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Record W1896581320 · doi:10.1002/bip.22218

Hydrodynamical properties of recombinant spider silk proteins: Effects of pH, salts and shear, and implications for the spinning process

2013· article· en· W1896581320 on OpenAlexaff
Jérémie Leclerc, Thierry Lefèvre, Martin Gauthier, Stéphane M. Gagné, Michéle Auger

Bibliographic record

VenueBiopolymers · 2013
Typearticle
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsUniversité LavalPROTEO
Fundersnot available
KeywordsSpider silkChemistrySpinningSILKPolymer scienceShear (geology)Chemical engineeringRecombinant DNASpiderPolymer chemistryBiophysicsBiochemistryComposite materialEcologyMaterials science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.252
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2013
Admission routes1
Has abstractyes

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