Uniformity Masks Design Method Based on the Shadow Matrix for Coating Materials with Different Condensation Characteristics

An intuitionistic method is proposed to design shadow masks to achieve thickness profile control for evaporation coating processes. The proposed method is based on the concept of the shadow matrix, which is a matrix that contains coefficients that build quantitive relations between shape parameters of masks and shadow quantities of substrate directly. By using the shadow matrix, shape parameters of shadow masks could be derived simply by solving a matrix equation. Verification experiments were performed on a special case where coating materials have different condensation characteristics. By using the designed mask pair with complementary shapes, thickness uniformities of better than 98% are demonstrated for MgF2 () and LaF3 () simultaneously on a 280 mm diameter spherical substrate with the radius curvature of 200 mm

Do Language Embeddings Capture Scales?

Pretrained Language Models (LMs) have been shown to possess significant linguistic, common sense, and factual knowledge. One form of knowledge that has not been studied yet in this context is information about the scalar magnitudes of objects. We show that pretrained language models capture a significant amount of this information but are short of the capability required for general common-sense reasoning. We identify contextual information in pre-training and numeracy as two key factors affecting their performance and show that a simple method of canonicalizing numbers can have a significant effect on the results.Comment: Accepted at EMNLP Findings 2020 and EMNLP BlackboxNLP workshop 2020; 8 pages, 2 figures; Minor changes to the acknowledgment sectio

Resveratrol Ameliorates Lipid Droplet Accumulation in Liver Through a SIRT1/ ATF6-Dependent Mechanism

Background/Aims: Lipid droplets (LDs) are dynamic organelles that store neutral lipids during times of energy excess, and an increased accumulation of LDs in the liver is closely linked to hepatic steatosis. Our previous studies suggested that resveratrol (RSV) supplement could improve hepatic steatosis, but the underlying mechanism, particularly which related to LD accumulation, has not yet been elucidated. Methods: A high-fat diet (HFD) and palmitic acid were used to induce hepatic steatosis in mouse liver and hepatocytes, respectively. The effects of RSV on LD accumulation were analyzed in vivo and in vitro. The effects of RSV on the expression levels of LD-associated genes (ATF6, Fsp27β/CIDEC, CREBH, and PLIN1) were measured by qRT-PCR and western blot assays, followed by KD or overexpression of SIRT1 and ATF6 with small interfering RNAs or overexpressed plasmids, respectively. The dual luciferase reporter assay, chromatin immunoprecipitation assay, coimmunoprecipitation, and proximity ligation assay were utilized to clarify the mechanism of transcriptional regulation and possible interaction between SIRT1 and ATF6. Results: There was a significant increase in the accumulation of LDs in liver and hepatocytes during the process of HFD-induced steatosis, respectively, which was significantly inhibited by RSV supplementation. RSV notably activated SIRT1 expression and decreased the expression levels of ATF6, Fsp27β/CIDEC, CREBH, and PLIN1, which are associated with LD accumulation. Interestingly, the inhibitory effects of RSV on LD accumulation and the associated expression of genes in hepatocytes were abrogated or strengthened with SIRT1 silencing or overexpression, respectively. On the contrary, the benefits of RSV in hepatocytes were eliminated or aggravated when transfected with the overexpressed ATF6 or ATF6 siRNA, respectively. Furthermore, we found that RSV stimulated SIRT1 expression significantly, which was followed by increased deacetylation and inactivation of ATF6, resulting in a positive feedback loop for SIRT1 transcription associated with ATF6 binding to the SIRT1 promoter region. Conclusion: Taken together, these findings indicate that RSV supplementation improves hepatic steatosis by ameliorating the accumulation of LDs, and this might be partially mediated by a SIRT1/ATF6-dependent mechanism

Identification of Glycine Receptor α3 as a Colchicine-Binding Protein

Colchicine (Col) is considered a kind of highly effective alkaloid for preventing and treating acute gout attacks (flares). However, little is known about the underlying mechanism of Col in pain treatment. We have previously developed a customized virtual target identification method, termed IFPTarget, for small-molecule target identification. In this study, by using IFPTarget and ligand similarity ensemble approach (SEA), we show that the glycine receptor alpha 3 (GlyRα3), which play a key role in the processing of inflammatory pain, is a potential target of Col. Moreover, Col binds directly to the GlyRα3 as determined by the immunoprecipitation and bio-layer interferometry assays using the synthesized Col-biotin conjugate (linked Col and biotin with polyethylene glycol). These results suggest that GlyRα3 may mediate Col-induced suppression of inflammatory pain. However, whether GlyRα3 is the functional target of Col and serves as potential therapeutic target in gouty arthritis requires further investigations

