Opposite Ability of Pre-TCR and αβTCR to Induce Apoptosis
Bibliographic record
Abstract
In early CD4(-)CD8(-) pro-thymocytes, signaling through the pre-TCR is crucial for survival and differentiation into CD4(+)CD8(+) cells. At this more mature stage, interactions between alphabetaTCR and self-Ag/MHC complexes in turn lead either to cell survival and differentiation (positive selection) or to cell death (negative selection). Intrinsic differences must therefore exist between pre-TCR signals in CD4(-)CD8(-) thymocytes and alphabetaTCR signals in CD4(+)CD8(+) cells, since only the latter can mediate a death signal. In this work, we directly compared the capability of pre-TCR and alphabetaTCR to induce apoptosis in a CD4(-)CD8(-) thymoma cell line following receptor cross-linking with mAbs. Cross-linking of alphabetaTCR triggered high levels of programmed cell death, mimicking the negative selection signal usually induced in CD4(+)CD8(+) thymocytes. In contrast, pre-TCR was very inefficient at inducing apoptosis upon cross-linking, despite similar levels of surface receptor expression. Importantly, inefficient apoptosis induction by the pre-TCR did not result from its weak association with TCRzeta chain, since TCRs containing alpha-pTalpha chimeric chains, binding weakly to TCRzeta, were still able to induce apoptosis. Although similar tyrosine phosphorylation and calcium influx were induced after either pre-TCR or alphabetaTCR cross-linking, the two pathways diverged at the level of Fas ligand induction. Among putative transcription factors involved in Fas ligand mRNA induction, Nur77 and NFAT transcriptional activities were readily induced after alphabetaTCR, but not pre-TCR, stimulation. Together, these results support the view that the structure of the pre-TCR and alphabetaTCR directly influences their apoptosis-inducing capabilities by activating distinct signaling pathways.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".