Factors Associated With COVID-19 Non-Vaccination in Switzerland: A Nationwide Study.

We compared socio-demographic characteristics, health-related variables, vaccination-related beliefs and attitudes, vaccination acceptance, and personality traits of individuals who vaccinated against COVID-19 and who did not vaccinate by December 2021. This cross-sectional study used data of 10,642 adult participants from the Corona Immunitas eCohort, an age-stratified random sample of the population of several cantons in Switzerland. We used multivariable logistic regression models to explore associations of vaccination status with socio-demographic, health, and behavioral factors.

A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data.

Background: There is an increasing interest in the use of Deep Learning (DL) based methods as a supporting analytical framework in oncology. However, most direct applications of DL will deliver models with limited transparency and explainability, which constrain their deployment in biomedical settings.

Methods: This systematic review discusses DL models used to support inference in cancer biology with a particular emphasis on multi-omics analysis.

Effectiveness of crisis resolution home treatment for the management of acute psychiatric crises in Southern Switzerland: a natural experiment based on geography.

Background: Crisis Resolution Home Treatment (CRHT) is an alternative to inpatient treatment for acute psychiatric crises management. However, evidence on CRHT effectiveness is still limited. In the Canton of Ticino (Southern Switzerland), in 2016 the regional public psychiatric hospital replaced one acute ward with a CRHT.

Methods for the Analysis of Topologically Associating Domains (TADs).

Chromatin folding in the 3D space of the nucleus can be explored through high-throughput chromosome conformation capture (Hi-C) approaches. These experiments quantify the number of interactions between any pair of genomic loci in the genome and, thus, allow building genome-scale maps of intra- and inter-chromosomal contacts (contact maps). Statistical and algorithmic analyses of Hi-C data consist in extracting information from these contact maps.

Systematic assessment of gene co-regulation within chromatin domains determines differentially active domains across human cancers.

Background: Spatial interactions and insulation of chromatin regions are associated with transcriptional regulation. Domains of frequent chromatin contacts are proposed as functional units, favoring and delimiting gene regulatory interactions. However, contrasting evidence supports the association between chromatin domains and transcription.