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Record W2380445851

Tissue distribution and excretion of Hylotelephin

2006· article· en· W2380445851 on OpenAlexaff
Liu Ying-ju

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectron Spin Resonance Studies
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsBeagleExcretionUrineKidneySpleenHigh-performance liquid chromatographyChemistryDistribution (mathematics)Internal medicineEndocrinologyChromatographyPharmacologyMedicineBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Objective To investigate tissue distribution of Hylotelephin in Beagle dogs and excretion of Hylotelephin in rats. Methods A high performance liquid chromatography (HPLC) with UV detection was developed to study the concentrations of Hylotelephin in biological samples, taking anthracene as an internal standard, Benzoyl chloride as the pre-column derivatization of Hylotelephin and methanol-water as the mobile phase. Results After a single intravenous dose of 10.6 mg/kg Hylotelephin in beagle dogs, parent drug was widely distributed to virtually all tissues in 5 min and the concentration of Hylotelephin in most tissues at 90 min were lower than those at 5 min obviously. Hylotelephin was mainly distributed in kidney, liver and spleen, secondly in heart, lung and intestine. The parent drug concentration in kidney, liver and spleen was similar to that in blood at the same time point. After a single intravenous dose of 36 mg/kg Hylotelephin in rats, the excretion of the parent drug in urine, feces and bile amounted to 88.45%, 0.61% and 1.08% of the dose, respectively. The parent drug excretion amounted to 67% of the dose in 3 h. Conclusion Hylotelephin was distributed and eliminated in Beagle dogs rapidly. It was mostly distributed in kidney, liver, spleen and plasma. The parent drug excretion was 88% via urine.

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 score0.090
Threshold uncertainty score0.158

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 head0.003
GPT teacher head0.224
Teacher spread0.221 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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