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Cardiac‐derived Erythropoietin: A Novel Therapeutic Strategy to Treat Myocardial Infarction?

2020· article· en· W3016605652 on OpenAlexaffabout
Jade P. Marrow, Melissa A. Allwood, Mathew J. Platt, Brittany A. Edgett, Nadya Romanova, Razan Alshamali, Keith R. Brunt, Jeremy A. Simpson

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicErythropoietin and Anemia Treatment
Canadian institutionsDalhousie UniversityUniversity of Guelph
Fundersnot available
KeywordsErythropoietinMedicineMyocardial infarctionParacrine signallingInfarctionInternal medicineCardioprotectionCardiologyCardiac function curveInotropeHypoxia (environmental)EndocrinologyHeart failureReceptor

Abstract

fetched live from OpenAlex

Background In response to hypoxia, the kidney is considered the major source for erythropoietin (EPO) – a protein responsible for stimulating hematopoiesis. Interestingly, recombinant human EPO (rhEPO) also has known anti‐apoptotic, cardioprotective, and inotropic effects. Preclinically, supraphysiological concentrations of rhEPO, given at the time of permanent coronary artery occlusion, is effective at reducing apoptosis in the area‐at‐risk, infarct size, and left ventricular remodeling and functional deficits. Clinically, researchers have encountered significant translational difficulties using EPO post‐myocardial infarction, as the hematopoietic effect of chronic rhEPO dosing limits its therapeutic use in patients. Emerging findings demonstrate that EPO mRNA expression occurs in non‐renal tissues, including the liver, bone, and reproductive organs, yet the evidence is divided with regards to the heart. Our preliminary data shows that cardiac EPO expression is upregulated during embryonic development, suggesting it has a paracrine role in cardiac development. Therefore, whether the adult heart produces EPO under a stress (e.g., myocardial infarction) and has physiological relevance remains unknown. Notably, in humans, serum EPO levels are elevated at 3 days post‐myocardial infarction, which indicates that the injured/hypoxic heart may produce EPO in vivo . Accordingly, our objective was to improve our understanding of the regulation and physiological significance of cardiac‐derived EPO using a murine model of myocardial infarction. It was hypothesized that a myocardial infarction would increase cardiac EPO mRNA expression, which may serve as a paracrine factor to preserve cardiac structure and function following an ischemic injury. Methods and Results Male CD1 mice were subjected to permanent ligation of the left anterior descending coronary artery to induce a myocardial infarction. At 12 h post‐surgery, hearts were harvested for qPCR analyses, which showed a significant upregulation in EPO mRNA expression. At 2, 4, and 9 weeks post‐myocardial infarction (when hearts were anoxic), hematocrit was significantly elevated, compared to age‐matched shams, indicating that serum EPO levels were still increased at these timepoints. To investigate whether cardiac EPO is driven solely by hypoxia, we subjected mice to severe hypoxia (9% O 2 ) for 24 h and evaluated EPO mRNA expression in the heart and kidney. Indeed, EPO expression was significantly increased in the kidney, while we observed a very modest increase in the heart. Conclusions Here we show that the heart is a significant non‐renal source of EPO post‐myocardial infarction. Further, profound hypoxia does not significantly drive cardiac‐derived EPO expression, suggesting it is regulated by a hypoxia‐independent mechanism post‐injury. Taken together, endogenous cardiac EPO production may be elevated to provide paracrine cardioprotective support following a myocardial infarction. Support or Funding Information Canadian Institutes of Health Research. Natural Sciences and Engineering Research Council of Canada.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 head0.039
GPT teacher head0.283
Teacher spread0.244 · 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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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