![Sample our Bioscience journals, sign in here to start your access, Latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5925/TOC-Subject-Sample-2021-Bioscience.jpg"})
Abstract
As a traditional Chinese medicine, strychnos alkaloids have wide effects including antitumor, analgesic, and anti-inflammatory. However, the therapeutic window of strychnos alkaloids is quite narrow due to potential neurotoxicity. Therefore, it is necessary to explore some efficient biomarkers to identify and predict the neurotoxicity induced by strychnos alkaloids and find a therapy to prevent the neurotoxicity of strychnos alkaloids. Based on the previous studies of our research team, 21 endogenous substances related to neurotoxicity were monitored in rats’ serum with HPLC-MS/MS and ELISA. Starting from these fundamentals, a Lasso-Logistic regression model was used to select efficient biomarkers from 21 endogenous substances to predict brain injury and verify the neuroprotective effect of peonies. Under the processing of the Lasso-Logistic regression model, 12 biomarkers were identified from 21 endogenous substances to predict the neurotoxicity induced by strychnos alkaloids. At the same time, the neuroprotective effect of peonies was further confirmed by evaluating the level of 12 biomarkers. The results indicated that the development of the Lasso-Logistic regression model would provide a new, simple and efficient method for the prediction and diagnosis of the neurotoxicity induced by strychnos alkaloids.
Disclosure statement
No potential conflict of interest was reported by the author(s).