfectious condition which involves immune oriented inflammation. Objective: The study's goal was to figure out what was causing the problem HMGB1 involved in regulating the autoimmune encephalomyelitis by regulating NF-κB. Materials and Methods: The expressions of HMGB1, miR-129-5p, and TLR4/NF-κB signalling pathway-related proteins were measured by qRT-PCR. To explore the differences among its control, models, and all groups, histopathology, immunohistochemistry, and immunofluorescence tests were performed. Results: According to the findings, miR-129-5p is in charge of suppressing HMGB1 production and inhibiting the TLR4/NF-κB signalling pathway. On development of autoimmune encephalomyelitis, neurons in the hippocampus area got injured in the miR-129-5p inhibitors class. In the miR-129-5p inhibitor class, expression of miR-129-5p reduced and HMGB1 elevated, increasing neuronal inflammation and damage. Impairment in the hippocampus, on the either side, was shown to be reduced in HMGB1 shRNA, miR-129-5p mimics, and TLR4/NF-κB classes. Conclusion: According to the study's findings, there is indeed a link among increased miR-129-5p and decreased HMGB1 expression and also suppression of the TLR4/NF-κB signal transduction pathway in autoimmune encephalomyelitis in the miR-129-5p inhibitors group. As a result, we may assume the autoimmune disease illness has progressed once concentrations of HMGB1, TLR4/NF-κB, and miR-129-5p have decreased.

Single-Cell Transcriptome Analysis Reveals Six Subpopulations Reflecting Distinct Cellular Fates in Senescent Mouse Embryonic Fibroblasts.

Replicative senescence is a hallmark of aging, which also contributes to individual aging. Mouse embryonic fibroblasts (MEFs) provide a convenient replicative senescence model. However, the heterogeneity of single MEFs during cellular senescence has remained unclear. Here, we conducted single-cell RNA sequencing on senescent MEFs. Principal component analysis showed obvious heterogeneity among these MEFs such that they could be divided into six subpopulations. Three types of gene expression analysis revealed distinct expression features of these six subpopulations. Trajectory analysis revealed three distinct lineages during MEF senescence. In the main lineage, some senescence-associated secretory phenotypes were upregulated in a subset of cells from senescent clusters, which could not be distinguished in a previous bulk study. In the other two lineages, a possibility of escape from cell cycle arrest and coupling between translation-related genes and ATP synthesis-related genes were also discovered. Additionally, we found co-expression of transcription factor HOXD8 coding gene and its potential target genes in the main lineage. Overexpression of Hoxd8 led to senescence-associated phenotypes, suggesting HOXD8 is a new regulator of MEF senescence. Together, our single-cell sequencing on senescent MEFs largely expanded the knowledge of a basic cell model for aging research.