scispace - formally typeset
Search or ask a question
Author

Mark M. Davis

Bio: Mark M. Davis is an academic researcher from Stanford University. The author has contributed to research in topics: T-cell receptor & T cell. The author has an hindex of 144, co-authored 581 publications receiving 74358 citations. Previous affiliations of Mark M. Davis include Washington University in St. Louis & University of Chicago.


Papers
More filters
Journal ArticleDOI
04 Oct 1996-Science
TL;DR: Tetramers of human lymphocyte antigen A2 that were complexed with two different human immunodeficiency virus (HIV)-derived peptides or with a peptide derived from influenza A matrix protein bound to peptide-specific cytotoxic T cells in vitro and to T cells from the blood of HIV-infected individuals and correlated well with cytotoxicity assays.
Abstract: Identification and characterization of antigen-specific T lymphocytes during the course of an immune response is tedious and indirect. To address this problem, the peptide-major histocompatability complex (MHC) ligand for a given population of T cells was multimerized to make soluble peptide-MHC tetramers. Tetramers of human lymphocyte antigen A2 that were complexed with two different human immunodeficiency virus (HIV)-derived peptides or with a peptide derived from influenza A matrix protein bound to peptide-specific cytotoxic T cells in vitro and to T cells from the blood of HIV-infected individuals. In general, tetramer binding correlated well with cytotoxicity assays. This approach should be useful in the analysis of T cells specific for infectious agents, tumors, and autoantigens.

3,824 citations

Journal ArticleDOI
09 Jul 1999-Science
TL;DR: Immunological synapse formation is now shown to be an active and dynamic mechanism that allows T cells to distinguish potential antigenic ligands and was a determinative event for T cell proliferation.
Abstract: The specialized junction between a T lymphocyte and an antigen-presenting cell, the immunological synapse, consists of a central cluster of T cell receptors surrounded by a ring of adhesion molecules. Immunological synapse formation is now shown to be an active and dynamic mechanism that allows T cells to distinguish potential antigenic ligands. Initially, T cell receptor ligands were engaged in an outermost ring of the nascent synapse. Transport of these complexes into the central cluster was dependent on T cell receptor—ligand interaction kinetics. Finally, formation of a stable central cluster at the heart of the synapse was a determinative event for T cell proliferation. A critical event in the initiation of the adaptive

2,988 citations

Journal ArticleDOI
04 Aug 1988-Nature
TL;DR: This view of T-cell recognition has implications for how the receptors might be selected in the thymus and how they (and immunoglobulins) may have arisen during evolution.
Abstract: The four distinct T-cell antigen receptor polypeptides (alpha, beta, gamma, delta) form two different heterodimers (alpha:beta and gamma:delta) that are very similar to immunoglobulins in primary sequence, gene organization and modes of rearrangement. Whereas antibodies have both soluble and membrane forms that can bind to antigens alone, T-cell receptors exist only on cell surfaces and recognize antigen fragments only when they are embedded in major histocompatibility complex (MHC) molecules. Patterns of diversity in T-cell receptor genes together with structural features of immunoglobulin and MHC molecules suggest a model for how this recognition might occur. This view of T-cell recognition has implications for how the receptors might be selected in the thymus and how they (and immunoglobulins) may have arisen during evolution.

2,858 citations

Journal ArticleDOI
TL;DR: Of 10 distinct cloned DNA copies of mRNAs expressed in T lymphocytes but not in B lymphocytes and associated with membrane-bound polysomes, one hybridizes to a region of the genome that has rearranged in a T- cell lymphoma and several T-cell hybridomas, suggesting that it encodes one chain of the elusive antigen receptor on the surface of T lymphocyte.
Abstract: Of 10 distinct cloned DNA copies of mRNAs expressed in T lymphocytes but not in B lymphocytes and associated with membrane-bound polysomes, one hybridizes to a region of the genome that has rearranged in a T-cell lymphoma and several T-cell hybridomas. These characteristics suggest that it encodes one chain of the elusive antigen receptor on the surface of T lymphocytes.

1,218 citations

Journal ArticleDOI
06 Apr 2007-Cell
TL;DR: It is shown that increasing miR-181a expression in mature T cells augments the sensitivity to peptide antigens, while inhibition in the immature T cells reduces sensitivity and impairs both positive and negative selection.

1,185 citations


Cited by
More filters
28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
24 May 2001-Nature
TL;DR: 21-nucleotide siRNA duplexes provide a new tool for studying gene function in mammalian cells and may eventually be used as gene-specific therapeutics.
Abstract: RNA interference (RNAi) is the process of sequence-specific, post-transcriptional gene silencing in animals and plants, initiated by double-stranded RNA (dsRNA) that is homologous in sequence to the silenced gene. The mediators of sequence-specific messenger RNA degradation are 21- and 22-nucleotide small interfering RNAs (siRNAs) generated by ribonuclease III cleavage from longer dsRNAs. Here we show that 21-nucleotide siRNA duplexes specifically suppress expression of endogenous and heterologous genes in different mammalian cell lines, including human embryonic kidney (293) and HeLa cells. Therefore, 21-nucleotide siRNA duplexes provide a new tool for studying gene function in mammalian cells and may eventually be used as gene-specific therapeutics.

10,451 citations

Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations