Rong Fan

This study enhances CAR-T cell migration through synthetic cytokine receptors, reducing metastasis in TNBC mouse models.

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.

StarTrak infers cellular migration and phylogeny by integrating somatic variants, spatial data, and transcriptomics at single-pixel resolution in spatial genomics.

The paper presents a single-cell atlas of noncoding RNAs during mouse organogenesis, revealing their cell-type-specific and lineage-regulated expression patterns.

REDCAT maps single-cell type-specific metabolic activities in tissues using multimodal all-optical imaging, revealing metabolic specialization and reprogramming in immune and liver tissues.

The paper uses single-cell foundation models to predict durable CAR T response from pre-infusion scRNA-seq data, achieving high accuracy without requiring perfect cell annotation.

This study introduces spatial-GPT, a platform for spatial glycan, protein, and transcriptome profiling in human liver tissues, revealing glyco-codes that define disease states and progression.

This paper uses surprisal information-theoretic analysis on spatial transcriptomic data from human glioblastoma to uncover hidden spatial programs and interactions not detected by standard methods.

This study identifies ECM-dominant cardiovascular diseases as driven by coordinated CDKN1A and CDKN2A senescence programs in fibroblasts and shows senolytic treatments improve cardiac function.

The paper introduces the SenNet Portal, a resource for senescent cell data and tools, and discusses its usage and future developments.

SpaMosaic integrates spatial multi-omics data using contrastive learning and graph neural networks, improving spatial domain identification and missing modality imputation across diverse datasets.

The paper identifies yeast-derived lipids that extend lifespan in Drosophila by remodeling metabolism in the gut and brain, enhancing tissue homeostasis and communication.

This study maps age-related cellular senescence in human lymph nodes, identifying senescence markers and spatial shifts in germinal center B cells.

The paper identifies a conserved activated valvular interstitial cell population across species and disease types that drives myxomatous mitral valve degeneration.

SuperFocus integrates histopathology with single-cell spatial multi-omics data from spot-based measurements, improving accuracy by 28-73% over existing methods.

Thermostable RNaseH release of barcoded cDNA keeps sections intact for CODEX imaging, yielding same-section whole-transcriptome and protein maps plus CODEX-guided spot deconvolution in FFPE tissues.

This paper introduces CAR-T-drug conjugates (CAR-T-D-C) to improve CAR-T therapy for solid tumors by combining chemotherapy with CAR-T cells, enhancing tumor infiltration and immune response.

SPACEc provides a Python workflow for analyzing multiplexed imaging data with interactive tools for image processing, segmentation, and spatial analysis.

The paper introduces SuMMIT-SRS, a multiplexed metabolic imaging technique, and demonstrates its application in various cell types to study metabolic rewiring.

The paper analyzes endothelial cell environments across organs using spatially resolved omics data and provides an interactive tool for visualizing cell distances and neighborhoods.

This study identifies two epigenetically-defined spatial niches in glioblastoma that influence cell state plasticity through local and long-range molecular signals.

ASTRO is an automated pipeline for spatial transcriptomics analysis, optimized for FFPE samples and capable of detecting coding and non-coding RNAs.

Perturb-DBiT co-sequences spatial transcriptomes and gRNAs on one tissue section, supporting genome-wide in vivo CRISPR screens in FFPE and fresh-frozen tumors across three cancer models.

The paper develops a computational method to analyze single-cell RNA-seq data to study cell-cell interactions in tumors, showing that CD40 agonist enhances immune checkpoint blockade by modulating myeloid-T cell interactions.

This paper introduces Patho-DBiT, a method for spatial transcriptomics in FFPE tissues, enabling RNA biology analysis including splicing, variants, and regulatory networks in clinical samples.

Spatial tri-omic sequencing (DBiT ARP-seq and DBiT CTRP-seq) and CODEX imaging map chromatin, RNA, and protein dynamics across mammalian brain development and lysolecithin-induced neuroinflammation.

The paper introduces NicheCompass, a graph deep learning method for characterizing cell niches in spatial omics data, showing improved performance in identifying and analyzing niches across multiple biological contexts.

The paper uses spatial-CUT&Tag data to analyze H3K4me3 domain organization in a mouse embryo, finding spatially coherent gene patterns associated with tissue boundaries and distinct chromatin state transitions.

This paper introduces scShift, a deep variational model that enables zero-shot characterization of single-cell biological states across datasets by overcoming batch effects.

SIMVI disentangles intrinsic and spatial-induced variations in spatial omics data, revealing spatial effects and biological dynamics across multiple datasets.