Effects of estradiol administration on brain activation and anhedonia in perimenopausal women: A pharmaco-fMRI study.

Background: Half of perimenopausal women experience depressive symptoms, including anhedonia. Anhedonia is associated with dysregulation of the frontostriatal circuit. Both the frontrostriatal circuit and depression may be regulated by the reproductive hormone estradiol (E2).

Adverse events associated with umbilical vascular catheters in neonatal intensive care: Development of a risk prediction model.

Background: Adverse events associated with umbilical vascular catheters occur frequently in the neonatal intensive care unit. International guidelines recommend limiting catheter dwell time to reduce the risk of adverse events, and this drives clinical decision-making regarding catheter removal, yet other risk factors may also influence the risk of adverse events.

Objectives: The aim of this study was to develop a clinically useful risk prediction model that could be utilised in the neonatal intensive care unit to identify infants at a greater risk of developing an adverse event associated with umbilical vascular catheters.

New Index Demonstrates Association between Social Vulnerability, Environmental Burden, and Kidney Failure Risk among Individuals with Glomerular Disease.

Background: The Centers for Disease Control and Prevention (CDC) Environmental Justice Index Social-Environmental Ranking (EJI-SER) combines a Social Vulnerability Module (SV) with an Environmental Burden Module (EB) to characterize cumulative environmental and social burden at the census tract level. This analysis evaluates the association between EJI-SER and kidney outcomes in glomerular disease (GD) patients.

Methods: Cure Glomerulopathy (CureGN) is an observational cohort study of adults and children with biopsy-proven GD.

Evaluation of a machine learning-based metabolic marker for coronary artery disease in the UK Biobank.

Background And Aims: An in silico quantitative score of coronary artery disease (ISCAD), built using machine learning and clinical data from electronic health records, has been shown to result in gradations of risk of subclinical atherosclerosis, coronary artery disease (CAD) sequelae, and mortality. Large-scale metabolite biomarker profiling provides increased portability and objectivity in machine learning for disease prediction and gradation. However, these models have not been fully leveraged.

Virus Association with Bacteria and Bacterial Cell Components Enhance Virus Infectivity.

The transmission and infection of enteric viruses can be influenced by co-existing bacteria within the environment and host. However, the viral binding ligands on bacteria and the underlying interaction mechanisms remain unclear. This study characterized the association of norovirus surrogate Tulane virus (TuV) and murine norovirus (MNV) as well as the human enteric virus Aichi virus (AiV) with six bacteria strains (Pantoea agglomerans, Pantoea ananatis, Bacillus cereus, Enterobacter cloacae, Exiguobacterium sibiricum, Pseudomonas spp.