A sensitive gas chromatographic-mass spectrometric assay was described for determination of beta-elemene and beta-elemenal in human plasma, which has been successfully applied in clinical trial. After liquid-liquid extraction and gas chromatographic separation, the analytes were identified and quantitated. Calibration curves were linear in range from 31.25 to 8000 ng mL(-1) and the limit of quantification for both was 31.25 ng mL(-1). Intra- and inter-day precision at three concentrations were 2.3-8.3% with accuracy of -8.5 to 6.1% for elemene and 3.0-9.9% with accuracy of -2.3 to 5.9% for elemenal. The method was validated to be suitable for further pharmacokinetic study.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jchromb.2008.12.038DOI Listing

Publication Analysis

Top Keywords

sensitive gas
8
gas chromatographic-mass
8
chromatographic-mass spectrometric
8
determination beta-elemene
8
beta-elemene beta-elemenal
8
beta-elemenal human
8
human plasma
8
validation sensitive
4
spectrometric method
4
method simultaneous
4

Similar Publications

Accurate estimation of interfacial tension (IFT) between nitrogen and crude oil during nitrogen-based gas injection into oil reservoirs is imperative. The previous research works dealing with prediction of IFT of oil and nitrogen systems consider synthetic oil samples such n-alkanes. In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil - nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs.

View Article and Find Full Text PDF

The laminae of varying lithologies are characteristic of shale oil reservoirs, with their pronounced heterogeneity and fluid-solid coupling significantly impacting oil productivity. To this end, this study initially quantified the permeability and mechanical heterogeneity in lamina-developed shale through permeability tests and quasi triaxial mechanical experiments on shale cores from different orientations in the Jiyang Depression. These tests revealed marked brittleness in horizontally oriented cores and elasticity in vertically oriented cores.

View Article and Find Full Text PDF

Greenhouse gases (GHGs) have caused great harm to the ecological environment, so it is necessary to screen gas sensor materials for detecting GHGs. In this study, we propose an ideal gas sensor design strategy with high screening efficiency and low cost targeting four typical GHGs (CO, CH, NO, SF). This strategy introduces machine learning (ML) methods based on density functional theory (DFT) to achieve accurate and rapid screening from a large number of candidate gas sensor materials.

View Article and Find Full Text PDF

A data transmission delay compensation algorithm for an interactive communication network of an offshore oil field operation scene in severe weather is proposed. To solve the problem of unstable microwave signals and a large amount of noise in the communication network caused by bad weather, the communication network signal denoising method based on Lagrange multiplier symplectic singular value mode decomposition is adopted, and the communication network data denoising process is realized through five steps; phase space reconstruction, symplectic geometric similarity transformation, grouping, diagonal averaging, and adaptive reconstruction. Simultaneously, the weak communication signal is compensated after being captured, that is, the characteristics of the weak signal are enhanced.

View Article and Find Full Text PDF

Multi Targeted Activity of Cocculus hirsutus through Modulation of DPP-IV and PTP-1B Leading to Enhancement of Glucose Uptake and Attenuation of Lipid Accumulation.

Appl Biochem Biotechnol

January 2025

Tissue Culture and Drug Discovery Laboratory, Department of Biotechnology, Anna University, Chennai, 600 025, India.

Multi-targeted therapies are gaining attention in the management of multifactorial diseases due to their poly pharmacology, enhanced potency and reduced toxicity. Metabolic disorders like Type 2 diabetes mellitus (T2DM) and obesity necessitate multi-targeted therapy to improve insulin sensitivity, regulate glucose homeostasis and support weight loss. Medicinal plants rich in bioactive compounds exhibit multi-targetted action with minimal side effects.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!