Targeted photodynamic therapy of cancer using a novel gallium (III) tris (ethoxycarbonyl) corrole conjugated‐mAb directed against cancer/testis antigens 83
Bibliographic record
Abstract
Photodynamic therapy (PDT) is a noninvasive, highly selective approach to the treatment of tumors. However, its therapeutic effect is limited by long-lasting skin phototoxicity. Therefore, to compromise this shortcoming, it is preferable to deliver photosensitizers selectively to tumor cells with the aid of antibodies specific against tumor-associated antigens. Cancer/testis antigens 83 (CT83), also called KK-LC-1 or CXorf61, recognized by cytotoxic T lymphocytes (CTL), has become a promising target for immunotherapy. Herein, we developed and characterized a novel mouse CT83 mAb 7G4 with a high affinity with Gallium (III) 5, 10, 15-tris (ethoxycarbonyl) corrole (1-Ga), a new and promising photosensitizer in PDT. The enzyme-linked immunosorbent assay (ELISA), flow cytometry and cytotoxicity activity assays revealed that 7G4-1-Ga was able to recognize human CT83 with high specificity. Furthermore, 7G4-1-Ga showed greater cytotoxicity to CT83-expressing human cancer cells in vitro than 1-Ga. These results suggest that the antibody-conjugated photosensitizer between anti-CT83 mAb and 1-Ga may have a good application in PDT, where the destruction of CT83-expressing tumor is required.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".