Influence of polymer size, liposomal composition, surface charge, and temperature on the permeability of pH-sensitive liposomes containing lipid-anchored poly(2-ethylacrylic acid)
Bibliographic record
Abstract
BACKGROUND: Liposomes containing pH-sensitive polymers are promising candidates for the treatment of tumors and localized infection. This study aimed to identify parameters influencing the extent of contents release from poly(ethylacrylic acid) (PEAA) vesicles, focusing on the effects of polymer size, lipid composition, vesicle surface charge, and temperature. METHODS: Anchored lipid pH-sensitive PEAA was synthesized using PEAA with a molecular weight of 8.4 kDa. PEAA vesicles were prepared by insertion of the lipid-anchored PEAA into preformed large unilamellar vesicles. The preformed liposomes were manipulated by varying the phosphocholine and cholesterol content, and by adding negative or positive charges to the liposomes. A calcein release assay was used to evaluate the effects of polymer size, liposome composition, surface charge, and temperature on liposomal permeability. RESULTS: The release efficiency of the calcein-entrapped vesicles was found to be dependent on the PEAA polymer size. PEAA vesicles containing a phosphatidylcholine to cholesterol ratio of 60:40 (mol/mol) released more than 80% of their calcein content when the molecular weight of PEAA was larger than 8.4 kDa. Therefore, the same-sized polymer of 8.4 kDa was used for the rest of study. The calcein release potential was found to decrease as the percentage of cholesterol increased and with an increase in the phosphocholine acyl chain length (DMPC DPPC DSPC). Negatively charged and neutral vesicles released similar amounts of calcein, whereas positively charged liposomes released a significant amount of their contents. pH-sensitive release was dependent on temperature. Dramatic content release was observed at higher temperatures. CONCLUSION: The observed synergistic effect of pH and temperature on release of the contents of PEAA vesicles suggests that this pH-sensitive liposome might be a good candidate for intracellular drug delivery in the treatment of tumors or localized infection.
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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 | 0.001 |
| 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) | 0.001 | 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".