Elevated IL-7 availability does not account for T cell proliferation in moderate lymphopenia. (104.11)
Bibliographic record
Abstract
Abstract Lymphopenia-induced proliferation (LIP) is a proliferative program initiated in response to T cell insufficiency caused by acute or chronic immunodepletion. Studies of lymphopenic mice have demonstrated that the cytokine IL-7 and TCR signaling are critical for LIP. We examined how these two factors impact T cell proliferation following transfer into moderately lymphopenic mice. We show here that moderate lymphopenia (~25% of WT lymphocytes) of IL-7Rα knock-in mutant (IL-7Rα449F) mice supports T cell proliferation, although with decreased frequency and kinetics compared to cells transferred to severely lymphopenic (5% of WT) IL-7Rα-/- hosts. Although previous studies have demonstrated that elevated IL-7 levels play an important role in LIP, IL-7 availability was not elevated in IL-7Rα449F mice. However, moderate lymphopenia increased access of transferred T cells to self-peptide presented on antigen presenting cells that can trigger TCR signaling and proliferation. Importantly, we did not detect significant changes in TCR Vβ usage of proliferated T cells recovered from either moderately or severely lymphopenic hosts. Our work demonstrates that polyclonal T cells retain a diverse TCR repertoire following proliferation mediated by either self-peptide/MHC interaction alone or in combination with IL-7, and that T cell reconstitution is most efficient in the presence of increased IL-7 availability.
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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 | 0.001 |
| 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".