Agonist CD40 antibody mediated stimulation of antigen presenting cells cannot replace CD4+ T help for an effective CD8+ killer response (132.20)
Bibliographic record
Abstract
Abstract CD8+ cytotoxic T lymphocytes (CTL) play a central role in the defense against a range of viral, bacterial and parasitic infections. However, the mechanisms by which CD4+ T-cells provide help remain largely elusive. Here, we investigated the concept of replacing CD4+ T-cells requirement for an effective CTL by stimulating antigen presenting cells (APCs) through agonist-CD40 antibody (Ab). C57BL/6 (B6) and MHC class II knockout (KO) mice were intravenously immunized with agonist-CD40 Ab-crosslinked OVA-pulsed DCs (DCova) derived from B6 as well as MHC II KO mice. Consistent with previous work, CD8+ killer response was elicited in MHC class II KO mice, even in the absence of CD4+ T help. Interestingly, DCova from B6 mouse mounted significantly (p<0.05) higher CTL response in B6 mice in comparison to MHC class II KO mice. In contrast, MHC class II KO mouse-derived DCova stimulated lower and roughly similar CTL response both in B6 and MHC class II KO mice. Notably, booster immunization revealed that, although agonist-CD40 Ab endowed DCova (MHC class II KO) the ability to activate CD8+ T killers in the absence of CD4+ T help, but failed to imprint memory programme both in B6 and MHC class II KO mice. Thus, our findings suggest that CD40 ligand (CD40L)-CD40 signaling alone to APCs cannot provide complete help, and besides CD40-CD40L, some other immune components must also be contributing to DC-CD4+ T cell cross-talk for an effective CTL response.
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) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".