Neural network analysis as a novel skin outcome in a trial of belumosudil in patients with systemic sclerosis.

Background: The modified Rodnan skin score (mRSS), used to measure dermal thickness in patients with systemic sclerosis (SSc), is agnostic to inflammation and vasculopathy. Previously, we demonstrated the potential of neural network-based digital pathology applied to stained skin biopsies from SSc patients as a quantitative outcome. We leveraged deep learning and histologic analyses of clinical trial biopsies to decipher SSc skin features 'seen' by artificial intelligence (AI).

Tissue-resident, extravascular Ly6c monocytes are critical for inflammation in the synovium.

Monocytes are abundant immune cells that infiltrate inflamed organs. However, the majority of monocyte studies focus on circulating cells, rather than those in tissue. Here, we identify and characterize an intravascular synovial monocyte population resembling circulating non-classical monocytes and an extravascular tissue-resident monocyte-lineage cell (TR-MC) population distinct in surface marker and transcriptional profile from circulating monocytes, dendritic cells, and tissue macrophages that are conserved in rheumatoid arthritis (RA) patients.

Three Distinct Transcriptional Profiles of Monocytes Associate with Disease Activity in Scleroderma Patients.

Objective: Patients with diffuse cutaneous systemic sclerosis (dcSSc) display a complex clinical phenotype. Transcriptional profiling of whole blood or tissue from patients are affected by changes in cellular composition that drive gene expression and an inability to detect minority cell populations. We undertook this study to focus on the 2 main subtypes of circulating monocytes, classical monocytes (CMs) and nonclassical monocytes (NCMs) as a biomarker of SSc disease severity.

A Novel MIP-1-Expressing Macrophage Subtype in BAL Fluid from Healthy Volunteers.

Tissue availability remains an important limitation of single-cell genomic technologies for investigating cellular heterogeneity in human health and disease. BAL represents a minimally invasive approach to assessing an individual's lung cellular environment for diagnosis and research. However, the lack of high-quality, healthy lung reference data is a major obstacle to using single-cell approaches to study a plethora of lung diseases.