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Record W4412795350 · doi:10.3791/68714

Optimizing and Evaluating Hand-drawing and Wet-spinning for Recombinant Spider Silk Fiber Production

2025· article· en· W4412795350 on OpenAlexaff
Anupama Ghimire, Hina Batool, Sara M. Evans, Donovan L. Rainey, A. Chen, Xiang‐Qin Liu, Jan K. Rainey

Bibliographic record

VenueJournal of Visualized Experiments · 2025
Typearticle
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSpinningSpider silkSILKRecombinant DNAFiberProduction (economics)SpiderBiologyComputer scienceMaterials scienceZoologyEconomicsComposite material

Abstract

fetched live from OpenAlex

Spider silks are renowned for their mechanical properties, with hallmark high strength, high extensibility, or a combination of these leading to high toughness. A typical female orb-weaving spider produces seven different types of silk, each typically spun from type-specific protein(s) and mechanically tailored for a distinct survival function. Recombinant spider silk production provides a promising route to obtain these materials, circumventing challenges in obtaining large quantities of natural silks and providing advantages in allowing for protein customization, for example, through site-directed mutagenesis or fusion protein construction. In the presented protocol, we outline a methodology for evaluating protein suitability for spinning through both hand-drawing and wet-spinning approaches. Starting with a suitably purified lyophilized protein powder, methods for optimizing the initial solubilized protein state to provide a high-concentration "spinning dope" state are detailed. Next, hand-drawing and wet-spinning approaches are compared, including a discussion on methods to modulate fiber behavior using a post-spin draw as part of the spinning process. A typical workflow to characterize the resulting silk fibers and make a decision on which spinning conditions are most likely to be fruitful is then detailed, including optical microscopy to evaluate fiber diameter and its uniformity; polarized light microscopy to estimate the degree of (supra)molecular alignment being achieved within the fiber; tensile testing to evaluate strength, extensibility, Young's modulus, and toughness; and Fourier transform infrared (FTIR) spectromicroscopy to evaluate protein secondary structuring within the fiber. This protocol has proven suitable for several different recombinant spider silk proteins based on repetitive and non-repetitive domains of aciniform (wrapping) silk; pyriform silk; and fusion proteins comprising aciniform, pyriform, and/or major ampullate (dragline) silk. Broader applicability is provided through several highlighted steps at which conditions and parameters may be varied to suit the behavior of an individual protein and to achieve differences in functional outcome.

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)0.001
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 score0.067
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.058
GPT teacher head0.448
Teacher spread0.389 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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