Hydrodynamical properties of recombinant spider silk proteins: Effects of pH, salts and shear, and implications for the spinning process
Bibliographic record
Abstract
We have investigated the effect of pH, salts and shear on the hydrodynamical diameter of recombinant major ampullate (MA) rMaSpI silk proteins in solution as a function of time using (1) H solution NMR spectroscopy. The results indicate that the silk proteins in solution are composed of two diffusing populations, a high proportion of "native" solubilized proteins and a small amount of high molecular weight oligomers. Similar results are observed with the MA gland content. Salts help maintaining the proteins in a compact form in solution over time and inhibit aggregation, the absence of salts triggering protein assembly leading to a gel state. Moreover, the aggregation kinetics of rMaSpI at low salt concentration accelerates as the pH is close to the isoelectric point of the proteins, suggesting that the pH decrease tends to slow down aggregation. The data also support the strong impact of shear on the spinning process and suggest that the assembly is driven by a nucleation conformational conversion mechanism. Thus, the adjustment of the physicochemical conditions in the ampulla seems to promote a stable, long term storage. In addition, the optimization of protein conformation as well as their unfolding and aggregation propensity in the duct leads to a specifically organized structure.
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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 | 0.001 |
| 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".