In-vitro and in-vivo evaluation of pH-responsive polymeric micelles in a photodynamic cancer therapy model
Bibliographic record
Abstract
pH-sensitive polymeric micelles of randomly and terminally alkylated N-isopropylacrylamide copolymers were prepared and characterized. Aluminium chloride phthalocyanine (AlClPc), a second generation sensitizer for the photodynamic therapy of cancer, was incorporated in the micelles by dialysis. Their photodynamic activities were evaluated in-vitro against EMT-6 mouse mammary tumour cells and in-vivo against EMT-6 tumours implanted intradermally on each hind thigh of Balb/c mice. pH-sensitive polymeric micelles were found to exhibit greater cytotoxicity in-vitro than control Cremophor EL formulations. In the presence of chloroquine, a weak base that raises the internal pH of acidic organelles, in-vitro experiments demonstrated the importance of endosomalllysosomal acidity for the pH-sensitive polymeric micelles to be fully effective. Biodistribution was assessed by fluorescence of tissue extracts after intravenous injection of 2 micromol kg(-1) AlClPc. The results revealed accumulation of AlClPc polymeric micelles in the liver, spleen and lungs, with a lower tumour uptake than AlClPc Cremophor EL formulations. However, polymeric micelles exhibited similar activity in-vivo to the control Cremophor EL formulations, demonstrating the higher potency of AlClPc polymeric micelles when localized in tumour tissue. It was concluded that polymeric micelles represent a good alternative to Cremophor EL preparations for the vectorization of hydrophobic drugs.
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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) | 0.001 | 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) | 0.001 | 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".