Design and Function of Engineered Protein Nanocages as a Drug Delivery System for Targeting Pancreatic Cancer Cells via Neuropilin-1
Bibliographic record
Abstract
We describe the development of neuropilin 1-binding peptide (iRGD)-nanocages that specifically target human pancreatic cancer cells in which an iRGD is joined to the surface of naturally occurring heat shock protein (HSP) cages. Using a genetic engineering approach, the iRGD domain was joined to the C-terminal region of the HSP cage using flexible linker moieties. The characteristics of the interdomain linkages between the nanocage and the iRGD domain play an important role in the specificity and affinity of the iRGD-nanocages for their target cells. An engineered L30-iRGD-nanocage with 30 amino acid linkers, (GGS)10, showed greater binding affinity for pancreatic cancer cells relative to that of other linkers. Furthermore, a moderately hydrophobic anticancer drug, OSU03012, was successfully incorporated into the L30-iRGD-nanocage by heating the mixture. The OSU03012-loaded L30-iRGD-nanocage induced cell death of pancreatic cancer cells by activating the caspase cascade more effectively than the same concentrations of free OSU03012. The iRGD-nanocages show great potential as a novel nanocarrier for pancreatic cancer-targeted drug delivery.
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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) | 0.000 | 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".