A Dangerous Curve: Impact of the COVID-19 Pandemic on Brace Treatment in Adolescent Idiopathic Scoliosis.

Study Design: Observational Cohort study.

Objectives: We aim to document the abandon and irregular compliance rate towards brace treatment during the COVID-19 pandemic and its impact on AIS progression.

Methods: We reviewed a database of AIS patients recruited between March and September 2020.

Nightmare frequency, nightmare distress, and psychopathology in female victims of childhood maltreatment.

This study investigated the relationships between a history of childhood maltreatment, the frequency of disturbing dreams, their associated distress, and the presence of psychopathology in 352 female undergraduate volunteers. Participants completed questionnaires assessing dream recall, bad dream and nightmare frequency, nightmare distress, psychological well-being, and history of childhood trauma. Four groups were investigated based on the type and severity of childhood maltreatments experienced.

Analysis of a simulated microarray dataset: comparison of methods for data normalisation and detection of differential expression (open access publication).

Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached.

Analysis of the real EADGENE data set: multivariate approaches and post analysis (open access publication).

The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand.

Analysis of the real EADGENE data set: comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (open access publication).

A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines.