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Biology subjects

Shinohara, H.

Publications and source records attributed to Shinohara, H..

2 recordsLinked to original sources

Imaging and single cell sequencing analyses of super-enhancer activation mediated by NF-κB in B cells

The transcription factor NF-{kappa}B, which plays an important role in cell fate determination, is involved in the activation of super-enhancers (SEs). However, the biological functions of the NF-{kappa}B SEs in gene control are not fully elucidated. We investigated the characteristics of NF-{kappa}B-mediated SE activity using fluorescence live-cell imaging of RelA, single-cell transcriptome, and chromatin accessibility analyses in anti-IgM-stimulated B cells. Cell stimulation induced nuclear foci formation of RelA and gene expression in a switch-like manner. The gained SEs induced a higher fold-change expression and enhanced cell-to-cell variability in transcriptional response. These properties were correlated with the number of gained cis-regulatory interactions, while switch-like gene induction was associated with the number of NF-{kappa}B binding sites in SE. Our study suggests that NF-{kappa}B SEs have unique roles for quantitative control of gene expression through direct binding to accessible DNA and enhanced DNA contacts.

molecular biology

Deep learning-based chest X-ray age serves as a novel biomarker for cardiovascular aging

Chest X-ray (CXR) is one of the most commonly performed medical imaging tests. Although aging, sex and disease status have been known to cause changes in CXR findings, the extent of these effects has not been fully characterized. Here, we present a deep neural network (DNN) model trained using more than 100,000 CXRs to estimate the patients age and sex solely from CXRs. Our DNN exhibited high performance in terms of estimating age and sex, with Pearsons correlation coefficient between the actual and estimated age of above 0.9 and an area under the ROC curve of 0.98 for sex estimation. The difference between the actual and estimated age is large in CXRs with abnormal findings, suggesting that the estimated age ("CXR age") can be a biomarker for disease status. Furthermore, by applying our DNN to CXRs of consecutive 1,562 hospitalized heart failure patients, we demonstrated that an elevated CXR age is not only associated with aging-related diseases, such as hypertension and atrial fibrillation, but also a worse outcome of heart failure. Given these results, our new concept "CXR age" serves as a novel biomarker for cardiovascular aging and can help clinicians to predict, prevent, and manage cardiovascular diseases.

bioinformatics