Effect of Pretreatment on Detection of 37 Pesticide Residues in Chrysanthemum indicum.

This study aimed to develop a method, followed by gas chromatography-mass spectrometry, for detecting 37 pesticides in Chrysanthemum indicum (C. indicum) and investigating the decrease in the matrix-induced enhancement effect. The influence of QuEChERS extraction and matrix solid-phase dispersion (MSPD) on the recovery and matrix effect (ME) was compared. extraction and matrix solid-phase dispersion (MSPD) on the recovery and matrix effect (ME) was compared to decrease the ME. The cleanup sorbents, volume and type of solvent, and treatment time were optimized. The accuracy (as recovery), precision (as relative standard deviation, RSD), linearity, limit of quantitation, and limit of detection were determined. The recoveries at the three levels using mixed standard solution ranged between 76% and 120% with RSD ≤15%, and 76% and 120% with RSD ≤11% for MSPD and QuEChERS extraction, respectively. The results suggested that the ME for 21 pesticides was in the range of 80%-120% after MSPD and 15% after QuEChERS extraction. QuEChERS extraction was simpler and faster than MSPD. This methodology was applied in the analysis of 27 C. indicum samples; phorate was most frequently detected (63.0% of the sample).

Evaluation of analgesic and anti-inflammatory activities of Rubia cordifolia L. by spectrum-effect relationships.

The objective of the current work was to evaluate the spectrum-effect relationships between high-performance liquid chromatography fingerprints and analgesic and anti-inflammatory effects of Rubia cordifolia L. extract (RCE), and to identify active components of RCE. Chemical fingerprints of ten batches of RC from various sources were obtained by HPLC, and similarity and hierarchical clustering analyses were carried out. Pharmacodynamic assays were performed in adjuvant-induced arthritis rat model to assess the analgesic and anti-inflammatory properties of RCE. The spectrum-effect relationships between chemical fingerprints and the analgesic and anti-inflammatory effects of RCE were established by gray correlation analysis. UPLC-ESI-MS was used to identify the structures of potential active components, by reference standards comparison. The results showed that a close correlation existed between chemical fingerprints with analgesic and anti-inflammatory activities, and alizarin, 6-hydroxyrubiadin, purpurin and rubiadin might be the active constituents of RCE. In addition, RCE attenuated pathological changes in adjuvant-induced arthritis. The current findings provide a strong basis for combining chemical fingerprints with analgesic and anti-inflammatory activities in assessing the spectrum-effect relationships of RCE.