Anti-VIP polyclonal antibody

This research reports on the development of a method to identify and quantify fungal biomass based on ergosterol autofluorescence using excitation-emission matrix (EEM) measurements. In the first stage of this work, several ergosterol extraction methods were evaluated by APCI-MS, where the ultrasound-assisted procedure showed the best results. Following an experimental design, various quantities of the dried mycelium of the fungus Schizophyllum commune were mixed with the starchy solid residue (BBR) from the babassu (Orbignya sp.) oil industry, and these samples were subjected to several ergosterol extraction methods. The EEM spectral data of the samples were subjected to Principal Component Analysis (PCA), which showed the possibility to qualitatively evaluate the presence of ergosterol in the samples by ergosterol autofluorescence without the addition of any reagent. In order to assess the feasibility of quantifying fungal biomass using ergosterol autofluorescence, the EEM spectral data and known amounts of fungal biomass were modeled using partial least squares (PLS) regression and a procedure of backward selection of predictors (AutoPLS) was applied to select the Excitation-Emission wavelength pairs that provide the lowest prediction error. The results revealed that the amount of fungal biomass in samples containing interfering substances (BBR) can be accurately predicted with (RCV)-C-2 = 0.939, (RP)-P-2 = 0.936, RPDcv = 4.07, RPDp = 4.06, RMSECV = 0.0731 and RMSEP = 0.0797. In order to obtain an easy-to-understand equation that expresses the relationship between fungal biomass and fluorescence intensity, multiple linear regression (MLR) was applied to the VIP variables selected by the AutoPLS method. The MLR model selected only 2 variables and showed a very good performance, with (RCV)-C-2 = 0.862, (RP)-P-2 = 0.809, RPDcv = 2.18, RPDp = 2.35, RMSECV = 0.137 and RMSEP = 0.138. This study demonstrated that ergosterol autofluorescence can be successfully used to quantify fungal biomass even when mixed with agroindustrial residues, in this case BBR.

With the worldwide growing interest and commercial value of traditional Chinese medicine (TCM) industries and products, the protection issue of TCM knowledge is increasingly concerned by Chinese government. Here, we investigated the current situation and trend of TCM development and knowledge protection in China through accessing academic research tools including China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP China Science and Technology Journal Database (VIP) and Google Scholar, analyzing the latest data released by National Administration of Traditional Chinese Medicine, China Statistical Yearbook of Chinese Medicine and China Statistical Yearbook. Our results demonstrate that current administration in China is continuing to support TCM development by increasing investment and expanding the scale in TCM research and administration. The increasing attention of Chinese scholars and government has led to laws and regulations issued more densely to strengthen TCM knowledge protection and promote fair use and fast development.