2-Phenyloxazole-4-carboxamide as a Scaffold for Selective Inhibition of Human Monoamine Oxidase B

A series of 2-phenyloxazoles bearing an amide group at position 4 were designed and synthesized for evaluation as potential inhibitors of human recombinant monoamine oxidases (hrMAOs). Results of kinetics experiments demonstrated that all compounds behave as competitive MAO inhibitors, with good selectivity toward the MAO-B isoform. The most potent and selective derivatives are characterized by inhibition constant (K_i) values in the sub-micromolar range and a good selectivity index (K_{i MAO-A}/K_{i MAO-B}>50). Some derivatives were also found to be able to inhibit MAO activity in nerve growth factor (NGF)-differentiated PC12 cells, taken as a model of neuronal cells. In particular, 2-(2-hydroxyphenyl)-N-phenyloxazole-4-carboxamide (compound 4 a ) may be a promising new scaffold, exerting the highest selectivity and inhibitory effect toward MAOs in NGF-differentiated PC12 cell lysates, without compromising cell viability. Molecular docking analysis allowed a rationalization of the experimentally observed binding affinity and selectivity.     

Deep Learning Based Process Analytics Model for Predicting Type 2 Diabetes Mellitus

Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it becomes inevitable to predict the risks of CKD and CHD in T2DM patients. The current research article presents automated Deep Learning (DL)-based Deep Neural Network (DNN) with Adagrad Optimization Algorithm i.e., DNN-AGOA model to predict CKD and CHD risks in T2DM patients. The paper proposes a risk prediction model for T2DM patients who may develop CKD or CHD. This model helps in alarming both T2DM patients and clinicians in advance. At first, the proposed DNN-AGOA model performs data preprocessing to improve the quality of data and make it compatible for further processing. Besides, a Deep Neural Network (DNN) is employed for feature extraction, after which sigmoid function is used for classification. Further, Adagrad optimizer is applied to improve the performance of DNN model. For experimental validation, benchmark medical datasets were used and the results were validated under several dimensions. The proposed model achieved a maximum precision of 93.99%, recall of 94.63%, specificity of 73.34%, accuracy of 92.58%, and F-score of 94.22%. The results attained through experimentation established that the proposed DNN-AGOA model has good prediction capability over other methods.     

Hydrogen production from thermal decomposition of ammonia-contaminated acid gas using a detailed reaction mechanism

The increase in the production of acid gas consisting of H₂S, CO₂, and associated impurities such as ammonia and hydrocarbons from oil and gas plants and gasification facilities has stimulated the interest in the development of alternative means of acid gas utilization to produce hydrogen and sulfur, simultaneously. The present literature lacks a detailed reaction mechanism that can reliably predict the thermal destruction of NH₃ and its blend with H₂S and CO₂ to facilitate process optimization and commercialization. In this paper, a detailed mechanism of NH₃ pyrolysis is developed and is merged with the reactions of NH₃ oxidation and H₂S/CO₂ thermal decomposition from our previous works. The mechanism is validated successfully using different sets of experimental data on the pyrolysis and oxidation of NH₃, H₂S, and CO₂. The proposed mechanism predicts the experimental data on NH₃ pyrolysis remarkably better than the existing mechanisms in the literature. The mechanism is used to investigate the effects of NH₃ concentration (0–20%) and reactor temperature (1000–1800 K) on the thermal decomposition of H₂S and CO₂. A synergistic effect is observed in the simultaneous decomposition of NH₃ and CO₂, i.e., NH₃ conversion is improved in the presence of CO₂ and the decomposition CO₂ to CO is enhanced in the presence of NH₃. The presence of H₂S suppressed NH₃ conversion, while the conversion of H₂S remained unchanged with increasing NH₃ concentration at temperature below 1400 K due to the low conversion of NH₃ (up to 18%). At temperature above 1400 K, NH₃ conversion increased rapidly and it triggered a decrease in H₂S conversion as well as the yields of H₂ and S₂. The major reactions involved in the decomposition of H₂S, CO₂, and NH₃ and the production of major products such as H₂, S₂, and CO are identified. The detailed reaction mechanism can facilitate the design and optimization of acid gas thermal decomposition to produce hydrogen and sulfur, simultaneously.     

建筑用钎焊合金的热腐蚀行为研究

研究了建筑用钎焊合金BCo46、DZ468和BNi-2在热腐蚀条件下的腐蚀行为。结果表明,在热腐蚀条件下,合金BCo46的抗腐蚀能力强于合金DZ468和BNi-2。3种合金在热腐蚀环境中都出现了硫化物析出和氧化薄膜溶解现象。     

致密油藏注天然气提高采收率研究现状

随着我国石油需求量不断增加,致密油藏的开发也愈发重要。如何高效开发致密油藏是一项重点难点,其中致密油藏注天然气提高采收率是一个极具潜力的研究方向。因此,本文着重介绍以天然气作为能量补充介质在国内外的研究现状和应用现状,并且从两相特征等方面总结了理论研究中的一些机理,对致密油藏注天然气提高采收率的发展前景进行了一定的展望。     

