Longitudinal investigation of neurobiological changes across pregnancy.

Pregnancy is a period of profound biological transformation. However, we know remarkably little about pregnancy-related brain changes. To address this gap, we chart longitudinal changes in brain structure during pregnancy and explore potential mechanisms driving these changes.

Active learning driven prioritisation of compounds from on-demand libraries targeting the SARS-CoV-2 main protease.

FEgrow is an open-source software package for building congeneric series of compounds in protein binding pockets. For a given ligand core and receptor structure, it employs hybrid machine learning/molecular mechanics potential energy functions to optimise the bioactive conformers of supplied linkers and functional groups. Here, we introduce significant new functionality to automate, parallelise and accelerate the building and scoring of compound suggestions, such that it can be used for automated design.

Mediators of a randomized controlled trial of a preventive intervention for youth of parents with depressive disorders.

Objective: The present study assessed two theory-driven mediators of the effects of a family group cognitive-behavioral (FGCB) preventive intervention for youth of parents with a history of major depressive disorder (MDD) or dysthymia on long-term youth psychopathology symptoms and diagnoses.

Method: Sample included 180 parents ( = 41.9, 89% female, 82% White, non-Hispanic) and one of their children/adolescents ages 9-15 years ( = 11.

Longitudinal Investigation of Neurobiological Changes Across Pregnancy.

Pregnancy is a period of profound biological transformation. However, we know remarkably little about pregnancy-related brain changes. To address this gap, we chart longitudinal changes in brain structure during pregnancy and explore potential mechanisms driving these changes.

Robust Automated Truncation Point Selection for Molecular Simulations.

Quantities calculated from molecular simulations are often subject to an initial bias due to unrepresentative starting configurations. Initial data are usually discarded to reduce bias. Chodera's method for automated truncation point selection [J.