Multifunctional Hydrophobized Microparticles for Accelerated Wound Healing after Endoscopic Submucosal Dissection

Endoscopic submucosal dissection (ESD) provides strong therapeutic benefits for early gastrointestinal cancer as a minimally invasive treatment. However, there is currently no reliable treatment to prevent scar contracture resulting from ESD which may lead to cicatricial stricture. Herein, a multifunctional colloidal wound dressing to promote tissue regeneration after ESD is demonstrated. This sprayable wound dressing, composed of hydrophobized microparticles, exhibits the multifunctionality necessary for wound healing including tissue adhesiveness, blood coagulation, re‐epithelialization, angiogenesis, and controlled inflammation based on hydrophobic interaction with biological systems. An in vivo feasibility study using swine gastric ESD models reveals that this colloidal wound dressing suppresses fibrosis and accelerates wound healing. Multifunctional colloidal and sprayable wound dressings have an enormous therapeutic potential for use in a wide range of biomedical applications including accelerated wound healing after ESD, prevention of perforation, and the treatment of inflammatory diseases.     

思维导图在《微机原理及接口技术》教学中的应用

思维导图作为一种可视化图形思维工具，可以有效表征知识体系、层次关系。本文针对《微机原理及接口技术》课程教学现状，介绍了思维导图的特点，分析了思维导图应用于该课程教学中的作用和意义，给出了用 MindManager软件绘制的8086CPU内部结构和输入输出接口的思维导图案例。教学实践证明，思维导图在《微机原理及接口技术》课程教学中可以激发学生学习兴趣，帮助学生建立“整体-局部”思想，促进学生对知识的理解和记忆，提升教学效果。     

Pseudouridine synthase 7 impacts Candida albicans rRNA processing and morphological plasticity

RNA can be modified in over 100 distinct ways, and these modifications are critical for function. Pseudouridine synthases catalyse pseudouridylation, one of the most prevalent RNA modifications. Pseudouridine synthase 7 modifies a variety of substrates in Saccharomyces cerevisiae including tRNA, rRNA, snRNA, and mRNA, but the substrates for other budding yeast Pus7 homologues are not known. We used CRISPR-mediated genome editing to disrupt Candida albicans PUS7 and find absence leads to defects in rRNA processing and a decrease in cell surface hydrophobicity. Furthermore, C. albicans Pus7 absence causes temperature sensitivity, defects in filamentation, altered sensitivity to antifungal drugs, and decreased virulence in a wax moth model. In addition, we find C. albicans Pus7 modifies tRNA residues, but does not modify a number of other S. cerevisiae Pus7 substrates. Our data suggests C. albicans Pus7 is important for fungal vigour and may play distinct biological roles than those ascribed to S. cerevisiae Pus7.     

Ordinary Gasoline Emissions Induce a Toxic Response in Bronchial Cells Grown at Air-Liquid Interface

Gasoline engine emissions have been classified as possibly carcinogenic to humans and represent a significant health risk. In this study, we used MucilAir™, a three-dimensional (3D) model of the human airway, and BEAS-2B, cells originating from the human bronchial epithelium, grown at the air-liquid interface to assess the toxicity of ordinary gasoline exhaust produced by a direct injection spark ignition engine. The transepithelial electrical resistance (TEER), production of mucin, and lactate dehydrogenase (LDH) and adenylate kinase (AK) activities were analyzed after one day and five days of exposure. The induction of double-stranded DNA breaks was measured by the detection of histone H2AX phosphorylation. Next-generation sequencing was used to analyze the modulation of expression of the relevant 370 genes. The exposure to gasoline emissions affected the integrity, as well as LDH and AK leakage in the 3D model, particularly after longer exposure periods. Mucin production was mostly decreased with the exception of longer BEAS-2B treatment, for which a significant increase was detected. DNA damage was detected after five days of exposure in the 3D model, but not in BEAS-2B cells. The expression of CYP1A1 and GSTA3 was modulated in MucilAir™ tissues after 5 days of treatment. In BEAS-2B cells, the expression of 39 mRNAs was affected after short exposure, most of them were upregulated. The five days of exposure modulated the expression of 11 genes in this cell line. In conclusion, the ordinary gasoline emissions induced a toxic response in MucilAir™. In BEAS-2B cells, the biological response was less pronounced, mostly limited to gene expression changes.     

Role of interface on irradiation damage of Cu−diamond composites using classical molecular dynamics simulations

Cu?diamond composites have been proposed as a candidate thermal management material for spacecraft electronics. Nevertheless, irradiation effects on the composites remain poorly understood at present. Here we focus on investigating the influence of Cu?diamond interfaces (CDIs) on energetic displacement cascades using atomistic simulations. Results show that a primary knock-on atom of Cu (PKA-Cu) can induce more significant damage than a PKA-C. Under almost all circumstances, the statistically averaged fraction of surviving interstitials is not only lower than that of vacancies but also no more than 1. Because of the unique nature in the mobility and interactions with CDIs, Cu interstitials exhibit the lowest concentration among all defects in most cases. The high residual rate of displaced defects in diamond makes it relatively difficult to heal. The structural damage is mainly manifested in a short-range disorder of diamond and a long-range disorder of Cu after irradiation. At elevated temperatures, the atomic displacement region may form compact chain-like defects to restrain lattice loosening. Despite the above, CDIs could act as effective sinks to facilitate the recombination and/or annihilation of irradiation-induced defects in all scenarios. This study provides an important insight into the understanding of the microscopic evolution of irradiation defects for the composites.     

