Leveraging cross-source heterogeneity to improve the performance of bulk gene expression deconvolution.

A main limitation of bulk transcriptomic technologies is that individual measurements normally contain contributions from multiple cell populations, impeding the identification of cellular heterogeneity within diseased tissues. To extract cellular insights from existing large cohorts of bulk transcriptomic data, we present CSsingle, a novel method designed to accurately deconvolve bulk data into a predefined set of cell types using a scRNA-seq reference. Through comprehensive benchmark evaluations and analyses using diverse real data sets, we reveal the systematic bias inherent in existing methods, stemming from differences in cell size or library size.

Light therapy for sleep disturbance comorbid depression in relation to neural circuits and interactive hormones-A systematic review.

Aim: To provide an overview of the evidence on the effect of light therapy on sleep disturbance and depression, identify the light-active neural and hormonal correlates of the effect of light therapy on sleep disturbance comorbid depression (SDCD), and construct the mechanism by which light therapy alleviates SDCD.

Methods: Articles published between 1981 and 2021 in English were accessed using Science Direct, Elsevier, and Google Scholar following a three-step searching process via evolved keywords. The evidence level, reliability, and credibility of the literature were evaluated using the evidence pyramid method, which considers the article type, impact factor, and journal citation report (JCR) partition.