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Lei Song, Ying-Min Lu, Jin-Chun Zhang, Yu-Min Yuan, Gui-Ru Li Department of Cardiology, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences, Shanghai, 202150, People’s Republic of ChinaCorrespondence: Ying-Min Lu, Department of Cardiology, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences, No. 25 of Nanmen Street, Chengqiao Town, Chongming District, Shanghai, 202150, People’s Republic of China, Tel +86-18939929687, Email Lu_yingmin_2023@163.comObjective: To investigate the association of S100A12 protein and C-reactive protein (CRP) with the onset of malignant ventricular arrhythmias (MVA) after acute myocardial infarction (AMI) in the elderly.Methods: A total of 159 elderly AMI patients admitted to Chongming Hospital affiliated to Shanghai University of Medicine & Health Sciences from January 2018 to January 2023 were enrolled in the study. CRP levels were determined using an automatic biochemical analyzer, and S100A12 levels were measured using enzyme-linked immunosorbent assay (ELISA). Patients were categorized based on the Lown classification into groups without MVA and with MVA. Univariate analysis was initially performed to identify independent variables, followed by multivariate logistic regression to determine the risk factors for malignant ventricular arrhythmias post-AMI. The predictive value of S100A12 protein and CRP for malignant ventricular arrhythmias after acute myocardial infarction in the elderly was analyzed using the receiver operating characteristic (ROC) curve.Results: Among the 159 patients with AMI, 27 (17%) had MVA. Multivariate logistic regression analysis indicated that both S100A12 protein and CRP could be independent risk factors for malignant ventricular arrhythmias following acute myocardial infarction in the elderly (p

The development of any industry cannot be done without social expectations. The industrial metaverse arises from customers' emphasis on their value, their desire for immersive experiences, and their vision for untrammeled economic transactions. This paper first introduces the definition, propositions, and metrics of the industrial metaverse towards Industry 5.0. Then, based on the understanding of physical space, cyber space, and social space, this paper proposes a five-layer framework for the industrial metaverse, which covers the perception layer, networking layer, fusion layer, interaction layer, and configuration layer. Subsequently, this paper further analyzes the key enablers and potential application scenarios of the industrial metaverse towards Industry 5.0. The technical challenges at different levels and social barriers from different perspectives are discussed. Finally, this paper highlights future research directions for the industrial metaverse towards Industry 5.0. It is expected that this framework study will provide researchers with an overview of the industrial metaverse and a deeper understanding of its development potential and obstacles., QC 20240820

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and viewpoint-conditioned neural networks, 3D Gaussian Splatting utilizes a set of Gaussian ellipsoids to model the scene so that efficient rendering can be accomplished by rasterizing Gaussian ellipsoids into images. Apart from the fast rendering speed, the explicit representation of 3D Gaussian Splatting facilitates editing tasks like dynamic reconstruction, geometry editing, and physical simulation. Considering the rapid change and growing number of works in this field, we present a literature review of recent 3D Gaussian Splatting methods, which can be roughly classified into 3D reconstruction, 3D editing, and other downstream applications by functionality. Traditional point-based rendering methods and the rendering formulation of 3D Gaussian Splatting are also illustrated for a better understanding of this technique. This survey aims to help beginners get into this field quickly and provide experienced researchers with a comprehensive overview, which can stimulate the future development of the 3D Gaussian Splatting representation.

Neural implicit representations, including Neural Distance Fields and Neural Radiance Fields, have demonstrated significant capabilities for reconstructing surfaces with complicated geometry and topology, and generating novel views of a scene. Nevertheless, it is challenging for users to directly deform or manipulate these implicit representations with large deformations in the real-time fashion. Gaussian Splatting(GS) has recently become a promising method with explicit geometry for representing static scenes and facilitating high-quality and real-time synthesis of novel views. However,it cannot be easily deformed due to the use of discrete Gaussians and lack of explicit topology. To address this, we develop a novel GS-based method that enables interactive deformation. Our key idea is to design an innovative mesh-based GS representation, which is integrated into Gaussian learning and manipulation. 3D Gaussians are defined over an explicit mesh, and they are bound with each other: the rendering of 3D Gaussians guides the mesh face split for adaptive refinement, and the mesh face split directs the splitting of 3D Gaussians. Moreover, the explicit mesh constraints help regularize the Gaussian distribution, suppressing poor-quality Gaussians(e.g. misaligned Gaussians,long-narrow shaped Gaussians), thus enhancing visual quality and avoiding artifacts during deformation. Based on this representation, we further introduce a large-scale Gaussian deformation technique to enable deformable GS, which alters the parameters of 3D Gaussians according to the manipulation of the associated mesh. Our method benefits from existing mesh deformation datasets for more realistic data-driven Gaussian deformation. Extensive experiments show that our approach achieves high-quality reconstruction and effective deformation, while maintaining the promising rendering results at a high frame rate(65 FPS on average)., Comment: 11 pages, 7 figures

