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Record W1979380267 · doi:10.1139/y09-059

A concise description of cardioprotective strategies in doxorubicin-induced cardiotoxicityThis article is one of a selection of papers published in a special issue celebrating the 125th anniversary of the Faculty of Medicine at the University of Manitoba.

2009· review· en· W1979380267 on OpenAlexafffundvenueabout
Ana Raquel Lehenbauer Lüdke, Abd Al‐Rahman Al‐Shudiefat, Sanjiv Dhingra, Davinder S. Jassal, Pawan K. Singal

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2009
Typereview
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsSt. Boniface Hospital
FundersCanadian Institutes of Health Research
KeywordsProbucolCardiotoxicityMedicineDoxorubicinPharmacologyCardiomyopathyCancerIntensive care medicineClinical trialChemotherapyInternal medicineHeart failureCholesterol

Abstract

fetched live from OpenAlex

Doxorubicin (Dox) is frequently used as a frontline chemotherapeutic agent against a variety of cancers. Tremendous progress has been made on its optimal usage over the last 40 years. However, cardiotoxicity still remains a major concern. The great promise in this matter is that the mechanisms leading to antitumor activity appear to be different from those leading to Dox-induced cardiomyopathy. In this regard, various cardioprotective agents have been discussed. Attention should be drawn to probucol, a lipid-lowering agent with potent antioxidant properties, which provides complete protection against Dox-induced cardiomyopathy in rats without interfering with the antitumor properties of Dox in an experimental setting. Clinical trials employing Dox therapy in combination with probucol are needed to determine whether the outstanding findings in animal experiments can be extrapolated to clinical results. We have much further to go before the establishment of cancer therapies without any risk of cardiac side effects.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.285
Teacher spread0.249 · 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 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

Citations81
Published2009
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and PharmacologySame topicChemotherapy-induced cardiotoxicity and mitigationFrench-language works237,207