MétaCan
Menu
Back to cohort
Record W2965544134 · doi:10.1073/pnas.1903228116

High-speed AFM reveals subsecond dynamics of cardiac thin filaments upon Ca <sup>2+</sup> activation and heavy meromyosin binding

2019· article· en· W2965544134 on OpenAlexafffund
Oleg S. Matusovsky, Alf Månsson, Malin Persson, Yu‐Shu Cheng, Dilson E. Rassier

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationVetenskapsrådetGovernment of CanadaCancer Research Institute, Kanazawa UniversityLinnéuniversitetetKanazawa UniversityCancer Research Institute
KeywordsHeavy meromyosinTropomyosinMyosinAtomic force microscopyActinChemistryBiophysicsCardiac muscleElectron microscopeTroponin CTroponinNanotechnologyMaterials sciencePhysicsAnatomyBiochemistryOpticsBiology

Abstract

fetched live from OpenAlex

] and the presence of weakly or strongly bound myosin. The weakly and strongly bound myosin induce similar changes in the structure of cTFs as confirmed by the local dynamical displacement of individual tropomyosin strands in the center of a regulatory unit of cTF at the relaxed and activation conditions. The displacement of tropomyosin at the relaxed conditions had never been visualized directly and explains the ability of myosin binding to TF at the relaxed conditions. Based on the ratios of nonactivated and activated segments within cTFs, we proposed a mechanism of tropomyosin switching from different states that includes both weakly and strongly bound myosin.

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 score0.003
Threshold uncertainty score0.009

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)0.0030.000

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 head0.025
GPT teacher head0.284
Teacher spread0.259 · 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

Citations29
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicCardiomyopathy and Myosin StudiesFrench-language works237,207