With the rapid development of XR, 3D generation and editing are becoming more and more important, among which, stylization is an important tool of 3D appearance editing. It can achieve consistent 3D artistic stylization given a single reference style image and thus is a user-friendly editing way. However, recent NeRF-based 3D stylization methods face efficiency issues that affect the actual user experience and the implicit nature limits its ability to transfer the geometric pattern styles. Additionally, the ability for artists to exert flexible control over stylized scenes is considered highly desirable, fostering an environment conducive to creative exploration. In this paper, we introduce StylizedGS, a 3D neural style transfer framework with adaptable control over perceptual factors based on 3D Gaussian Splatting (3DGS) representation. The 3DGS brings the benefits of high efficiency. We propose a GS filter to eliminate floaters in the reconstruction which affects the stylization effects before stylization. Then the nearest neighbor-based style loss is introduced to achieve stylization by fine-tuning the geometry and color parameters of 3DGS, while a depth preservation loss with other regularizations is proposed to prevent the tampering of geometry content. Moreover, facilitated by specially designed losses, StylizedGS enables users to control color, stylized scale and regions during the stylization to possess customized capabilities. Our method can attain high-quality stylization results characterized by faithful brushstrokes and geometric consistency with flexible controls. Extensive experiments across various scenes and styles demonstrate the effectiveness and efficiency of our method concerning both stylization quality and inference FPS.

Streptococcus agalactiae (GBS) is an important Gram-positive pathogen of fish aquaculture worldwide. In this study, we performed a comparative analysis of GBS S03 (serotype III) and S07 (serotype Ia) isolated from Schizothorax spp.. We explored the association between phenotypic antibiotic resistance, virulence, and genomic characteristics. Antimicrobial sensitivity tests on 12 common antibiotics using the disc diffusion method revealed that the GBS S03 resisted seven antibiotics, while GBS S07 showed sensitivity to eleven antibiotics. Pathogenicity analysis demonstrated greater virulence of GBS S07 than S03. Then, the occurrence of antibiotic resistance and virulence genes were identified using the whole-genome sequence (WGS) of GBS S03 and GBS S07. Besides just GBS S03 had gyrA and parC gene mutations, there were mefE, tetO, lnuB, lsaE, APH3', and sat-4 resistance genes present only in GBS S03 genome. In addition to 51 virulence genes in both GBS S03 and S07 genomes, GBS S07 carried virulence genes associated with invasion, such as SAN1519, rfbA and cylE_ genes. There was complete concordance between genotypic evidence and phenotypic characteristics. Virulence factors and phylogenetic analysis showed that GBS S03 and human sources shared an extremely close evolutionary relationship. Our findings also provide important proof for using WGS as an effective tool for phenotypic predictions of GBS.

Yu-Guo Yuan,1,2,* Ya-Xin Zhang,1,* Song-Zi Liu,1,* Abu Musa Md Talimur Reza,3 Jia-Lin Wang,1,2 Ling Li,1,2 He-Qing Cai,1,2 Ping Zhong,1 Il-Keun Kong4 1College of Veterinary Medicine, Yangzhou University, Yangzhou, People’s Republic of China; 2Jiangsu Co-Innovation Center of Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, People’s Republic of China; 3Department of Molecular Biology and Genetics Faculty of Basic Sciences, Gebze Technical University, Kocaeli, Republic of Turkiye; 4Division of Applied Life Science (BK21 Four), Institute of Agriculture and Life Science, Gyeongsang National University, Jinju, Gyeongnam Province, Republic of Korea*These authors contributed equally to this workCorrespondence: Yu-Guo Yuan; Il-Keun Kong, Email yyg9776430@163.com; ikong7900@gmail.comIntroduction: The increasing industrial and biomedical utilization of graphene oxide silver nanoparticles (GO-AgNPs) raises the concern of nanosafety: exposure to the AgNPs or GO-AgNPs increases the generation of reactive oxygen species (ROS), causes DNA damage and alters the expression of whole transcriptome including mRNA, miRNA, tRNA, lncRNA, circRNA and others. Although the roles of different RNAs in epigenetic toxicity are being studied during the last decade, but still we have little knowledge about the role of circle RNAs (circRNAs) in epigenetic toxicity.Methods: Rabbit fetal fibroblast cells (RFFCs) were treated with 0, 8, 16, 24, 32 and 48 μg/mL GO-AgNPs to test the cell viability and 24 μg/mL GO-AgNPs was selected as the experimental dose. After 24 h treatment with 24 μg/mL GO-AgNPs, the level of ROS, malondialdehyde (MDA), superoxide dismutase (SOD), intracellular ATP, glutathione peroxidase (GPx), and glutathione reductase (Gr) were measured in the RFFCs. High-throughput whole transcriptome sequencing was performed to compare the expression of circRNAs, long non-coding RNAs (lncRNA) and m

