Battle between influenza A virus and a newly identified ZAPL antiviral activity

Influenza A virus infection causes a highly contagious annual respiratory disease in humans as well as periodic pandemics with higher mortality rates. The Krug laboratory has shown that one of the major ways that the influenza virus NS1 protein counteracts host antiviral responses is to bind the 30 kDa subunit of the cleavage and polyadenylation specificity factor (CPSF30). As a consequence, 3’ end processing of cellular pre-mRNAis is inhibited, leading to reduced production of cellular mRNAs, including interferon mRNAs. I showed that NS1-CPSF30 complexes contain an array of cellular proteins. I purified the NS1-CPSF30 complexes from virus infected cells by affinity selection of CPSF30 and the NS1 protein. I identified the associated cellular proteins by mass spectrometry. Two cellular RNA helicases, DDX21 and DHX30, were identified. SiRNA knockdown of either RNA helicase enhanced virus replication, indicating that DDX21 and DHX30 inhibit influenza A virus replication. Further study demonstrated that DDX21 RNA helicase inhibits viral RNA synthesis, and is countered by the NS1 protein. The cellular ZAPL antiviral protein was also identified in the NS1-CPSF30 complexes. Previous studies have shown that ZAPL antiviral activity is mediated by its N-terminal zinc-fingers, which targets viral mRNA of several viruses for degradation. Little is known about the antiviral role of the ZAPL C-terminal PARP domain. Here I discovered the antiviral role of ZAPL C-terminal PARP domain against influenza A virus. I showed that the ZAPL PARP domain targets the viral polymerase PA and PB2 proteins. These two viral polymerases are poly(ADP-ribosylated), presumably by other PARP protein(s). The ZAPL-associated, poly(ADP-ribosylated) PA and PB2 are then ubiquitinated and proteasomally degraded. This ZAPL antiviral activity is counteracted by the binding of polymerase PB1 protein to the WWE region adjacent to the PARP domain, and causes PA and PB2 to dissociate from ZAPL and thus escape degradation. Because PB1 displaces PA and PB2 and protects them from ZAPL-mediated degradation, endogenous ZAPL only moderately inhibits influenza A virus replication (20-30-fold), as determined by siRNA knockdown experiment. These results suggest that influenza A virus has partially won the battle against the newly identified ZAPL antiviral activity.Microbiolog

Analysis of nonlinear dynamic behavior and pull-in prediction of micro circular plate actuator

The dynamic behavior of micro circular plate electrostatic devices is not easily analyzed using traditional methods such as perturbation theory or Galerkin approach method due to the complexity of the interactions among the electrostatic coupling effect, the residual stress and the nonlinear electrostatic force. Accordingly, the present study proposes a approach for analyzing the dynamic response of such devices using a hybrid numerical scheme comprising the differential transformation method and the finite difference method. The feasibility of the proposed approach is demonstrated by modeling the dynamic response of a micro circular plate actuated by a DC voltage. The numerical results for the pull-in voltage are found to deviate by no more than 0.27 % from those derived in the literature using various computational methods. Thus, the basic validity of the hybrid numerical scheme is confirmed. Moreover, the effectiveness of a combined DC/AC loading scheme in driving the micro circular actuator is examined. It is shown that the use of an AC actuating voltage in addition to the DC driving voltage provides an effective means of tuning the dynamic response of the micro circular plate

A Review Of Data Monetization: Strategic Use Of Big Data

In this data-rich big data age, industries are capable to collect data that could not be imagined before. Many industries today are now thinking of how to better use these data assets properly to generate value, either for internal or external purpose. Data monetization is adopted as one of strategies used to create additional stream of revenue from the discovery, capture, storage, analysis, dissemination, and use of that data. It gains in popularity among different industries. The three research questions of interest to this study are: (1) what does data monetization mean to business; (2) what are types of data monetization and industries currently use; (3) how to initiate a data monetization strategy. To address these questions, this study did a comprehensive review of prior research from academia as well as from industry. This study clarifies and defines the data monetization, presents the synthesis of use cases learned from other industries as well as provides guiding principles of how to start with data monetization. The contributions of this study are twofold. First, this paper contributes to industry communities that start to explore opportunities of creating value from their data assets but lack of directions and how to. Second, this study contributes to raise awareness of academic communities over the potential of big data monetization research and the opportunities in further discussing the converging information system and strategy domain

