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Record W2515532989 · doi:10.1002/jmr.2560

Antiamyloidogenic Effects of Ellagic Acid on Human Serum Albumin Fibril Formation Induced by Potassium Sorbate and Glucose

2016· article· en· W2515532989 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 Molecular Recognition · 2016
Typearticle
Languageen
FieldMedicine
TopicGinkgo biloba and Cashew Applications
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of TehranIran National Science FoundationIran's National Elites Foundation
KeywordsEllagic acidChemistryPotassium sorbateThioflavinHuman serum albuminAntioxidantPotassiumOxidative stressBiochemistryCongo redOrganic chemistryPolyphenolAdsorption

Abstract

fetched live from OpenAlex

Oxidative stress has the main role in protein conformational changes and consequent direct involvement in different kind of diseases. Potassium sorbate as a widespread industrial preservative and glucose are two important oxidants that can be involved in oxidative stress. In this study the effect of ellagic acid as a phenolic antioxidant on amyloid fibril formation of human serum albumin upon incubation of potassium sorbate and glucose was studied using thioflavin T assay, surface tension, atomic force microscopy, Amadori product, and carbonyl content assays. The thioflavin T assay and atomic force microscopy micrographs demonstrated the antiamyloidogenic effect of ellagic acid on the human serum albumin fibril formation. This antioxidant also had the repair effect on surface tension of the modified human serum albumin (amyloid intermediates), which was destructed, caused by potassium sorbate and glucose. This mechanism takes place because of potent carbonyl stress suppression effect of ellagic acid, which was strengthening by potassium sorbate in the presence and absence of glucose.

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 score0.074
Threshold uncertainty score0.340

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 head0.016
GPT teacher head0.264
Teacher spread0.247 · 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