Yu-Guo Yuan,1,2 Jia-Lin Wang,1,2 Ya-Xin Zhang,1,2 Ling Li,1,2 Abu Musa Md Talimur Reza,3 Sangiliyandi Gurunathan4 1Department of Clinical Veterinary Medicine, College of Veterinary Medicine, Yangzhou University, Yangzhou, Jiangsu, People’s Republic of China; 2Jiangsu Co-Innovation Center of Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, Jiangsu, People’s Republic of China; 3Department of Molecular Biology and Genetics, Faculty of Science, Gebze Technical University, Gebze, Kocaeli, Türkiye; 4Department of Biotechnology, Rathinam College of Arts and Science, Coimbatore, TN, IndiaCorrespondence: Yu-Guo Yuan; Sangiliyandi Gurunathan, Email yyg9776430@163.com; gsangiliyandi@yahoo.comAbstract: Exosomes are nanovesicles with a wide range of chemical compositions used in many different applications. Mesenchymal stem cell-derived exosomes (MSCs-EXOs) are spherical vesicles that have been shown to mediate tissue regeneration in a variety of diseases, including neurological, autoimmune and inflammatory, cancer, ischemic heart disease, lung injury, and liver fibrosis. They can modulate the immune response by interacting with immune effector cells due to the presence of anti-inflammatory compounds and are involved in intercellular communication through various types of cargo. MSCs-EXOs exhibit cytokine storm-mitigating properties in response to COVID-19. This review discussed the potential function of MSCs-EXOs in a variety of diseases including neurological, notably epileptic encephalopathy and Parkinson’s disease, cancer, angiogenesis, autoimmune and inflammatory diseases. We provided an overview of exosome biogenesis and factors that regulate exosome biogenesis. Additionally, we highlight the functions and potential use of MSCs-EXOs in the treatment of the inflammatory disease COVID-19. Finally, we covered a strategies and challenges of MSCs-EXOs. Finally, we discuss conclusion and future perspectives of MSC

Aiming at improving the survey efficiency of the Wide Field Survey Telescope, we have developed a basic scheduling strategy that takes into account the telescope characteristics, observing conditions, and weather conditions at the Lenghu site. The sky area is divided into rectangular regions, referred to as `tiles', with a size of 2.577 deg * 2.634 deg slightly smaller than the focal area of the mosaic CCDs. These tiles are continuously filled in annulars parallel to the equator. The brightness of the sky background, which varies with the moon phase and distance from the moon, plays a significant role in determining the accessible survey fields. Approximately 50 connected tiles are grouped into one block for observation. To optimize the survey schedule, we perform simulations by taking into account the length of exposures, data readout, telescope slewing, and all relevant observing conditions. We utilize the Greedy Algorithm for scheduling optimization. Additionally, we propose a dedicated dithering pattern to cover the gaps between CCDs and the four corners of the mosaic CCD array, which are located outside of the 3 deg field of view. This dithering pattern helps to achieve relatively uniform exposure maps for the final survey outputs., Comment: 14 pages, 7 figures, 1 table. Accepted for pubulication in Research in Astronomy and Astrophysics

Lysosomes and the endoplasmic reticulum (ER) are Ca2+ stores mobilized by the second messengers NAADP and IP3, respectively. Here, we establish Ca2+ signals between the two sources as fundamental building blocks that couple local release to global changes in Ca2+. Cell-wide Ca2+ signals evoked by activation of endogenous NAADP-sensitive channels on lysosomes comprise both local and global components and exhibit a major dependence on ER Ca2+ despite their lysosomal origin. Knockout of ER IP3 receptor channels delays these signals, whereas expression of lysosomal TPC2 channels accelerates them. High-resolution Ca2+ imaging reveals elementary events upon TPC2 opening and signals coupled to IP3 receptors. Biasing TPC2 activation to a Ca2+-permeable state sensitizes local Ca2+ signals to IP3. This increases the potency of a physiological agonist to evoke global Ca2+ signals and activate a downstream target. Our data provide a conceptual framework to understand how Ca2+ release from physically separated stores is coordinated.

