Development of MIF/IL-1 beta biosensors for discovery of critical quality attributes and potential allergic rhinitis targets from clinical real-world data by intelligent algorithm coupled with
Author(s): Ma, LJ (Ma, Lijuan); Zheng, YF (Zheng, Yanfei); Wang, J (Wang, Ji); Li, QQ (Li, Qianqian); Zeng, JQ (Zeng, Jingqi); Wang, ZJ (Wang, Zijian); Hou, TJ (Hou, Tingjun); Zhang, Y (Zhang, Yang); Li, MS (Li, Mingshuang); Shen, RM (Shen, Rongmin); Chen, XM (Chen, Xuemei); Qin, JB (Qin, Jingbo); Lei, LT (Lei, Leting); Xia, Q (Xia, Qing); Wang, Q (Wang, Qi); Qiao, YJ (Qiao, Yanjiang); Wu, ZS (Wu, Zhisheng)
Source: BIOSENSORS & BIOELECTRONICS Volume: 194 Article Number: 113608 DOI: 10.1016/j.bios.2021.113608 Published: DEC 15 2021
Abstract: There are still huge challenges from clinical real-world data to accurate targets and critical quality attributes (CQAs) for effective treatment of allergic rhinitis (AR). Here, we present a novel integrated strategy that biosensors and intelligent algorithms were used to angle AR targets and CQAs from clinical real world. Firstly, bagging and boosting partial least squares discrimination analysis (PLS-DA) and Monte-Carlo sampling were proposed to screen accurate AR targets. Macrophage migration inhibitory factor (MIF) and Interleukin-1beta (IL1 beta) potential targets were obtained based on large-scale analysis of one thousand proteins and in-depth precise screening of seventy proteins. Furthermore, high electron mobility transistor (HEMT) biosensors were fabricated and successfully modified by MIF and IL-1 beta potential targets with a low detection concentration as 1 pM and quantitative range from 1 pM to 10 nM. Surprisingly, through MIF/IL-1 beta biosensors, we angled 5-O-methylvisammioside, amygdalin, and cimicifugoside three CQAs. The strong interaction was discovered among three CQAs and MIF/IL-1 beta biosensors with almost all KD up to 10 11 M. Finally, interaction among three CQAs and MIF/IL-1 beta biosensors were evaluated by in vitro and vivo experiments. In this paper, two critical potential targets and three effective CQAs for AR treatment were discovered and validated by biosensor and advanced algorithms. It provides a superior integrated idea for angling critical targets and CQAs from clinical real-world data by biosensors and informatics.
Accession Number: WOS:000697620500004
PubMed ID: 34500224
ISSN: 0956-5663
eISSN: 1873-4235
Full Text: https://www.sciencedirect.com/science/article/pii/S095656632100645X?via%3Dihub
