Can Fear Stop Animal Cruelty in Fashion Industry? The Effect of Negative Arousal in a Nonprofit Organization’s Social Media Campaigns

This study focuses on the issue of animal cruelty which is a relatively under-investigated topic in the fashion industry and aims to investigate how different levels of animal cruelty depicted in nonprofit organizations’ ethical consumption campaigns translate into viewers’ negative emotions and lead to supportive behavior and ethical consumption intention

An Empirical Study on L2 Accents of Cross-lingual Text-to-Speech Systems via Vowel Space

With the recent developments in cross-lingual Text-to-Speech (TTS) systems, L2 (second-language, or foreign) accent problems arise. Moreover, running a subjective evaluation for such cross-lingual TTS systems is troublesome. The vowel space analysis, which is often utilized to explore various aspects of language including L2 accents, is a great alternative analysis tool. In this study, we apply the vowel space analysis method to explore L2 accents of cross-lingual TTS systems. Through the vowel space analysis, we observe the three followings: a) a parallel architecture (Glow-TTS) is less L2-accented than an auto-regressive one (Tacotron); b) L2 accents are more dominant in non-shared vowels in a language pair; and c) L2 accents of cross-lingual TTS systems share some phenomena with those of human L2 learners. Our findings imply that it is necessary for TTS systems to handle each language pair differently, depending on their linguistic characteristics such as non-shared vowels. They also hint that we can further incorporate linguistics knowledge in developing cross-lingual TTS systems.Comment: Submitted to ICASSP 202

Prognostic role of computed tomography analysis using deep learning algorithm in patients with chronic hepatitis B viral infection

Background/Aims The prediction of clinical outcomes in patients with chronic hepatitis B (CHB) is paramount for effective management. This study aimed to evaluate the prognostic value of computed tomography (CT) analysis using deep learning algorithms in patients with CHB. Methods This retrospective study included 2,169 patients with CHB without hepatic decompensation who underwent contrast-enhanced abdominal CT for hepatocellular carcinoma (HCC) surveillance between January 2005 and June 2016. Liver and spleen volumes and body composition measurements including subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle indices were acquired from CT images using deep learning-based fully automated organ segmentation algorithms. We assessed the significant predictors of HCC, hepatic decompensation, diabetes mellitus (DM), and overall survival (OS) using Cox proportional hazard analyses. Results During a median follow-up period of 103.0 months, HCC (n=134, 6.2%), hepatic decompensation (n=103, 4.7%), DM (n=432, 19.9%), and death (n=120, 5.5%) occurred. According to the multivariate analysis, standardized spleen volume significantly predicted HCC development (hazard ratio [HR]=1.01, P=0.025), along with age, sex, albumin and platelet count. Standardized spleen volume (HR=1.01, P<0.001) and VAT index (HR=0.98, P=0.004) were significantly associated with hepatic decompensation along with age and albumin. Furthermore, VAT index (HR=1.01, P=0.001) and standardized spleen volume (HR=1.01, P=0.001) were significant predictors for DM, along with sex, age, and albumin. SAT index (HR=0.99, P=0.004) was significantly associated with OS, along with age, albumin, and MELD. Conclusions Deep learning-based automatically measured spleen volume, VAT, and SAT indices may provide various prognostic information in patients with CHB

Self-Correcting HVAC Controls Project Final Report

This document represents the final project report for the Self-Correcting Heating, Ventilating and Air-Conditioning (HVAC) Controls Project jointly funded by Bonneville Power Administration (BPA) and the U.S. Department of Energy (DOE) Building Technologies Program (BTP). The project, initiated in October 2008, focused on exploratory initial development of self-correcting controls for selected HVAC components in air handlers. This report, along with the companion report documenting the algorithms developed, Self-Correcting HVAC Controls: Algorithms for Sensors and Dampers in Air-Handling Units (Fernandez et al. 2009), document the work performed and results of this project

Stochastic electrotransport selectively enhances the transport of highly electromobile molecules

