MétaCan
Menu
Back to cohort
Record W2016176103 · doi:10.1097/mco.0b013e328354a326

Catalase polymorphisms and metabolic diseases

2012· review· en· W2016176103 on OpenAlexaff
Marylise Hébert-Schuster, Emmanuelle Fabre, Valérie Nivet‐Antoine

Bibliographic record

VenueCurrent Opinion in Clinical Nutrition & Metabolic Care · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlutathione Transferases and Polymorphisms
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsCatalaseSingle-nucleotide polymorphismDyslipidemiaBiologyDiseaseInsulin resistanceSNPGeneticsDiabetes mellitusBioinformaticsMedicineGeneGenotypeInternal medicineEndocrinologyOxidative stress

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This review summarizes our current understanding of the implication of catalase polymorphisms in the occurrence, control and comorbidities of metabolic diseases. RECENT FINDINGS: Whatever impaired glucose tolerance, insulin resistance on diabetes and whatever their occurrence or implications, the studies taken together converge toward the hypothesis that catalase polymorphisms play a role in glucose disorders. -262C/T and -844A>G single nucleotide polymorphisms are associated to hypertension susceptibility and/or onset. Concerning dyslipidemia, very recent studies requiring confirmation report a -262C/T implication. Finally, a role of catalase polymorphisms in bone metabolism is described. SUMMARY: Plethora of studies on catalase SNPs and their link with diseases exist. It is now clear that genetic variations in the catalase gene and its promoter are putative risk factors for metabolic disease. The question of how these polymorphisms actively play a role in various metabolisms remains unanswered. Further functional studies are required in order to gain a deeper insight into the direct role of catalase.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.102
GPT teacher head0.421
Teacher spread0.319 · 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 designNot applicable
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

Citations38
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in Clinical Nutrition & Metabolic CareSame topicGlutathione Transferases and PolymorphismsFrench-language works237,207