Effects of Liposomal Phospholipids and Lipid Transport-Related Protein on the Intracellular Fate of Encapsulated Doxorubicin
Bibliographic record
Abstract
We have previously reported the intracellular trafficking mechanism of liposomal phospholipids. In the present study, we investigated the effects of liposomal phospholipids on the intracellular trafficking of doxorubicin (DXR). In DXR-encapsulated liposomes, polyethylene glycol (PEG)-modified phospholipids have been widely used as one of the liposomal lipids. First, we investigated the intracellular trafficking mechanism of 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) and (1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy-PEG2000] (PEG2000-DSPE), and demonstrated that the intracellular trafficking pathways of phospholipids changed by PEG modification. Then, we evaluated the effects of liposomal DXR on the intracellular trafficking of liposomal phospholipids. Under the phosphatidylinositol transfer protein (PITP)-suppressing condition by siRNA treatment, the intracellular amounts of DSPC derived from DXR-encapsulated liposomes were larger than that from nonencapsulated liposomes. Moreover, following the effects of liposomal phospholipids on the intracellular amounts of DXR, the intracellular amounts of DXR were increased under the PITP-suppressing condition in DXR-encapsulated liposomes. We showed that intracellular DXR was associated with the complex of PITP and DSPC, and the extracellular efflux of DXR was enhanced by complex formation with PITP and DSPC.
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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) | 0.001 | 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".