Photodynamic Actinometry Using Microspheres: Concept, Development and Responsivity¶
Bibliographic record
Abstract
Photodynamic therapy (PDT) relies on three main ingredients, oxygen, light and photoactivating compounds, although the PDT response is definitively contingent on the site and level of reactive oxygen species (ROS) generation. This study describes the development of a novel, fluorescent-based actinometer microsphere system as a means of discerning spatially resolved dosimetry of total fluence and ROS production. Providing a high resolution, localized, in situ measurement of fluence and ROS generation is critical for developing in vivo PDT protocols. Alginate-poly-L-lysine-alginate microspheres were produced using ionotropic gelation of sodium alginate droplets, ranging from 80 to 200 microm in diameter, incorporating two dyes, ADS680WS (ADS) and Rhodophyta-phycoerythrin (RPE), attached to the spheres' inside and outside layers, respectively. To test the responsivity and dynamic range of RPE for ROS detection, the production of ROS was initiated either chemically using increasing concentrations of potassium perchromate or photochemically using aluminum tetrasulphonated phthalocyanine. The generation of singlet oxygen was confirmed by phosphorescence at 1270 nm. The resulting photodegradation and decrease in fluorescence of RPE was found to correlate with increased perchromate or PDT treatment fluence, respectively. This effect was independent of pH (6.5-8) and could be inhibited using sodium azide. RPE was not susceptible to photobleaching with light alone (670 nm; 150 Jcm(-2)). ADS, which absorbs light between 600 and 750 nm, showed a direct correlation between radiant exposure (670 nm; 0-100 Jcm(-2)) and diminished fluorescence. Photobleaching was independent of irradiance (10-40 mW cm(-2)). We propose that actinometer microspheres may provide a means for obtaining high spatial resolution information regarding delivered PDT dose within model systems during investigational PDT development and dosimetric information for clinical extracorporeal PDT as in the case of ex vivo bone marrow purging.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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".