MétaCan
Menu
Back to cohort
Record W2810959595 · doi:10.5539/ijb.v10n3p62

Assessment of the Hypoglycemic Effects of the Aqueous Extracts of Bauhinia forficata in Wistar Rats Fed with a High Fat Diet

2018· article· en· W2810959595 on OpenAlexvenueno aff
Igor F. S. Oliveira, Hellen S. Neves, Myllena F. Franco, Aluana Santana Carlos, Simoni Machado de Medeiros, Adalgiza Mafra Moreno, Andressa Nunes Araujo, Vítor Tenorio

Bibliographic record

VenueInternational Journal of Biology · 2018
Typearticle
Languageen
FieldMedicine
TopicNatural Antidiabetic Agents Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCarbohydrateAnimal scienceChemistryInternal medicineEndocrinologyMedicineBiology

Abstract

fetched live from OpenAlex

This study aimed at analyzing both body and glycemic parameters resulting from the administration of high fat diet and Bauhinia forficata aqueous extract (AqE) in rats. Initially, sixty-day-old rats were divided into two groups. Group C was fed with normocaloric diet and group D was fed with a high fat diet composed of 20% proteins; 48% carbohydrate, 20% lipid, 4% cellulose, 5% vitamin and mineral salts. On the 120 day-old group D was subdivided with another D + I group, fed a hyperlipid diet plus administration of Bauhinia forficata AqE for gavage. During experimental period, body mass, food intake and glucose were evaluated. The animals were sacrificed at the age of 150 days. Group D, at 120 days, presented higher body mass compared to group C, but there were no changes in dietary intake. The glycaemia of group D increased compared to group C. At 150 days, the D + I group had a decrease in body mass and glycaemia, and group D continued to gain body mass without changing food intake. Therefore, the findings show that the two-month-diet-period increased body weight and blood glucose. AqE of plant B. forficata has pharmacological potential in reducing body mass and decreasing in blood glucose concentrations.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.172

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 head0.010
GPT teacher head0.302
Teacher spread0.292 · 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 designObservational
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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of BiologySame topicNatural Antidiabetic Agents StudiesFrench-language works237,207