Background: T cells in the thymus undergo opposing positive and negative selection processes so that the only T cells entering circulation are those bearing a T cell receptor (TCR) with a low affinity for self. The mechanism differentiating negative from positive selection is poorly understood, despite the fact that inherited defects in negative selection underlie organ-specific autoimmune disease in AIRE-deficient people and the non-obese diabetic (NOD) mouse strain
Results: Here we use homogeneous populations of T cells undergoing either positive or negative selection in vivo together with genome-wide transcription profiling on microarrays to identify the gene expression differences underlying negative selection to an Aire-dependent organ-specific antigen, including the upregulation of a genomic cluster in the cytogenetic band 2F. Analysis of defective negative selection in the autoimmune-prone NOD strain demonstrates a global impairment in the induction of the negative selection response gene set, but little difference in positive selection response genes. Combining expression differences with genetic linkage data, we identify differentially expressed candidate genes, including Bim, Bnip3, Smox, Pdrg1, Id1, Pdcd1, Ly6c, Pdia3, Trim30 and Trim12.
Conclusion: The data provide a molecular map of the negative selection response in vivo and, by analysis of deviations from this pathway in the autoimmune susceptible NOD strain, suggest that susceptibility arises from small expression differences in genes acting at multiple points in the pathway between the TCR and cell death.
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http://dx.doi.org/10.1186/gb-2007-8-1-r12 | DOI Listing |
Plant Dis
January 2025
Henan University of Science and Technology, agricultural college, Luoyang, [Select a State/Province], China;
Sweetpotato Stem Rot Nematode () causes the most devastating disease affecting sweetpotato production in China. The objectives of this study were: i) establish a quantification method using real-time PCR for of sweetpotato; ii) analyze the effect of density at harvest on the percentage of disease incidence in sweetpotatoes; and iii) evaluate the effect of soil physical properties on disease incidence. Populations of isolated from 28 different production areas in Henan Province exhibited identical sequences, and then real-time PCR specific primers (PRNf and PRNr) were designed.
View Article and Find Full Text PDFPlant Dis
January 2025
No. 483, Wushan Road, Tianhe District,Guangzhou, China, 510642;
Pitaya canker disease, caused by , is the primary threat to pitaya cultivation, significantly compromising fruit quality and reducing yield. WRKY transcription factors are essential regulators in plant pathogen recognition and defense mechanisms, yet their specific roles in the development of pitaya canker disease remain largely unexplored. In this study, five genes (, , , , and ) associated with pitaya canker disease were identified through RNA-Seq analysis.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Industrial and Systems Engineering, The University of Florida, GAINESVILLE, FL, United States.
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.
View Article and Find Full Text PDFAdv Biotechnol (Singap)
January 2025
School of Agriculture and Biotechnology, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, People's Republic of China.
Low efficiency and high surface runoff of 2,4-dichlorophenoxyacetic acid (2,4-D) from agricultural field threaten crop yield severely. Layered double hydroxides (LDH) have shown promising adsorption properties for 2,4-D. However, the comparison of two environmentally friendly LDHs (i.
View Article and Find Full Text PDFTrop Anim Health Prod
January 2025
Laboratory of Small Ruminant Genetics, Breeding and Reproduction, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China.
Growth traits are one of the focuses of sheep breeding, and growth curve is an effective method to describe growth traits. The body weight of Yiling sheep at 0, 120, 180, 360 and 540 days of age were fitted with five common nonlinear growth models: Logistic, Gompertz, Von Bertalanffy, Brody and Negative exponential, and the growth models were evaluated by goodness of fit standard. The results showed that the Von Bertalanffy model was suitable for characterizing the growth of Yiling sheep.
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