Facilely Prepared Cl-Doped Graphene as an Efficient Anode for the Electrochemical Catalytic Degradation of Acetaminophen

The application of electrochemical catalytic oxidation in wastewater treatment with powerful Cldoped graphene as an anode has been discussed as a novel approach to degrade acetaminophen effectively. The characteristics of Cl-doped graphene that were related to Cl loading content and microscopic morphology were analyzed by using several instruments, and the defects created by Cl doping were identified. Quenching experiments and electron paramagnetic resonance detection were proposed to clarify the mechanism underlying the production of active free radicals by Cldopedgraphene. The degradation results indicated that efficiency increased with the percentage of Cl atoms doped into the graphene. The best degradation efficiency of acetaminophen could reach 98% when Cl-GN-12 was used. In the process of electrocatalytic oxidation, O•−2, and active chlorine, as the main active species, persistently attacked acetaminophen into open-ring intermediates, such as 4-chlororesorcinol, and finally into CO2 and H2O.

Discovery of a Novel MyD88 Inhibitor M20 and Its Protection Against Sepsis-Mediated Acute Lung Injury

Myeloid differentiation factor 88 (MyD88) is a hub protein in the Toll-like receptor signaling pathway, which acts as a master switch for numerous inflammatory diseases, including acute lung injury (ALI). Although this protein is considered as a crucial therapeutic target, there are currently no clinically approved MyD88-targeting drugs. Based on previous literature, here we report the discovery via computer-aided drug design (CADD) of a small molecule, M20, which functions as a novel MyD88 inhibitor to efficiently relieve lipopolysaccharide-induced inflammation both in vitro and in vivo. Computational chemistry, surface plasmon resonance detection (SPR) and biological experiments demonstrated that M20 forms an important interaction with the MyD88-Toll/interleukin-1 receptor domain and thereby inhibits the protein dimerization. Taken together, this study found a MyD88 inhibitor, M20, with a novel skeleton, which provides a crucial understanding in the development and modification of MyD88 inhibitors. Meanwhile, the favorable bioactivity of the hit compound is also conducive to the treatment of acute lung injury or other more inflammatory diseases.

Fully Automated Magnetic Resonance Detection and Segmentation of Brain using Convolutional Neural Network

The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition score, contours are merged and classified again to check the change in the recognition score. The features for classification are extracted from small fixed-size patches over neighboring contours and matched against the trained deep learning representations this approach enables Tesseract to easily handle MRI sample results broken into multiple parts, which is impossible if each contour is processed separately Hard to read! Try to split sentences. The CNN inception network seem to be a suitable choice for the evaluation of the synthetic MRI samples with 3000 features, and 12000 samples of images as data augmentation capacities favors data which is similar to the original training set and thus unlikely to contain new information content with an accuracy of 98.68%. The error is only 1.32% with the increasing the number of training samples, but the most significant impact in reducing the error can be made by increasing the number of samples.