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Effects of Vernonia amygdalina Leaf on Nutritional and Biochemical Parameters in Alloxan-Induced Diabetic Rats

2018· article· en· W2800742650 on OpenAlexvenueno aff
Nuria Amaechi, P. C. Ojimelukwe, Samuel O. Onoja

Bibliographic record

VenueJournal of Nutritional Therapeutics · 2018
Typearticle
Languageen
FieldMedicine
TopicNatural Antidiabetic Agents Studies
Canadian institutionsnot available
Fundersnot available
KeywordsVernonia amygdalinaAlloxanDiabetes mellitusChemistryTraditional medicineEndocrinologyInternal medicineBiologyMedicine

Abstract

fetched live from OpenAlex

The effects of Vernonia amygdalina leaf on the nutritional and biochemical parameters in alloxan-induced diabetic rat were investigated. Vernonia amygdalina (VA) leaf was squeeze-washed, dried, pulverized and mixed with standard feed at 2.5%, 5%, 10% and 20%. The proximate nutrient composition of the standard and prepared rations was determined. The Vernonia amygdalina incorporated rations and standard ration were fed to alloxan-induced diabetic rats for 70 consecutive days. Thereafter the nutritional and biochemical parameters as well as the histopathology of pancreas vital organs of the treated rats were determined. The Vernonia Amygdalina at 2.5% inclusion rate significantly (p < 0.05) reversed the nutritional indices and biochemical parameters which were compromised in diabetic rats fed with standard ration alone. The VA also reversed the degenerative changes in the pancreatic islet induced by alloxan. Vernonia Amygdalina has potent antidiabetic activity and its incorporation in excess of 5% in the diet should be avoided.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.546

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 head0.030
GPT teacher head0.299
Teacher spread0.269 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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