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Role of catecholamine oxidation in sudden cardiac death

2010· review· en· W1872172232 on OpenAlexaff
Naranjan S. Dhalla, Adriana Adameová, Meera Kaur

Bibliographic record

VenueFundamental and Clinical Pharmacology · 2010
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
Fundersnot available
KeywordsCatecholamineSudden cardiac deathInternal medicineSudden deathCardiologyMedicine

Abstract

fetched live from OpenAlex

Although sudden cardiac death is a leading cause of mortality, the mechanisms for its pathogenesis are poorly understood. Because overactivation of sympathetic nervous system is invariably seen in subjects with high risk for sudden cardiac death, elevated levels of circulating catecholamine levels are considered to result in lethal ventricular arrhythmias and subsequent sudden cardiac death. Such arrhythmogenic effects of catecholamines are generally believed to occur by their actions on α-adrenoceptors in coronary arteries for inducing coronary spasm and subsequent myocardial ischemia as well as on β-adrenoceptors in cardiomyocytes for increasing the concentration of cyclic AMP excessively and producing defects in intracellular Ca2+ handling. Experimental evidence from our laboratory has revealed that excessive amounts of circulating catecholamines are oxidized to aminochromes, which are highly reactive quinine compounds. The oxidation products of catecholamines have been demonstrated to produce subcellular alterations, intracellular Ca2+ overload, coronary spasm, myocardial cell damage, depletion of high energy stores, and ventricular arrhythmias. In addition, oxyradicals, which are known to generate oxidative stress and produce cardiotoxic effects, including arrhythmias, are formed during the oxidation of catecholamines. Accordingly, it is proposed that oxidation of catecholamines and the generation of oxidative stress under stressful conditions may play a critical role in the genesis of ventricular arrhythmias that may result in sudden cardiac death.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
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 head0.041
GPT teacher head0.427
Teacher spread0.386 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations98
Published2010
Admission routes1
Has abstractyes

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