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Record W2742722735 · doi:10.1038/cr.2017.87

Cardiotrophin 1 stimulates beneficial myogenic and vascular remodeling of the heart

2017· article· en· W2742722735 on OpenAlexafffund
Mohammad Abdul‐Ghani, Colin Suen, Baohua Jiang, Yupu Deng, Jonathan J. Weldrick, Charis Putinski, Steve Brunette, Tom T. Lee, Peter Flynn, Frans H. H. Leenen, Patrick G. Burgon, Duncan J. Stewart, Lynn A. Megeney

Bibliographic record

VenueCell Research · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsCarleton UniversityOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMuscle hypertrophyHeart failureBiologyInternal medicineVascularityStimulationCardiologyEndocrinologyMedicinePathology

Abstract

fetched live from OpenAlex

The post-natal heart adapts to stress and overload through hypertrophic growth, a process that may be pathologic or beneficial (physiologic hypertrophy). Physiologic hypertrophy improves cardiac performance in both healthy and diseased individuals, yet the mechanisms that propagate this favorable adaptation remain poorly defined. We identify the cytokine cardiotrophin 1 (CT1) as a factor capable of recapitulating the key features of physiologic growth of the heart including transient and reversible hypertrophy of the myocardium, and stimulation of cardiomyocyte-derived angiogenic signals leading to increased vascularity. The capacity of CT1 to induce physiologic hypertrophy originates from a CK2-mediated restraining of caspase activation, preventing the transition to unrestrained pathologic growth. Exogenous CT1 protein delivery attenuated pathology and restored contractile function in a severe model of right heart failure, suggesting a novel treatment option for this intractable cardiac disease.

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 score0.005

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 head0.078
GPT teacher head0.372
Teacher spread0.294 · 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

Citations45
Published2017
Admission routes2
Has abstractyes

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