Antitumor Efficacy of Photodynamic Therapy Using Novel Nanoformulations of Hypocrellin Photosensitizer SL052
Bibliographic record
Abstract
Recent preclinical and clinical testing of hypocrellin-based photosensitizer SL052 for use in photodynamic therapy (PDT) of cancer has shown encouraging results. Further optimization of its formulation for delivery could considerably extend the therapeutic efficiency of this drug. A nanoformulation encapsulating SL052 into biodegradable polymer poly(lactic-co-glycolic acid) (PLGA) was developed using a single-emulsion solvent evaporation technique and characterized in terms of particle size and loading of the photosensitizing agent. This nanoformulation, SL052-PLGA-nanoparticles (NPs), was compared with recently created nanoformulation based on polyvinylpyrrolidone (SL052-PVP-NPs) and standard liposomal SL052 preparation in terms of efficacy when used for PDT treatment of squamous cell carcinomas SCCVII growing subcutaneously in syngeneic mice. The therapeutic effect of PDT using these three different SL052 formulations was tested for both 1 and 4 h intervals between drug injection and tumor light exposure. The longer time interval produced higher tumor cure rates with all SL052 preparations. With both drug-light intervals, PDT based on SL052-PLGA-NPs produced superior therapeutic benefit compared with the other two SL052 formulations.
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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".