Drug Targeting Strategies Based on Charge Dependent Uptake of Nanoparticles into Cancer Cells
Bibliographic record
Abstract
The aim of this review was to describe the preferred charged nano-particles (CNPs) for targeted delivery in tumor cells. Zeta Potential (ZP), which represents the surface charge of NPs was highlighted in cell entrance and interactions. In this regard, various types of endocytosis pathways which are involved in NPs' uptake were first introduced. Then, significance of positively charged NPs (PCNPs) in proton sponge effect corresponding to lysosomal escape was discussed. Cells prefer to endocyte the NPs with positive charge in passive targeting and gene delivery, while in active targeting; the charge of receptors' ligand binding site determines the NPs cellular uptake. Moreover, pH-sensitive NPs represent charge reversible behavior depending on pH changes which leads to longer blood circulation residence and higher uptake at acidic microenvironment of the cancer media. Role of the CNPs in overcoming multidrug resistance (MDR) and bypassing p-glycoprotein was further investigated.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".