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Record W135168099

Blood and Liver Antioxidant Capacity of Mice Fed High Fat Diet Supplemented with Digested Oat Bran Proteins

2014· article· en· W135168099 on OpenAlexaff
Sara Jodayree, Zachary R. Patterson, Harry A. Mackay, Alfonso Abizaid, Apollinaire Tsopmo

Bibliographic record

VenueFood and Public Health · 2014
Typearticle
Languageen
FieldMedicine
TopicBiochemical effects in animals
Canadian institutionsCarleton University
Fundersnot available
KeywordsOxygen radical absorbance capacityAntioxidantChemistryHydrolysateOxidative stressSuperoxide dismutaseFood scienceInternal medicineBranEndocrinologyBiochemistryAntioxidant capacityBiologyMedicineHydrolysis
DOInot available

Abstract

fetched live from OpenAlex

The aim of this study was to assess the effect of three concentrations of oat bran protein hydrolysate (OPH) (1, 10, 10 mg/g diet) on oxidative stress marker in high fat fed animals. CD-1 male mice were placed into five groups and fed normal diet (ND), high fat (HF), and HF containing 1, 10, and 100 mg OPH/g of HF-diet for 3 weeks. Blood was collected at necropsy and analyze for glucose and markers of oxidative stress. At the highest level of OPH the oxygen radical absorbance capacity value of erythrocytes (123.1 ± 11.1 mMTrolox equivalents (TE)/mL blood) was higher (p < 0.05) than the value of HF group (96.5 ± 6.6 mM TE/mL) indicating higher scavenging activity that may be explained by higher thiol concentration detected. Liver superoxide dismutase (SOD) antioxidant enzyme activity was 13.2% lower in mice on HF-diet compared to those who received normal diet. Supplementation of HF-diet with OPH increased SOD activity to ND group level. OPH also had positive effect on respiratory exchange ratios but did not affect liver scavenging activity, calorie intake or bodyweight.In conclusion, addition OPH to HF diet increased radical scavenging activity in erythrocytes and SOD activity in mice liver samples.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.471

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 head0.024
GPT teacher head0.252
Teacher spread0.228 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

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