Collagen – a newly discovered major player in protein corona formation on nanoparticles
Bibliographic record
Abstract
Tracking protein corona (PC) formation on the surface of nanoparticles (NPs) is a prerequisite for successful design of next generation nanocarriers with predictable fate and behavior. However, PC formation has mostly been investigated for plasma proteins without considering potential competition with the extravascular proteins either when the NPs exit the blood circulation or when they are injected extravascularly. This study investigates the deposition of collagen, an extravascular protein that is the most abundant in the body, and albumin, the most abundant vascular protein, on the surface of gold (Au) NPs using UV-Vis and fluorescence spectroscopy with the support of mathematical modeling. Moreover, a novel spectroscopic approach to determining the protein-NP binding constants and surface occupancy is presented. We show that albumin and collagen have drastically different affinities for Au NPs. Our data demonstrates that the surface bound albumin can be exchanged with collagen confirming the dynamic nature of PC in the extravascular milieu. We propose that future PC investigations in the framework of drug delivery should rely on understanding of the NP transit in the body, and include competition experiments with relevant vascular and extravascular proteins. Furthermore, our results that reveal very strong binding of collagen to AuNPs may lay the foundation for designing long circulating collagen-coated NPs with minimal surface adsorption of plasma proteins and, thus, reduced immune recognition.
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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 | 0.000 |
| 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".