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Record W1511744475

Abstract 13353: Methylglyoxal Induces Stem Cell Dysfunction Through Impaired Matrix Interactions After Myocardial Infarction

2014· article· en· W1511744475 on OpenAlexaff
Nick J. R. Blackburn, Branka Vulesevic, Brian McNeill, Aleksandra Ostojic, Ross W. Milne, Erik J. Suuronen

Bibliographic record

VenueCirculation · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Glycation End Products research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMethylglyoxalMedicineMyocardial infarctionGlycationEjection fractionInternal medicineHeart failureCardiologyApoptosisEndocrinologyArterioleDiabetes mellitusEnzymeCirculatory systemBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Background: Advanced glycation end-products (AGEs) have been associated with poorer outcomes in heart failure (HF) after myocardial infarction (MI). The contribution of AGEs to post-MI injury has yet to be shown. Methylglyoxal (MG) is considered the most important AGE precursor. To elucidate the role of MG in post-MI repair, this study used a mouse model that over-expresses the MG-metabolizing enzyme glyoxalase-1 (GLO1). Methods/Results: MI was induced in GLO1 over-expressing mice and their wild-type (WT) littermates. MI resulted in increased MG levels in hearts of both mouse groups. Left ventricular ejection fraction was superior in GLO1 mice (46.0±3.3%) compared to WT (33.9±1.8%, p=0.008) at 4 weeks post-MI. GLO1 mice also had smaller infarcts (41.5±2.2% vs. 57.3±7.1%, p=0.05) and improved chamber volumes. Immunohistochemistry at 4 weeks post-MI revealed greater arteriole (p=0.006) and capillary (p=0.03) density in GLO1 vs. WT mice, and an overall reduction in cardiomyocyte death through apoptosis (p=0....

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0040.001

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 head0.020
GPT teacher head0.304
Teacher spread0.284 · 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
Published2014
Admission routes1
Has abstractyes

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