A scoping review of statistical methods to investigate colocalization between genetic associations and microRNA expression in osteoarthritis.

Background: Genetic colocalization analysis is a statistical method that evaluates whether two traits (e.g., osteoarthritis [OA] risk and microRNA [miRNA] expression levels) share the same or distinct genetic association signals in a locus typically identified in genome-wide association studies (GWAS).

Developmental approach of safety in ergonomics/human factors: insights of constructed safety in six work environments.

This article brings together works on the concept of constructed safety in ergonomics, carried out over the last twenty-five years. Firstly, we situate this approach to safety in relation to previously developed existing models (e.g.

Long-term activity of social insects responsible for the physical fertility of soils in the tropics.

Ferralsols correspond to the red and yellow soils that are common in the tropics. They are deeply weathered but physical fertility is high because they exhibit a strong microgranular structure whose origin is still actively debated. In the present study, we looked for evidence of the biological origin of the structure resulting from soil fauna activity.

Characterization of direct and/or indirect genetic associations for multiple traits in longitudinal studies of disease progression.

When quantitative longitudinal traits are risk factors for disease progression and subject to random biological variation, joint model analysis of time-to-event and longitudinal traits can effectively identify direct and/or indirect genetic association of single nucleotide polymorphisms (SNPs) with time-to-event. We present a joint model that integrates: (1) a multivariate linear mixed model describing trajectories of multiple longitudinal traits as a function of time, SNP effects, and subject-specific random effects and (2) a frailty Cox survival model that depends on SNPs, longitudinal trajectory effects, and subject-specific frailty accounting for dependence among multiple time-to-event traits. Motivated by complex genetic architecture of type 1 diabetes complications (T1DC) observed in the Diabetes Control and Complications Trial (DCCT), we implement a 2-stage approach to inference with bootstrap joint covariance estimation and develop a hypothesis testing procedure to classify direct and/or indirect SNP association with each time-to-event trait.

Industry 4.0 design project based on exposure situations: A case study in aeronautics.

Background: Industry 4.0 generates risks renewing stakes for design projects integrating work activities, as can be done in activity centred ergonomics and participatory ergonomics.

Objective: This article aims to show the contribution of using typical situations to define requirements for Industry 4.