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Record W2978966259 · doi:10.1038/s42003-019-0595-z

SR9009 administered for one day after myocardial ischemia-reperfusion prevents heart failure in mice by targeting the cardiac inflammasome

2019· article· en· W2978966259 on OpenAlexafffund
Cristine J. Reitz, Faisal J. Alibhai, Tarak Nath Khatua, Mina Rasouli, Byram W. Bridle, Thomas P. Burris, Tami A. Martino

Bibliographic record

VenueCommunications Biology · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsUniversity of Guelph
FundersCIHR Skin Research Training CentreCanadian Institutes of Health ResearchGovernment of CanadaHeart and Stroke Foundation of Canada
KeywordsInflammasomeMedicineMyocardial infarctionCardiac function curveReperfusion injuryHeart failureCircadian rhythmInflammationIschemiaDownregulation and upregulationRegulatorCardiologyIn vivoPharmacologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Reperfusion of patients after myocardial infarction (heart attack) triggers cardiac inflammation that leads to infarct expansion and heart failure (HF). We previously showed that the circadian mechanism is a critical regulator of reperfusion injury. However, whether pharmacological targeting using circadian medicine limits reperfusion injury and protects against HF is unknown. Here, we show that short-term targeting of the circadian driver REV-ERB with SR9009 benefits long-term cardiac repair post-myocardial ischemia reperfusion in mice. Gain and loss of function studies demonstrate specificity of targeting REV-ERB in mice. Treatment for just one day abates the cardiac NLRP3 inflammasome, decreasing immunocyte recruitment, and thereby allowing the vulnerable infarct to heal. Therapy is given in vivo, after reperfusion, and promotes efficient repair. This study presents downregulation of the cardiac inflammasome in fibroblasts as a cellular target of SR9009, inviting more targeted therapeutic investigations in the future.

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 score0.008

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 integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.282
Teacher spread0.269 · 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

Citations118
Published2019
Admission routes2
Has abstractyes

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