Data-driven detection of age-related arbitrary monotonic changes in single-cell gene expression distributions.

Identification of genes whose expression increases or decreases with age is central to understanding the mechanisms behind aging. Recent scRNA-seq studies have shown that changes in single-cell expression profiles with aging are complex and diverse. In this study, we introduce a novel workflow to detect changes in the distribution of arbitrary monotonic age-related changes in single-cell expression profiles.

Visualization of the landscape of the read alignment shape of ATAC-seq data using Hellinger distance metric.

Assay for Transposase-Accessible Chromatin using high-throughput sequencing (ATAC-seq) is the popular technique using next-generation sequencing to measure chromatin accessibility and identify open chromatin regions. While read alignment shape information of next-generation sequencing data with intensity information has been used in various bioinformatics methods, few studies have focused on pure shape information alone. In this study, we investigated what types of ATAC-seq read alignment shapes are observed for the promoter region and whether the pure shape information was related or unrelated to other gene features.

Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging.

Background: Aging affects the incidence of diseases such as cancer and dementia, so the development of biomarkers for aging is an important research topic in medical science. While such biomarkers have been mainly identified based on the assumption of a linear relationship between phenotypic parameters, including molecular markers, and chronological age, numerous nonlinear changes between markers and aging have been identified. However, the overall landscape of the patterns in nonlinear changes that exist in aging is unknown.

Mathematical model for the relationship between single-cell and bulk gene expression to clarify the interpretation of bulk gene expression data.

Background: Differential expression analysis is a standard approach in molecular biology. For example, genes whose expression levels differ between diseased and non-diseased samples are considered to be associated with that disease. On the other hand, differential variability analysis focuses on the differences of the variances of gene expression between sample groups.

Serum Periostin Level and Genetic Polymorphisms Are Associated with Vertebral Fracture in Chinese Postmenopausal Women.

Purposes: In order to investigate the association between serum periostin levels and the variation of its encoding gene and the prevalence of vertebral fractures and bone mineral density (BMD) in Chinese postmenopausal women, an association study was performed.

Materials And Methods: 385 postmenopausal women were recruited. For participants without a history of vertebral fracture, lateral X-rays of the spine covering the fourth thoracic spine to the fifth lumbar spine were performed to detect any asymptomatic vertebral fractures.

Cell population-based framework of genetic epidemiology in the single-cell omics era.

Genetic epidemiology is a rapidly advancing field due to the recent availability of large amounts of omics data. In recent years, it has become possible to obtain omics information at the single-cell level, so genetic epidemiological models need to be updated to integrate with single-cell expression data. In this perspective paper, we propose a cell population-based framework for genetic epidemiology in the single-cell era.

Data-driven comparison of multiple high-dimensional single-cell expression profiles.

Comparing multiple single-cell expression datasets such as cytometry and scRNA-seq data between case and control donors provides information to elucidate the mechanisms of disease. We propose a completely data-driven computational biological method for this task. This overcomes the challenges of conventional cellular subset-based comparisons and facilitates further analyses such as machine learning and gene set analysis of single-cell expression datasets.

Effects of uninterrupted sinusoidal LF-EMF stimulation on LTP induced by different combinations of TBS/HFS at the Schaffer collateral-CA1 of synapses.

Long-term potentiation (LTP) is an important aspect of synaptic plasticity and is one of the main mechanisms involved in memory. Low-frequency electromagnetic fields (LF-EMFs) such as transcranial magnetic stimulation are emerging neuromodulation tools for the regulation of LTP. However, whether LF-EMFs have different effects on different types of LTP has not yet been verified.

Determination of cholesterol and four phytosterols in foods without derivatization by gas chromatography-tandem mass spectrometry.

In this study, a method for determination of cholesterol and four phytosterols by gas chromatography coupled with electron impact ionization mode-tandem mass spectrometry without derivatization in general food was developed. The sample was saponified with 7.5% KOH in methanol.