Job-shop scheduling problem (JSP) is a mathematical optimization problem widely used in industries like manufacturing, and flexible JSP (FJSP) is also a common variant. Since they are NP-hard, it is intractable to find the optimal solution for all cases within reasonable times. Thus, it becomes important to develop efficient heuristics to solve JSP/FJSP. A kind of method of solving scheduling problems is construction heuristics, which constructs scheduling solutions via heuristics. Recently, many methods for construction heuristics leverage deep reinforcement learning (DRL) with graph neural networks (GNN). In this paper, we propose a new approach, named residual scheduling, to solving JSP/FJSP. In this new approach, we remove irrelevant machines and jobs such as those finished, such that the states include the remaining (or relevant) machines and jobs only. Our experiments show that our approach reaches state-of-the-art (SOTA) among all known construction heuristics on most well-known open JSP and FJSP benchmarks. In addition, we also observe that even though our model is trained for scheduling problems of smaller sizes, our method still performs well for scheduling problems of large sizes. Interestingly in our experiments, our approach even reaches zero gap for 49 among 50 JSP instances whose job numbers are more than 150 on 20 machines.

Pure electric vehicles (PEVs) are increasingly adopted to decarbonize the transport sector and mitigate global warming. However, the inadequate PEV charging infrastructure may hinder the further adoption of PEVs in the large-scale traffic network, which calls for effective planning solutions for the charging station (CS) placement. The deployment of charging infrastructure inevitably increases the load on the associated power distribution network. Therefore, we are motivated to develop a comprehensive multi-objective framework for optimal CS placement in a traffic network overlaid by a distribution network, considering multiple stakeholders' interested factors, such as traffic flow, PEV charging time cost, PEV travel distance, and the reliability of the distribution network. We leverage a cross-entropy-based method to solve the optimal CS placement and evaluate our method in a real-world 183-node traffic network in Chengdu, China, overlaid by a 26-region distribution network. It is demonstrated that our work provides various viable planning options favoring different objectives for the stakeholders' decision-making in practice., Comment: IEEE I&CPS Asia 2023 (2023 IEEE IAS Industrial and Commercial Power System Asia Conference)

BackgroundMuscle denervation from trauma and motor neuron disease causes disabling morbidities. A limiting step in functional recovery is the regeneration of neuromuscular junctions (NMJs) for reinnervation. Stem cells have the potential to promote these regenerative processes, but current approaches have limited success, and the optimal types of stem cells remain to be determined. Neural crest stem cells (NCSCs), as the developmental precursors of the peripheral nervous system, are uniquely advantageous, but the role of NCSCs in neuromuscular regeneration is not clear. Furthermore, a cell delivery approach that can maintain NCSC survival upon transplantation is critical.MethodsWe established a streamlined protocol to derive, isolate, and characterize functional p75+ NCSCs from human iPSCs without genome integration of reprogramming factors. To enhance survival rate upon delivery in vivo, NCSCs were centrifuged in microwell plates to form spheroids of desirable size by controlling suspension cell density. Human bone marrow mesenchymal stem cells (MSCs) were also studied for comparison. NCSC or MSC spheroids were injected into the gastrocnemius muscle with denervation injury, and the effects on NMJ formation and functional recovery were investigated. The spheroids were also co-cultured with engineered neuromuscular tissue to assess effects on NMJ formation in vitro.ResultsNCSCs cultured in spheroids displayed enhanced secretion of soluble factors involved in neuromuscular regeneration. Intramuscular transplantation of spheroids enabled long-term survival and retention of NCSCs, in contrast to the transplantation of single-cell suspensions. Furthermore, NCSC spheroids significantly improved functional recovery after four weeks as shown by gait analysis, electrophysiology, and the rate of NMJ innervation. MSC spheroids, on the other hand, had insignificant effect. In vitro co-culture of NCSC or MSC spheroids with engineered myotubes and motor neurons further evide

