MétaCan
Menu
Back to cohort
Record W2761171465 · doi:10.5539/jfr.v6n6p29

Effect of Asperagillus awamori on Alloxan-induced Mouse Hyperglycemia

2017· article· en· W2761171465 on OpenAlexvenueno aff
Shota Masuda, Yoshinao Okachi, Takumi Hirao, Kosuke Matsuoka, Ryusei Miura, Shunya Miyoshi, Takayuki Murakami, Junji Inoue, Kohji Ishihara, Noriyoshi Masuoka

Bibliographic record

VenueJournal of Food Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsnot available
Fundersnot available
KeywordsAspergillus awamoriAlloxanInsulinEndocrinologyChemistryFermentationInternal medicineMedicineFood scienceDiabetes mellitus

Abstract

fetched live from OpenAlex

Problem statement: Though alloxan-induced mouse hyperglycemia was ameliorated by feeding of 5 % Asperagillus awamori (A. awamori)-fermented burdock root diet (fermented burdock diet), it is unclear whether the anti-hyperglycemia activity is due to A. awamori or antioxidant activity induced by the fermentation.Methods: A 0.05 % A. awamori diet was prepared. Acatalasemic mice, having a quite low catalase activity in blood, were divided three groups, and each group fed control, A. awamori and the fermented burdock diets for 14 weeks, separately. Then, alloxan monohydrate (200 mg/ kg of body weight) was intraperitoneally administrated to each mouse. Glucose, insulin, C-peptide contents in blood and glucose tolerance tests (GTTs) were examined. Results: Incidence of alloxan-induced hyperglycemia in acatalasemic mice maintained with the A. awamori diet or the fermented burdock diet was low (20 or 25%) compared to that (75%) maintained with the control diet. Feeding the A. awamori diet ameliorated insulin, C-peptide in blood and GTT like as mice fed the fermented burdock diet. It indicated that A. awamori in these diets plays an important role for the prevention of alloxan-induced hyperglycemia.Conclusions: It is suggested that A. awamori has the anti-hyperglycemia activity.

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)0.001
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 score0.008
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.053
GPT teacher head0.391
Teacher spread0.338 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Food ResearchSame topicEnzyme Production and CharacterizationFrench-language works237,207