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Record W2097923189 · doi:10.5539/jfr.v2n5p132

Effect of Acrylamide on Liver Proteins Expression in Mice

2013· article· en· W2097923189 on OpenAlexvenueno aff
Ahlam Al‐Azkawi, Saif N. Al-Bahry, I.Y. Mahmoud, Michael J. Barry

Bibliographic record

VenueJournal of Food Research · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPotato Plant Research
Canadian institutionsnot available
Fundersnot available
KeywordsAcrylamidePolyacrylamide gel electrophoresisDetoxification (alternative medicine)Gel electrophoresisProteomicsChemistryBiochemistryToxicityMetabolismMolecular massMolecular biologyBiologyEnzymeMedicineGenePathology

Abstract

fetched live from OpenAlex

<p>Carbohydrate rich food cooked at high temperature can lead to the formation of acrylamide. The aim of this investigation is to analyze the proteomics of mice liver in response to acrylamide intoxication since the liver is the major site of acrylamide detoxification and metabolism. The liver protein pattern from sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDS-PAGE) treated mice with acrylamide in drinking water for 9 weeks did not show variations from the control. However, analysis by 2-D gel of liver proteins from mice treated with 0.5 µg acrylamide/kg for 9 weeks showed variations in protein expression. At least 10 protein spots were significantly affected (T > 2) by the acrylamide treatment. The affected proteins were identified using MALDI TOF/TOF and mass searches through Mascot. These proteins were up-regulated or down-regulated depending on their physiological function. Probably the proteins are involved in detoxification of acrylamide or cell protection. The data from this study shows that proteomics is a valuable tool for assessing acrylamide toxicity in the affected tissues.</p>

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)0.004
metaresearch head score (Gemma)0.001
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 score0.051
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.056
GPT teacher head0.330
Teacher spread0.274 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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