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Recombinant Pyriform Silk Fiber Mechanics Are Modulated by Wet-Spinning Conditions

2019· article· en· W2972533521 on OpenAlexafffund
Jeffrey R. Simmons, Lingling Xu, Jan K. Rainey

Bibliographic record

VenueACS Biomaterials Science & Engineering · 2019
Typearticle
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsSILKSpider silkSpinningSpiderMaterials sciencePolymer scienceFiberHelicitySynthetic fiberComposite materialBiologyEcologyPhysics

Abstract

fetched live from OpenAlex

Pyriform silk is a critically important fiber in spider web construction. It functions in a glue-coated attachment disc to form junctions in spider webs, connecting the web to disparate materials. Despite the biological importance of this silk, both natural and recombinant pyriform silk have yet to be structurally or mechanically characterized. In this study, we demonstrate recombinant production of a 477 amino acid protein based on Argiope argentata pyriform silk. This pyriform silk protein shows α-helicity in both an aqueous buffer and in a fluorinated acid- and alcohol-based spinning dope. Wet-spinning produced fibers having no visible defects in surface or cross-sectional analysis, with mechanical behavior varying as a function of postspin stretching conditions and correlating to loss of α-helicity in the fibrous state. Multiple conditions gave rise to fibers that are both strong and extensible, contrasting with some other silks that are biased toward being strong or extensible. This behavior is strikingly similar to recombinant aciniform silk, despite distinct primary structuring and composition.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2019
Admission routes2
Has abstractyes

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