Daily Respiratory Research Analysis

Early detection of widespread undiagnosed sleep apnea is crucial for preventing its severe health complications. However, large-scale diagnosis faces inaccessible monitoring and trust barriers in automated analysis, particularly due to the absence of transparent artificial intelligence frameworks capable of monitoring adaptation. Here, we develop Apnea Interact Xplainer, a transparent system enabling sleep apnea diagnosis through flexible channel analysis across clinical and home settings. Analyzing 15,807 polysomnography recordings from seven independent multi-ethnic cohorts, our system achieves accuracies of 0.738-0.810 for four-level severity classification, with 99.8% accuracy within one severity grade and R-squared of 0.92-0.96 for apnea-hypopnea index prediction on external test cohorts. The system provides multi-level expert-logic interpretable visualization of respiratory patterns enabling transparent collaborative decision-making. Notably, it achieves a sensitivity of 0.970 for early sleep apnea detection using only oximetry signals, while providing nightly risk assessment and intelligent monitoring reports. This study establishes a paradigm shift in advancing early and cost-effective sleep apnea diagnosis through transparent artificial intelligence.

Respiratory syncytial virus (RSV) is a globally prevalent pathogen, causes severe disease in older adults, and is the leading cause of bronchiolitis and pneumonia in the United States for children during their first year of life. Despite its prevalence worldwide, RSV-specific treatments remain unavailable for most infected patients. Here, we leveraged a combination of genome-wide CRISPR knockout screening and single-cell RNA sequencing to improve our understanding of the host determinants of RSV infection and the host response in both infected cells and uninfected bystanders. These data reveal temporal transcriptional patterns that are markedly different between RSV-infected and bystander-activated cells. Our data show that expression of interferon-stimulated genes is primarily observed in bystander activated cells, while genes implicated in the unfolded protein response and cellular stress are upregulated specifically in RSV-infected cells. Furthermore, genome-wide CRISPR screens identified multiple host factors important for viral infection, findings which we contextualize relative to 29 previously published screens across 17 additional viruses. These unique data complement and extend prior studies that investigate the proinflammatory response to RSV infection, and juxtaposed to other viral infections, provide a rich resource for further hypothesis testing.IMPORTANCERespiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection in infants and the elderly. Despite its substantial global health burden, RSV-targeted treatments remain unavailable for the majority of individuals. While vaccine development is underway, a detailed understanding of the host response to RSV infection and identification of required human host factors for RSV may provide insight into combatting this pathogen. Here, we utilized single-cell RNA sequencing and functional genomics to understand the host response in both RSV-infected and bystander cells, identify what host factors mediate infection, and contextualize these findings relative to dozens of previously reported screens across 17 additional viruses.

OBJECTIVES: Pediatric acute respiratory distress syndrome (PARDS) guidelines recommend limiting airway plateau pressure (Pplat) to 28 cm H 2 O, allowing for higher limits when chest wall compliance (C CW ) is poor since less of the pressure is transmitted to lung (transpulmonary pressure). Transpulmonary pressure depends on Pplat and the ratio of lung elastance to respiratory system elastance (E L /E RS ). E L /E RS measurement requires esophageal manometry, although it is not routinely available. We sought to determine if routinely available clinical data could reliably predict E L /E RS or changes in E L /E RS , to understand when Pplat greater than 28 cm H 2 O could be acceptable. DESIGN: Secondary analysis of randomized controlled trial with esophageal manometry monitoring. SETTING: Quaternary PICU. PATIENTS: Mechanically ventilated children with PARDS. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Two hundred seven patients and 750 patient days were included. Using the first day per patient, median E L /E RS was 0.83 (interquartile range, 0.72-0.87), with a weak negative correlation with respiratory system compliance (C RS ) ( r = -0.26; p < 0.001). C RS was strongly correlated with lung compliance (C l ) ( r = 0.94; p < 0.001) and moderately correlated with C CW ( r = 0.53; p < 0.001). Multivariable analysis identified that higher C RS , younger age and peripheral neuromuscular disease were associated with higher C CW , while higher C RS was the only variable independently associated with higher C l (all p < 0.01). When trying to predict high (> 0.9) or low (< 0.7) E L /E RS , C RS was the only variable retaining an independent association: lower C RS (C RS × 10 [mL/cm H 2 O/kg × 1/10]) with high E L /E RS (odds ratio [OR], 0.70; 95% CI, 0.54-0.86; p = 0.002; area under the receiver operating characteristic curve [AUC], 0.73) and higher C RS (C RS × 10 [mL/cm H 2 O/kg × 1/10]) with low E L /E RS (OR, 1.14; 95% CI, 1.02-1.28; p = 0.017; AUC, 0.60). Change in E L /E RS from day to day was not predictable. CONCLUSIONS: In PARDS, C RS is more strongly tied to C l than C CW . While E L /E RS is not easily predictable from clinical variables, when C RS is low, E L /E RS is generally high. Therefore, increasing Pplat above the suggested thresholds when C RS is impaired may be inappropriate without measuring esophageal pressure.