Nondestructive chemical processing of porous samples such as fixed biological tissues typically relies on molecular diffusion. Diffusion into a porous structure is a slow process that significantly delays completion of chemical processing. Here, we present a novel electrokinetic method termed stochastic electrotransport for rapid nondestructive processing of porous samples. This method uses a rotational electric field to selectively disperse highly electromobile molecules throughout a porous sample without displacing the low-electromobility molecules that constitute the sample. Using computational models, we show that stochastic electrotransport can rapidly disperse electromobile molecules in a porous medium. We apply this method to completely clear mouse organs within 1–3 days and to stain them with nuclear dyes, proteins, and antibodies within 1 day. Our results demonstrate the potential of stochastic electrotransport to process large and dense tissue samples that were previously infeasible in time when relying on diffusion.Simons Foundation. Postdoctoral FellowshipLife Sciences Research FoundationBurroughs Wellcome Fund (Career Awards at the Scientific Interface)Searle Scholars ProgramMichael J. Fox Foundation for Parkinson's ResearchUnited States. Defense Advanced Research Projects AgencyJPB FoundationNational Institutes of Health (U.S.)National Institutes of Health (U.S.) (Grant 1-U01-NS090473-01

Genome-Wide Association Study on Longitudinal Change in Fasting Plasma Glucose in Korean Population

Background Genome-wide association studies (GWAS) on type 2 diabetes mellitus (T2DM) have identified more than 400 distinct genetic loci associated with diabetes and nearly 120 loci for fasting plasma glucose (FPG) and fasting insulin level to date. However, genetic risk factors for the longitudinal deterioration of FPG have not been thoroughly evaluated. We aimed to identify genetic variants associated with longitudinal change of FPG over time. Methods We used two prospective cohorts in Korean population, which included a total of 10,528 individuals without T2DM. GWAS of repeated measure of FPG using linear mixed model was performed to investigate the interaction of genetic variants and time, and meta-analysis was conducted. Genome-wide complex trait analysis was used for heritability calculation. In addition, expression quantitative trait loci (eQTL) analysis was performed using the Genotype-Tissue Expression project. Results A small portion (4%) of the genome-wide single nucleotide polymorphism (SNP) interaction with time explained the total phenotypic variance of longitudinal change in FPG. A total of four known genetic variants of FPG were associated with repeated measure of FPG levels. One SNP (rs11187850) showed a genome-wide significant association for genetic interaction with time. The variant is an eQTL for NOC3 like DNA replication regulator (NOC3L) gene in pancreas and adipose tissue. Furthermore, NOC3L is also differentially expressed in pancreatic β-cells between subjects with or without T2DM. However, this variant was not associated with increased risk of T2DM nor elevated FPG level. Conclusion We identified rs11187850, which is an eQTL of NOC3L, to be associated with longitudinal change of FPG in Korean population

Heterogeneous nuclear ribonucleoprotein A1 post-transcriptionally regulates Drp1 expression in neuroblastoma cells.

Excessive mitochondrial fission is associated with the pathogenesis of neurodegenerative diseases. Dynamin-related protein 1 (Drp1) possesses specific fission activity in the mitochondria and peroxisomes. Various post-translational modifications of Drp1 are known to modulate complex mitochondrial dynamics. However, the post-transcriptional regulation of Drp1 remains poorly understood. Here, we show that the heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) regulates Drp1 expression at the post-transcriptional level. hnRNP A1 directly interacts with Drp1 mRNA at its 3'UTR region, and enhances translation potential without affecting mRNA stability. Down-regulation of hnRNP A1 induces mitochondrial elongation by reducing Drp1 expression. Moreover, depletion of hnRNP A1 suppresses 3-NP-mediated mitochondrial fission and dysfunction. In contrast, over-expression of hnRNP A1 promotes mitochondrial fragmentation by increasing Drp1 expression. Additionally, hnRNP A1 significantly exacerbates 3-NP-induced mitochondrial dysfunction and cell death in neuroblastoma cells. Interestingly, treatment with 3-NP induces subcellular translocation of hnRNP A1 from the nucleus to the cytoplasm, which accelerates the increase in Drp1 expression in hnRNP A1 over-expressing cells. Collectively, our findings suggest that hnRNP A1 controls mitochondrial dynamics by post-transcriptional regulation of Drp1.This research was supported by a grant of the Korea–UK Collaborative Alzheimer's Disease Research Project by Ministry of Health & Welfare, Republic of Korea (A120196, HI14C1913) and was supported by the Basic Science Research Program of the National Research Foundation, Republic of Korea (2014R1A2A1A11053431). We are grateful to Wellcome Trust, Principal Research Fellowship to DCR (095317/Z/11/Z)This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.bbagrm.2015.10.01

