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Record W1966184664 · doi:10.1021/jf0711901

Effect of Selenium- and Glutathione-Enriched Yeast Supplementation on a Combined Atherosclerosis and Diabetes Hamster Model

2007· article· en· W1966184664 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2007
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsLallemand (Canada)
Fundersnot available
KeywordsGlutathioneGlutathione peroxidaseSeleniumAntioxidantYeastTriglycerideChemistryHamsterGPX4BiochemistryGPX3Diabetes mellitusGlutathione disulfideInternal medicineCholesterolEndocrinologyBiologyMedicineEnzyme

Abstract

fetched live from OpenAlex

Selenium has a central role in antioxidant pathways as a cofactor to glutathione peroxidase. The present study evaluated the effects of four different preparations of inactivated yeast containing various concentrations of selenium and glutathione on a combined atherosclerosis and diabetes hamster model. The hamsters were supplemented with the yeast products for three months. The enriched yeast with the highest selenium and glutathione levels reduced the weight loss induced by diabetes, inhibited an increase in plasma cholesterol and triglyceride caused by a high-cholesterol and high-fat diet, increased the time taken for oxidation of lower density lipoproteins (lag time), and inhibited the formation of atherosclerosis better than low selenium/glutathione yeast supplementation. It was concluded that the yeast prepared to provide high selenium and high glutathione was the best for effecting beneficial changes in glutathione, cholesterol, atherosclerosis, and for demonstrating an antioxidant effect. The high selenium and low glutathione yeast was the best for improving selenium and glucose levels.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.229
Teacher spread0.219 · 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