Temporal Segregation of 4-1BB Versus CD28-Mediated Costimulation: 4-1BB Ligand Influences T Cell Numbers Late in the Primary Response and Regulates the Size of the T Cell Memory Response Following Influenza Infection
Bibliographic record
Abstract
In this report, we demonstrate that CD28(-/-) mice are severely impaired in the initial expansion of D(b)/NP366-374-specific CD8 T cells in response to influenza virus infection, whereas 4-1BB ligand (4-1BBL)(-/-) mice show no defect in primary T cell expansion to influenza virus. In contrast, 4-1BBL(-/-) mice show a decrease in D(b)/NP366-374-specific T cells late in the primary response. Upon secondary challenge with influenza virus, 4-1BBL(-/-) mice show a decrease in the number of D(b)/NP366-374-specific T cells compared to wild-type mice such that the level of the CD8 T cell expansion during the in vivo secondary response is reduced to the level of a primary response, with concomitant reduction of CTL effector function. In contrast, Ab responses, as well as secondary CD4 T cell responses, to influenza are unaffected by 4-1BBL deficiency. Thus, CD28 is critical for initial T cell expansion, whereas 4-1BB/4-1BBL signaling affects T cell numbers much later in the response and is essential for the survival and/or responsiveness of the memory CD8 T cell pool.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".