Enhancing thymic function improves T-cell reconstitution and immune responses in aged mice
Bibliographic record
Abstract
Age-related thymic involution leads to diminished output of naïve T-cells. While this process is suggested to increase the risk of disease severity in the elderly following infection, direct evidence is lacking. We developed two mouse models that allow us to experimentally prevent or reverse thymic involution. Constitutive Myc expression in thymic epithelial cells (TEC) of middle-aged mice enhanced thymic function, and increased numbers of peripheral naïve CD4 and CD8 T-cells. Inducible Myc expression reversed age-related thymic involution and partially recovered peripheral naïve T-cell numbers. Importantly, improving thymic function in these settings preserved T-cell-dependent antibody responses and significantly reduced T-cell-associated mortality after infection with Toxoplasma gondii. Improved thymic function also rebalanced age-associated alterations in the Treg pool, and mitigated loss of the transcriptional Th1 signature in aged conventional T-cells. Our findings support the value of TEC-focused thymic regeneration strategies for enhancement of T-cell-mediated immunity in the elderly.
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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 | 0.001 | 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".