Kupffer cells do not play a role in governing the efficacy of liposomal mitoxantrone used to treat a tumor model designed to assess drug delivery to liver.
Bibliographic record
Abstract
A tumor model designed to assess liposome-mediated drug delivery to liver has been used in an attempt to better understand the mechanism of activity of liposomal mitoxantrone, a liposomal anticancer drug formulation that appears to be uniquely effective in treating this tumor model. Reductions in liposomal mitoxantrone accumulation in the liver were achieved either by use of poly(ethylene)glycol (PEG)-modified lipids or by methods designed to deplete liver phagocytes, a method referred to as hepatic mononuclear phagocytic system (MPS) blockade. A 2-fold reduction in mitoxantrone delivery to the liver was obtained using a mitoxantrone formulation with PEG-modified lipids, and a 3-fold reduction was obtained when liposomal mitoxantrone was given to animals pretreated to induce hepatic MPS blockade. Results demonstrate that the liposomal mitoxantrone formulation prepared with PEG-modified lipids was significantly less active than the formulations that did not contain PEG lipids, with median survival times of 17 days and 100% 60-day survival, respectively. In contrast, hepatic MPS blockade had no effect on the therapeutic activity of 1,2-dimyristoyl phosphatidylcholine/cholesterol (DMPC/Chol) mitoxantrone (100% 60-day survival). These data suggest that the hepatic MPS does not play a role in mediating the therapeutic activity of DMPC/Chol mitoxantrone in the treatment of liver localized disease. Results with formulations prepared with a PEG-stabilized surface, however, suggest that nonspecific methods to decrease liposome cell interactions inhibit the therapeutic activity of DMPC/Chol mitoxantrone.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".