Diversity in Expression Biases of Lineage-Specific Genes During Development and Anhydrobiosis Among Tardigrade Species.

Lineage-specific genes can contribute to the emergence and evolution of novel traits and adaptations. Tardigrades are animals that have adapted to tolerate extreme conditions by undergoing a form of cryptobiosis called anhydrobiosis, a physical transformation to an inactive desiccated state. While studies to understand the genetics underlying the interspecies diversity in anhydrobiotic transitions have identified tardigrade-specific genes and family expansions involved in this process, the contributions of species-specific genes to the variation in tardigrade development and cryptobiosis are less clear.

Validation of the General Health Questionnaire 12 for assessing psychological distress in patients with chronic low back pain.

Background: The General Health Questionnaire 12 (GHQ-12) is a short easy-to-use scale to assess psychological distress. The GHQ-12 has not been validated for assessing psychological distress in patients with chronic low back pain (LBP).

Objective: To investigate the psychometric properties of the GHQ-12 in patients with chronic LBP.

Evaluation of semi-mechanistic models to predict soil to grass transfer factor of Cs based on long term observations in French pastures.

The aim of this study was to evaluate and improve the accuracy of the semi-mechanistic models used in regulatory exposure assessment tools, to describe the transfer factors of Cs from pasture soils to grass observed in different grazing areas of France between 2004 and 2017. This involved a preliminary parameterization step of the dynamic factor describing the ageing of radiocesium in the root zone using a Bayesian approach. A data set with mid-term (10 years about) and long term (more than 20 years) field and literature data from 4 European countries was used.

The Pharmacophore Network: A Computational Method for Exploring Structure-Activity Relationships from a Large Chemical Data Set.

Historically, structure-activity relationship (SAR) analysis has focused on small sets of molecules, but in recent years, there has been increasing efforts to analyze the growing amount of data stored in public databases like ChEMBL. The pharmacophore network introduced herein is dedicated to the organization of a set of pharmacophores automatically discovered from a large data set of molecules. The network navigation allows to derive essential tasks of a drug discovery process, including the study of the relations between different chemical series, the analysis of the influence of additional chemical features on the compounds' activity, and the identification of diverse binding modes.