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Record W3133490551 · doi:10.1093/toxsci/kfab026

Low-Level Metal Contamination and Chelation in Cardiovascular Disease—A Ripe Area for Toxicology Research

2021· review· en· W3133490551 on OpenAlexaff
Francisco Ujueta, Ana Navas‐Acién, Koren K. Mann, Rakesh Prashad, Gervasio A. Lamas

Bibliographic record

VenueToxicological Sciences · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsMcGill University
Fundersnot available
KeywordsContaminationEnvironmental chemistryToxicologyChelationChemistryBiologyEcology

Abstract

fetched live from OpenAlex

Cardiovascular disease remains the leading cause of death worldwide. In spite of cardiovascular prevention, there is residual risk not explicable by traditional risk factors. Metal contamination even at levels previously considered safe in humans may be a potential risk factor for atherosclerosis. This review examines evidence that 2 metals, lead, and cadmium, demonstrate sufficient toxicological and epidemiologic evidence to attribute causality for atherosclerotic disease. Basic science suggests that both metals have profound adverse effects on the human cardiovascular system, resulting in endothelial dysfunction, an increase in inflammatory markers, and reactive oxygen species, all of which are proatherosclerotic. Epidemiological studies have shown both metals to have an association with cardiovascular disease, such as peripheral arterial disease, ischemic heart disease, and cardiovascular mortality. This review also examines edetate disodium-based chelation as a possible pharmacotherapy to reduce metal burden in patients with a history of cardiovascular disease and thus potentially reduce cardiovascular events.

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)0.007
metaresearch head score (Gemma)0.002
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 score0.997
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.335
GPT teacher head0.419
Teacher spread0.084 · 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

Citations15
Published2021
Admission routes1
Has abstractyes

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