Targeting B16 tumors<i>in vivo</i>with peptide-conjugated gold nanoparticles
Bibliographic record
Abstract
This study examines the effects of polyethylene glycol (PEG) and peptide conjugation on the biodistribution of ultrasmall (2.7 nm) gold nanoparticles in mice bearing B16 melanoma allografts. Nanoparticles were delivered intravenously, and biodistribution was measured at specific timepoints by organ digestion and inductively coupled plasma mass spectrometry. All major organs were examined. Two peptides were tested: the cyclic RGD peptide (cRGD, which targets integrins); and a recently described peptide derived from the myxoma virus. We found the greatest specific tumor delivery using the myxoma peptide, with or without PEGylation. Un-PEGylated cRGD performed poorly, but PEGylated RGD showed a significant transient collection in the tumor. Liver and kidney were the primary targets of all constructs. None of the particles were able to cross the blood-brain barrier. Although it was able to deliver Au to B16 cells, the myxoma peptide did not show any cytotoxic activity against these cells, in contrast to previous reports. These results indicate that the effect of passive targeting by PEGylation and active targeting by peptides can be independent or combined, and that they should be evaluated on a case-by-case basis when designing new nanosystems for targeted therapies. Both myxoma peptide and cRGD should be considered for specific targeting to melanoma, but a thorough investigation of the cytotoxicity of the myxoma peptide to different cell lines remains to be performed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".