No abstract

For thousands of years, corn silk has been widely used as an antidiabetic, antioxidant, and antihyperlipidemic and for other effects, but there is a lack of studies that correlate the extracts of flavonoid composition with their biological activities. Thus, the objectives of this study were to optimize the conditions for extracting flavonoids, identify flavonoids, and correlate the flavonoid composition with the biological activities in corn silk. The response surface experiments showed that the highest flavonoid content was predicted at 45.321 min, 57.349°C, 26.089 mL/g, and 71.269%, respectively. The verification experiment results under these optimized conditions showed an ultrasonic time of 45 min, an ultrasonic temperature of 57°C, a liquid-to-material ratio of 26, and an ethanol volume fraction of 70%. No significant differences (the relative error is 4.378%) were observed between the theoretical and experimental TFC values, indicating that the developed models were accurate. Under these optimum extraction conditions, 20 major compounds were identified and quantified by UPLC-LTQ/Orbitrap MS. Furthermore, these optimum ethanol extracts of corn silk are effective against Bacillus subtilis and hypoglycemic activity compared with the traditional heating reflux extraction method. Six corn silk components seem to be the main contributors to the inhibitory effect against Bacillus subtilis and hyperglycemia activities. These results are useful for the application of corn silk in the food or pharmaceutical industry.

No abstract

Plant-produced coumarins have been shown to play an important role in assembly of the plant microbiomes and iron acquisition. Coumarins can also be produced by some microorganisms.

Poria cocos (PC) is an important fungus with high medicinal and nutritional values. However, the quality of PC is heavily dependent on multiple factors in the cultivation regions. Traditional methods are not able to perform quality evaluation for this fungus in a short time, and a new method is needed for rapid quality assessment. Here, we used near-infrared (NIR) spectroscopy combined with chemometric method to identify the cultivation regions and determine PC chemical compositions. In our study, 138 batches of samples were collected and their cultivation regions were distinguished by combining NIR spectroscopy and random forest method (RFM) with an accuracy as high as 92.59%. In the meantime, we used partial least square regression (PLSR) to build quantitative models and measure the content of water-soluble extract (WSE), ethanol-soluble extract (ASE), polysaccharides (PSC) and the sum of five triterpenoids (SFT). The performance of these models were verified with correlation coefficients (R2cal and R2pre) above 0.9 for the four quality parameters and the relative errors (RE) of PSC, WSE, ASE and SFT at 4.055%, 3.821%, 4.344% and 3.744%, respectively. Overall, a new approach was developed and validated which is able to distinguish PC production regions, quantify its chemical contents, and effectively evaluate PC quality.