Contribution of 4–1<scp>BB</scp>L on radioresistant cells in providing survival signals through 4–1<scp>BB</scp> expressed on <scp>CD</scp>8+ memory <scp>T</scp> cells in the bone marrow
Bibliographic record
Abstract
The persistence of memory lymphocytes is a critical feature of adaptive immunity. The TNF family ligand 4-1BBL supports the antigen-independent survival of CD8⁺ memory T cells. Here, we show that mice lacking 4-1BB only on αβ T cells show a similar defect in CD8⁺ T-cell recall responses, as previously shown in 4-1BBL-deficient mice. We show that 4-1BB is selectively expressed on BM CD8⁺ but not CD4⁺ memory T cells of unimmunized mice. Its ligand, 4-1BBL, is found on VCAM-1⁺ stromal cells, CD11c⁺ cells, and a Gr1(lo) myeloid population in unimmunized mice. Adoptive transfer of in vitro generated memory T cells into mice lacking 4-1BBL only on radioresistant cells recapitulates the defect in CD8⁺ T-cell survival seen in the complete knockout mice, with smaller effects of 4-1BBL on hematopoietic cells. In BM, adoptively transferred DsRed CD8⁺ memory T cells are most often found in proximity to VCAM-1⁺ cells or Gr1⁺ cells, followed by B220⁺ cells and to a much lesser extent near CD11c⁺ cells. Thus, a VCAM-1⁺CD45(-) stromal cell is a plausible candidate for the radioresistant cell that provides 4-1BBL to CD8⁺ memory T cells in the BM.
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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) | 0.001 | 0.001 |
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".