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Improving survival with cytoprotective therapeutics administered after a myocardial infarction in the absence of reperfusion (1080.9)

2014· article· en· W1775970800 on OpenAlexaffabout
Mathew J. Platt, Scott E. Henry, Jason S. Huber, Sohrab Lutchmedial, Kieth Brunt, Jeremy A. Simpson

Bibliographic record

VenueThe FASEB Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsDalhousie UniversitySaint John Regional HospitalUniversity of Guelph
Fundersnot available
KeywordsMedicineMyocardial infarctionHeminInternal medicineCardiologyPopulationOcclusionCoronary occlusionInfarctionSurgery

Abstract

fetched live from OpenAlex

A strong negative correlation between the size of a myocardial infarction (MI) and the long‐term survival of the patient exists in the clinical population. The current gold standard treatment for reducing infarct size in MI patients is acute reperfusion therapy (ART). Due to various contraindications, up to 30 percent of eligible patients do not receive ART. Thus, there is an urgent need for pharmacological alternatives in this substantive population. As patients experiencing a MI can only be treated after the event precipitates symptoms, the purpose of this study was to establish if a cytoprotective agent, hemin, can reduce infarct size and subsequent mortality when administered after a permanent coronary occlusion without reperfusion. Methods. Mice were treated with either hemin or vehicle 30 minutes following the induction of a MI. Results. Four weeks post MI, infarct size was significantly reduced in hemin treated (HT) mice compared to vehicle controls (VC) indicating preserved myocardial tissue (44.0±4.2% and 60.2±0.8% respectively; p<0.05). Kaplan‐Meier curves demonstrate HT mice had significantly higher 4‐week survival rates than VC (78% and 56% respectively; p<0.05). Conclusions. This data demonstrates the potential of a cytoprotective therapeutic to reduced infarct size and improve survival when administered after a permanent occlusion in the absence of reperfusion. Grant Funding Source : Canadian Institute of Health and Research

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 score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.023
GPT teacher head0.278
Teacher spread0.255 · 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 routes2
Has abstractyes

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