bluuebunny/crossref_metadata_2025_split huggingface dataset:
WBP2 negatively regulates the Hippo pathway by competitively binding to WWC3 with LATS1 to promote non-small cell lung cancer progression
Authors: Han Qiang , Rong Xuezhu , Lin Xuyong , Zhang Xiupeng , Fan Chuifeng , Zhao Huanyu , Wang Enhua 
Published: April 2021

AbstractWW domain binding protein-2 (WBP2) can function as a Yes-associated protein/transcriptional co-activator with PDZ-binding motif (YAP/TAZ) co-activator and has a crucial role in promoting breast cancer progression. However, the expression and potential molecular mechanisms of WBP2 in the context of lung cancer are not fully understood. We determined that WBP2 was highly expressed in lung cancer specimens and cell lines and that this expression was closely related to the advanced pTNM stage, lymph node metastasis, and poor prognosis of patients. In addition, gain- and loss-of-function experiments revealed that WBP2 could significantly promote the proliferation and invasion of lung cancer cells both in vivo and in vitro. To elucidate the underlying molecular mechanism, we determined that wild-type WBP2 could competitively bind to the WW domain of WWC3 (WW and C2 domain-containing-3) with LATS1 (Large tumor suppressor-1) through its PPxY motifs, thus inhibiting the formation of the WWC3-LATS1 complex, reducing the phosphorylation level of LATS1, suppressing the activity of the Hippo pathway, and ultimately promoting YAP nuclear translocation. Therefore, from the aspect of upstream molecules of Hippo signaling, WBP2 promotes the malignant phenotype of lung cancer cells in a unique manner that is not directly dependent upon YAP, thus providing a corresponding experimental basis for the development of targeted therapeutic drugs for lung cancer.
Jordan products of quantum channels and their compatibility
Authors: Girard Mark , Plávala Martin , Sikora Jamie 
Published: April 2021

AbstractGiven two quantum channels, we examine the task of determining whether they are compatible—meaning that one can perform both channels simultaneously but, in the future, choose exactly one channel whose output is desired (while forfeiting the output of the other channel). Here, we present several results concerning this task. First, we show it is equivalent to the quantum state marginal problem, i.e., every quantum state marginal problem can be recast as the compatibility of two channels, and vice versa. Second, we show that compatible measure-and-prepare channels (i.e., entanglement-breaking channels) do not necessarily have a measure-and-prepare compatibilizing channel. Third, we extend the notion of the Jordan product of matrices to quantum channels and present sufficient conditions for channel compatibility. These Jordan products and their generalizations might be of independent interest. Last, we formulate the different notions of compatibility as semidefinite programs and numerically test when families of partially dephasing-depolarizing channels are compatible.
Direct electrosynthesis of 52% concentrated CO on silver’s twin boundary
Authors: Tang Can , Gong Peng , Xiao Taishi , Sun Zhengzong 
Published: April 2021

AbstractThe gaseous product concentration in direct electrochemical CO2 reduction is usually hurdled by the electrode’s Faradaic efficiency, current density, and inevitable mixing with the unreacted CO2. A concentrated gaseous product with high purity will greatly lower the barrier for large-scale CO2 fixation and follow-up industrial usage. Here, we developed a pneumatic trough setup to collect the CO2 reduction product from a precisely engineered nanotwinned electrocatalyst, without using ion-exchange membrane. The silver catalyst’s twin boundary density can be tuned from 0.3 to 1.5 × 104 cm−1. With the lengthy and winding twin boundaries, this catalyst exhibits a Faradaic efficiency up to 92% at −1.0 V and a turnover frequency of 127 s−1 in converting CO2 to CO. Through a tandem electrochemical-CVD system, we successfully produced CO with a volume percentage of up to 52%, and further transformed it into single layer graphene film.
Taming nitroformate through encapsulation with nitrogen-rich hydrogen-bonded organic frameworks
Authors: Zhang Jichuan , Feng Yongan , Staples Richard J. , Zhang Jiaheng , Shreeve Jean’ne M. 
Published: April 2021

