科研动态
  • Streptococcal pyrogenic exotoxin B cleaves GSDMA and triggers pyroptosis

    Gasdermins, a family of five pore-forming proteins (GSDMA–GSDME) in humans expressed predominantly in the skin, mucosa and immune sentinel cells, are key executioners of inflammatory cell death (pyroptosis), which recruits immune cells to infection sites and promotes protective immunity. Pore formation is triggered by gasdermin cleavage. Although the proteases that activate GSDMB, C, D and E have been identified, how GSDMA—the dominant gasdermin in the skin—is activated, remains unknown. Streptococcus pyogenes, also known as group A Streptococcus (GAS), is a major skin pathogen that causes substantial morbidity and mortality worldwide.

  • The lysosomal Rag-Ragulator complex licenses RIPK1– and caspase-8–mediated pyroptosis by Yersinia

    Host cells initiate cell death programs to limit pathogen infection. Inhibition of transforming growth factor–β–activated kinase 1 (TAK1) by pathogenic Yersinia in macrophages triggers receptor-interacting serine-threonine protein kinase 1 (RIPK1)–dependent caspase-8 cleavage of gasdermin D (GSDMD) and inflammatory cell death (pyroptosis). A genome-wide CRISPR screen to uncover mediators of caspase-8–dependent pyroptosis identified an unexpected role of the lysosomal folliculin (FLCN)–folliculin-interacting protein 2 (FNIP2)–Rag-Ragulator supercomplex, which regulates metabolic signaling and the mechanistic target of rapamycin complex 1 (mTORC1).

  • Clustering single-cell RNA-seq data with a model-based deep learning approach

    Single-cell RNA sequencing (scRNA-seq) promises to provide higher resolution of cellular differences than bulk RNA sequencing. Clustering transcriptomes profiled by scRNA-seq has been routinely conducted to reveal cell heterogeneity and diversity. However, clustering analysis of scRNA-seq data remains a statistical and computational challenge, due to the pervasive dropout events obscuring the data matrix with prevailing ‘false’ zero count observations.

  • MATHLA: a robust framework for HLA‑peptide binding prediction integrating bidirectional LSTM and multiple head attention mechanism

    Background: Accurate prediction of binding between class I human leukocyte antigen (HLA) and neoepitope is critical for target identification within personalized T-cell based immunotherapy.
    Results: We present a pan-allele HLA-peptide binding prediction framework-MATHLA which integrates bi-directional long short-term memory network and multiple head attention mechanism.
    Conclusion: Our method demonstrates the necessity of further development of deep learning algorithm in improving and interpreting HLA-peptide binding prediction in parallel to increasing the amount of high-quality HLA ligandome data.

  • Liquid Biopsy Applications in the Clinic

    The global liquid biopsy industry is expected to exceed $US5 billion by 2023. One application of liquid biopsy technology is the diagnosis of disease using biomarkers found in blood, urine, stool, saliva, and other biological samples from patients. These biomarkers could be DNA, RNA, protein, or even a cell. More recently, the use of cell-free DNA from plasma is emerging as an important minimally invasive tool for clinical diagnosis. The development of technology has increased the diversity of its application. Here, we discuss how liquid biopsies have been used in the clinic, and how personalized medicine are likely to use liquid biopsies in the near future.

共有2页首页上一页12下一页尾页

“码”上关注

深圳市新合生物医疗科技有限公司

地址:北京市昌平区生命科学园生命园路29号1幢2层





文章
  • 文章
  • 产品
  • 商铺
  • 论坛
  • 视频
搜索

网站:www.neocura.com.cn

邮箱:info@neocura.net

电话:010-80766127




深圳市龙华区银星智界二期一号楼B座12楼





广州市黄埔区连云路388号B座10层

技术支持: 恒基联合 | 管理登录