Interaction of Liposomal Formulations of Meta‐tetra(hydroxyphenyl)chlorin (Temoporfin) with Serum Proteins: Protein Binding and Liposome Destruction
Bibliographic record
Abstract
mTHPC is a non polar photosensitizer used in photodynamic therapy. To improve its solubility and pharmacokinetic properties, liposomes were proposed as drug carriers. Binding of liposomal mTHPC to serum proteins and stability of drug carriers in serum are of major importance for PDT efficacy; however, neither was reported before. We studied drug binding to human serum proteins using size-exclusion chromatography. Liposomes destruction in human serum was measured by nanoparticle tracking analysis (NTA). Inclusion of mTHPC into conventional (Foslip(®)) and PEGylated (Fospeg(®)) liposomes does not affect equilibrium serum protein binding compared with solvent-based mTHPC. At short incubation times the redistribution of mTHPC from Foslip(®) and Fospeg(®) proceeds by both drug release and liposomes destruction. At longer incubation times, the drug redistributes only by release. The release of mTHPC from PEGylated vesicles is delayed compared with conventional liposomes, alongside with greatly decreased liposomes destruction. Thus, for long-circulation times the pharmacokinetic behavior of Fospeg(®) could be influenced by a combination of protein- and liposome-bound drug. The study highlights the modes of interaction of photosensitizer-loaded nanovesicles in serum to predict optimal drug delivery and behavior in vivo in preclinical models, as well as the novel application of NTA to assess the destruction of liposomes.
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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".