Anti-CD3 scFv-B7.1 fusion protein expressed on the surface of HeLa cells provokes potent T-lymphocyte activation and cytotoxicityThis paper is one of a selection of papers in this Special Issue, entitled International Symposium on Recent Advances in Molecular, Clinical, and Social Medicine, and has undergone the Journal's usual peer-review process.
Bibliographic record
Abstract
The targeting of tumor cells by cytotoxic T lymphocytes is a promising strategy for biotherapy, but T cells require 2 signals via the T-cell receptor - CD3 complex and CD28 molecules for activation. To bridge the gap between cytotoxic T lymphocytes and tumor cells, our objective in this study was to describe the construction and the cell surface-anchored expression of a fusion protein, anti-CD3 scFv-B7.1, derived from inserting a fusion gene encoding anti-CD3 scFv and the extra-cellular domain of B7.1 fused by the splicing by overlap extension method into a mammalian expression vector, pDisplay. Transfection of the recombinant vector by electroporation into HeLa cells resulted in the production of protein migrating at approximately 57 kDa under reducing conditions. The expressed fusion protein could bind to T lymphocytes and induce strong T-cell activation. Meanwhile, a potent cytotoxicity was induced in the mixed culture of T-cell-modified tumor cells in a 96 h methyl-thiazolyl-diphenyl tetrazolium bromide assay. Our results indicate that this bifunctional protein, through activating T lymphocytes to lyse homologous human carcinomas, may be of potential value for T-cell-based immunotherapeutical treatment protocols in vivo.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".