Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: In photodynamic therapy (PDT), photosensitizers are activated by light of a specific wavelength and produce cytotoxic molecules to damage diseased tissues. Most photosensitizers are hydrophobic and easily aggregate in aqueous solution. To maintain their photodynamic activity and to enhance delivery efficiency of photosensitizers, various pharmaceutical carriers and delivery systems have been investigated for photosensitizers. This review will focus on liposomal nanostructures for the delivery of photosensitizing agents. METHODS: The published literature of liposomal structures, formulations, and pharmaceutical applications for photosensitizer delivery was reviewed with the main focus on articles published between 2004 and 2011 after the two excellent reviews by Derycke et al., Adv Drug Deliv Rev 2004:56(1); 17-30 and Chen et al., Expert Opin Drug Deliv 2005:2(3);477-487. Many articles dating back to 1970s were also covered for the purpose of obtaining information about historoical development of liposomal formulations for photosensitizer delivery. The systematic search was performed using several electronic databases, including Pubmed and Medline with the key search terms including PDT, photosensitizer, liposome, nanoparticle, formulation, biodistribution, etc. RESULTS: This review focuses on liposomal nanostructures with an in depth discussion on the liposomal structure, size-related effect on blood circulation and composition of phospholipids. Different active targeting strategies will also be reviewed which serve to improve specific targeting of photosensitizers to diseased tissue. To further enhance the selective release and accumulation of photosensitizers at the targeted tissue, triggered release methods have been developed. Many other liposomal structure-based nanoparticles have been developed for improved delivery efficiency for topical and systemic administration of pharmaceutics. Finally, a new class of phototransducing liposomes called "porphysomes" will also be introduced, which achieves intrinsic multifunctionality together with structure simplicity. CONCLUSION: Liposomes have been proved to be efficient and safe organic carriers for photosensitizers. Multifunctional liposomal formulations, such as porphysome, are further explored for clinic theranostic applications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".