AbstractOwing to its simple preparation and high oxygen content, nitroformate [−C(NO2)3, NF] is an extremely attractive oxidant component for propellants and explosives. However, the poor thermostability of NF-based derivatives has been an unconquerable barrier for more than 150 years, thus hindering its application. In this study, the first example of a nitrogen-rich hydrogen-bonded organic framework (HOF-NF) is designed and constructed through self-assembly in energetic materials, in which NF anions are trapped in pores of the resulting framework via the dual force of ionic and hydrogen bonds from the strengthened framework. These factors lead to the decomposition temperature of the resulting HOF-NF moiety being 200 °C, which exceeds the challenge of thermal stability over 180 °C for the first time among NF-based compounds. A large number of NF-based compounds with high stabilities and excellent properties can be designed and synthesized on the basis of this work.
SOX4 and SMARCA4 cooperatively regulate PI3k signaling through transcriptional activation of TGFBR2
Authors: Mehta Gaurav A. , Angus Steven P. , Khella Christen A. , Tong Kevin , Khanna Pooja , Dixon Shelley A. H. , Verzi Michael P. , Johnson Gary L. , Gatza Michael L. 
Published: April 2021

AbstractDysregulation of PI3K/Akt signaling is a dominant feature in basal-like or triple-negative breast cancers (TNBC). However, the mechanisms regulating this pathway are largely unknown in this subset of aggressive tumors. Here we demonstrate that the transcription factor SOX4 is a key regulator of PI3K signaling in TNBC. Genomic and proteomic analyses coupled with mechanistic studies identified TGFBR2 as a direct transcriptional target of SOX4 and demonstrated that TGFBR2 is required to mediate SOX4-dependent PI3K signaling. We further report that SOX4 and the SWI/SNF ATPase SMARCA4, which are uniformly overexpressed in basal-like tumors, form a previously unreported complex that is required to maintain an open chromatin conformation at the TGFBR2 regulatory regions in order to mediate TGFBR2 expression and PI3K signaling. Collectively, our findings delineate the mechanism by which SOX4 and SMARCA4 cooperatively regulate PI3K/Akt signaling and suggest that this complex may play an essential role in TNBC genesis and/or progression.
Characterization of clostridium botulinum neurotoxin serotype A (BoNT/A) and fibroblast growth factor receptor interactions using novel receptor dimerization assay
Authors: James Nicholas G. , Malik Shiazah , Sanstrum Bethany J. , Rhéaume Catherine , Broide Ron S. , Jameson David M. , Brideau-Andersen Amy , Jacky Birgitte S. 
Published: April 2021

AbstractClostridium botulinum neurotoxin serotype A (BoNT/A) is a potent neurotoxin that serves as an effective therapeutic for several neuromuscular disorders via induction of temporary muscular paralysis. Specific binding and internalization of BoNT/A into neuronal cells is mediated by its binding domain (HC/A), which binds to gangliosides, including GT1b, and protein cell surface receptors, including SV2. Previously, recombinant HC/A was also shown to bind to FGFR3. As FGFR dimerization is an indirect measure of ligand-receptor binding, an FCS & TIRF receptor dimerization assay was developed to measure rHC/A-induced dimerization of fluorescently tagged FGFR subtypes (FGFR1-3) in cells. rHC/A dimerized FGFR subtypes in the rank order FGFR3c (EC50 ≈ 27 nM) > FGFR2b (EC50 ≈ 70 nM) > FGFR1c (EC50 ≈ 163 nM); rHC/A dimerized FGFR3c with similar potency as the native FGFR3c ligand, FGF9 (EC50 ≈ 18 nM). Mutating the ganglioside binding site in HC/A, or removal of GT1b from the media, resulted in decreased dimerization. Interestingly, reduced dimerization was also observed with an SV2 mutant variant of HC/A. Overall, the results suggest that the FCS & TIRF receptor dimerization assay can assess FGFR dimerization with known and novel ligands and support a model wherein HC/A, either directly or indirectly, interacts with FGFRs and induces receptor dimerization.
Conditional RAC1 knockout in motor neurons restores H-reflex rate-dependent depression after spinal cord injury
Authors: Benson Curtis A. , Olson Kai-Lan , Patwa Siraj , Reimer Marike L. , Bangalore Lakshmi , Hill Myriam , Waxman Stephen G. , Tan Andrew M. 
Published: April 2021

