Zihai Li

This study shows that supplementing alpha-ketoglutarate (aKG) improves T cell function and immunotherapy effectiveness in NSCLC by reversing epigenetic changes associated with T cell exhaustion.

This study shows that extracellular vesicles from dedifferentiated liposarcoma suppress macrophage STING signaling, leading to immune dysfunction and poor response to immunotherapy.

The paper uses nonlinear mixed-effects modeling to study synergy between immune checkpoint and thrombin inhibitors in a mouse colon cancer model, identifying mechanisms like CD8+ T cell expansion.

This paper introduces EmitGCL, a deep-learning framework that predicts future metastasis in cancer with high accuracy, identifies biomarkers, and validates therapeutic targets.

This study identifies the MHC-I alpha3 domain-CD8 interaction as an inhibitory pathway that restrains CD8+ T-cell activation and maintains tolerance in vivo.

This study characterizes myeloid sarcoma through multi-omic profiling, identifies RAS pathway activation as a hallmark, and shows RAS inhibition reduces tumor burden in mouse models.

This study investigates respiratory IgA responses after SARS-CoV-2 infection, vaccination, or hybrid immunity, showing that mucosal booster vaccination enhances IgA and protective immunity.

The paper develops a workflow for targeted proteomics using a hybrid quadrupole-linear ion trap instrument, demonstrating consistent quantification without high-mass accuracy.

The paper examines spatial fencing patterns of tumor cells by immune and non-immune cells in solid cancers and links these patterns to cancer progression and treatment response.

spaDesign provides a statistical framework to optimize sequencing depth in spatial transcriptomics experiments by simulating data and estimating required sequencing depth for detecting spatial domains.

MarsGT identifies rare cell populations in multi-omics single-cell data, outperforming existing tools and revealing novel biological insights in human and mouse datasets.

This paper introduces SpaGFT, a graph Fourier transform model for spatial omics data analysis, enabling accurate identification of tissue modules and their functional relationships in spatial transcriptomics and proteomics data.

RESEPT uses deep learning to visualize and characterize tissue architecture from spatial transcriptomics data, revealing pathological structures in Alzheimer's and glioblastoma samples.

DeepMAPS infers biological networks from single-cell multi-omics data using a heterogeneous graph transformer, outperforming existing tools in cell clustering and pathway prediction.

This paper introduces SPRUCE, a Bayesian spatial multivariate mixture model for spatial transcriptomics data, which identifies cell sub-populations while accounting for skewness and spatial correlation.

IRIS-FGM is an R package for analyzing scRNA-Seq data to identify functional gene modules, cluster cells, and perform enrichment analysis, with support for Seurat objects.