Segmenting Taipei’s Real Estate Data – A Cluster Analysis

Data mining has been widely used for knowledge discovery from large amount of data. In this paper, clustering analysis is applied to Taiwan government open data platform (DATA.GOV.TW), segmenting the real estate data so as to understand the real estate market structure in Taiwan. This paper use design science research methodology (DSRM) as research method. The result provides valuable insights into market structures in Taipei City that has limited addressed in past research and contributes to real estate agencies and practitioners an insight-seeking approach that they can follow to generate values from data

Enzymatic Cross-Linking of Dynamic Thiol-Norbornene Click Hydrogels

Enzyme-mediated in situ forming hydrogels are attractive for many biomedical applications because gelation afforded by enzymatic reactions can be readily controlled not only by tuning macromer compositions, but also by adjusting enzyme kinetics. For example, horseradish peroxidase (HRP) has been used extensively for in situ cross-linking of macromers containing hydroxyl-phenol groups. The use of HRP to initiate thiol-allylether polymerization has also been reported, yet no prior study has demonstrated enzymatic initiation of thiol-norbornene gelation. In this study, we discovered that HRP can generate the thiyl radicals needed for initiating thiol-norbornene hydrogelation, which has only been demonstrated previously using photopolymerization. Enzymatic thiol-norbornene gelation not only overcomes light attenuation issue commonly observed in photopolymerized hydrogels, but also preserves modularity of the cross-linking. In particular, we prepared modular hydrogels from two sets of norbornene-modified macromers, 8-arm poly(ethylene glycol)-norbornene (PEG8NB) and gelatin-norbornene (GelNB). Bis-cysteine-containing peptides or PEG-tetra-thiol (PEG4SH) was used as a cross-linker for forming enzymatically and orthogonally polymerized hydrogel. For HRP-initiated PEG-peptide hydrogel cross-linking, gelation efficiency was significantly improved via adding tyrosine residues on the peptide cross-linkers. Interestingly, these additional tyrosine residues did not form permanent dityrosine cross-links following HRP-induced gelation. As a result, they remained available for tyrosinase-mediated secondary cross-linking, which dynamically increased hydrogel stiffness. In addition to material characterizations, we also found that both PEG- and gelatin-based hydrogels exhibited excellent cytocompatibility for dynamic 3D cell culture. The enzymatic thiol-norbornene gelation scheme presented here offers a new cross-linking mechanism for preparing modularly and dynamically cross-linked hydrogels

Improving gelation efficiency and cytocompatibility of visible light polymerized thiol-norbornene hydrogels via addition of soluble tyrosine

Hydrogels immobilized with biomimetic peptides have been used widely for tissue engineering and drug delivery applications. Photopolymerization has been among the most commonly used techniques to fabricate peptide-immobilized hydrogels as it offers rapid and robust peptide immobilization within a crosslinked hydrogel network. Both chain-growth and step-growth photopolymerizations can be used to immobilize peptides within covalently crosslinked hydrogels. A previously developed visible light mediated step-growth thiol-norbornene gelation scheme has demonstrated efficient crosslinking of hydrogels composed of an inert poly(ethylene glycol)-norbornene (PEGNB) macromer and a small molecular weight bis-thiol linker, such as dithiothreitol (DTT). Compared with conventional visible light mediated chain-polymerizations where multiple initiator components are required, step-growth photopolymerized thiol-norbornene hydrogels are more cytocompatible for the in situ encapsulation of radical sensitive cells (e.g., pancreatic β-cells). This contribution explored visible light based crosslinking of various bis-cysteine containing peptides with macromer 8-arm PEGNB to form biomimetic hydrogels suitable for in situ cell encapsulation. It was found that the addition of soluble tyrosine during polymerization not only significantly accelerated gelation, but also improved the crosslinking efficiency of PEG-peptide hydrogels as evidenced by a decreased gel point and enhanced gel modulus. In addition, soluble tyrosine drastically enhanced the cytocompatibility of the resulting PEG-peptide hydrogels, as demonstrated by in situ encapsulation and culture of pancreatic MIN6 β-cells. This visible light based thiol-norbornene crosslinking mechanism provides an attractive gelation method for preparing cytocompatible PEG-peptide hydrogels for tissue engineering applications

Biomimetic and enzyme-responsive dynamic hydrogels for studying cell-matrix interactions in pancreatic ductal adenocarcinoma

