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The Effects of Zataria Multiflora Hydroalcoholic Extract on Some Liver Enzymes, Cholesterol, Triglyceride, HDL-Cholesterol, LDL-Cholesterol, Albumin and Total Protein in Rat

2012· article· en· W2333139800 on OpenAlexvenueno aff
Ameneh Khoshvaghtı, Saeed Nazıfı, Seena Derakhshaniyan, Bijan Akbarpour

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2012
Typearticle
Languageen
FieldMedicine
TopicNatural Antidiabetic Agents Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTriglycerideAlbuminCholesterolBlood lipidsTraditional medicineLipid profileTotal cholesterolDistilled waterMedicineChemistryInternal medicineChromatography

Abstract

fetched live from OpenAlex

Zataria multiflora is a valuable medicinal plant grown extensively in Iran, Pakistan and Afghanistan. The chemical compositions of their extracts have been extensively characterized in Iran and Pakistan. The present study was undertaken to investigate the effects of Zataria multiflora on some liver enzymes, triglyceride, cholesterol, HDL-cholesterol, LDL-cholesterol, albumin and total protein in rat. Sixty adult male Wistar rats weighing about 200 to 220 g were divided into six groups of ten. The control group (group 1) did not receive any drug. The sham group (group 2) received 2 cc of distilled water. The other four experimental groups (groups 3 to 6) including very low (100 mg/kg BW), low (200 mg/kg BW), medium (300 mg/kg BW) and maximum dose (400 mg/kg BW) received Zataria multiflora hydroalcoholic extract intraperitoneally daily for 28 days. After 28 days all animals in the different groups were weighed and blood samples were collected from heart vein. Serum biochemical parameters were measured using validated standard methods. The results of this study showed Zattaria multiflora hydroalcoholic extract analyses various lipids in lipid tissues and transfer to blood for elimination from body.

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)0.002
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 score0.573
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.015
GPT teacher head0.261
Teacher spread0.245 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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