A specific cytotoxic T‐lymphocyte epitope presentation system for antitumor immunity
Bibliographic record
Abstract
The magnitude of CTL-mediated immunity response is highly dependent on the density of antigenic peptide-MHC I complexes at the cell surface. In this study, we adopt a novel strategy to promote the surface level of specific peptide-MHC I complexes. The strategy combines the inhibition of transporter associated with antigen processing (TAP) with the delivery of specific peptide into endoplasmic reticulum directly without the help of TAP. First, RNA interference (RNAi) technology was used to inhibit TAP expression for blocking endogenous epitope-assembled MHC class I on cell surface. Second, a peptide epitope of interest was covalently linked onto human beta-2-microglobulin (beta2m). Both TAP-specific siRNA and the peptide-linked beta2m were delivered into antigen-presentation cells sequentially or simultaneously using a retrovirus delivery system. The combined strategy produces a significant amount of MHC I loaded with specific epitopes on the surface while reducing endogenously peptide-assembled MHC class I both in vitro and in vivo. The efficacy of induction of specific immune response with the strategy against tumor cells is demonstrated in both tumor cell lines and a syngenic graft tumor model.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".