Thymus Reconstitution in Young and Aged Mice Is Facilitated by In Vitro-Generated Progenitor T Cells
Bibliographic record
Abstract
The prolonged lag in T cell recovery seen in older patients undergoing hematopoietic stem cell transplant (HSCT), after chemo-/radiotherapy, can lead to immune dysfunction. As a result, recovering patients may experience a relapse in malignancies and opportunistic infections, leading to high mortality rates. The delay in T cell recovery is partly due to thymic involution, a natural collapse in the size and function of the thymus, as individuals age, and partly due to the damage sustained by the thymic stromal cells through exposure to chemo-/radiotherapy. There is a clear need for new strategies to accelerate intrathymic T cell reconstitution when treating aged patients to counter the effects of involution and cancer therapy regimens. Adoptive transfer of human progenitor T (proT) cells has been shown to accelerate T cell regeneration in radiation-treated young mice and to restore thymic architecture in immunodeficient mice. Here, we demonstrate that the adoptive transfer of in vitro-generated proT cells in aged mice (18-24 months) accelerated thymic reconstitution after treatment with chemotherapy and gamma irradiation compared to HSCT alone. We noted that aged mice appeared to have a more limited expansion of CD4-CD8- thymocytes and slower temporal kinetics in the development of donor proT cells into mature T cells, when compared to younger mice, despite following the same chemo/radiation regimen. This suggests a greater resilience of the young thymus compared to the aged thymus. Nevertheless, newly generated T cells from proT cell engrafted aged and young mice were readily present in the periphery accelerating the reappearance of new naïve T cells. Accelerated T cell recovery was also observed in both aged and young mice receiving both proT cells and HSCT. The strategy of transferring proT cells can potentially be used as an effective cellular therapy in aged patients to improve immune recovery and reduce the risk of opportunistic infections post-HSCT.
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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".