Role of intermediate phase for stable cycling of Na_7V_4(P_2O_7)_4PO_4 in sodium ion battery

Sodium ion batteries offer promising opportunities in emerging utility grid applications because of the low cost of raw materials, yet low energy density and limited cycle life remain critical drawbacks in their electrochemical operations. Herein, we report a vanadium-based ortho-diphosphate, Na_7V_4(P_2O_7)_4PO_4, or VODP, that significantly reduces all these drawbacks. Indeed, VODP exhibits single-valued voltage plateaus at 3.88 V vs. Na/Na+ while retaining substantial capacity (>78%) over 1,000 cycles. Electronic structure calculations reveal that the remarkable single plateau and cycle life originate from an intermediate phase (a very shallow voltage step) that is similar both in the energy level and lattice parameters to those of fully intercalated and deintercalated states. We propose a theoretical scheme in which the reaction barrier that arises from lattice mismatches can be evaluated by using a simple energetic consideration, suggesting that the presence of intermediate phases is beneficial for cell kinetics by buffering the differences in lattice parameters between initial and final phases. We expect these insights into the role of intermediate phases found for VODP hold in general and thus provide a helpful guideline in the further understanding and design of battery materials

Simple, Scalable Proteomic Imaging for High-Dimensional Profiling of Intact Systems

Combined measurement of diverse molecular and anatomical traits that span multiple levels remains a major challenge in biology. Here, we introduce a simple method that enables proteomic imaging for scalable, integrated, high-dimensional phenotyping of both animal tissues and human clinical samples. This method, termed SWITCH, uniformly secures tissue architecture, native biomolecules, and antigenicity across an entire system by synchronizing the tissue preservation reaction. The heat- and chemical-resistant nature of the resulting framework permits multiple rounds (>20) of relabeling. We have performed 22 rounds of labeling of a single tissue with precise co-registration of multiple datasets. Furthermore, SWITCH synchronizes labeling reactions to improve probe penetration depth and uniformity of staining. With SWITCH, we performed combinatorial protein expression profiling of the human cortex and also interrogated the geometric structure of the fiber pathways in mouse brains. Such integrated high-dimensional information may accelerate our understanding of biological systems at multiple levels.Simons Foundation. Postdoctoral FellowshipLife Sciences Research FoundationBurroughs Wellcome Fund (Career Award at the Scientific Interface)Searle Scholars ProgramMichael J. Fox Foundation for Parkinson's ResearchUnited States. Defense Advanced Research Projects AgencyNational Institutes of Health (U.S.) (1-U01-NS090473-01

GABA Neuronal Deletion of Shank3 Exons 14–16 in Mice Suppresses Striatal Excitatory Synaptic Input and Induces Social and Locomotor Abnormalities

Shank3 is an excitatory postsynaptic scaffolding protein implicated in multiple brain disorders, including autism spectrum disorders (ASD) and Phelan-McDermid syndrome (PMS). Although previous neurobiological studies on Shank3 and Shank3-mutant mice have revealed diverse roles of Shank3 in the regulation of synaptic, neuronal and brain functions, whether Shank3 expression in specific cell types distinctly contributes to mouse phenotypes remains largely unclear. In the present study, we generated two Shank3-mutant mouse lines (exons 14–16) carrying global and GABA neuron-specific deletions and characterized their electrophysiological and behavioral phenotypes. These mouse lines show similar decreases in excitatory synaptic input onto dorsolateral striatal neurons. In addition, the abnormal social and locomotor behaviors observed in global Shank3-mutant mice are strongly mimicked by GABA neuron-specific Shank3-mutant mice, whereas the repetitive and anxiety-like behaviors are only partially mimicked. These results suggest that GABAergic Shank3 (exons 14–16) deletion has strong influences on striatal excitatory synaptic transmission and social and locomotor behaviors in mice