Immunological perspective of self versus tumor antigens: insights from the RIP‐gp model
Bibliographic record
Abstract
Self-reactive T cells in the body are controlled by mechanisms of peripheral tolerance that limit their activation and induction of immune pathology. Our understanding of these mechanisms has been advanced by the use of tissue-specific promoters to express neo-self-antigens. Here, we present findings using the RIP-gp (rat insulin promoter-glycoprotein) transgenic mouse, which expresses the lymphocytic choriomeningitis virus glycoprotein (LCMV-gp) specifically in the pancreatic β islet cells. T cells responsive to this antigen remain ignorant of the LCMV-gp expressed by the islets, and breaking tolerance is dependent upon the maturation status of antigen-presenting cells, the avidity of the T-cell receptor ligation, and the level of major histocompatibility complex expression in the pancreas. Furthermore, decreased activity of Casitas B-lineage lymphoma b, a negative regulator of T-cell receptor signaling, can allow recognition and destruction of the pancreatic islets. This review discusses the roles of these factors in the context of anti-tissue responses, both in the setting of autoimmunity and in anti-tumor immunity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".