Internalization of benzylisoquinoline alkaloids by resting and activated bone marrow-derived mast cells utilizes energy-dependent mechanisms
Bibliographic record
Abstract
Abstract Berberine (BBR), a benzylisoquinoline alkaloid, binds to heparin and targets glycosaminoglycan-rich granules of myeloid-derived mast cells, but, the mechanism of berberine’s internalization is poorly understood. Our data showed that 84±3.3% of highly granulated bone marrow-derived mast cells (BMMC) internalized BBR (10 ug/mL) after 45 hr. Methanol fixation completely blocked this process, suggesting an energy-dependent active transport mechanism, and 3-mtheyladenine (600 uM) inhibited internalization by ~43%, indicating that lysosomal self-degradation via the autophagy pathway was involved. BBR incorporation into lipoplexes did not improve BBR internalization, but, rather decreased it by ~30% (1 ug/mL Lipo/BBR; n=3, p<0.05), suggesting that BBR internalization may utilize clathrin-dependent endosomal endocytosis. Interleukin-3 (IL-3)-mediated activation of BMMC augmented BBR internalization (~54% by 40 ng/mL IL-3) in a concentration-dependent manner, further suggesting that clathrin-mediated endocytosis as well as active cell division, have a profound role in BBR internalization. Altogether, our data suggest that internalization of BBR in resting and IL-3 activated BMMC, utilizes clathrin-dependent pathway. Our findings provide important new mechanistic insights into the internalization of benzylsoquinoline compounds by resting and activated mast cells and open new avenues for designing organelle-targeted nanotherapeutics.
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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".