Current update of a thermosensitive liposomes composed of DPPC and Brij78
Bibliographic record
Abstract
Thermosensitive liposomes (TSLs) have been a prominent area of study in the discipline of tumour-targeted chemotherapeutics. The representative product of TSLs is ThermoDox® (DPPC/lyso-PC/PEG-lipid), which has advanced to Phase III clinical trials. Various groups have sought to develop a new TSL to improve upon the LTSL (lyso-lipid temperature-sensitive liposomes) formulation that is used to prepare ThermoDOX®. This review focuses on the development and recent update of an innovative TSL formulation, HaT-liposomes composed of DPPC and Brij78. Various parameters of LTSL and HaT-liposomes are compared, including size, loading efficiency, transition temperature, temperature-dependent release kinetics, stability, pharmacokinetics, biodistribution and antitumour activity. Theranostic techniques involving HaT-liposomes are reported with regard to magnetic resonance imaging of drug delivery to tumours and identification of an early therapeutic biomarker in the treated tumour. The development of a further improved TSL formulation upon HaT-liposomes with improved stability and prolonged blood circulation is reported. Delivery of membrane impermeable drugs using HaT-liposomes is explored. Finally, the challenges and future perspectives of this technology are discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".