Age-dependent Zap70 expression in thymocytes regulates selection of the neonatal regulatory T cell repertoire
Bibliographic record
Abstract
The Foxp3⁺ regulatory T (Treg) cell repertoire carries age-dependent biases, with neonatal subsets enriched for highly self-reactive clones. However, the thymocyte features distinguishing neonatal from adult Treg selection remain unclear. Here, we show that neonatal double-positive mouse thymocytes, unlike their adult counterparts, fail to upregulate Zap70 during thymic selection, creating a calcium signaling bottleneck. This attenuated Zap70-dependent signaling limits negative selection, allowing highly self-reactive clones to evade deletion. Modulating Zap70 expression alters this balance; reducing Zap70 in adults rescues development of these clones, whereas increasing Zap70 in neonates enforces their deletion. Similarly, enhancing neonatal calcium signaling via increased LAT Y136-mediated PLCγ1 activation promotes clonal deletion. Analysis of pediatric human thymi reveals that ZAP70 expression remains low during the first year of life, aligning with the peak window for thymic Treg cell development. These findings suggest that age-dependent Zap70 expression regulates negative selection and thymic Treg cell development. Lo and colleagues report that double-positive thymocytes from neonates express less Zap70 and show reduced Ca2⁺/NFAT signaling compared to double-positive thymocytes from older thymi. This diminished Ca2⁺ signaling alters negative selection for self-reactive TCRs, resulting in a cell-intrinsic temporal window for regulatory T versus conventional T cell development in the thymus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".