Environmental predictors of pulmonary nontuberculous mycobacteria (NTM) sputum positivity among persons with cystic fibrosis in the state of Florida.

Nontuberculous mycobacteria (NTM) are opportunistic human pathogens that are commonly found in soil and water, and exposure to these organisms may cause pulmonary nontuberculous mycobacterial disease. Persons with cystic fibrosis (CF) are at high risk for developing pulmonary NTM infections, and studies have shown that prolonged exposure to certain environments can increase the risk of pulmonary NTM. It is therefore important to determine the risk associated with different geographic areas. Using annualized registry data obtained from the Cystic Fibrosis Foundation Patient Registry for 2010 through 2017, we conducted a geospatial analysis of NTM infections among persons with CF in Florida. A Bernoulli model in SaTScan was used to identify clustering of ZIP codes with higher than expected numbers of NTM culture positive individuals. Generalized linear mixed models with a binomial distribution were used to test the association of environmental variables and NTM culture positivity. We identified a significant cluster of M. abscessus and predictors of NTM sputum positivity, including annual precipitation and soil mineral levels.

Parsing Immune Correlates of Protection Against SARS-CoV-2 from Biomedical Literature.

After the emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in 2019, identification of immune correlates of protection (CoPs) have become increasingly important to understand the immune response to SARS-CoV-2. The vast amount of preprint and published literature related to COVID-19 makes it challenging for researchers to stay up to date on research results regarding CoPs against SARS-CoV-2. To address this problem, we developed a machine learning classifier to identify papers relevant to CoPs and a customized named entity recognition (NER) model to extract terms of interest, including CoPs, vaccines, assays, and animal models. A user-friendly visualization tool was populated with the extracted and normalized NER results and associated publication information including links to full-text articles and clinical trial information where available. The goal of this pilot project is to provide a basis for developing real-time informatics platforms that can inform researchers with scientific insights from emerging research.