P-glycoprotein (P-gp), a membrane-bound transporter, can eliminate xenobiotics by transporting them out of the cells or blood-brain barrier (BBB) at the expense of ATP hydrolysis. Thus, P-gp mediated efflux plays a pivotal role in altering the absorption and disposition of a wide range of substrates. Nevertheless, the mechanism of P-gp substrate efflux is rather complex since it can take place through active transport and passive permeability in addition to multiple P-gp substrate binding sites. A nonlinear quantitative structure-activity relationship (QSAR) model was developed in this study using the novel machine learning-based hierarchical support vector regression (HSVR) scheme to explore the perplexing relationships between descriptors and efflux ratio. The predictions by HSVR were found to be in good agreement with the observed values for the molecules in the training set (n = 50, r² = 0.96, q²_CV = 0.94, RMSE = 0.10, s = 0.10) and test set (n = 13, q² = 0.80–0.87, RMSE = 0.21, s = 0.22). When subjected to a variety of statistical validations, the developed HSVR model consistently met the most stringent criteria. A mock test also asserted the predictivity of HSVR. Consequently, this HSVR model can be adopted to facilitate drug discovery and development.

An outbreak of novel coronavirus(2019-nCoV) that began in Wuhan, China, is rapidly spreading to all over China, and gradually to multiple countries. Regarding to put the epidemic prevention and spread under the control, early identification and diagnosis play a critical role. Patients with initially no or mild symptoms of Novel Coronavirus Pneumonia (2019-nCoV), namely “stealth” infection, often lack of typical clinical evidence to establish the diagnosis. Based on the clinical analysis of 4 cases in stealth infection, the results of this study highlight that early diagnosis requires a combination of epidemiological history, clinical manifestations, early chest CT examination, and 2019-nCoV RNA test (nucleic acid test), with particular emphasis on definite epidemiological history and early chest CT findings when positive nucleic acid tests lag behind.

Fast-scan cyclic voltammetry (FSCV) is an electrochemical sensing technique that can be used for neurochemical sensing with high spatiotemporal resolution. Carbon fiber microelectrodes (CFMEs) are traditionally used as FSCV sensors. However, CFMEs are prone to electrochemical fouling caused by oxidative byproducts of repeated serotonin (5-HT) exposure, which makes them less suitable as a chronic 5-HT sensor. Our team is developing a boron-doped diamond microelectrode (BDDME) that has previously been shown to be relatively resistant to fouling caused by protein adsorption (biofouling). We sought to determine if the BDDME exhibits resistance to electrochemical fouling, which we explored on electrodes fabricated with either femtosecond laser cutting or physical cleaving. We recorded the oxidation current response after 25 repeated injections of 5-HT in a flow-injection-cell and compared the current drop from the first to the last injection. The 5-HT responses were compared to dopamine (DA), a neurochemical that is known to produce minimal fouling oxidative byproducts and have a stable repeated response. Physical cleaving of the BDDME yielded a reduction in fouling due to 5-HT compared to the CFME and the femtosecond laser cut BDDME. However, the femtosecond laser cut BDDME exhibited a large increase in sensitivity over the cleaved BDDME. An extended stability analysis was conducted for all device types following 5-HT fouling tests. This analysis demonstrated an improvement in the long-term stability of boron doped diamond over CFMEs, as well as a diminishing sensitivity of the laser cut BDDME over time. This work reports the electrochemical fouling performance of the BDDME when it is repeatedly exposed to DA or 5-HT, which informs the development of a chronic, diamond-based electrochemical sensor for long-term neurotransmitter measurements in vivo.