Machine Learning-Assisted Automatically Electrochemical Addressable Cytosensing Arrays for Anticancer Drug Screening.

The high-throughput and accurate screening of anticancer drugs is crucial to the preclinical assessment of candidate drugs and remains challenging. Herein, an automatically electrochemical addressable cytosensor (AEAC) for the efficient screening of anticancer drugs is reported. This sensor consists of sectionalized laser-induced graphene arrays decorated by the rhombohedral TiO2 and spherical Pt nanoparticles (LIG-TiO2-Pt) with high electrocatalytic activity for H2O2 and a homemade Ag/Pt electrode couple fixed onto the robot arm. The immobilization of laminin on the surface of LIG-TiO2-Pt can promote its biocompatibility for the growth and proliferation of various tumor cells, which empowers the in situ monitoring of H2O2 directly released from these live cells for drug screening. A machine learning (ML) algorithm is employed to eliminate the possible random or systematic errors of AEAC, realizing rapid, high-throughput, and accurate prediction of different types of anticancer drugs. This ML-assisted AEAC provides a powerful approach to accelerate the evolution of sensing-served tumor therapy.

Graphene/metal-organic framework nano-sandwiches derived N, P-codoped porous carbon nanosheets as robust material for electrochemical analysis.

Construction of novel two-dimensional porous carbon nanosheets with superior electrochemical activity is of great challenge. Here, graphene/ZIF-8 nano-sandwiches derived N, P-codoped porous carbon nanosheets (N, P-codoped PCN) was easily obtained by sequential room temperature self-assembly and high-temperature carbonization method. Relative to the widely used physically exfoliated graphene nanosheets (GN) and graphene/ZIF-8 derived N-doped porous carbon nanosheets (N-doped PCN), N, P-codoped PCN displayed larger active surface, faster electron transport ability and stronger physical adsorption ability, which can be ascribed to the dual doping effect of heteroatoms N and P. As a result, N, P-codoped PCN exhibited remarkable oxidation signal enhancement for tumor marker (8-hydroxy-2'-deoxyguanosine), analgesic and antipyretic drug (acetaminophen) and organic pesticide (benomyl). Besides, the limits of detection were measured as low as 1.58 nM, 7.50 nM and 2.10 nM with sensitivity of 270.00 µA µM-1 cm-2, 757.14 µA µM-1 cm-2 and 272.86 µA µM-1 cm-2 for 8-hydroxy-2'-deoxyguanosine, acetaminophen and benomyl, respectively. Basing on this, a novel and highly sensitive electrochemical sensing platform was developed. It is believed that the reported two-dimensional N, P-codoped PCN with unique structure and composition is highly valuable for the development of carbon-based electrochemical sensors.