Cross-Linking of Signal Transducer and Activator of Transcription 3—A Molecular Marker for the Photodynamic Reaction in Cells and Tumors
Bibliographic record
Abstract
PURPOSE: Photodynamic therapy (PDT) depends on the delivery of a photosensitizer to the target tissue that, under light exposure, produces singlet oxygen and other reactive oxygen species, which in turn cause the death of the treated cell. This study establishes a quantitative marker for the photoreaction that will predict the outcome of PDT. EXPERIMENTAL DESIGN: Cells in tissue culture, murine s.c. tumors, and endobronchial carcinomas in patients were treated with PDT, and the noncleavable cross-linking of the latent signal transducer and activator of transcription 3 (STAT3) was determined. RESULTS: Murine and human cancer cell lines reacted to PDT by an immediate covalent cross-linking of STAT3 to homodimeric and other complexes. The magnitude of this effect was strictly a function of the PDT reaction that is determined by the photosensitizer concentration and light dose. The cross-link reaction of STAT3 was proportional to the subsequent cytotoxic outcome of PDT. An equivalent photoreaction as detected in vitro occurred in tumors treated in situ with PDT. The light dose-dependent STAT3 cross-linking indicated the relative effectiveness of PDT as a function of the distance of the tissue to the treating laser light source. Absence of cross-links correlated with treatment failure. CONCLUSIONS: The data suggest that the relative amount of cross-linked STAT3 predicts the probability for beneficial outcome, whereas absence of cross-links predicts treatment failure. Determination of STAT3 cross-links after PDT might be clinically useful for early assessment of PDT response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".