In Operando Imaging Electrostatic-Driven Disassembly and Reassembly of Collagen Nanostructures
Bibliographic record
Abstract
Collagen is the most abundant protein in tissue scaffolds in live organisms. Collagen can self-assemble in vitro, which has led to a number of biotechnological and biomedical applications. To understand the dominant factors that participate in the formation of collagen nanostructures, here we study in real time and with nanoscale resolution the disassembly and reassembly of collagens. We implement a high-speed force microscope, which provides in situ high spatiotemporal resolution images of collagen nanostructures under changing pH conditions. The disassembly and reassembly are dominated by the electrostatic interactions among amino-acid residues of different molecules. Acidic conditions favor disassembly by neutralizing negatively charged residues. The process sets a net repulsive force between collagen molecules. A neutral pH favors the presence of negative and positively charged residues along the collagen molecules, which promotes their electrostatic attraction. Molecular dynamics simulations reproduce the experimental behavior and validate the electrostatic-based model of the disassembly and reassembly processes.
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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".