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Record W2741064680 · doi:10.1101/171447

Single-molecule assay for proteolytic susceptibility using centrifuge force microscopy:force-induced destabilization of collagen‘s triple helix

2017· preprint· en· W2741064680 on OpenAlexafffund
Michael W.H. Kirkness, Nancy R. Forde

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCentrifugeTriple helixProteolysisMicroscopyChemistryBiophysicsMoleculeCleavage (geology)MicroscopeThroughputAtomic force microscopyNanotechnologyMaterials scienceBiological systemWirelessComputer sciencePhysicsBiochemistryEnzymeStereochemistryBiologyOpticsComposite materialOrganic chemistryTelecommunications

Abstract

fetched live from OpenAlex

Force plays a key role in regulating dynamics of biomolecular structure and interactions, yet techniques are lacking to manipulate and continuously read out this response with high throughput. We present an enzymatic assay for force-dependent accessibility of structure that makes use of a wireless mini-radio centrifuge force microscope (MR.CFM) to provide a real-time readout of kinetics. The microscope is designed for ease of use, fits in a standard centrifuge bucket, and offers high-throughput, video-rate readout of individual proteolytic cleavage events. Proteolysis measurements on thousands of tethered collagen molecules show a load-enhanced trypsin sensitivity, indicating destabilization of the triple helix.

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 score0.003

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 integrity0.0010.000
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 head0.035
GPT teacher head0.277
Teacher spread0.241 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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