ATM deficiency disrupts Tcra locus integrity and the maturation of CD4+CD8+ thymocytes
Bibliographic record
Abstract
Mutations in ATM (ataxia-telangiectasia mutated) cause ataxia-telangiectasia (AT), a disease characterized by neurodegeneration, sterility, immunodeficiency, and T-cell leukemia. Defective ATM-mediated DNA damage responses underlie many aspects of the AT syndrome, but the basis for the immune deficiency has not been defined. ATM associates with DNA double-strand breaks (DSBs), and some evidence suggests that ATM may regulate V(D)J recombination. However, it remains unclear how ATM loss compromises lymphocyte development in vivo. Here, we show that T-cell receptor beta (TCRbeta)-dependent proliferation and production of TCRbeta(low) CD4+CD8+ (DP) thymocytes occurred normally in Atm-/- mice. In striking contrast, the postmitotic maturation of TCRbeta(low) DP precursors into TCRbeta(int) DP cells and TCRbeta(hi) mature thymocytes was profoundly impaired. Furthermore, Atm-/- thymocytes expressed abnormally low amounts of TCRalpha mRNA and protein. These defects were not attributable to the induction of a BCL-2-sensitive apoptotic pathway. Rather, they were associated with frequent biallelic loss of distal Va gene segments in DP thymocytes, revealing that ATM maintains Tcra locus integrity as it undergoes V(D)J recombination. Collectively, our data demonstrate that ATM loss increases the frequency of aberrant Tcra deletion events, which compromise DP thymocyte maturation and likely promote the generation of oncogenic TCR translocations.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".