Exploring the transformability of polymer-lipid hybrid nanoparticles and nanomaterial-biology interplay to facilitate tumor penetration, cellular uptake and intracellular targeting of anticancer drugs
Bibliographic record
Abstract
BACKGROUND: Successful delivery of anticancer drugs to intracellular targets requires different properties of the nanocarrier to overcome multiple transport barriers. However, few nanocarrier systems, to date, possess such properties, despite knowledge about the biological fate of inorganic and polymeric nanocarriers in relation to their fixed size, shape and surface properties. Herein, a polymer-lipid hybrid nanoparticle (PLN) system is described with size and shape transformability and its mechanisms of cellular uptake and intracellular trafficking are studied. METHODS: Pharmaceutical lipids were screened for use in transformable PLN. Mechanisms of cellular uptake and the role of fatty acid-binding proteins in intracellular trafficking of PLN were investigated in breast cancer cells. Intra-tumoral penetration and retention of doxorubicin (DOX) were evaluated by confocal microscopy. RESULTS: The lead PLNs showed time-dependent size reduction and shape change from spherical to spiky shape. This transformability of PLNs and lipid trafficking pathways facilitated intracellular transport of DOX-loaded PLN (DOX-PLN) into mitochondria and nuclei. DOX-PLN significantly increased DOX penetration and retention over free DOX or non-transformable liposomal DOX particles at 4 h post-intravenous administration. CONCLUSION: Transformability of PLN and lipid-biology interplay can be exploited to design new nanocarriers for effective drug delivery to tumor cells and intracellular targets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".