Characterization of time-domain fluorescence properties of typical photosensitizers for photodynamic therapy
Bibliographic record
Abstract
We report the investigation of fluorescence lifetime of delta-aminolevulinic acid (ALA) induced protoporphyrin IX (PpIX) and Photofrin© in vitro in MAT-LyLu (MLL) rat prostate adenocarcinoma cells. Photodynamic therapy (PDT) has been extensively investigated in the past decade as an effective treatment option for various types of invasive tumors. The efficacy of PDT treatment depends strongly on cell uptake and subsequent excitation of the photosensitizers. Characterization of fluorescence lifetime of these drugs provides the basis for further investigation of in vivo PDT dosage measurements using time-domain spectroscopy and imaging. Physiologically relevant concentrations of the photosensitizer solutions were prepared. A picosecond diode laser was used to excite the two drugs and the time-resolved fluorescence decay was recorded using a time-correlated single photon counting (TCSPC) system. MLL cells were incubated with the photosensitizers and were treated with light under well-oxygenated or hypoxic conditions. Fluorescence lifetime images of these cells were recorded by a confocal FLIM microscope. The measured fluorescence lifetimes of both photosensitizers are much longer than typical endogenous tissue fluorescence, which suggests time-domain methods are good candidates for in vivo PDT monitoring.
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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) | 0.000 | 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 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".