Mature dendritic cells pulsed with exosomes stimulate efficient cytotoxic T‐lymphocyte responses and antitumour immunity
Bibliographic record
Abstract
Exosomes (EXO) derived from dendritic cells (DC), which express major histocompatibility complex (MHC) and costimulatory molecules, have been used for antitumour vaccines. However, they are still less effective by showing only prophylatic immunity in animal models or very limited immune responses in clinical trials. In this study, we showed that ovalbumin (OVA) protein-pulsed DC (DC(OVA))-derived EXO (EXO(OVA)) displayed MHC class I-OVA I peptide (pMHC I) complexes, CD11c, CD40, CD80, CCR7, DEC205, Toll-like receptor 4 (TLR4), TLR9, MyD88 and DC-SIGN molecules, but at a lower level than DC(OVA). EXO(OVA) can be taken up by DC through LFA-1/CD54 and C-type lectin/mannose (glucosamine)-rich C-type lectin receptor (CLR) interactions. Mature DC pulsed with EXO(OVA), which were referred to as mDC(EXO), expressed a higher level of pMHC I, MHC II, and costimulatory CD40, CD54 and CD80 than DC(OVA). The mDC(EXO) could more strongly stimulate OVA-specific CD8(+) T-cell proliferation in vitro and in vivo, and more efficiently induce OVA-specific cytotoxic T-lymphocyte responses, antitumour immunity and CD8(+) T-cell memory in vivo than EXO(OVA) and DC(OVA). In addition, mDC(EXO) could also more efficiently eradicate established tumours. Therefore, mature DC pulsed with EXO may represent a new, highly effective DC-based vaccine for the induction of antitumour immunity.
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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) | 0.001 | 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) | 0.001 | 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".