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Record W2272683596 · doi:10.1016/j.yjmcc.2016.02.003

Probing the mechanism of cardiovascular drugs using a covalent levosimendan analog

2016· article· en· W2272683596 on OpenAlexafffund
Sandra E. Pineda-Sanabria, Ian M. Robertson, Yin‐Biao Sun, Malcolm Irving, Brian D. Sykes

Bibliographic record

VenueJournal of Molecular and Cellular Cardiology · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversity of Alberta
FundersMedical Research CouncilCanadian Institutes of Health ResearchAlberta InnovatesBritish Heart Foundation
KeywordsLevosimendanCovalent bondTroponin CIn vivoBiophysicsChemistryMechanism (biology)Covalent bindingSensitizationCardiac muscleTroponin IPharmacologyInternal medicineMedicineHeart failure

Abstract

fetched live from OpenAlex

One approach to improve contraction in the failing heart is the administration of calcium (Ca(2+)) sensitizers. Although it is known that levosimendan and other sensitizers bind to troponin C (cTnC), their in vivo mechanism is not fully understood. Based on levosimendan, we designed a covalent Ca(2+) sensitizer (i9) that targets C84 of cTnC and exchanged this complex into cardiac muscle. The NMR structure of the covalent complex showed that i9 binds deep in the hydrophobic pocket of cTnC. Despite slightly reducing troponin I affinity, i9 enhanced the Ca(2+) sensitivity of cardiac muscle. We conclude that i9 enhances Ca(2+) sensitivity by stabilizing the open conformation of cTnC. These findings provide new insights into the in vivo mechanism of Ca(2+) sensitization and demonstrate that directly targeting cTnC has significant potential in cardiovascular therapy.

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 score0.145
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.017
GPT teacher head0.234
Teacher spread0.218 · 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

Citations18
Published2016
Admission routes2
Has abstractyes

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