A genetically based computational drug repurposing framework for rapid identification of candidate compounds: application to COVID-19.

Background: The development and approval of novel drugs are typically time-intensive and expensive. Leveraging a computational drug repurposing framework that integrates disease-relevant genetically regulated gene expression (GReX) and large longitudinal electronic medical record (EMR) databases can expedite the repositioning of existing medications. However, validating computational predictions of the drug repurposing framework remains a challenge.

Fully automated coronary artery calcium score and risk categorization from chest CT using deep learning and multiorgan segmentation: A validation study from National Lung Screening Trial (NLST).

Background: The National Lung Screening Trial (NLST) has shown that screening with low dose CT in high-risk population was associated with reduction in lung cancer mortality. These patients are also at high risk of coronary artery disease, and we used deep learning model to automatically detect, quantify and perform risk categorisation of coronary artery calcification score (CACS) from non-ECG gated Chest CT scans.

Materials And Methods: Automated calcium quantification was performed using a neural network based on Mask regions with convolutional neural networks (R-CNN) for multiorgan segmentation.

Delta opioid receptors affect acoustic features of song during vocal learning in zebra finches.

Delta-opioid receptors (δ-ORs) are known to be involved in associative learning and modulating motivational states. We wanted to study if they were also involved in naturally-occurring reinforcement learning behaviors such as vocal learning, using the zebra finch model system. Zebra finches learn to vocalize early in development and song learning in males is affected by factors such as the social environment and internal reward, both of which are modulated by endogenous opioids.

Use and Costs of Supplemental Benefits in Medicare Advantage, 2017-2021.

Importance: Nearly all Medicare Advantage (MA) plans offer dental, vision, and hearing benefits not covered by traditional Medicare (TM). However, little is known about MA enrollees' use of those benefits or how much they cost MA insurers or enrollees.

Objective: To estimate use, out-of-pocket (OOP) spending, and insurer payments for dental, hearing, and vision services among Medicare beneficiaries.

Improving 1-year liver allograft survival hazard ratios.

Background: The Scientific Registry for Transplant Recipients (SRTR) publishes outcomes of all transplant centres in the USA two times a year. The outcomes are publicly available and used by insurance payers and patients to assess the performance of a programme. Poor performance can result in temporary suspension or termination of a transplant programme.