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Record W4413754680 · doi:10.1016/j.jacbts.2025.04.006

Novel Peptide Therapeutics Targeting the L-Type Calcium Channel Prevent Hypertrophic Cardiomyopathy by Decreasing Mitochondrial Energetics

2025· article· en· W4413754680 on OpenAlexaff
Teagan Er, Daniel C. Reinke, Alice J. Francis, Tanya Solomon, Helena M. Viola, Henrietta Cserné Szappanos, Caitlyn Richworth, Catherine Jenkins, Juan E. Camacho Londoño, Padmapriya Ponnuswamy, Ciaran McFarlane, Filip Van Petegem, Livia C. Hool

Bibliographic record

VenueJACC Basic to Translational Science · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversity of British Columbia
FundersNational Health and Medical Research CouncilWoodsideCSL Limited
KeywordsHypertrophic cardiomyopathyCardiomyopathyMedicineCalciumEnergeticsPeptideCalcium channelMitochondrionInternal medicineHeart failureCardiologyPharmacologyCell biologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Mitochondrial dysfunction is considered to drive the development of hypertrophic cardiomyopathy (HCM). In search of a preventative HCM therapy, we explored the efficacy of amino acid peptide variants that could alter the L-type Ca2+ channel’s regulation of mitochondrial energetics. We confirmed that 3 of the 4 variant peptides bound with high affinity to the beta subunit. In vivo treatment of cTnI-G203S and αMHC403/+ mice with the peptide variants prevented the development of HCM and improved contractile function. Here, we describe a novel therapy that uniquely targets the L-type Ca2+ channel to modify mitochondrial function and prevent HCM.

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 integrity0.0000.001
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 head0.026
GPT teacher head0.293
Teacher spread0.267 · 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
Published2025
Admission routes1
Has abstractyes

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