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。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

The process of programmed cell death, or apoptosis, is generally characterized by distinct morphological characteristics and energy-dependent biochemical mechanisms. Apoptosis is considered a vital component of various processes including normal cell turnover, proper development and functioning of the immune system, hormone-dependent atrophy, embryonic development and chemical-induced cell death. Inappropriate apoptosis (either too little or too much) is a factor in many human conditions including neurodegenerative diseases, ischemic damage, autoimmune disorders and many types of cancer. The ability to modulate the life or death of a cell is recognized for its immense therapeutic potential. Therefore, research continues to focus on the elucidation and analysis of the cell cycle machinery and signaling pathways that control cell cycle arrest and apoptosis. To that end, the field of apoptosis research has been moving forward at an alarmingly rapid rate. Although many of the key apoptotic proteins have been identified, the molecular mechanisms of action or inaction of these proteins remain to be elucidated. The goal of this review is to provide a general overview of current knowledge on the process of apoptosis including morphology, biochemistry, the role of apoptosis in health and disease, detection methods, as well as a discussion of potential alternative forms of apoptosis.

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Apoptosis: A Review of Programmed Cell Death

At high concentrations, free radicals and radical-derived, nonradical reactive species are hazardous for living organisms and damage all major cellular constituents. At moderate concentrations, how...

/pdf/free-radicals-in-the-physiological-control-of-cell-function-g3w3iyr0ph.pdf

Free Radicals in the Physiological Control of Cell Function

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Machine Learning : A Probabilistic Perspective

Comprehensive Integration of Single-Cell Data.

Proteomics and genomics: The emergent properties of biomarkers in mechanism and medicine

The present invention provides an approach for the simultaneous determination of the activation states of a plurality of proteins in single cells. This approach permits the rapid detection of heterogeneity in a complex cell population based on activation states, and the identification of cellular subsets that exhibit correlated changes in activation within the cell population. Moreover, this approach allows the correlation of cellular activities or properties. In addition, the use of potentiators of cellular activation allows for characterization of such pathways and cell populations.

Methods and compositions for risk stratification

Inhibition of HMGcoA reductase by atorvastatin prevents and reverses MYC-induced lymphomagenesis

The transcription factor JUN is highly expressed in pulmonary fibrosis. Its induction in mice drives lung fibrosis, which is abrogated by administration of anti-CD47. Here, we use high-dimensional mass cytometry to profile protein expression and secretome of cells from patients with pulmonary fibrosis. We show that JUN is activated in fibrotic fibroblasts that expressed increased CD47 and PD-L1. Using ATAC-seq and ChIP-seq, we found that activation of JUN rendered promoters and enhancers of CD47 and PD-L1 accessible. We further detect increased IL-6 that amplified JUN-mediated CD47 enhancer activity and protein expression. Using an in vivo mouse model of fibrosis, we found two distinct mechanisms by which blocking IL-6, CD47 and PD-L1 reversed fibrosis, by increasing phagocytosis of profibrotic fibroblasts and by eliminating suppressive effects on adaptive immunity. Our results identify specific immune mechanisms that promote fibrosis and suggest a therapeutic approach that could be used alongside conventional anti-fibrotics for pulmonary fibrosis.

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Activation of JUN in fibroblasts promotes pro-fibrotic programme and modulates protective immunity.

Autoimmune disorders represent inappropriate immune responses directed at self-tissue. Antigen-specific CD4+ T cells and antigen-presenting dendritic cells (DCs) are important mediators in the pathogenesis of auto-immune disease and thus are ideal candidates for adoptive cellular gene therapy, an ex vivo approach to therapeutic gene transfer. Using retrovirally transduced cells and luciferase bioluminescence, we have demonstrated that primary T cells, T cell hybridomas, and DCs rapidly and preferentially home to the sites of inflammation in animal models of multiple sclerosis, arthritis, and diabetes. These cells, transduced with retroviral vectors to drive expression of various “regulatory proteins” such as IL-4, IL-10, IL-12p40, and anti-TNF scFv, deliver these immunoregulatory proteins to the inflamed lesions, providing therapy for experimental autoimmune encephalitis (EAE), collagen-induced arthritis (CIA), and nonobese diabetic mice (NOD).

Garry P. Nolan

Papers

Proteomics and genomics: The emergent properties of biomarkers in mechanism and medicine

Methods and compositions for risk stratification

Inhibition of HMGcoA reductase by atorvastatin prevents and reverses MYC-induced lymphomagenesis

Activation of JUN in fibroblasts promotes pro-fibrotic programme and modulates protective immunity.

Treatment of autoimmune disease by adoptive cellular gene therapy.