Maternal and Placental Antibody Responses in SARS-CoV-2 Vaccination and Natural Infection During Pregnancy.

Background: As COVID-19 becomes endemic, understanding antibody response and transfer during pregnancy is crucial to inform policy and vaccination schedules. While good immunogenicity has been shown from SARS-CoV-2 vaccines, few data are available demonstrating functional responses in pregnant populations and infants.

Methods: A prospective, multi-site observational study was completed across 14 centers in England from April 23, 2020, to December 21, 2022.

Advanced Analytic and Pitch-Tracking Metrics Associated with UCL Surgery in Major League Baseball Pitchers: A Case-Control Study.

Background: Ulnar collateral ligament (UCL) injury rates have been rising steadily, while the recent development of advanced analytics and pitch-tracking analysis now drives player development and evaluation throughout Major League Baseball (MLB).

Purpose: To evaluate the association between several advanced analytic and pitch-tracking metrics on UCL surgery rates in MLB pitchers.

Study Design: Case-control study.

Too Far From Relatives? Impact of the Genetic Distance on the Success of Exon Capture in Phylogenomics.

The exon capture approach allows for sequencing a large number of loci to reconstruct phylogenetic relationships at varying taxonomic levels. In order to efficiently recover the targeted loci, the probes designed to capture the exons need to be genetically sufficiently similar to bind to the DNA, with a proposed limit of 10% of divergence. However, this threshold has never been tested with a specific protocol.

Multi-objective latent space optimization of generative molecular design models.

Molecular design based on generative models, such as variational autoencoders (VAEs), has become increasingly popular in recent years due to its efficiency for exploring high-dimensional molecular space to identify molecules with desired properties. While the efficacy of the initial model strongly depends on the training data, the sampling efficiency of the model for suggesting novel molecules with enhanced properties can be further enhanced via latent space optimization (LSO). In this paper, we propose a multi-objective LSO method that can significantly enhance the performance of generative molecular design (GMD).