PED: a novel predictor-encoder-decoder model for Alzheimer drug molecular generation.

Alzheimer's disease (AD) is a gradually advancing neurodegenerative disorder characterized by a concealed onset. Acetylcholinesterase (AChE) is an efficient hydrolase that catalyzes the hydrolysis of acetylcholine (ACh), which regulates the concentration of ACh at synapses and then terminates ACh-mediated neurotransmission. There are inhibitors to inhibit the activity of AChE currently, but its side effects are inevitable.

Nonasymptotic Fractional Derivative Estimation of the Pseudo-State for a Class of Fractional-Order Partial Unknown Nonlinear Systems.

This work is devoted to the nonasymptotic and robust fractional derivative estimation of the pseudo-state for a class of fractional-order nonlinear systems with partial unknown terms in noisy environments. In particular, the estimation for the pseudo-state can be obtained by setting the fractional derivative's order to zero. For this purpose, the fractional derivative estimation of the pseudo-state is achieved by estimating both the initial values and the fractional derivatives of the output, thanks to the additive index law of fractional derivatives.

Common salts directed the growth of metal-free horizontal SWNT arrays.

Acquiring metal-free horizontal single-walled carbon nanotube (SWNT) arrays is of paramount importance for the development of stable nanodevices. However, the majority of SWNTs are prepared with transition metal-based catalysts, which will inevitably leave metallic residuals and deteriorate the device performance. Here, green and low-cost NaCl is developed as a metal-free catalyst.

An innovative modulating functions method for pseudo-state estimation of fractional order systems.

In this paper, the objective is to estimate the pseudo-state of fractional order systems defined by the Caputo fractional derivative from discrete noisy output measurement. For this purpose, an innovative modulating functions method is proposed, which can provide non-asymptotic estimation within finite-time and is robust against corrupting noises. First, the proposed method is directly applied to the Brunovsky's observable canonical form of the considered system.

En Route to High-Density Chiral Single-walled Carbon Nanotube Arrays using Solid Trojan Catalysts.

Solid catalyst is widely recognized as an effective strategy to control the chirality of single-walled carbon nanotubes (SWNTs). However, it is still not compatible with high density in horizontal arrays. "Trojan" catalysts strategy is one of the most effective methods to realize SWNTs with high density and has great potential in chirality control.

IL-23 Inhibits Trophoblast Proliferation, Migration, and EMT via Activating p38 MAPK Signaling Pathway to Promote Recurrent Spontaneous Abortion.

As a vital problem in reproductive health, recurrent spontaneous abortion (RSA) affects about 1% of women. We performed this study with an aim to explore the molecular mechanism of interleukin-23 (IL-23) and find optimal or effective methods to improve RSA. First, ELISA was applied to evaluate the expressions of IL-23 and its receptor in HTR-8/SVneo cells after IL-23 treatment.

CSConv2d: A 2-D Structural Convolution Neural Network with a Channel and Spatial Attention Mechanism for Protein-Ligand Binding Affinity Prediction.

The binding affinity of small molecules to receptor proteins is essential to drug discovery and drug repositioning. Chemical methods are often time-consuming and costly, and models for calculating the binding affinity are imperative. In this study, we propose a novel deep learning method, namely CSConv2d, for protein-ligand interactions' prediction.

SE-OnionNet: A Convolution Neural Network for Protein-Ligand Binding Affinity Prediction.

Deep learning methods, which can predict the binding affinity of a drug-target protein interaction, reduce the time and cost of drug discovery. In this study, we propose a novel deep convolutional neural network called SE-OnionNet, with two squeeze-and-excitation (SE) modules, to computationally predict the binding affinity of a protein-ligand complex. The OnionNet is used to extract a feature map from the three-dimensional structure of a protein-drug molecular complex.

DL-SMILES#: A Novel Encoding Scheme for Predicting Compound Protein Affinity Using Deep Learning.

