Phototransformation of hematoporphyrin in aqueous solution: Anomalous behavior at low oxygen concentration
Bibliographic record
Abstract
The photoactivation of a photosensitizer is the initial step in photodynamic therapy (PDT) where photochemical reactions result in the production of reactive oxygen species and eventually cell death. In addition to oxidizing biomolecules, some of these photochemical reactions lead to photosensitizer degradation at a rate dependent on the oxygen concentration among other factors. We investigated photodegradation of Photogem ® (28 μM), a hematoporphyrin derivative, at different oxygen concentrations (9.4 to 625.0 μM) in aqueous solution. The degradation was monitored by fluorescence spectroscopy. The degradation rate (M/s) increases as the oxygen concentration increases when the molar ratio of oxygen to Photogem® is greater than 1. At lower oxygen concentrations (<25 μM) an inversion of this behavior was observed. The data do not fit a simple kinetic model of first-order dependence on oxygen concentration. This inversion of the degradation rate at low oxygen concentration has not previously been demonstrated and highlights the relationship between photosensitizer and oxygen concentrations in determining the photobleaching mechanism(s). The findings demonstrate that current models for photobleaching are insufficient to explain completely the effects at low oxygen concentration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".