Advanced Photosensitizer Activation Strategies for Smarter Photodynamic Therapy Beacons
Bibliographic record
Abstract
Abstract Photodynamic therapy (PDT) is a clinical treatment in which a light‐absorbing drug called a photosensitizer (PS) is combined with light and molecular oxygen to generate cytotoxic singlet oxygen. PDT provides additional tissue selectivity compared to conventional chemotherapy as singlet oxygen is generated only in areas in which PS accumulates and that are simultaneously illuminated by a light source with sufficient irradiance and dose. Early PDT beacons built on this concept by adding an analyte‐responsive element that simultaneously turns on PDT and fluorescence, providing both an additional layer of selectivity and real‐time feedback of the PS′s activation state. More recent PDT beacons have expanded this idea, with new methods now available for sensing analytes, generating singlet oxygen, and reporting treatment status. In this Minireview, we consider developments in advanced activation strategies implemented in therapeutic and theranostic beacons.
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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 | 0.000 | 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 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".