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Record W2056016810 · doi:10.13034/cysj-2014-006

Spider silk protein structure analysis by FTIR and STXM spectromicroscopy techniques

2014· article· en· W2056016810 on OpenAlexafffundvenue
J. Normandeau, Chris van Kessel, David N. Nicholson, B. Rahusaar Routledge, A. Fawcett, L. Lim-Cole, Charmaine Condy, Nicole J. Sylvain, Tracy L. Walker, Ferenc Borondics

Bibliographic record

VenueJournal of Student Science and Technology · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsCanadian Light Source (Canada)University of Toronto
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsSILKSpiderSpider silkChemistryFourier transform infrared spectroscopyInfrared spectroscopyPolymer chemistryMaterials scienceNuclear chemistryCrystallographyChemical engineeringBiologyOrganic chemistryEcologyComposite material

Abstract

fetched live from OpenAlex

Spider silk displays incredible strength and elas¬ticity for its size and weight.[1] These properties have sparked interest in determining the protein structures of the silk fibers allowing for the pro¬duction of synthetic silks.[2] This study compares the mid-infrared (Mid IR) spectra of silk from five different spider species to investigate the com-monalities between species and web type. The results demonstrate the Mid IR spectra from all types of spider silk to be similar, showing protein peaks in the Amide I and II regions. To study the environmental effects of the acid solution on the silk protein structure, two of the five species’ silk: Black & Yellow Orb Weaver (Argiope aurantia) and Black Widow (Latrodectus hesperus), were exposed to either rain water or 0.001 M sulphuric acid solution, similar to acid rain in pH. Spectra obtained at the Mid IR beamline and the data obtained from the X-ray Absorption Near Edge Spectroscopy (XANES) were compared for these samples to see the effect of the acid rain-like solu¬tion on the silk proteins. No conclusive evidence from the data is present to suggest that the acid rain solution had an effect on the protein structures of either type of spider silk. La soie d’araignée est à la fois robuste et flexible pour sa taille et son poids.[1] Ces propriétés ont piqué la curiosité de déterminer la structure des protéines des fibres de soie qui pourrait permettre éventuelle¬ment la production des soies synthétiques.[2] Cette étude compare les spectres mi- infrarouges (Mi IR) de soie de cinq espèces différentes d’araignée afin de trouver des similitudes entre les espèces et les genres de toiles. Les résultats démontrent que les spectres mi- infrarouges de tout type de soie d’araignée étudié sont similaires, présentant des apogées de protéines dans les régions de l’Amide I et II. Afin d’étudier les effets environnementaux d’une solution acide sur la structure de la proté¬ine de soie, la soie de deux des cinq espèces, le orbe tisserand noir et jaune (Argiope aurantia) et la veuve noire (Latrodectus Hesperus), ont été expo¬sé soit à la pluie naturelle soit à une solution d’acide sulfurique 0.001 M qui est proche au pH de la pluie acide. Les spectres obtenus à l’onde dirigée Mi IR et les données obtenues de l’absorption de la radi¬ographie près du seuil de la spectroscopie (ARSS) ont été comparés de ces échantillons afin de con¬stater l’effet de la solution d’acide sulfurique sur des protéines de soie. Il n’y avait aucune preuve probante des données suggérant que la solution d’acide sulfurique avait un effet sur la structure des protéines de soie des araignées étudié.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.279
Teacher spread0.274 · 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

Citations4
Published2014
Admission routes3
Has abstractyes

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Same venueJournal of Student Science and TechnologySame topicSilk-based biomaterials and applicationsFrench-language works237,207