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Roles of nitric oxide, superoxide, and peroxynitrite in myocardial ischemia-reperfusion injury and ischemic preconditioning

2001· book-chapter· en· W91961007 on OpenAlexaff
Péter Ferdinándy, Richard Schulz

Bibliographic record

VenueBirkhäuser Basel eBooks · 2001
Typebook-chapter
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineIschemiaCardiologyNitric oxideMyocardial infarctionInternal medicinePeroxynitriteReperfusion injuryDyslipidemiaDiseaseSuperoxide

Abstract

fetched live from OpenAlex

Ischemic heart disease, a major cause of mortality in industrialized countries, is characterized by insufficient blood supply to certain regions of the myocardium which leads to tissue necrosis (infarction). It develops secondary to a variety of disorders such as hypertension, atherosclerosis, dyslipidemia, and diabetes. The treatment of this condition has entered a new era in which mortality can be approximately halved by procedures which allow for the rapid restoration of blood flow (reperfusion), to the ischemie zone of the myocardium. Reperfusion, however, may lead to further complications such as diminished cardiac contractile function (stunning) and arrhythmias. Therefore, development of cardioprotective agents to improve myocardial function, decrease the incidence of arrhythmias, lessen necrotic tissue mass, and delay the onset of necrosis as a result of ischemia-reperfusion is of great clinical importance. The heart was also found to have an inherent ability to adapt to ischemie stress called ischemie preconditioning (PC) [1]. It is a well described adaptive response in which brief exposure of the heart to brief episode(s) of ischemia (PC ischemia) markedly enhances its ability to withstand a subsequent ischemie injury (test ischemia) (see for review see [2]).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.156
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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 teacher head, not a consensus.

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

Citations3
Published2001
Admission routes1
Has abstractyes

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