Xiting Yan

This study shows that a single crystalline silica exposure causes subclinical cardiopulmonary abnormalities in mice, with sex-dependent effects on lung mechanics and transcriptomic responses.

This study identifies a monocyte-macrophage-fibroblast axis in post-COVID-19 lung fibrosis using multi-omic profiling and shows its potential as a therapeutic target.

The paper identifies cell types regulated by circulating miRNAs linked to asthma exacerbations using scRNA-seq and validates findings in GEO datasets.

SPEAK identifies spatial domains in spatial transcriptomics data using a large language model and expert-aligned prompts, showing improved accuracy and interpretability.

The paper develops a multimodal model to predict biological age using vascular microstructure and biomechanical parameters in mice, achieving high predictive accuracy.

This paper shows biologic therapy in severe asthma reduces a specific activated eosinophil subpopulation linked to worse asthma control and lung function.

This study quantifies biological cardiopulmonary aging in mice by integrating biomechanics and single-cell transcriptomics, revealing non-linear aging patterns and cell-type-specific gene expression changes.

This study identifies early alveolar niche disruption and aberrant epithelial reprogramming in IPF using multi-modal analyses of patient cohorts.

The paper investigates age-related changes in proximal pulmonary artery mechanics in mouse models, finding increased stiffness and collagen reorientation linked to aging biomarkers and cellular senescence.

This study uses scRNA-seq and scATAC-seq to show chronic cigarette smoke exposure enhances inflammatory and survival pathways in lung epithelial responses to influenza and hyperoxia.

Single-nucleus multiomic and ex vivo lung slice profiling of human idiopathic pulmonary fibrosis identifies Alveolar Intermediate cells bridging alveolar and Aberrant Basaloid states and reveals AP-1 chromatin injury memory.

This study uses single-cell RNA sequencing to analyze sputum cells from asthma patients and controls, identifying dysregulated pathways and communication networks involved in asthma pathogenesis.

This study examines hypoxia-induced cardiopulmonary remodeling in mice, finding that pulmonary artery stiffening due to collagen remodeling precedes and correlates with cardiac and lung dysfunction, with partial recovery observed after normoxia.

This study uses single-cell RNA sequencing to identify common and distinct immune aberrations in IPF and FHP, revealing shared monocyte features and disease-specific lymphocyte and receptor repertoires.

SDePER improves cell type deconvolution in spatial transcriptomic data by addressing platform effects, sparsity, and spatial correlation, achieving more accurate results than existing methods.

iDESC identifies differential expression in scRNA-seq data with multiple subjects by separating subject effects from disease effects, showing better performance than existing methods.

This study uses multi-omic data to identify age-related changes in lung cell composition and molecular programs associated with aging and senescence.

G2S3 improves single-cell RNA sequencing data by imputing dropouts using a gene graph, enhancing expression recovery and analysis.

The paper identifies gene signatures predictive of asthma severity using a denoising autoencoder and random forest classifier applied to sputum gene expression data.

This study uses single-cell RNA-seq to identify aberrant cell populations in IPF lungs, revealing novel basaloid cells and vascular endothelial changes.

The paper integrates heterogeneous RNA-seq data from asthmatic patients to uncover gene-microbe interactions and their clinical associations.