BFAST: joint dimension reduction and spatial clustering with Bayesian factor analysis for zero-inflated spatial transcriptomics data.

The development of spatially resolved transcriptomics (ST) technologies has made it possible to measure gene expression profiles coupled with cellular spatial context and assist biologists in comprehensively characterizing cellular phenotype heterogeneity and tissue microenvironment. Spatial clustering is vital for biological downstream analysis. However, due to high noise and dropout events, clustering spatial transcriptomics data poses numerous challenges due to the lack of effective algorithms.

Single-cell multi-modal chromatin profiles revealing epigenetic regulations of cells in hepatocellular carcinoma.

Background: Various epigenetic regulations systematically govern gene expression in cells involving various biological processes. Dysregulation of the epigenome leads to aberrant transcriptional programs and subsequently results in diseases, such as cancer. Therefore, comprehensive profiling epigenomics is essential for exploring the mechanisms underlying gene expression regulation during development and disease.

Spatial transcriptomics in pancreatic cancer: Advances, prospects and challenges.

Pancreatic cancer remains one of the deadliest malignancies with an overall 5-year survival rate of 13 %. This dismal fact can be partly attributed to currently limited understanding of tumor heterogeneity and immune microenvironment. Traditional bulk-sequencing techniques overlook the diversity of tumor cells, while single-cell sequencing disorganizes the position localizing of cells in tumor microenvironment.

Uncovering the Bronchoalveolar Single-Cell Landscape of Patients With Pulmonary Tuberculosis With Human Immunodeficiency Virus Type 1 Coinfection.

Background: Coinfection of human immunodeficiency virus type 1 (HIV-1) is the most significant risk factor for tuberculosis (TB). The immune responses of the lung are essential to restrict the growth of Mycobacterium tuberculosis and avoid the emergence of the disease. Nevertheless, there is still limited knowledge about the local immune response in people with HIV-1-TB coinfection.

Modulation Mechanism of Wuniuzao Dark Tea Polysaccharide on Lipid Metabolism in Hyperlipidemic Mice Induced by High-Fat Diet.

The aim of this study was to investigate the functional mechanism of Wuniuzao dark tea polysaccharide (WDTP) that protect against hyperlipidemia in mice induced by high-fat diet. WDTP was extracted by hot water, isolated and purified by DEAE-52 chromatography and characterized by high-performance liquid chromatograph (HPLC), Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscope (SEM). Different doses (200 or 800 mg/kg/day) of WDTP were orally administered to mice induced by high-fat diet to evaluate the mechanism of WDTP regulating lipid metabolism.

Single cell multi-omics reveal intra-cell-line heterogeneity across human cancer cell lines.

Human cancer cell lines have long served as tools for cancer research and drug discovery, but the presence and the source of intra-cell-line heterogeneity remain elusive. Here, we perform single-cell RNA-sequencing and ATAC-sequencing on 42 and 39 human cell lines, respectively, to illustrate both transcriptomic and epigenetic heterogeneity within individual cell lines. Our data reveal that transcriptomic heterogeneity is frequently observed in cancer cell lines of different tissue origins, often driven by multiple common transcriptional programs.

Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans.

Single-cell multiomics reveals heterogeneous cell states linked to metastatic potential in liver cancer cell lines.

Hepatocellular carcinoma (HCC) is the most common liver cancer with a high rate of metastasis. However, the molecular mechanisms that drive metastasis remain unclear. We combined single-cell transcriptomic, proteomic, and chromatin accessibility data to investigate how heterogeneous phenotypes contribute to metastatic potential in five HCC cell lines.

Single-cell transcriptomic landscape identifies the expansion of peripheral blood monocytes as an indicator of HIV-1-TB co-infection.

Certain circulating cell subsets are involved in immune dysregulation in human immunodeficiency virus type 1 (HIV-1) and tuberculosis (TB) co-infection; however, the characteristics and role of these subclusters are unknown. Peripheral blood mononuclear cells (PBMCs) of patients with HIV-1 infection alone (HIV-pre) and those with HIV-1-TB co-infection without anti-TB treatment (HIV-pre & TB-pre) and with anti-TB treatment for 2 weeks (HIV-pre & TB-pos) were subjected to single-cell RNA sequencing (scRNA-seq) to characterize the transcriptome of different immune cell subclusters. We obtained > 60,000 cells and identified 32 cell subclusters based on gene expression.

Comprehensive analysis of Transcription Factors identified novel prognostic biomarker in human bladder cancer.

Transcriptional factors (TFs) are responsible for regulating the transcription of pro-oncogenes and tumor suppressor genes in the process of tumor development. However, the role of these transcription factors in Bladder cancer (BCa) remains unclear. And the main purpose of this research is to explore the possibility of these TFs serving as biomarkers for BCa.