MétaCan
Menu
Back to cohort
Record W2386485093

The pharmacokinetics of the Main Ingredient in Zaoren-an-shen Granule in Rats

2014· article· en· W2386485093 on OpenAlexaff
Sha Li

Bibliographic record

VenueJournal of Northwest University · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGinseng Biological Effects and Applications
Canadian institutionsScience North
Fundersnot available
KeywordsChemistryChromatographyGranule (geology)PharmacokineticsIngredientActive ingredientSodiumHigh-performance liquid chromatographyGradient elutionProtein precipitationPharmacologyFood science
DOInot available

Abstract

fetched live from OpenAlex

To establish HPLC method for simultaneously determination of the active ingredients in Zaoren-anshen granule( spinosa,salvianic acid A sodium,schisandrin) in rats. Acetonitrile precipitation preparation of plasma samples,C18 reversed-phase chromatography gradient elution method and separation pinosa,salvianic acid a sodium,schisandrin,internal standard curve method were used to calculate three kinds of effective component content. Three indicators composition was maintained at the linear ranges( 10 ~ 300μg / mL for spinosin,1. 25 ~ 62. 5 μg / mL for salvianic acid A sodium,5. 0 ~ 250 μg / mlμg / mL for schisandrin). Three effective constituents measured in daytime and over days showed that the of relative standard deviation was less than 15%. The recovery rates of the samples with low,medium and high concentration were higher than 85%. Normal rats after oral administration Zaoren-an-shen granule,their spinosin conformed to the one-compertment model,both of salvianic acid A and schisandrin conformed to the two-compertment open model. This method can simultaneously determine spinosa,salvianic acid A sodium and schisandrin in plasma samples,can be ex-pected to become a method to research the pharmacokinetic of Zaoren-an-shen granule.

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 score0.595
Threshold uncertainty score0.116

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 head0.006
GPT teacher head0.217
Teacher spread0.211 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Northwest UniversitySame topicGinseng Biological Effects and ApplicationsFrench-language works237,207