SUMA: a lightweight machine learning model-powered shared nearest neighbour-based clustering application interface for scRNA-Seq data.

Background/aim: Single-cell transcriptomics (scRNA-Seq) explores cellular diversity at the gene expression level. Due to the inherent sparsity and noise in scRNA-Seq data and the uncertainty on the types of sequenced cells, effective clustering and cell type annotation are essential. The graph-based clustering of scRNA-Seq data is a simple yet powerful approach that presents data as a "shared nearest neighbour" graph and clusters the cells using graph clustering algorithms.

Improving the filtering of false positive single nucleotide variations by combining genomic features with quality metrics.

Motivation: Technical errors in sequencing or bioinformatics steps and difficulties in alignment at some genomic sites result in false positive (FP) variants. Filtering based on quality metrics is a common method for detecting FP variants, but setting thresholds to reduce FP rates may reduce the number of true positive variants by overlooking the more complex relationships between features. The goal of this study is to develop a machine learning-based model for identifying FPs that integrates quality metrics with genomic features and with the feature interpretability property to provide insights into model results.

In silico analysis of metabolic effects of bipolar disorder on prefrontal cortex identified altered GABA, glutamate-glutamine cycle, energy metabolism and amino acid synthesis pathways.

Bipolar disorder (BP) is a lifelong psychiatric condition, which often disrupts the daily life of the patients. It is characterized by unstable and periodic mood changes, which cause patients to display unusual shifts in mood, energy, activity levels, concentration and the ability to carry out day-to-day tasks. BP is a major psychiatric condition, and it is still undertreated.

Integration of transcriptomic profile of SARS-CoV-2 infected normal human bronchial epithelial cells with metabolic and protein-protein interaction networks.

A novel coronavirus (SARS-CoV-2, formerly known as nCoV-2019) that causes an acute respiratory disease has emerged in Wuhan, China and spread globally in early 2020. On January the 30th, the World Health Organization (WHO) declared spread of this virus as an epidemic and a public health emergency. With its highly contagious characteristic and long incubation time, confinement of SARS-CoV-2 requires drastic lock-down measures to be taken and therefore early diagnosis is crucial.

FLASH Irradiation Spares Lung Progenitor Cells and Limits the Incidence of Radio-induced Senescence.

Purpose: One of the main limitations to anticancer radiotherapy lies in irreversible damage to healthy tissues located within the radiation field. "FLASH" irradiation at very high dose-rate is a new treatment modality that has been reported to specifically spare normal tissue from late radiation-induced toxicity in animal models and therefore could be a promising strategy to reduce treatment toxicity.

Experimental Design: Lung responses to FLASH irradiation were investigated by qPCR, single-cell RNA sequencing (sc-RNA-Seq), and histologic methods during the acute wound healing phase as well as at late stages using C57BL/6J wild-type and Terc mice exposed to bilateral thorax irradiation as well as human lung cells grown .