Basic Medical Sciences

Spatial transcriptomics and machine learning define exhaustion-like bone marrow T-cell islands associated with myeloma progression and clinical risk

• Using Xenium 5K spatial transcriptomics data across the myeloma disease spectrum (healthy controls, MGUS, smoldering myeloma, and multiple myeloma), we combined Gaussian mixture model spatial clustering with multi-layer perceptron machine learning to systematically characterize exhaustion-like T cells in the bone marrow microenvironment. We defined a novel spatial niche—exhaustion-like bone marrow T-cell islands (eBM-TIs)—and demonstrated their association with disease progression and clinical risk.
• This manuscript is currently under peer review. The preprint version is available on medRxiv and via clicking here.

Clinical Medicine and Epidemiological research

Hyperthermic intrathoracic chemotherapy in overcoming tyrosine kinase inhibitor resistance in a patient with malignant pleural effusion: a case report

• You can find a PDF copy here simply by clicking