Advances in Type I Diabetes Associated Tolerance Mechanisms
Bibliographic record
Abstract
Type 1 diabetes (T1D) is an autoimmune disease resulting from the destruction of insulin-producing pancreatic beta cells by autoreactive T cells. The polygenic trait for T1D risk implicates many genes that have an impact on fundamental immunological processes such as central and peripheral tolerance. Several pieces of evidence have suggested that many of the genetic loci that are directly linked to type 1 diabetes susceptibility modulate the generation and/or the activation of autoreactive T-lymphocytes. We and others have proposed a critical role for medullary thymic epithelial cells (mTEC) forming the Hassall's corpuscles in T-cell tolerance. Indeed, mTEC have been found to express promiscuous self-antigens, used directly or through thymic dendritic cells to drive either negative selection of insulin-reacting precursors or their differentiation into naturally occurring regulatory Foxp3+ CD4+ CD25+ T cells. In the periphery, naturally occurring Foxp3+ CD4+ CD25+regulatory T (Treg) cells represent the master cells in dominant peripheral T-cell tolerance. The development and function of Treg cells are ultimately linked to IL-2 and Foxp3 expression. This review addresses recent literature and emerging concepts of central and peripheral T-cell tolerance with regards to T1D.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".