Exploration of the efficacy and mechanism of treating head wind disease with the combination change of ginger volatile oil and gingerol by using content-weighted network pharmacology technology

Background:Exploring the efficacy,potential components,and mechanism of the combination of ginger essential oil and gingerols in the treatment of head wind disease based on network pharmacology technology with content weight.Methods:The experimental groups were divided into:0:10,1:4,1:2,1:1,2:1,4:1,10:0.The relative content(Ri)of the chemical constituents of ginger's volatile oil was determined using gas chromatography-mass spectrometry(GC-MS).Additionally,the physicochemical and biological property parameters(LogP,MDCK,PPB,MW)of the components were considered.To assess the quantitative effect of the components,a grading score was performed,and the quantitative effect index(Ki)was calculated.Subsequently,the target effect index(Ti)was calculated by combining the component-target matching score(Fit score).Using these calculations,the target effect score A was determined under the influence of multiple components targeting different targets.Key targets with A≥1000 were identified.To predict the targets related to head wind disease,the Comparative Toxicogenomics Database(https://ctdbase.org/),Gene Cards(https://www.genecards.org/),and Disgenet database(https://www.disgenet.org/)were utilized.The key targets,obtained from different proportions of ginger's volatile oil and gingerol,were intersected with the predicted targets.This facilitated network pharmacological analysis and verification of the efficacy.Results:The content of volatile oil in ginger demonstrated an impact on key targets associated with the volatile oil group.Each specific combination of volatile oil consistently activated distinct pathways,with variations stemming from changes in content.Experimental testing revealed that different combinations of ginger's volatile oil and gingerol effectively alleviated migraine symptoms in rats.Conclusion:Through the application of content-weighted network pharmacology technology and pharmacodynamic verification,it was determined that altering the ratio between ginger's volatile oil and gingerol leads to variations in potential targets and pathways,consequently impacting its efficacy.

Varietal difference in the correlation between leaf nitrogen content and photosynthesis in rice(Oryza sativa L.) plants is related to specific leaf weight

Increasing leaf photosynthesis per area（A） is of great importance to achieve yield further improvement. The aim of this study was to exploit varietal difference in A and its correlation with specific leaf weight（SLW）. Twelve rice cultivars, including 6 indica and 6 japonica varieties, were pot-grown under two N treatments, low N（LN） and sufficient N（SN）. Leaf photosynthesis and related parameters were measured at tillering stage. Compared with LN treatment, A, stomatal conductance（g_s）, mesophyll conductance（g_m）, leaf N content（N_（area））, and chlorophyll content were significantly improved under SN treatment, while SLW and photosynthetic N use efficiency（PNUE） were generally decreased. Varietal difference in A was positively related to both g_s and g_m, but not related to N_（area）. This resulted in a low PNUE in high N_（area） leaves. Varietal difference in PNUE was generally negatively related to SLW. Response of PNUE to N supply varied among different rice cultivars, and interestingly, the decrease in PNUE under SN was negatively related to the decrease in SLW. With a higher N_（area）, japonica rice cultivars did not show a higher A than indica rice cultivars because of possession of high-SLW leaves. Therefore, varietal difference in A was not related to N_（area）, and SLW can substantially interfere with the correlation between A and N_（area）. These findings may provide useful information for rice breeders to maximize A and PNUE, rather than over reliance on N_（area） as an indicator of photosynthetic performance.