Cell Death by Apoptosis in Epidermal Biology

Homeostasis in continually renewing tissues is maintained by a tightly regulated balance between cell proliferation, cell differentiation, and cell death. Until recently, proliferation was thought to be the primary point of control in the regulation of normal tissue kinetic homeostasis and as such has been the major focus of both understanding the etiology of disease and developing therapeutic strategies. Now, physiologic cell death, known as apoptosis (â-pôp-tō'sîs, â-pōp-tō'sîs [Thomas CL (ed.): Taber's Cyclopedic Medical Dictionary. F.A. Davis, Co., Philadelphia, 1989)] has gained scientific recognition as an active regulatory mechanism, complementary, but functionally opposite, to proliferation with important roles in shaping and maintaining tissue size and prevention of disease. In this review we will describe the concept of apoptosis and discuss possible molecular mechanisms of its regulation that may have implications for skin biology

GNE: A Deep Learning Framework for Gene Network Inference by Aggregating Biological Information

BACKGROUND: The topological landscape of gene interaction networks provides a rich source of information for inferring functional patterns of genes or proteins. However, it is still a challenging task to aggregate heterogeneous biological information such as gene expression and gene interactions to achieve more accurate inference for prediction and discovery of new gene interactions. In particular, how to generate a unified vector representation to integrate diverse input data is a key challenge addressed here. RESULTS: We propose a scalable and robust deep learning framework to learn embedded representations to unify known gene interactions and gene expression for gene interaction predictions. These low- dimensional embeddings derive deeper insights into the structure of rapidly accumulating and diverse gene interaction networks and greatly simplify downstream modeling. We compare the predictive power of our deep embeddings to the strong baselines. The results suggest that our deep embeddings achieve significantly more accurate predictions. Moreover, a set of novel gene interaction predictions are validated by up-to-date literature-based database entries. CONCLUSION: The proposed model demonstrates the importance of integrating heterogeneous information about genes for gene network inference. GNE is freely available under the GNU General Public License and can be downloaded from GitHub ( https://github.com/kckishan/GNE )

Human IRF1 governs macrophagic IFN-γ immunity to mycobacteria

Inborn errors of human IFN-γ-dependent macrophagic immunity underlie mycobacterial diseases, whereas inborn errors of IFN-α/β-dependent intrinsic immunity underlie viral diseases. Both types of IFNs induce the transcription factor IRF1. We describe unrelated children with inherited complete IRF1 deficiency and early-onset, multiple, life-threatening diseases caused by weakly virulent mycobacteria and related intramacrophagic pathogens. These children have no history of severe viral disease, despite exposure to many viruses, including SARS-CoV-2, which is life-threatening in individuals with impaired IFN-α/β immunity. In leukocytes or fibroblasts stimulated in vitro, IRF1-dependent responses to IFN-γ are, both quantitatively and qualitatively, much stronger than those to IFN-α/β. Moreover, IRF1-deficient mononuclear phagocytes do not control mycobacteria and related pathogens normally when stimulated with IFN-γ. By contrast, IFN-α/β-dependent intrinsic immunity to nine viruses, including SARS-CoV-2, is almost normal in IRF1-deficient fibroblasts. Human IRF1 is essential for IFN-γ-dependent macrophagic immunity to mycobacteria, but largely redundant for IFN-α/β-dependent antiviral immunity

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Induction of TR4 Orphan Receptor by Retinoic Acid in Human HaCaT Keratinocytes

Human TR4 orphan receptor (TR4) can modulate the transcriptional activity of the reporter gene containing an AGGTCA direct repeat-hormone response element. Here we studied the potential role of TR4 in human HaCaT keratinocytes. Using a chloramphenicol acetyltransferase reporter gene assay, it was shown that TR4 can suppress retinoic acid-induced transactivation by 47.3% in human HaCaT keratinocytes. Electrophoretic mobility shift assay indicated that this suppression may be due to TR4 binding with higher affinity to the retinoic acid response element than retinoid receptors. Western blot analysis further suggested that retinoic acid can increase the expression of TR4 protein in human HaCaT keratinocytes, indicating that TR4 acts as a negative feedback modulator for retinoic acid action. Interestingly, TR4 expression is increased in normal human keratinocytes when substituting a low calcium medium with a high calcium medium. Together, our data suggested, for the first time, that an orphan receptor, such as TR4, may play an important part in retinoid-mediated signaling pathways in human keratinocytes, providing a new insight into keratinocyte biology