Sci‐YIS Fri ‐ 03: Calculation of singlet oxygen dose from photosensitizer photobleaching during mTHPC or Photofrin photodynamic therapy <i>in vitro</i>
Bibliographic record
Abstract
Photodynamic therapy (PDT) is emerging as a treatment option for various malignant conditions. PDT damage is caused by the generation of singlet oxygen. This process is dependent on the complex interaction between the photosensitizer (PS), treatment light, and oxygen. Since these parameters may be highly variable among patients and may change during treatment, it is difficult to predict therapeutic outcome based on administered PS and delivered light dose alone. An implicit dose metric model has been proposed in which singlet oxygen dose is monitored by the decrease in PS fluorescence during treatment caused by reactions between PS and singlet oxygen. To investigate this, MatLyLu (MLL) rat prostate adenocarcinoma cells were incubated with Foscan (mTHPC) or Photofrin and treated with the appropriate wavelength of light. Fluorescence was monitored during treatment and, at selected fluence levels, cell viability was determined using a colony formation assay. Singlet oxygen dose models were developed based on measurements of PS fluorescence and reaction kinetics. Cell survival correlated well to calculated singlet oxygen dose, independent of initial PS concentration, treatment fluence rate, and oxygenation. These results indicate that investigation of photobleaching is warranted as an in vivo dose metric. We found 1.5 ± 0.3 and 0.45 ± 0.09 mM of singlet oxygen was required to reduce the survival fraction by 1/e for mTHPC and Photofrin respectively.
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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) | 0.000 | 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) | 0.002 | 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".