Optimizing pH-responsive Polymeric Micelles for Drug Delivery in a Cancer Photodynamic Therapy Model
Bibliographic record
Abstract
Different pH-sensitive, randomly- and terminally-alkylated N-isopropylacrylamide (NIPAM) copolymers were synthesized and used to prepare pH-responsive polymeric micelles (PM). These copolymers were modified from previously-studied copolymers by incorporating an additional hydrophilic monomer, N-vinyl-2-pyrrolidone (VP) to decrease uptake by the mononuclear phagocyte system (MPS) and improve localization in tumors. VP lowered the phase transition pH of the copolymers but did not affect the onset of micellization. The in vitro cytotoxicity of the copolymers was evaluated on EMT-6 mouse mammary tumor cells in comparison to Cremophor EL (CRM). The anticancer photosensitizer aluminum chloride phthalocyanine (AlClPc) was loaded into the PM with a standard dialysis procedure. Biodistribution and in vivo photodynamic activity were then evaluated in Balb/c mice bearing intradermal EMT-6 tumors. All NIPAM copolymers demonstrated substantially lower cell cytotoxicity than the control surfactant CRM. In vivo, similar AlClPc tumor uptake was observed for the PM and CRM formulations. However, the PM appeared to exhibit greater activity in vivo than CRM formulation at an AlClPc subtherapeutic dose. Therefore, NIPAM-based copolymers containing VP units represent promising alternatives for the formulation of poorly water-soluble phthalocyanines.
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 | 0.000 |
| 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".