CD8+ Cytotoxic T-APC Stimulate Central Memory CD8+ T Cell Responses via Acquired Peptide-MHC Class I Complexes and CD80 Costimulation, and IL-2 Secretion
Bibliographic record
Abstract
We previously showed that naive CD4+ Th cells acquire peptide-MHC class I (pMHC I) and costimulatory molecules from OVA-pulsed dendritic cells (DC(OVA)), and act as Th-APCs in stimulation of CD8+ CTL responses. In this study, we further demonstrated that naive CD8+ cytotoxic T (Tc) cells also acquire pMHC I and costimulatory CD54 and CD80 molecules by DC(OVA) stimulation, and act as Tc-APC. These Tc-APC can play both negative and positive modulations in antitumor immune responses by eliminating DC(OVA) and neighboring Tc-APC, and stimulating OVA-specific CD8+ central memory T responses and antitumor immunity. Interestingly, the stimulatory effect of Tc-APC is mediated via its IL-2 secretion and acquired CD80 costimulation, and is specifically targeted to OVA-specific CD8+ T cells in vivo via its acquired pMHC I complexes. These principles could be applied to not only antitumor immunity, but also other immune disorders (e.g., autoimmunity).
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".