Deep learning model to discriminate diverse infection types based on pairwise analysis of host gene expression.

Accurate detection of pathogens, particularly distinguishing between Gram-positive and Gram-negative bacteria, could improve disease treatment. Host gene expression can capture the immune system's response to infections caused by various pathogens. Here, we present a deep neural network model, bvnGPS2, which incorporates the attention mechanism based on a large-scale integrated host transcriptome dataset to precisely identify Gram-positive and Gram-negative bacterial infections as well as viral infections. We performed analysis of 4,949 blood samples across 40 cohorts from 10 countries using our previously designed omics data integration method, iPAGE, to select discriminant gene pairs and train the bvnGPS2. The performance of the model was evaluated on six independent cohorts comprising 374 samples. Overall, our deep neural network model shows robust capability to accurately identify specific infections, paving the way for precise medicine strategies in infection treatment and potentially also for identifying subtypes of other diseases.

Associations Between Air Pollution Exposure and Daily Pediatric Outpatient Visits for Dry Eye Disease: A Time-Series Study in Shenzhen, China.

Objectives: This study aimed to investigate the associations between air pollution exposure and pediatric outpatient visits for dry eye disease (DED) in Shenzhen, China. Methods: Generalized additive models were utilized to explore the acute effects of air pollution exposure on pediatric outpatient visits for DED. Results: Single-day lag exposures to NO2, O3, PM2.5, and PM10 were associated with DED outpatient visits at lag days 0, 6, 4 and 2. Relative risks (RRs) for DED given a 10-µg/m3 increase in NO2, O3, PM2.5, and PM10 concentrations were 1.062[95% confidence interval (CI) 1.003, 1.123], 1.015(95% CI 1.001, 1.031), 1.052(95% CI 1.001, 1.115), and 1.038 (95% CI 1.002, 1.076), respectively. RR for DED given a 10-µg/m3 increase in NO2 over cumulative lag days 0-1 was 1.075 (95% CI 1.009, 1.147), and RR for DED given a 10-µg/m3 increase in PM10 over cumulative lag days 0-4 was 1.051 (95% CI 1.003, 1.102). Conclusion: The observed associations between air pollution and outpatient visits for DED may provide evidence for policy makers to consider implementing measures to reduce the risk of DED owing to air pollution in China.