Identifying potential key metabolic pathways and biomarkers in glaucoma: a systematic review and meta-analysis.

Background: Glaucoma, a leading cause of irreversible blindness worldwide, is characterised by retinal ganglion cell degeneration. Increasing evidence points to metabolic dysfunction, particularly mitochondrial dysfunction, as a contributing factor to glaucomatous neurodegeneration. This systematic review and meta-analysis aimed to identify key metabolic pathways and biomarkers associated with primary open-angle glaucoma (POAG).

Facilitators and Barriers to Acceptability of a Biopsy-First Approach in the Diagnostic Evaluation for Endometrial Cancer Among Black Women.

Background: Black people in the U.S. with endometrial cancer have a 5-year mortality rate that is more than twice that of white patients.

Excitatory and inhibitory neurotransmitter alterations with advancing age and injury in the mouse retina.

Increasing age and elevated intraocular pressure (IOP) are the two major risk factors for glaucoma, the most common cause of irreversible blindness worldwide. Accumulating evidence is pointing to metabolic failure predisposing to neuronal loss with advancing age and IOP injury. Many neurotransmitters are synthesized from endogenous metabolites and are essential for correct cell to cell signaling along the visual pathways.

Comparing conventional and Bayesian workflows for clinical outcome prediction modelling with an exemplar cohort study of severe COVID-19 infection incorporating clinical biomarker test results.

Purpose: Assessing risk factors and creating prediction models from real-world medical data is challenging, requiring numerous modelling decisions with clinical guidance. Logistic regression is a common model for such studies, for which we advocate the use of Bayesian methods that can jointly deliver probabilistic risk factor inference and prediction. As an exemplar, we compare Bayesian logistic regression with horseshoe priors and Projective Prediction variable selection with the established frequentist LASSO approach, to predict severe COVID-19 outcomes (death or ICU admittance) from demographic and laboratory biomarker data.