Interleukin-21 Accelerates Thymic Recovery from Glucocorticoïd-Induced Atrophy
Bibliographic record
Abstract
Both physiological and psychological stress cause thymic atrophy via glucocorticoïd (GC)-dependent apoptosis of double-positive (DP) thymocytes. Given the pervasiveness of stress, GC-induced thymic atrophy is arguably the most common type of acquired immunodeficiency. We recently reported that interleukin-21 (IL-21) has a unique ability to expand the small subset of DP thymocytes (CD69(+)) which are ongoing positive selection, and that administration of IL-21 increases thymic output in aged mice. The goal of this study was to evaluate whether IL-21 could mitigate GC-induced thymic atrophy. In contrast to double-negative (DN) and single-positive (SP) thymocytes, most DP thymocytes (CD69(-)) do not constitutively express the IL-21 receptor (IL-21R). Accordingly, CD69(-) DP thymocytes from PBS-treated mice were unresponsive to IL-21 administration. However, following GC injection, surviving CD69(-) DP thymocytes up-regulated IL-21R and responded to IL-21 treatment as evidenced by enhancement of Bcl6 expression and phosphorylation of STAT1, STAT3 and STAT5. Consequently, IL-21 administration to GC-treated mice accelerated thymic recovery by expanding considerably DP thymocytes and, to a lesser extent, DN thymocytes. However, IL-21-induced expansion of DN/DP thymocytes did not alter the diversity of the intrathymic or peripheral T-cell receptor (TCR) repertoire. We conclude that IL-21 dramatically accelerates recovery from GC-induced thymic atrophy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".