Employing one-step coupling cold plasma and thermal polymerization approach to construct nitrogen defect-rich carbon nitrides toward efficient visible-light-driven hydrogen generation

Construction of structural defects in photocatalysts is a powerful tool for regulating their photocatalytic performance. In this work, we develop a facile one-step coupling cold plasma and thermal polymerization approach to synthesize a series of nitrogen defect-rich graphitic carbon nitrides (C₃N_4-x), which are used for visible-light-driven hydrogen generation from water. The nitrogen defect-induced band structure regulation of C₃N_4-x catalysts can be carried out through controlling the bombardment time and excitation power of generator during the plasma modification process. The defective C₃N_4-x catalysts have the extended visible light absorption and improved separation efficiency of photogenerated charge carriers, which results in the boosted hydrogen generation activity. Particularly, the optimal C₃N_4-x possesses a hydrogen generation rate of 2.46 mmol h^?1 g^?1, which is about 4.5 times higher than the pristine C₃N₄ synthesized by the single thermal polymerization of urea. The cold plasma modification-based one-step synthesis approach guides us for rationally designing defective nanomaterials with excellent catalytic performance.     

Sn-induced CuO–CeO2 catalysts with improved performance for CO preferential oxidation in H2-rich streams

Sn modified CuO–CeO₂ catalysts with different Sn loadings were prepared by a facile, green and solvent-free method. The effect of Sn/Ce ratio over Sn–Cu–Ce-x (x = 0, 1, 2.5, 5, 7.5) samples on CO activity and O₂ selectivity was investigated. The samples were characterized by various techniques using N₂-adsorption/desorption, XRD, H₂-TPR, XPS, Raman and in-situ DRIFTS. It was revealed that stronger interaction between acitve sites and support, higher amounts of Sn²⁺ and Ce³⁺, associated with increased amount of oxygen vacancies, were observed on the catalyst of Sn–Cu–Ce-5. As a result, the optimized catalyst displayed an excellent catalytic performance even in the presence of CO₂ and H₂O. In this sense, probing the Sn modified CuO–CeO₂ catalyst can elucidate some useful keys for the development of high CO₂ and H₂O-resistance catalyst during CO-preferential oxidation in H₂-rich streams.     

A review on modeling of solar photovoltaic systems using artificial neural networks,fuzzy logic,genetic algorithm and hybrid models

The uncertainty associated with modeling and performance prediction of solar photovoltaic systems could be easily and efficiently solved by artificial intelligence techniques. During the past decade of 2009 to 2019, artificial neural network (ANN), fuzzy logic (FL), genetic algorithm (GA) and their hybrid models are found potential artificial intelligence tools for performance prediction and modeling of solar photovoltaic systems. In addition, during this decade there is no extensive review on applicability of ANN, FL, GA and their hybrid models for performance prediction and modeling of solar photovoltaic systems. Therefore, this article focuses on extensive review on design, modeling, maximum power point tracking, fault detection and output power/efficiency prediction of solar photovoltaic systems using artificial intelligence techniques of the ANN, FL, GA and their hybrid models. In addition, the selected articles on the solar radiation prediction using ANN, FL, GA and their hybrid models are also summarized. Total of 122 articles are reviewed and summarized in the present review for the period of 2009 to 2019 with 90 articles in the field of {ANN, FL, GA and their hybrid models} + solar photovoltaic systems and 32 articles in the field of {ANN, FL, GA and their hybrid models} + solar radiation. The review shows the suitability and reliability of ANN, FL, GA and hybrid models for accurate prediction of the solar radiation and the performance characteristics of solar photovoltaic systems. In addition, this review presents the guidance for the researchers and engineers in the field of solar photovoltaic systems to select the suitable prediction tool for enhancement of the performance characteristics of the solar photovoltaic systems and the utilization of the available solar radiation.     

Experimental investigations and constitutive modeling of cyclic interface shearing between HDPE geomembrane and sandy gravel

This paper presents the results of experimental investigations and constitutive modeling of cyclic interface shearing between HDPE geomembrane and cohesionless sandy gravel. A series of cyclic interface shear tests was performed using a large-scale cyclic shear apparatus with servo controlled system. Particular attention was paid to the influences of the amount of shear-displacement amplitude, number of cycles, shear rate and the normal pressure on the mechanical response. The experimental results show that the path of the shear stress against the cyclic shear displacement is strongly non-linear and forms a closed hysteresis loop, which is pressure dependent, but almost independent of the shear rate. For small shear-displacement amplitudes, the obtained damping ratio is significantly greater than zero, which is different to the behavior usually observed for cyclic soil to soil shearing. In order to describe the pressure dependency of the hysteresis loop using a single set of constitutive parameters, new approximation functions are put forward and embedded into the concept of the Masing rule. Further, a new empirical function is proposed for the damping ratios to capture the experimental data for both small and large cyclic shear-displacement amplitudes. The included model parameters are easy to calibrate and the new functions may also be useful in developing enhanced constitutive models for the simulation of the cyclic interface shear behavior between other geosynthetics and soils.