In this study, the combination of chemometric resolution and cubic spline data interpolation was investigated as a method to correct the retention time shifts for chromatographic fingerprints of herbal medicines obtained by high-performance liquid chromatography-diode array detection (HPLC-DAD). With the help of the resolution approaches in chemometrics, it was easy to identify the purity of chromatographic peak clusters and then resolve the two-dimensional response matrix into chromatograms and spectra of pure chemical components so as to select multiple mark compounds involved in chromatographic fingerprints. With these mark components determined, the retention time shifts of chromatographic fingerprints might be then corrected effectively. After this correction, the cubic spline interpolation technique was then used to reconstruct new chromatographic fingerprints. The results in this work showed that, the purity identification of the chromatographic peak clusters together with the resolution of overlapping peaks into pure chromatograms and spectra by means of chemometric approaches could provide the sufficient chromatographic and spectral information for selecting multiple mark compounds to correct the retention time shifts. The cubic spline data interpolation technique was user-friendly to the reconstruction of new chromatographic fingerprints with correction. The successful application to the simulated and real chromatographic fingerprints of two Cortex cinnamomi, fifty Rhizoma chuanxiong, ten Radix angelicae and seventeen Herba menthae samples from different sources demonstrated the reliability and applicability of the approach investigated in this work. Pattern recognition based on principal component analysis for identifying inhomogenity in chromatographic fingerprints from real herbal medicines could further interpret it.
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http://dx.doi.org/10.1016/j.chroma.2003.12.049 | DOI Listing |
Zhongguo Zhong Yao Za Zhi
September 2024
School of Pharmaceutical Sciences, Guizhou Medical University Guiyang 561113, China Engineering Research Center for the Development and Application of Ethnic Medicine and TCM (Ministry of Education),Guizhou Medical University Guiyang 550004, China State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University Guiyang 550004, China.
This study aimed to provide scientific evidence for predicting quality markers(Q-markers) of Xuebijing Injection by establishing high-performance liquid chromatography(HPLC) fingerprints of 25 batches of Xuebijing Injection and determining the contents of 9 major components, as well as conducting network pharmacology research. Thirty common peaks were identified by fingerprints of 25 batches of Xuebijing Injection samples, and 12 chromatographic peaks were determined, with similarity ranging from 0.970 to 0.
View Article and Find Full Text PDFArch Environ Contam Toxicol
December 2024
School of Engineering and Architecture, Department of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, Terracini 28, 40131, Bologna, Italy.
Concerning the entrance of oil into the Persian Gulf due to the presence of oil fields in this ecosystem, a wide investigation was carried out in 2017 to evaluate the hydrocarbons source identification and chemical fingerprinting. To this end, surface sediments were collected from the Persian Gulf. In the laboratory, compounds (n-alkanes, PAHs, hopane and sterane) were then extracted with a Soxhlet system and two steps of chromatographic columns and analyzed using a GC-MS instrument.
View Article and Find Full Text PDFJ Comput Aided Mol Des
December 2024
Pharmaceutical and Pharmacological Sciences, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
Molecular machine learning (ML) has proven important for tackling various molecular problems, such as predicting molecular properties based on molecular descriptors or fingerprints. Since relatively recently, graph neural network (GNN) algorithms have been implemented for molecular ML, showing comparable or superior performance to descriptor or fingerprint-based approaches. Although various tools and packages exist to apply GNNs in molecular ML, a new GNN package, named MolGraph, was developed in this work with the motivation to create GNN model pipelines highly compatible with the TensorFlow and Keras application programming interface (API).
View Article and Find Full Text PDFJ Chromatogr A
November 2024
Department of Pharmacology, Center for Innovative Drug Research and Evaluation, Institute of Medical Science and Health, The Hebei Collaboration Innovation Center for Mechanism, Diagnosis and Treatment of Neurological and Psychiatric Disease, The Key Laboratory of Neural and Vascular Biology, Ministry of Education, Hebei Medical University, Shijiazhuang 050011, China. Electronic address:
J Diabetes Metab Disord
December 2024
Laboratoire des Sciences Fondamentales, Université Amar Telidji, Laghouat, BP37G Algeria.
Aims: Desf. (Anacardiaceae) is traditionally used in Mediterranean medicine, with previous studies showing antidiabetic potential in its fruits and leaves. This study evaluates the antidiabetic activity of galls (PAG) extracts using in vitro, chemometric, and in silico approaches.
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