AbstractA major complication with spinal cord injury (SCI) is the development of spasticity, a clinical symptom of hyperexcitability within the spinal H-reflex pathway. We have previously demonstrated a common structural motif of dendritic spine dysgenesis associated with hyperexcitability disorders after injury or disease insults to the CNS. Here, we used an adeno-associated viral (AAV)-mediated Cre-Lox system to knockout Rac1 protein expression in motor neurons after SCI. Three weeks after AAV9-Cre delivery into the soleus/gastrocnemius of Rac1-“floxed” adult mice to retrogradely infect spinal alpha-motor neurons, we observed significant restoration of RDD and reduced H-reflex excitability in SCI animals. Additionally, viral-mediated Rac1 knockdown reduced presence of dendritic spine dysgenesis on motor neurons. In control SCI animals without Rac1 knockout, we continued to observe abnormal dendritic spine morphology associated with hyperexcitability disorder, including an increase in mature, mushroom dendritic spines, and an increase in overall spine length and spine head size. Taken together, our results demonstrate that viral-mediated disruption of Rac1 expression in ventral horn motor neurons can mitigate dendritic spine morphological correlates of neuronal hyperexcitability, and reverse hyperreflexia associated with spasticity after SCI. Finally, our findings provide evidence of a putative mechanistic relationship between motor neuron dendritic spine dysgenesis and SCI-induced spasticity.
Multi‐scale capsule generative adversarial network for snow removal
Authors: Yang Fei , Zhang Jialu , Zhang Qian 
Published: April 2021

AbstractSnowflakes captured on photos may severely decrease the visual quality and cause difficulties for vision analysis systems. Most noise removal frameworks are designed for de‐raining or de‐hazing, regarding rain or haze as translucent masks on clean images. However, snowflakes are different from them in terms of sizes, shapes, transparencies and floating trajectories, which decreases the performance of de‐raining or de‐hazing models in processing snowy images. In this work, we propose an effective multi‐scale generative adversarial network framework for single‐image snow removal, which is built with a multi‐scale structure to identify various scales of snowflakes and a capsule‐based structure to fuse the features extracted from the multi‐scale encoding branches, so that different scaled features could be summarised and learnt by a joint framework. The overall framework is supervised by a weighted joint loss with an iterative training procedure to keep the training stability for the multi‐branch‐based structure. The experimental results demonstrate that our model outperforms the state‐of‐the‐art comparisons.
Optimal radiation pattern synthesis of mutually coupled antenna array using an efficient compensation method
Authors: Das Avishek , Mandal Durbadal , Kar Rajib 
Published: April 2021

AbstractAn efficient compensation method is proposed for the reduction of mutual coupling among the elements of an antenna array using the optimum current amplitude excitation weights. The performance of an antenna array degrades heavily due to mutual coupling. The mutual coupling effect can neither be eliminated nor be ignored in the context of the antenna array design. Several analytical and numerical techniques have been proposed in the past few decades for the calculation and compensation of mutual coupling effect. Here, the mutual coupling is compensated by reducing the driving impedance of each identical array element in the array by adopting grey wolf optimization and moth flame optimization algorithms, respectively. The sum of the driving impedances of each element of the antenna array is reduced efficiently by adjusting the feed current amplitudes of all the individual array elements. Compared to the existing known methods, the proposed method is less complex, cost‐effective and easy to implement for commercial and industrial applications to achieve better performance.
Implementation of all‐optical Toffoli gate by 2D Si–air photonic crystal
Authors: De Paromita , Ranwa Sapana , Mukhopadhyay Sourangshu 
Published: April 2021

