Discovery of optimal cell type classification marker genes from single cell RNA sequencing data.

The use of single cell/nucleus RNA sequencing (scRNA-seq) technologies that quantitively describe cell transcriptional phenotypes is revolutionizing our understanding of cell biology, leading to new insights in cell type identification, disease mechanisms, and drug development. The tremendous growth in scRNA-seq data has posed new challenges in efficiently characterizing data-driven cell types and identifying quantifiable marker genes for cell type classification. The use of machine learning and explainable artificial intelligence has emerged as an effective approach to study large-scale scRNA-seq data.

Development of a Medical Complexity Score for Pediatric Aerodigestive Patients.

Objective: To develop a complexity scoring system to characterize the diverse population served in pediatric aerodigestive clinics and help predict their treatment outcomes.

Study Design: A 7-point medical complexity score was developed through an iterative group consensus of relative stakeholders to capture the spectrum of comorbidities among the aerodigestive population. One point was assigned for each comorbid diagnosis in the following categories: airway anomaly, neurologic, cardiac, respiratory, gastrointestinal, genetic diagnoses, and prematurity.

An integrated cell atlas of the lung in health and disease.

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population.

Leveraging Electronic Health Records for Guideline-Based Asthma Documentation.

Background: Asthma is the most common pediatric chronic disease; thus, clinical guidelines have been developed for its assessment and management, which rely on systematic symptom documentation. Electronic health records (EHR) have the potential to record clinical data systematically; however, variability in documentation persists.

Objective: To identify if the use of a structured asthma template is associated with increased guideline-based asthma documentation and clinical outcomes when compared with the use of nonstructured ones.

A single-cell regulatory map of postnatal lung alveologenesis in humans and mice.

Ex-utero regulation of the lungs' responses to breathing air and continued alveolar development shape adult respiratory health. Applying single-cell transposome hypersensitive site sequencing (scTHS-seq) to over 80,000 cells, we assembled the first regulatory atlas of postnatal human and mouse lung alveolar development. We defined regulatory modules and elucidated new mechanistic insights directing alveolar septation, including alveolar type 1 and myofibroblast cell signaling and differentiation, and a unique human matrix fibroblast population.

Epigenetic Regulation of Myofibroblast Phenotypes in Fibrosis.

Purpose Of Review: Myofibroblasts are the fundamental drivers of fibrosing disorders; there is great value in better defining epigenetic networks involved in myofibroblast behavior. Complex epigenetic paradigms, which are likely organ and/or disease specific, direct pathologic myofibroblast phenotypes. In this review, we highlight epigenetic regulators and the mechanisms through which they shape myofibroblast phenotype in fibrotic diseases of different organs.