<i>In Vitro</i> Survival of Nonsmall Cell Lung Cancer Cells Following Combined Treatment with Ionizing Radiation and Photofrin‐mediated Photodynamic Therapy
Bibliographic record
Abstract
It has been suggested that combination high dose rate (HDR) intraluminal brachytherapy and photodynamic therapy (PDT) in nonsmall cell lung cancer (NSCLC) may improve efficacy of treatment, reduce toxicity and enhance quality of life for patients. To provide a cellular basis for this we examined the in vitro sensitivity of MRC5 normal lung fibroblasts and four NSCLC cell lines following HDR radiation, PDT and combined HDR radiation and PDT. HDR radiation was cobalt-60 gamma rays (1.5-1.9 Gy min(-1)). For PDT treatment, cells were exposed to 2.5 microg mL(-1) Photofrin for 18-24 h followed by light exposure (20 mW cm(-2)). For combined treatment cells were exposed to Photofrin and then either exposed to light and 15-30 min later exposed to HDR radiation or exposed to HDR radiation and 15-30 min later exposed to light. D(37) values calculated from clonogenic survival curves indicated a six-fold difference in HDR radiation sensitivity and an eight-fold difference in PDT sensitivity. The effect of combined treatment was not significantly different from an additive effect of the individual treatment modalities for the NSCLC cells, but was significantly less than additive for the MRC5 cells. These results suggest an equivalent tumor cell kill may be possible at reduced systemic effects to patients.
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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) | 0.001 | 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) | 0.001 | 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".