AbstractThe quantum Toffoli gate is one of the essential reversible universal logic gates widely used for optical data processing. Herein, a new scheme of developing all‐optical Toffoli gate using a two‐dimensional silicon–air photonic crystal is proposed. For the realization of the Toffoli gate, the principles of constructive and destructive interference of light are used. The Toffoli gate comprises two‐input–three‐output‐based optical AND gate, and a two‐input–one‐output optical XOR gate. Two Y junction power splitters have been used at the two inputs of the AND gate. The operating wavelength of the proposed Toffoli gate is 1550 nm along with the wafer size of 50 µm × 50 µm. The performance of the Toffoli gate has been analysed and simulated by the plane‐wave expansion method and finite‐difference time‐domain method. The response time and contrast ratios are also obtained from the simulation. The proposed Toffoli gate is intensity encoded with no non‐linear material within the crystal which shows significant improvement over other proposals.
Design of efficient N‐bit shift register using optimized D flip flop in quantum dot cellular automata technology
Authors: Yaqoob Salma , Ahmed Suhaib , Naz Syed Farah , Bashir Sadaf , Sharma Sparsh 
Published: April 2021

AbstractThere is a need for secure and powerful nano communication systems with ultra‐low power consumption in the new digital age. Quantum‐dot cellular automata (QCA) is a technology which can be used for designing these systems. In the nano regime, relative to complementary metal oxide semiconductor technology, QCA is able to work with greater speed and lower power dissipation along with high density. This study examines the applicability and viability of using QCA to construct the sequential circuits. An optimized D flip flop is designed in QCA. The fault tolerance for single cell omission and single cell addition defects of the proposed flip flop is also presented. This flip flop is then used to design 2‐, 3‐, 4‐ and 8‐bit shift registers which can be efficiently scaled up to N‐bits. The operations of all proposed designs are validated using QCADesigner tool and the energy dissipation analysis is done using QCAPro tool. The performance comparison shows that the proposed QCA designs are cost efficient and they can be utilized efficiently in designing digital communication systems which require small area along with high speed and ultra‐low power consumption.
Cytokinetic abscission is part of the midblastula transition in early zebrafish embryogenesis
Authors: Adar-Levor Shai , Nachmias Dikla , Gal-Oz Shani T. , Jahn Yarden M. , Peyrieras Nadine , Zaritsky Assaf , Birnbaum Ramon Y. , Elia Natalie 
Published: April 2021

SignificanceIn this work, we show that the last step of cytokinesis, termed abscission, is delayed in early zebrafish embryos. As a result, sibling cells remain connected to one another by a thin membrane bridge for several cycles, forming clusters of interconnected cells. Bridge severing (i.e., abscission) commences at the 10th cell cycle when embryos enter the midblastula transition switch, in which embryonic cells become individualized and exhibit the characteristics of mature cells. Cells connected by intercellular bridges shared similar cellular behaviors, such as transcription onset and cell shape. Our data suggest that cell–cell connectivity is maintained in early embryos through persistent bridge connections that allow cells to coordinate their behavior during embryonic development.
Cellulase immobilization on TEOS encapsulated and APTES functionalized magnetic nanoparticles (MNPs)
Authors: Samiur Rashid Shah , Hossain Sikder Md. Belal , Ab. Rahim Mohd Hasbi Bin , Nor Mazila Binti Ramli Aizi , Bin Roslan Rashidi 
Published: April 2021

Abstract
Immobilized enzymes are more stable and more resistant to environmental changes in contrast to free enzymes in solution. Magnetic nanoparticles (MNPs) are potential immobilization supports materials for enzymes and easily recovered for reuse. It has low toxicity effects and fast separation from reaction mixtures simply by use of external magnets. Enzyme immobilization technology also helps to boost the enzyme’s properties by using the technique to keep it in separate support or matrix. The aim of immobilization is to render the enzyme immobile so that it is reusable during the reaction, which leads to a more efficient process and easy separation from the substance. The aims of this investigation were to encapsulate (coat) and functionalize MNPs by using TEOS and APTES respectively for reusable cellulase immobilization on that as a supports matrix. The silicon encapsulation with TEOS and amino functionalization of synthesized MNPs was confirmed by the FT-IR and XRD. Cellulase was immobilized successfully on that nanoparticles and also confirmed by FT-IR, cellulase assay. The immobilized enzymes showed a satisfactory level of reusability (51%) after 10 consecutive reaction cycles.
The Efficient Resource Scheduling Strategy in Cloud: A Metaheuristic Approach
Authors: Maheshwari Shilpa , Shiwani Savita , Choudhary Surendra Singh 
Published: April 2021