Fabrication of core–shell nanocomposites with enhanced photocatalytic efficacy

The current study establishes the unprecedented involvement in the evolution and production of novel core–shell nanocomposites composed of nanosized titanium dioxide and aniline‐o‐phenylenediamine copolymer. TiO₂@copoly(aniline and o‐phenylenediamine) (TiO₂@PANI‐o‐PDA) core–shell nanocomposites were chemically synthesized in a molar ratio of 5:1 of the particular monomers and several weights of nano‐TiO₂ via oxidative copolymerization. The construction of the TiO₂@PANI‐o‐PDA core–shell nanocomposites was ascertained from Fourier transform IR spectroscopy, UV–visible spectroscopy and XRD. A reasonable thermal behavior for the original copolymer and the TiO₂@PANI‐o‐PDA core–shell nanocomposites was investigated. The bare PANI‐o‐PDA copolymer was thermally less stable than the TiO₂@PANI‐o‐PDA nanocomposites. The core–shell feature of the nanocomposites was found to have core and shell sizes of 17 nm and 19–26 nm, respectively. In addition, it was found that the addition of a high ratio of TiO₂ nanoparticles increases the electrical conductivity and consequently lowers the electrical resistivity of the TiO₂@PANI‐o‐PDA core–shell nanocomposites. The hybrid photocatalysts exhibit a dramatic photocatalytic efficacy of methylene blue degradation under solar light irradiation. A plausible interpretation of the photocatalytic degradation results of methylene blue is also demonstrated. Our setup introduces a facile, inexpensive, unique and efficient technique for developing new core–shell nanomaterials with various required functionalities and colloidal stabilities. © 2018 Society of Chemical Industry     

Dihydrotanshinone,a Natural Diterpenoid,Preserves Blood-Retinal Barrier Integrity via P2X7 Receptor

Activation of P2X7 signaling, due to high glucose levels, leads to blood retinal barrier (BRB) breakdown, which is a hallmark of diabetic retinopathy (DR). Furthermore, several studies report that high glucose (HG) conditions and the related activation of the P2X7 receptor (P2X7R) lead to the over-expression of pro-inflammatory markers. In order to identify novel P2X7R antagonists, we carried out virtual screening on a focused compound dataset, including indole derivatives and natural compounds such as caffeic acid phenethyl ester derivatives, flavonoids, and diterpenoids. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) rescoring and structural fingerprint clustering of docking poses from virtual screening highlighted that the diterpenoid dihydrotanshinone (DHTS) clustered with the well-known P2X7R antagonist JNJ47965567. A human-based in vitro BRB model made of retinal pericytes, astrocytes, and endothelial cells was used to assess the potential protective effect of DHTS against HG and 2′(3′)-O-(4-Benzoylbenzoyl)adenosine-5′-triphosphate (BzATP), a P2X7R agonist, insult. We found that HG/BzATP exposure generated BRB breakdown by enhancing barrier permeability (trans-endothelial electrical resistance (TEER)) and reducing the levels of ZO-1 and VE-cadherin junction proteins as well as of the Cx-43 mRNA expression levels. Furthermore, HG levels and P2X7R agonist treatment led to increased expression of pro-inflammatory mediators (TLR-4, IL-1β, IL-6, TNF-α, and IL-8) and other molecular markers (P2X7R, VEGF-A, and ICAM-1), along with enhanced production of reactive oxygen species. Treatment with DHTS preserved the BRB integrity from HG/BzATP damage. The protective effects of DHTS were also compared to the validated P2X7R antagonist, JNJ47965567. In conclusion, we provided new findings pointing out the therapeutic potential of DHTS, which is an inhibitor of P2X7R, in terms of preventing and/or counteracting the BRB dysfunctions elicited by HG conditions.     

Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

Occurrence and distribution of dibenzofurans and benzo[b]naphthofurans in the crude oils from the Northern and offshore Niger Delta basin,Nigeria

The occurrence and distributions of dibenzofurans (DBFs) and benzo[b]naphthofurans were investigated in crude oils from Niger Delta, Nigeria, by gas chromatography-mass spectrometry-mass spectrometry. The distribution of DBFs was characterized by the predominance of C₂-dibenzofurans. 4-Methyldibenzofuran was the most abundant among the methyldibenzofurans isomers while dimethyldibenzofuran-2 (DMDBF-2), ethyldibenzofuran-1, DMDBF-3, and DMDBF-6 occurred in higher amounts when compared with other DMDBFs. Among the benzonaphthofurans, the abundance of benzo[b]naphtho[2,1-d]furan was higher than other isomers. The DBFs distributions in the oils were not affected by source facies and depositional environments. However, the DBFs concentrations increased with increasing maturity in oils from ADL and MJO oilfields.     

Amine-containing olefin copolymer with CO2-switchable oil absorption and desorption

Global decrease in crude oil resources and frequent crude oil leaks cause the energy crisis and ecological pollution. The absorption and release of leaked crude oil through absorption materials are a necessary process for environmental protection and recycling. In this article, a CO₂-responsive olefin copolymer was obtained by copolymerization of styrene and an amine-containing olefin monomer. The structure of resultant copolymer was characterized by FTIR; thermal properties and CO₂-responsive morphology changes were determined by DSC/TGA and SEM, respectively. Copolymers had certain absorption capacity for toluene with absorption rate up to 180.0%. The absorbed toluene could be released upon CO₂ stimulation with desorption rate up to 84.6%. The CO₂-responsive copolymer could be regenerated through a simple heating process and showed stable absorption–desorption performance even after being recycled for 4 times. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47439.