Nontransformed and Cancer Cells Can Utilize Different Endocytic Pathways To Internalize Dendritic Nanoparticle Variants: Implications on Nanocarrier Design
Bibliographic record
Abstract
Three hyperbranched polyglycerol nanoparticle (HPG NP) variants were synthesized and fluorescently labeled for the study of their cellular interactions. The polymeric nanoparticle that contains a hydrophobic core and a hydrophilic HPG shell, HPG-C 10 -HPG, is taken up faster by HT-29 cancer cells than nontransformed cells, while similar uptake rates are observed with both cell types for the nanoparticle HPG-C 10 -PEG that contains a hydrophobic core and a polyethylene glycol shell. The nanoparticle HPG-104, containing neither the hydrophobic core nor the polyethylene glycol shell, is taken up faster by nontransformed cells than HT-29 cells. Importantly, cancer and normal cells can utilize different endocytic mechanisms for the internalization of these HPG NPs. Both HPG-C 10 -HPG and HPG-C 10 -PEG are taken up by HT-29 cells through clathrin-mediated endocytosis and macropinocytosis. Nontransformed cells, however, take up HPG-C 10 -HPG and HPG-104 through macropinocytosis, while these cells utilize both clathrin-mediated endocytosis and macropinocytosis to internalize HPG-C 10 -PEG.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".