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Record W3204546574 · doi:10.30683/1929-2279.2020.09.01

A HPLC-UV Method for the Quantification of Regorafenib in Tumor

2020· article· en· W3204546574 on OpenAlexvenueno aff
Yao Li, Meng-Ning Wei, Zhang Wen-ji, Zhi Shi

Bibliographic record

VenueJournal of cancer research updates · 2020
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRegorafenibHepatocellular carcinomaChromatographyHigh-performance liquid chromatographyChemistryProtein precipitationCalibration curveColorectal cancerMedicineDetection limitCancerCancer researchInternal medicine

Abstract

fetched live from OpenAlex

Regorafenib has been approved for the treatment of colorectal cancer, gastrointestinal stromal tumor and hepatocellular carcinoma. High-performance liquid chromatography (HPLC) was developed and validated for determination of regorafenib in xenograft tumors. After protein precipitation with acetonitrile, regorafenib were separated using gradient elution (C18 Ultrabase column). Quantification was performed at 262 nm. Calibration curves were linear over the range 48.8-50000 ng/ml. The assay was applied to the determination of the drug in the tumor of nude mice receiving regorafenib 50 mg orally, and could be useful for therapeutic drug monitoring of regorafenib in routine clinical practice.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.378
Threshold uncertainty score0.142

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.189
GPT teacher head0.510
Teacher spread0.321 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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