Modeling and NMR Data Elucidate the Structure of a G-Quadruplex-Ligand Interaction for a Pu22T-Cyclometalated Iridium(III) System.

Cyclometalated iridium(III) complexes are increasingly being developed for application in G-quadruplex (GQ) nucleic acid biosensors. We monitored the interactions of a GQ structure with an iridium(III) complex by nuclear magnetic resonance (NMR) titrations and subsequently compared the binding site inferred from NMR with binding positions modeled by molecular docking and molecular dynamics simulations. When titrated into a solution of G-quadruplex , compound ), [Ir(ppy)(pizp)](PF), where ppy is 2-phenylpyridine and pizp is 2-phenylimidazole[4,5f][1,10]phenanthroline, had the greatest impact on the hydrogen chemical shifts of G5, G8, G9, G13, and G17 residues of , indicating end-stacking at the 5' tetrad.

Sex-Specific Effects of Early Life Unpredictability on Hippocampal and Amygdala Responses to Novelty in Adolescents.

Background: Unpredictable childhood experiences are an understudied form of early life adversity that impacts neurodevelopment in a sex-specific manner. The neurobiological processes by which exposure to early-life unpredictability impacts development and vulnerability to psychopathology remain poorly understood. The present study investigates the sex-specific consequences of early-life unpredictability on the limbic network, focusing on the hippocampus and the amygdala.

Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.

Background: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data introduces variability and limits the reproducibility of aortic hemodynamics visualization and quantitative flow-related parameter computation. This paper explores the potential of deep learning to improve 4D flow CMR segmentation by developing models for automatic segmentation and analyzes the impact of the training data on the generalization of the model across different sites, scanner vendors, sequences, and pathologies.

Individual longitudinal changes in DNA-methylome identify signatures of early-life adversity and correlate with later outcome.

Adverse early-life experiences (ELA) affect a majority of the world's children. Whereas the enduring impact of ELA on cognitive and emotional health is established, there are no tools to predict vulnerability to ELA consequences in an individual child. Epigenetic markers including peripheral-cell DNA-methylation profiles may encode ELA and provide predictive outcome markers, yet the interindividual variance of the human genome and rapid changes in DNA methylation in childhood pose significant challenges.