Choir Participation and Community Wellbeing: A Social Identity Approach

Research about choir and community wellbeing shows that there is a positive association between the two constructs. In addition, the positive association between choir participation and community wellbeing seems to be stronger if the activity fosters a place to socialize and gain an identity through the leisure pursuit. This research looks at the relationship between choir participation and community wellbeing using Social Identity Approach (SIA). SIA suggests that participants benefit from a leisure activity to the degree in which they identify themselves with the group. This research takes SIA into consideration to explain the positive relationship between choir participation and community wellbeing, where social opportunities and social identity mediates the positive association between participating in a choir and community wellbeing. A serial mediation model was designed to test the positive association between the two variables. Social opportunities and social identity were added to the mediation model to test their indirect effect on choir participations positive effect on wellbeing. Social opportunities variable was placed as the antecedent variable to consequent variable of social identity. Findings show that choir participation is positively associated to community wellbeing. In addition, results show that the positive effect is fully mediated by social opportunities and social identity provided by the choir

Neonatal hyperbilirubinemia and G71R mutation of the UGT1A1 gene in Turkish patients.

Objective. Nonphysiologic hyperbilirubinemia of unexplained cause is prevalent among Turkish newborns, suggesting that there might be genetic risk factors in this population. Mutation of the UGT1A1 gene, glycine to arginine at codon 71 (G71R), is related to the development of neonatal jaundice in East Asian populations but the frequency of this mutation is rare among Caucasian populations. There are insufficient data on the G71R mutation in Turkish newborns with hyperbilirubinemia. The aim of this study was to investigate the genotypic distribution of the G71R mutation and its relationship with nonphysiologic hyperbilirubinemia of unexplained cause in Turkish newborns

Distribution of monocyte chemoattractant protein-1 (MCP-1 A-2518G) and chemokine receptor (CCR2-V64.) gene variants in hyperbilirubinemic newborns

Hyperbilirubinemia is one of the most crucial syndromes, which is characterized by high levels of bilirubin, especially when it occurs in newborns. Bilirubin has cytoprotective properties with an antioxidant function and plays several major roles in the inflammation process with its members such as chemokines. The monocyte chemoattractant protein-1 (MCP-1) is a member of the C-C chemokine family and it has been associated with the inflammatory process. There are no data on the chemokine and its receptor genotypes in hyperbilirubinemic newborns to show their distribution. The aim of this study is to investigate the genotypic relationship of MCP-1 and its receptor CCR2-V64. with hyperbilirubinemia in Turkish newborns. A total of 85 newborns were included in the study: 20 infants with hyperbilirubinemia (hyperbilirubinemic group) and 65 infants without hyperbilirubinemia (non-hyperbilirubinemic group). Genotyping of MCP-1 A-2518G and CCR2-V64. gene polymorphisms were detected by PCR-RFLP, respectively. MCP-1 GG genotype in patients was higher than the controls and this genotype had 2.69 times higher risk for hyperbilirubinemic neonates (P: 0.20). The frequency of MCP-1 A-2518G G+ genotype in patients was higher than the controls (55.0% and 38.5%, respectively). The results of our preliminary study suggest that MCP-1 G+ genotype has the ability to increase the hyperbilirubinemia risk of newborns. These results should be focused on to research on a larger scale to confirm the findings

DISCERN: deep single-cell expression reconstruction for improved cell clustering and cell subtype and state detection

Abstract Background Single-cell sequencing provides detailed insights into biological processes including cell differentiation and identity. While providing deep cell-specific information, the method suffers from technical constraints, most notably a limited number of expressed genes per cell, which leads to suboptimal clustering and cell type identification. Results Here, we present DISCERN, a novel deep generative network that precisely reconstructs missing single-cell gene expression using a reference dataset. DISCERN outperforms competing algorithms in expression inference resulting in greatly improved cell clustering, cell type and activity detection, and insights into the cellular regulation of disease. We show that DISCERN is robust against differences between batches and is able to keep biological differences between batches, which is a common problem for imputation and batch correction algorithms. We use DISCERN to detect two unseen COVID-19-associated T cell types, cytotoxic CD4+ and CD8+ Tc2 T helper cells, with a potential role in adverse disease outcome. We utilize T cell fraction information of patient blood to classify mild or severe COVID-19 with an AUROC of 80% that can serve as a biomarker of disease stage. DISCERN can be easily integrated into existing single-cell sequencing workflow. Conclusions Thus, DISCERN is a flexible tool for reconstructing missing single-cell gene expression using a reference dataset and can easily be applied to a variety of data sets yielding novel insights, e.g., into disease mechanisms

Single-cell multiomic analysis of thymocyte development reveals drivers of CD4+ T cell and CD8+ T cell lineage commitment.

The development of CD4+ T cells and CD8+ T cells in the thymus is critical to adaptive immunity and is widely studied as a model of lineage commitment. Recognition of self-peptide major histocompatibility complex (MHC) class I or II by the T cell antigen receptor (TCR) determines the CD8+ or CD4+ T cell lineage choice, respectively, but how distinct TCR signals drive transcriptional programs of lineage commitment remains largely unknown. Here we applied CITE-seq to measure RNA and surface proteins in thymocytes from wild-type and T cell lineage-restricted mice to generate a comprehensive timeline of cell states for each T cell lineage. These analyses identified a sequential process whereby all thymocytes initiate CD4+ T cell lineage differentiation during a first wave of TCR signaling, followed by a second TCR signaling wave that coincides with CD8+ T cell lineage specification. CITE-seq and pharmaceutical inhibition experiments implicated a TCR-calcineurin-NFAT-GATA3 axis in driving the CD4+ T cell fate. Our data provide a resource for understanding cell fate decisions and implicate a sequential selection process in guiding lineage choice