The tumor microenvironment (TME) governs all aspects of cancer progression and in vitro 3D cell culture platforms are increasingly developed to emulate the interactions between components of the stromal tissues and cancer cells. However, conventional cell culture platforms are inadequate in recapitulating the TME, which has complex compositions and dynamically changing matrix mechanics. In this study, we developed a dynamic gelatin-hyaluronic acid hybrid hydrogel system through integrating modular thiol-norbornene photopolymerization and enzyme-triggered on-demand matrix stiffening. In particular, gelatin was dually modified with norbornene and 4-hydroxyphenylacetic acid to render this bioactive protein photo-crosslinkable (through thiol-norbornene gelation) and responsive to tyrosinase-triggered on-demand stiffening (through HPA dimerization). In addition to the modified gelatin that provides basic cell adhesive motifs and protease cleavable sequences, hyaluronic acid (HA), an essential tumor matrix, was modularly and covalently incorporated into the cell-laden gel network. We systematically characterized macromer modification, gel crosslinking, as well as enzyme-triggered stiffening and degradation. We also evaluated the influence of matrix composition and dynamic stiffening on pancreatic ductal adenocarcinoma (PDAC) cell fate in 3D. We found that either HA-containing matrix or a dynamically stiffened microenvironment inhibited PDAC cell growth. Interestingly, these two factors synergistically induced cell phenotypic changes that resembled cell migration and/or invasion in 3D. Additional mRNA expression array analyses revealed changes unique to the presence of HA, to a stiffened microenvironment, or to the combination of both. Finally, we presented immunostaining and mRNA expression data to demonstrate that these irregular PDAC cell phenotypes were a result of matrix-induced epithelial-mesenchymal transition (EMT)

Estimating Classification Accuracy for Unlabeled Datasets Based on Block Scaling

This paper proposes an approach called block scaling quality (BSQ) for estimating the prediction accuracy of a deep network model. The basic operation perturbs the input spectrogram by multiplying all values within a block by , where  is equal to 0 in the experiments. The ratio of perturbed spectrograms that have different prediction labels than the original spectrogram to the total number of perturbed spectrograms indicates how much of the spectrogram is crucial for the prediction. Thus, this ratio is inversely correlated with the accuracy of the dataset. The BSQ approach demonstrates satisfactory estimation accuracy in experiments when compared with various other approaches. When using only the Jamendo and FMA datasets, the estimation accuracy experiences an average error of 4.9% and 1.8%, respectively. Moreover, the BSQ approach holds advantages over some of the comparison counterparts. Overall, it presents a promising approach for estimating the accuracy of a deep network model

Development of vital signs detection system with ground noise cancellation

This study provides an experimental procedure and a noise immunity method for detecting the vital signs of a person in a vehicle. Velocity sensors that are convenient and accurate at acquiring data are adopted to detect the involuntary body vibrations. Two kinds of algorithms were proposed for detecting the vital signs in different environments with various ground noise level. To reduce the ground noise effect generated from extreme environments, a ground sensor also is used to measure the vibration amplitude of ground surface for calculating the car body response to provide excellent noise cancelling method. Measuring and processing the vibrations are effective methods for detecting people concealed in a vehicle. The complete detecting system was verified through experiment conducted with a passenger car

Mutations in the PKM2 exon-10 region are associated with reduced allostery and increased nuclear translocation.

PKM2 is a key metabolic enzyme central to glucose metabolism and energy expenditure. Multiple stimuli regulate PKM2's activity through allosteric modulation and post-translational modifications. Furthermore, PKM2 can partner with KDM8, an oncogenic demethylase and enter the nucleus to serve as a HIF1α co-activator. Yet, the mechanistic basis of the exon-10 region in allosteric regulation and nuclear translocation remains unclear. Here, we determined the crystal structures and kinetic coupling constants of exon-10 tumor-related mutants (H391Y and R399E), showing altered structural plasticity and reduced allostery. Immunoprecipitation analysis revealed increased interaction with KDM8 for H391Y, R399E, and G415R. We also found a higher degree of HIF1α-mediated transactivation activity, particularly in the presence of KDM8. Furthermore, overexpression of PKM2 mutants significantly elevated cell growth and migration. Together, PKM2 exon-10 mutations lead to structure-allostery alterations and increased nuclear functions mediated by KDM8 in breast cancer cells. Targeting the PKM2-KDM8 complex may provide a potential therapeutic intervention