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Record W2005457796 · doi:10.1177/109980040000200106

Iron-Overload Cardiomyopathy: Evidence for a Free Radical– Mediated Mechanism of Injury and Dysfunction in a Murine Model

2000· article· en· W2005457796 on OpenAlexaff
Wally J. Bartfay, Emma Bartfay

Bibliographic record

VenueBiological Research For Nursing · 2000
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsQueen's University
Fundersnot available
KeywordsCardiomyopathyHeart failureGlutathione peroxidaseMedicineAntioxidantInternal medicineHemochromatosisOxidative stressReactive oxygen speciesCardiologySuperoxide dismutaseEndocrinologyChemistryBiochemistry

Abstract

fetched live from OpenAlex

Iron-overload cardiomyopathy is a restrictive cardiomyopathy that manifests itself as systolic or diastolic dysfunction secondary to increased deposition of iron in the heart and occurs with common genetic disorders such as primary hemochromatosis and beta-thalassemia major. Although the exact mechanism of iron-induced heart failure remains to be elucidated, the toxicity of iron in biological systems is believed to be attributed to its ability to catalyze the generation of oxygen-free radicals. In the current investigation, the dose-dependent effects of chronic iron-loading on heart tissue concentrations of iron, glutathione peroxidase (GPx) activity, free-radical production, and cardiac dysfunction were investigated in a murine model of iron-overload cardiomyopathy. It was shown that chronic iron-overload results in dose-dependent (a) increases in myocardial iron burden, (b) decreases in the protective antioxidant enzyme GPx activity, (c) increased free-radical production, and (d) increased mortality. These findings show that the mechanism of iron-induced heart dysfunction involves in part free radical-mediated processes.

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)0.001
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
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.220
GPT teacher head0.459
Teacher spread0.239 · 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

Citations66
Published2000
Admission routes1
Has abstractyes

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Same venueBiological Research For NursingSame topicTrace Elements in HealthFrench-language works237,207