Introduction: Drug repositioning aims to screen drugs and therapeutic goals from approved drugs and abandoned compounds that have been identified as safe. This trend is changing the landscape of drug development and creating a model of drug repositioning for new drug development. In the recent decade, machine learning methods have been applied to predict the binding affinity of compound proteins, while deep learning is recently becoming prominent and achieving significant performances.

Predicting Drug-Target Affinity Based on Recurrent Neural Networks and Graph Convolutional Neural Networks.

Background: Drug development requires a lot of money and time, and the outcome of the challenge is unknown. So, there is an urgent need for researchers to find a new approach that can reduce costs. Therefore, the identification of drug-target interactions (DTIs) has been a critical step in the early stages of drug discovery.

Normal-pulse-voltage-assisted in situ fabrication of graphene-wrapped MOF-derived CuO nanoflowers for water oxidation.

Chemical vapor deposition (CVD) and normal pulse voltage (NPV) are adopted to construct high-quality graphene-wrapped CuO nanoflowers grown in situ on copper foam (CuO NP@G/CF) as an efficient oxygen evolution reaction (OER) electrocatalyst. The CuO NF@G/CF electrode exhibits a small overpotential of 320 mV to drive a current density of 10 mA cm with a low Tafel slope of 63.1 mV dec.

Methylation-Induced Reversible Metallic-Semiconducting Transition of Single-Walled Carbon Nanotube Arrays for High-Performance Field-Effect Transistors.

Acquirement of aligned semiconducting single-walled carbon nanotube (s-SWNT) arrays is one of the most promising directions to break Moore's Law, thus developing the next-generation electronic devices. Despite that widespread approaches have been developed, it is still a great challenge to facilely prepare s-SWNT arrays with tunable electronic properties. Herein, a different perspective is proposed to produce s-SWNT arrays by implementing reversible methylation reactions on the as-grown aligned SWNT arrays.

Observer design for a class of nonlinear piecewise systems. Application to an epidemic model with treatment.

Susceptible Exposed Infectious and Recovered epidemic model endowed with a treatment function (SEIR-T model) is a well-known model used to reproduce the behavior of an epidemic, where the susceptible population and the exposed population need to be estimated to predict and control the propagation of a contagious disease. This paper focuses on the nonlinear observer design for a class of nonlinear piecewise systems including SEIR-T models. For this purpose, two changes of coordinates are provided to transform the considered systems into an extended nonlinear observer normal form, on which a high gain observer can be applied.

Receptivity assessment of an ultrasonographic homogeneous endometrium in the late follicular phase of infertile women with natural cycles.

Objective: The purpose of this study was to assess the receptivity of the homogeneous endometrium in the late follicular phase in infertile women with natural cycles.

Study Design: Twenty-eight infertile women with ultrasonographically homogeneous (group 1) or trilaminar (group 2) endometria in the late follicular phase underwent endometrial biopsies. Some molecular markers and development of pinopodes were evaluated.

[Metabolic footprint in conditioned culture medium of placental explants: a comparison between early-onset and late-onset severe preeclampsia].

Objective: To explore the differences of metabolic footprint in the conditioned culture medium of placental explants between early-onset and late-onset severe preeclampsia.

Methods: In 13 cases of early-onset severe preeclampsia and 14 cases of late-onset severe preeclampsia, the placentas were sampled at the surface of the maternal placenta. High performance liquid chromatography-mass spectrometry (HPLC-MS) was used to determine the differences in the metabolites in the conditioned culture medium of the placental villous explants cultured in 6% atmospheric O(2) for 96 h.

Ursodeoxycholic acid in the treatment of intraheptic cholestasis of pregnancy.

In order to observe the effect of ursodeoxycholic acid (UDCA) in the treatment of intrahepatic cholestasis of pregnancy (ICP), 68 patients with ICP were equally divided into treatment group and control group at random. The patients in treatment group were administered with UDCA 300 mg three times every day and those in control group received a combination of 10% glucose, Vitamin C and Inosine. Itching scores, serum ALT and total bile acids (TBA) were measured before, during and after treatment.