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Record W1513704891 · doi:10.1196/annals.1420.010

<i>Sarcomere Mechanics in Uniform and Nonuniform Cardiac Muscle</i>

2008· article· en· W1513704891 on OpenAlexaff
Henk E.D.J. ter Keurs, Tsuyoshi Shinozaki, Ying Ming Zhang, Yuji Wakayama, Yoshinao Sugai, Yutaka Kagaya, Penelope A. Boyden, Bruno D. Stuyvers, Amir Landesberg

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2008
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversity of Calgary
FundersNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsSarcomereCardiac muscleChemistryMyocyteSigmaVentricleFrank–Starling law of the heartBiophysicsPhysicsAnatomyInternal medicineBiologyStroke volumeMedicine

Abstract

fetched live from OpenAlex

Starling's law and the end-systolic pressure-volume relationship (ESPVR) reflect the effect of sarcomere length (SL) on the development of stress (sigma) and shortening by myocytes in the uniform ventricle. We show here that tetanic contractions of rat cardiac trabeculae exhibit a sigma-SL relationship at saturating [Ca2+] that depends on sarcomere geometry in a manner similar to that of skeletal sarcomeres and the existence of opposing forces in cardiac muscle shortened below slack length. The sigma-SL -[Ca2+](free) relationships (sigma-SL-Ca relationships) at submaximal [Ca2+] in intact and skinned trabeculae were similar, although the sensitivity for Ca2+ of intact muscle was higher. We analyzed the mechanisms underlying the sigma-SL-Ca relationship by using a kinetic model assuming that the rates of Tn-C Ca2+ binding and/or cross-bridge (XB) cycling are determined by either the SL, [Ca2+], or sigma. We analyzed the correlation between the model results and steady-state sigma measurements at varied SL at [Ca2+] from skinned rat cardiac trabeculae to test the hypotheses that the dominant feedback mechanism is SL-, sigma-, or [Ca2+]-dependent, and that the feedback mechanism regulates Tn-C Ca2+ affinity, XB kinetics, or the unitary XB force. The analysis strongly suggests that the feedback of the number of strong XBs to cardiac Tn-C Ca2+ affinity is the dominant mechanism regulating XB recruitment. Using this concept in a model of twitch-sigma accurately reproduced the sigma-SL-Ca relationship and the time courses of twitch sigma and the intracellular [Ca2+]i. The foregoing concept has equally important repercussions for the nonuniformly contracting heart, in which arrhythmogenic Ca2+ waves arise from weakened areas in the cardiac muscle. These Ca2+ waves can reversibly be induced with nonuniform excitation-contraction coupling (ECC) by the cycle of stretch and release in the border zone between the damaged and intact regions. Stimulus trains induced propagating Ca2+ waves and reversibly induced arrhythmias. We hypothesize that rapid force loss by the sarcomeres in the border zone during relaxation causes Ca2+ release from Tn-C and initiates Ca2+ waves propagated by the sarcoplasmic reticulum (SR). Modeling of the response of the cardiac twitch to rapid force changes using the feedback concept uniquely predicts the occurrence of [Ca2+]i transients as a result of accelerated Ca2+ dissociation from Tn-C. These results are consistent with the hypothesis that a force feedback to Ca2+ binding by Tn-C is responsible for Starling's law and the ESPVR in the uniform myocardium and leads to a surge of Ca2+ released by the myofilaments during relaxation in the nonuniform myocardium, which initiates arrhythmogenic propagating Ca2+ release by the SR.

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)0.001
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
Metaresearch0.0000.001
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 head0.091
GPT teacher head0.320
Teacher spread0.229 · 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

Citations21
Published2008
Admission routes1
Has abstractyes

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