Using fluorescence to augment the efficacy of photodynamic therapy
Bibliographic record
Abstract
Photodynamic Therapy (PDT) is a relatively novel oncological treatment modality, in which a patient is administered a photosensitive drug, called a photosensitizer. After allowing sufficient time for biodistribution, the cancerous area is irradiated with light of the appropriate wavelength, activating the photosensitizer to produce highly reactive singlet oxygen, which produces a highly localized cell kill. The efficacy of PDT is determined by a) the intensity of the light b) the local concentration of the photosensitizer, and c) the availability of oxygen. However, with the clinical application of PDT, the patient is simply administered a body mass dependent quantity of photosensitizer, and then the target area is administered a prescribed amount of radiant energy (joules per cubic centimetre). For treatment of superficial malignancies, PDT has many successes; however, interstitial PDT (PDT of solid, internal malignancies) has inconsistent outcomes mostly due to the inability to predict, calculate or measure the variables that affect PDT: the radiation dose, oxygen concentration, and the photosensitizer concentration. We have developed sophisticated methods to determine the behaviour of light in homogeneous biological tissues. Tissue oxygen levels can be replenished by fractionating the light dose - allowing areas of your target tissue to go through a "dark" cycle during PDT. However, to date, there has not been an accurate method of determining tissue photosensitizer concentrations in-vivo. We are researching the efficacy of a novel hypocrellin derivative, SL-052. Like other photosensitizers available, SL-052 shows strong therapeutic photodynamic activity when irradiated by 635 nm light. Like most photosensitizers, SL-052 exhibits fluorescent activity, but SL-052 also shows strong fluorescent emission at 725nm when excited by 635 nm. The intensity of the fluorescent emission can been correlated with the local concentration of the photosenstizer. However, many clinically available photosensitizers require that fluorescence is excited using a wavelength of light much shorter than the therapeutic wavelength. This characteristic allows us to monitor the availability of the photosensitizer during PDT and to correlate the outcome of PDT to the observed fluorescence. In this paper, we monitor the temporal distribution of SL-052 in the Dunning R3327-AT cell line grown on the flank of a Fisher Copenhangen rats.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".