PKCα Translocation and Actin Remodeling in Contracting A7r5 Smooth Muscle Cells

Recent research indicates that protein kinase C (PKC) plays an important role in smooth muscle contraction. Because PKC activation and specificity of substrate phosphorylation is believed to be associated with the relocalization of the enzyme to specific cell sites, we first investigated the subcellular translocation of PKCα in A7r5 smooth muscle cells by confocal microscopy through use of standard immunohistologic staining and PKCα - enhanced green fluorescent protein (PKCα -EGFP) fusion protein expression. PKCα was diffusely distributed throughout the cytosol in the unstimulated A7r5 cell. Upon stimulation with phorbol 12, 13 dibutyrate (PDBu), PKCα was translocated primarily to either the perinuclear region of the cell or to subplasmalemmal sites depending on the concentration of the stimulating agent. Specifically, PKCα was translocated to the perinuclear area in response to high PDBu concentrations (10-5 M to10-6 M) and relocated to the plasma membrane at lower PDBu concentrations (10-7 M to10-8 M). Translocation of PKCα to the perinucleus but not the plasmalemma was blocked by the use of colchicine to disrupt cell microtubules. By comparison, cytochalasin B disruption of actin microfilaments had no significant effect on PKCα translocation to either the plasmalemma or the perinucleus. The results indicate that the target site of PKCα translocation may vary with activating stimulus strength in A7r5 cells and that the translocation of the isoform to the perinuclear region of the cell is dependent on an intact microtubular cytoskeleton. This suggests that multiple pathways are available for the redistribution of PKCα that may employ different mechanisms to regulate the movement and/or docking of the isoform at specific target sites. We next compared the spatial and temporal pattern of PKCα translocation in response to different stimulating agents in live A7r5 smooth muscle cell preparations utilizing cells transfected with PKCα-EGFP. PDBu (10-8 M) induced a slow but robust and irreversible relocation of the PKCα -EGFP fusion protein from the cytosol to the plasmalemma. By comparison, thapsigargin (10-5 M) and A23187 (2 X 10-5 M) induced a rapidly transient translocation to the cell membrane, which was completed within 4 minutes. In contrast to these agents, angiotensin II (Ang II, 10-6 M) caused only partial relocalization of cytosolic PKCα-EGFP to brightly fluorescing patches at the cell periphery. Moreover, the translocation of the kinase to peripheral patches was completed within seconds and the fusion protein returned to the cytosol within 2 minutes. The PKC inhibitor staurosporine blocked cellular contraction to PDBu but not to A23187 and had no effect on PKCα- EGFP translocation. By comparison, the calcium chelators EDTA and BAPTA-AM blocked the contraction to A23187, attenuated the contraction to PDBu, and abolished the translocation of PKCα-EGFP by both agents. The results show that A7r5 cells retain the ability to respond to several types of contractile agents and the spatial and temporal characteristics of individual PKC isoform translocation may differ markedly, depending on the stimulating agent

An improved two-vector model predictive torque control based on RMS duty ratio optimization for pmsm

This paper proposes an improved two-vector model-predictive torque control (MPTC) strategy to reduce the average torque ripple and improve the flux tracking performance. When determining the duty ratio of vector combination, this method aims at restricting the root mean square (RMS) error of both torque and flux during the whole control period. Every vector combination and corresponding time duration are evaluated in the cost function, which leads to global restriction of torque ripple and flux ripple. In order to avoid increasing switching frequency and computational burden, a restriction is added on the second vector. The three candidates of the second vector are the two adjacent vectors of the first one and zero vector. Simulation results are provided to show the effectiveness of the proposed strategy

Leveraging Communication Tools to Reduce Consumers’ Privacy Concern in the On-demand Services: An Extended S-O-R Model of Perceived Control and Structural Assurance

To use the on-demand services, consumers need to disclose themselves to some extent, which inevitably raises their privacy concerns. Different from previous literature exploring privacy assurance mechanisms, we employ the stimulus– organism–response framework to investigate how communication tools (environmental stimuli) influence consumers’ perceived control, structural assurance, as well as their service platform- and provider-related privacy concerns (organisms), which subsequently impact new consumers’ intention and regular consumers’ continuance intention to use the on-demand services (behavior responses). The models will be tested based on survey data collected from on-demand service consumers. The potential theoretical contributions and practical implications are discussed

Entity Synonym Discovery via Multipiece Bilateral Context Matching

Being able to automatically discover synonymous entities in an open-world setting benefits various tasks such as entity disambiguation or knowledge graph canonicalization. Existing works either only utilize entity features, or rely on structured annotations from a single piece of context where the entity is mentioned. To leverage diverse contexts where entities are mentioned, in this paper, we generalize the distributional hypothesis to a multi-context setting and propose a synonym discovery framework that detects entity synonyms from free-text corpora with considerations on effectiveness and robustness. As one of the key components in synonym discovery, we introduce a neural network model SYNONYMNET to determine whether or not two given entities are synonym with each other. Instead of using entities features, SYNONYMNET makes use of multiple pieces of contexts in which the entity is mentioned, and compares the context-level similarity via a bilateral matching schema. Experimental results demonstrate that the proposed model is able to detect synonym sets that are not observed during training on both generic and domain-specific datasets: Wiki+Freebase, PubMed+UMLS, and MedBook+MKG, with up to 4.16% improvement in terms of Area Under the Curve and 3.19% in terms of Mean Average Precision compared to the best baseline method.Comment: In IJCAI 2020 as a long paper. Code and data are available at https://github.com/czhang99/SynonymNe

Are research contributions assigned differently under the two contributorship classification systems in PLoS ONE?

Contributorship statements have been effective at recording granular author contributions in research articles and have been broadly used to understand how labor is divided across research teams. However, one major limitation in existing empirical studies is that two classification systems have been adopted, especially from its most important data source, journals published by the Public Library of Science (PLoS). This research aims to address this limitation by developing a mapping scheme between the two systems and using it to understand whether there are differences in the assignment of contribution by authors under the two systems. We use all research articles published in PLoS ONE between 2012 to 2020, divided into two five-year publication windows centered by the shift of the classification systems in 2016. Our results show that most tasks (except for writing- and resource-related tasks) are used similarly under the two systems. Moreover, notable differences between how researchers used the two systems are also examined and discussed. This research offers an important foundation for empirical research on division of labor in the future, by enabling a larger dataset that crosses both, and potentially other, classification systems

Sub-sampling and weighting approaches to model checking

Master'sMASTER OF SCIENC