Assembly of collagen fibril meshes using gold nanoparticles functionalized with tris(hydroxymethyl)phosphine‐alanine as multivalent cross‐linking agents
Bibliographic record
Abstract
We report on the use of tris(hydroxymethyl)phosphine-alanine (THPAL) functionalized gold nanoparticles as a multivalent cross-linking agent to assemble collagen fibrils into a mesh-like structure. Atomic force microscopy (AFM) was used for characterization of the structure after adsorption onto an atomically flat mica substrate, revealing a mesh-like construct in which the collagen fibrils and the gold nanoparticles interact to form interconnected nodes measuring from 100 to 500 nm. As expected, the density of the collagen mesh can be increased with a higher initial concentration of gold nanoparticles. The maximum thickness of the meshes (∼ 20 nm) obtained through cross-sectional height measurements confirms that the adsorbed structure consists of a single layer of collagen fibrils/gold nanoparticles assembled in two-dimensions. We propose that the capability of gold nanoparticles functionalized with the THPAL to bind to several collagen fibrils combined with the large persistence length of the fibrils, which was reported to be in the hundreds of nanometer range, are determinant factors for the preferential 2D growth of the mesh in solution.
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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".