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Although nucleoporin 98 (NUP98) fusion oncogenes often drive aggressive pediatric leukemia by altering chromatin structure and expression of HOX genes, underlying mechanisms remain elusive. Here, we report that a Hoxb-associated lncRNA HoxBlinc was aberrantly activated in NUP98-PHF23 fusion-driven leukemias. HoxBlinc chromatin occupancies led to elevated MLL1 recruitment and aberrant homeotic topologically associated domains (TADs) that enhanced chromatin accessibilities and activated homeotic/hematopoietic oncogenes.

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Background: We aimed to characterize factors associated with the under-studied complication of cognitive decline in aging people with long-duration type 1 diabetes (T1D).

Methods: Joslin "Medalists" (n = 222; T1D ≥ 50 years) underwent cognitive testing. Medalists (n = 52) and age-matched non-diabetic controls (n = 20) underwent neuro- and retinal imaging.

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Hypoxia is a major cause of pulmonary hypertension (PH) worldwide, and it is likely that interstitial pulmonary macrophages contribute to this vascular pathology. We observed in hypoxia-exposed mice an increase in resident interstitial macrophages, which expanded through proliferation and expressed the monocyte recruitment ligand CCL2. We also observed an increase in CCR2+ macrophages through recruitment, which express the protein thrombospondin-1 that functionally activates TGF-beta to cause vascular disease.

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Imaging-based spatial transcriptomics (iST), such as MERFISH, CosMx SMI, and Xenium, quantify gene expression level across cells in space, but more importantly, they directly reveal the subcellular distribution of RNA transcripts at the single-molecule resolution. The subcellular localization of RNA molecules plays a crucial role in the compartmentalization-dependent regulation of genes within individual cells. Understanding the intracellular spatial distribution of RNA for a particular cell type thus not only improves the characterization of cell identity but also is of paramount importance in elucidating unique subcellular regulatory mechanisms specific to the cell type.

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Background: The implementation of large language models (LLMs), such as BART (Bidirectional and Auto-Regressive Transformers) and GPT-4, has revolutionized the extraction of insights from unstructured text. These advancements have expanded into health care, allowing analysis of social media for public health insights. However, the detection of drug discontinuation events (DDEs) remains underexplored.

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