GJIC Enhances the phototoxicity of photofrin‐mediated photodynamic treatment by the mechanisms related with ROS and Calcium pathways
Bibliographic record
Abstract
Despite initially positive responses, recurrences after Photodynamic treatment (PDT) can occur and there is need for improvement in the effectiveness of PDT. Our study uniquely showed that there was a significantly gap junctional intercellular communication (GJIC)‐dependent PDT cytotoxicity. The presence of GJIC composed of Connexin 32 increased the PDT phototoxicity in transfected HeLa cells and in the xenograft tumors, and the enhanced phototoxicity of Photofrin‐mediated PDT by GJIC was related with ROS and calcium pathways. Our study indicates the possibility that up‐regulation or maintenance of gap junction functionality may be used to increase the efficacy of PDT. The phototoxicity effect of Photofrin was substantially greater in Dox‐treated cells, which expressed the Cx32 and formed the GJ, than Dox‐untreated. magnified image The phototoxicity effect of Photofrin was substantially greater in Dox‐treated cells, which expressed the Cx32 and formed the GJ, than Dox‐untreated.
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) | 0.002 | 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".