Search Results
You are looking at 1 - 3 of 3 items for
- Author or Editor: Huang Wei x
- Refine by Access: Content accessible to me x
A residue analytical method was developed for the determination of trichlorfon, chlorpyrifos, dimethoate, β cypermethrin, deltamethrin, and chlorothalonilin in six leafy vegetables by gas chromatography–electron capture detector (GC–ECD) and gas chromatography–flame photometric detector (GC–FPD). The method had a good linearity (R 2 ≥ 0.9924) and precision (RSD ≤ 14.0%). The limits of quantification (LOQ) of six pesticides were all 0.01 mg/kg. Average recoveries of six pesticides ranged from 81% to 119%. The developed method was successfully applied to study the initial deposits, degrade characteristics, and terminal residues for six pesticides applied to six leafy vegetables under the same dose of formulation. The half-life of six pesticides was in the range of 0.8–8.8 days. The highest initial deposits, maximal residues, and terminal residues were found on leaf mustard and sweet potato leaves as the same pesticides were applied in different crops. Therefore, leaf mustard can be selected as representative commodity in the same subgroup to realize the residual extrapolation. This conclusion should be considered as a complement on crop classification of China.
Abstract
Ganoderma lucidum (GL), also known as Reishi or Lingzhi, is a medicinal mushroom widely used in traditional and folk medicines. The extracts made from the fruiting body and spore of naturally grown GL are the most frequently used in commercial products. More than 400 compounds have been identified in GL with the triterpenoids considered to be the major active components. Large variations in the chemical components were reported in previous studies and there is no comprehensive study of the content of multiple major triterpenoids in the GL product. In addition, there is no report in the comparison of chemical profiles in different parts of GL (i.e., fruiting body and spore). Determining the chemical composition and comparing the differences between fruiting body and spore are essential for the identity, efficacy and safety of various GL products.
In this study, 13 compounds (ganoderenic Acid C, ganoderic Acid C2, ganoderic Acid G, ganoderic Acid B, ganoderenic Acid B, ganoderic Acid A, ganoderic Acid H, ganoderenic Acid D, ganoderic Acid D, ganoderic Acid F, ganoderic Acid DM, ganoderol A, and ergosterol) were selected as the chemical markers. The purpose of this study is to develop an HPLC-DAD fingerprint method for quantification of these active components in GL (spore and fruiting body) and test the feasibility of using the HPLC-DAD fingerprint for quality control or identity determination of GL products.
The results showed that this method could determine the levels of the major components accurately and precisely. Among the 13 components, 11 ganoderma acids were identified to be proper chemical markers for quality control of GL products, while ganoderal A was in a very low amount and ergosterol was not a specific marker in GL. The extracts of fruiting body contained more chemical compounds than those of spore, indicating that these 11 compounds could be a better chemical marker for the fruiting body than the spore. The HPLC chemical fingerprint analysis showed higher variability in the quality of GL harvest in different years, while lesser variation in batches harvested in the same year.
In conclusion, an HPLC assay detecting 11 major active components and a fingerprinting method was successfully established and validated to be feasible for quality control of most commercial GL products.
Background and aims
This large-scale study aimed to test (a) associations of problematic Internet use (PIU) and sleep disturbance with suicidal ideation and suicide attempts among Chinese adolescents and (b) whether sleep disturbance mediates the association between PIU and suicidal behavior.
Methods
Data were drawn from the 2017 National School-based Chinese Adolescents Health Survey. A total of 20,895 students’ questionnaires were qualified for analysis. The Young’s Internet Addiction Test was used to assess PIU, and level of sleep disturbance was measured by the Pittsburgh Sleep Quality Index. Multilevel logistic regression models and path models were utilized in analyses.
Results
Of the total sample, 2,864 (13.7%) reported having suicidal ideation, and 537 (2.6%) reported having suicide attempts. After adjusting for control variables and sleep disturbance, PIU was associated with an increased risk of suicidal ideation (AOR = 1.04, 95% CI = 1.03−1.04) and suicide attempts (AOR = 1.03, 95% CI = 1.02−1.04). Findings of the path models showed that the standardized indirect effects of PIU on suicidal ideation (standardized β estimate = 0.092, 95% CI = 0.082−0.102) and on suicide attempts (standardized β estimate = 0.082, 95% CI = 0.068−0.096) through sleep disturbance were significant. Conversely, sleep disturbance significantly mediated the association of suicidal behavior on PIU.
Discussion and conclusions
There may be a complex transactional association between PIU, sleep disturbance, and suicidal behavior. The estimates of the mediator role of sleep disturbance provide evidence for the current understanding of the mechanism of the association between PIU and suicidal behavior. Possible concomitant treatment services for PIU, sleep disturbance, and suicidal behavior were recommended.