Abstract
The cloud computing is evolving as a high-performance computing platform due to broad-scale, flexible computational architecture and heterogeneous collection of autonomous systems. Cloud technology uses concept of virtualization for managing resources, which develops resource scheduling as a key issue. The scheduling of cloud tasks is an NP-complete problem and therefore irreconcilable with particular solution. Also, with the huge collection of a database system, the management of resources and tasks becomes complex with specific to the completion time requirements and cost constraints. To resolve this problem, a number of meta-heuristic algorithms have been developed. Due to redundant wastage of resources and time, the under and over-provisioning is one kind of issues leads to either degradation in performance or wastage of cloud resources. To overcome these kinds of problems, we introduce a task scheduling approach by incorporating reinforcement learning along with the nature-inspired meta-heuristic optimization to maximizing cloud throughput, minimizing completion time & production cost in IaaS cloud. By reinforcement learning, the agent will choose appropriate action among a set of available actions and the scheduler succeeds towards task allocation resulted to decrease makespan and increasing system utilization rate.
Analysis of Machine Learning Techniques for Detection System for Web Applications Using Data Mining
Authors: Kumar Jugnesh , Goyal S B , Bedi Pradeep , Kumar Sunil , Shrivastava Ashish 
Published: April 2021

Abstract
Security is a key problem to each computer and computer networks. Intrusion detection System (IDS) is one of the most important research problems in community safety. IDSs are advanced to stumble on each acknowledged and unknown assaults. IDS employs many methods to secure information systems and networks against community-based and host-based threats. IDS utilises different machine learning methods. This thesis analyses IDS machine-learning methods. It also discusses several similar research completed between 2000 and 2012 and specialises in engineering techniques. Linked experiments include used unmarried, hybrid, ensemble, baseline, and datasets.
Influence of pre-loading on the flexural behaviour of annealed glass
Authors: Ravimony Raji , Joseph Anitha , Mangal Lalu 
Published: April 2021

Abstract
Transparency, a highly sought aspect in architectural applications, has led to rising demand for glass in buildings and other structures. The changeover of the role of architectural glass makes it inevitable to characterize the mechanical properties of glass as individually as has been done for all other conventional materials employed in structural applications. Thus the awareness of glass strength is vital for the design of transparent structures made of structural glass. The present work reports displacement-controlled four-point bending tests performed on a set of annealed glass specimens to study the effect of pre-loading value and its duration on the flexural behaviour. Analysis of variance is carried out in Minitab 19 to study the effect of pre-loading and thickness of glass on the failure stress ratio. Analysis of variance results show that pre-load is the most significant factor for the failure stress ratio.
Damage study in concrete subjected to various loading by monitoring the surface resistivity
Authors: Mathew Jeena , Vishnudas Subha 
Published: April 2021

Abstract
Detection of damages and cracks and their progress in concrete structure is a grave concern. Incipient damages are often not noticeable and hence visual inspections or using of low frequency response methods and other NDE techniques may not give a significant reflection on the same. Permitting the damages/cracks to progress until they are well noticeable and making an attempt to detect and restore the structure would be a serious threat to the reliability and service life of the structure at least in case of a strategically vital one. With the advantages of non-invasion, non-radiation, low-cost and high-speed, electrical resistance measurement is a promising technique in this regard. In this study an attempt is made to analyse the changes in electrical resistivity of concrete structural elements when subjected to different types of loading. Electrical resistivity measurements were carried out on specimens like cubes, beams and cylinders under the action of compressive, flexural and tensile load respectively. In addition, study was conducted on cubes under repeated cycles of compressive loading.
Machine learning applications in structural engineering - a review
Authors: Haneena Jasmine P , Arun S 
Published: April 2021

Abstract
Machine learning (ML) is a major subfield of artificial intelligence (AI) that provides systems, the ability to automatically learn and improve from experience without being explicitly programmed. With its ability to capture complex behaviour of structures and systems, ML has been proposed as a solution to overcome the limitations of conventional methods in Structural Engineering. This paper is an insight in to a few of such applications, based on neural networks, Support Vector Machines and Nearest Neighbours, projecting their accuracy in performance.