Biodegradable Thermosensitive Hydrogel for SAHA and DDP Delivery: Therapeutic Effects on Oral Squamous Cell Carcinoma Xenografts

Background: OSCC is one of the most common malignancies and numerous clinical agents currently applied in combinative chemotherapy. Here we reported a novel therapeutic strategy, SAHA and DDP-loaded PECE (SAHA-DDP/PECE), can improve the therapeutic effects of intratumorally chemotherapy on OSCC cell xenografts. Objective/Purpose: The objective of this study was to evaluate the therapeutic efficacy of the SAHA-DDP/PECE in situ controlled drug delivery system on OSCC cell xenografts. Methods: A biodegradable and thermosensitive hydrogel was successfully developed to load SAHA and DDP. Tumorbeared mice were intratumorally administered with SAHA-DDP/PECE at 50 mg/kg (SAHA) +2 mg/kg (DDP) in 100 ul PECE hydrogel every two weeks, SAHA-DDP at 50 mg/kg(SAHA) +2 mg/kg(DDP) in NS, 2 mg/kg DDP solution, 50 mg/kg SAHA solution, equal volume of PECE hydrogel, or equal volume of NS on the same schedule, respectively. The antineoplastic actions of SAHA and DDP alone and in combination were evaluated using the determination of tumor volume, immunohistochemistry, western blot, and TUNEL analysis. Results: The hydrogel system was a free-flowing sol at 10uC, become gel at body temperature, and could sustain more than 14 days in situ. SAHA-DDP/PECE was subsequently injected into tumor OSCC tumor-beared mice. The results demonstrated that such a strategy as this allows the carrier system to show a sustained release of SAHA and DDP in vivo, and coul

Genome-wide association meta-analysis of corneal curvature identifies novel loci and shared genetic influences across axial length and refractive error

Abstract: Corneal curvature, a highly heritable trait, is a key clinical endophenotype for myopia - a major cause of visual impairment and blindness in the world. Here we present a trans-ethnic meta-analysis of corneal curvature GWAS in 44,042 individuals of Caucasian and Asian with replication in 88,218 UK Biobank data. We identified 47 loci (of which 26 are novel), with population-specific signals as well as shared signals across ethnicities. Some identified variants showed precise scaling in corneal curvature and eye elongation (i.e. axial length) to maintain eyes in emmetropia (i.e. HDAC11/FBLN2 rs2630445, RBP3 rs11204213); others exhibited association with myopia with little pleiotropic effects on eye elongation. Implicated genes are involved in extracellular matrix organization, developmental process for body and eye, connective tissue cartilage and glycosylation protein activities. Our study provides insights into population-specific novel genes for corneal curvature, and their pleiotropic effect in regulating eye size or conferring susceptibility to myopia

Graph Edge Convolutional Neural Networks for Skeleton-Based Action Recognition

Body joints, directly obtained from a pose estimation model, have proven effective for action recognition. Existing works focus on analyzing the dynamics of human joints. However, except joints, humans also explore motions of limbs for understanding actions. Given this observation, we investigate the dynamics of human limbs for skeleton-based action recognition. Specifically, we represent an edge in a graph of a human skeleton by integrating its spatial neighboring edges (for encoding the cooperation between different limbs) and its temporal neighboring edges (for achieving the consistency of movements in an action). Based on this new edge representation, we devise a graph edge convolutional neural network. Considering the complementarity between graph node convolution and edge convolution, we further construct two hybrid networks by introducing different shared intermediate layers to integrate graph node- and edge-convolutional neural networks. Our contributions are twofold, graph edge convolution and hybrid networks for integrating the proposed edge convolution and the conventional node convolution. Experimental results on the Kinetics and NTU-RGB+D datasets demonstrate that our graph edge convolution is effective at capturing the characteristics of actions and that our graph edge convolutional neural network significantly outperforms existing state-of-the-art skeleton-based action recognition methods