Electroceuticals provide promising opportunities for peripheral nerve regeneration, in terms of modulating the extensive endogenous tissue repair mechanisms between neural cell body, axons and target muscles. However, great challenges remain to deliver effective and controllable electroceuticals via bioelectronic implantable device. In this review, the modern fabrication methods of bioelectronic conduit for bridging critical nerve gaps after nerve injury are summarized, with regard to conductive materials and core manufacturing process. In addition, to deliver versatile electrical stimulation, the integration of implantable bioelectronic device is discussed, including wireless energy harvesters, actuators and sensors. Moreover, a comprehensive insight of beneficial mechanisms is presented, including up-to-datein vitro, in vivoand clinical evidence. By integrating conductive biomaterials, 3D engineering manufacturing process and bioelectronic platform to deliver versatile electroceuticals, the modern biofabrication enables comprehensive biomimetic therapies for neural tissue engineering and regeneration in the new era.

We propose the term and concept XV (eXtended meta/omni/uni/Verse) as an alternative to, and generalization of, the shared/social virtual reality widely known as ``metaverse''. XV is shared/social XR. We, and many others, use XR (eXtended Reality) as a broad umbrella term and concept to encompass all the other realities, where X is an ``anything'' variable, like in mathematics, to denote any reality, X $\in$ \{physical, virtual, augmented, \ldots \} reality. Therefore XV inherits this generality from XR. We begin with a very simple organized taxonomy of all these realities in terms of two simple building blocks: (1) physical reality (PR) as made of ``atoms'', and (2) virtual reality (VR) as made of ``bits''. Next we introduce XV as combining all these realities with extended society as a three-dimensional space and taxonomy of (1) ``atoms'' (physical reality), (2) ``bits'' (virtuality), and (3) ``genes'' (sociality). Thus those working in the liminal space between Virtual Reality (VR), Augmented Reality (AR), metaverse, and their various extensions, can describe their work and research as existing in the new field of XV. XV includes the metaverse along with extensions of reality itself like shared seeing in the infrared, ultraviolet, and shared seeing of electromagnetic radio waves, sound waves, and electric currents in motors. For example, workers in a mechanical room can look at a pump and see a superimposed time-varying waveform of the actual rotating magnetic field inside its motor, in real time, while sharing this vision across multiple sites. Presented at IEEE Standards Association, Behind and Beyond the Metaverse: XV (eXtended meta/uni/Verse), Thurs. Dec. 8, 2022, 2:15-3:30pm, EST., Comment: 9 pages, 10 figures, presented at the IEEE Standards Association panel entitled "Behind and Beyond the Metaverse", Thurs. Dec. 8th, 2022. This work is entitled "Beyond the Metaverse: XV (eXtended meta/uni/Verse)" and was presented that day from 2:15pm to 3:30pm EST (Eastern Standard Time)

Eliminating ghosting artifacts due to moving objects is a challenging problem in high dynamic range (HDR) imaging. In this letter, we present a hybrid model consisting of a convolutional encoder and a Transformer decoder to generate ghost-free HDR images. In the encoder, a context aggregation network and non-local attention block are adopted to optimize multi-scale features and capture both global and local dependencies of multiple low dynamic range (LDR) images. The decoder based on Swin Transformer is utilized to improve the reconstruction capability of the proposed model. Motivated by the phenomenal difference between the presence and absence of artifacts under the field of structure tensor (ST), we integrate the ST information of LDR images as auxiliary inputs of the network and use ST loss to further constrain artifacts. Different from previous approaches, our network is capable of processing an arbitrary number of input LDR images. Qualitative and quantitative experiments demonstrate the effectiveness of the proposed method by comparing it with existing state-of-the-art HDR deghosting models. Codes are available at https://github.com/pandayuanyu/HSTHdr.

Capturing highly appreciated star field images is extremely challenging due to light pollution, the requirements of specialized hardware, and the high level of photographic skills needed. Deep learning-based techniques have achieved remarkable results in low-light image enhancement (LLIE) but have not been widely applied to star field image enhancement due to the lack of training data. To address this problem, we construct the first Star Field Image Enhancement Benchmark (SFIEB) that contains 355 real-shot and 854 semi-synthetic star field images, all having the corresponding reference images. Using the presented dataset, we propose the first star field image enhancement approach, namely StarDiffusion, based on conditional denoising diffusion probabilistic models (DDPM). We introduce dynamic stochastic corruptions to the inputs of conditional DDPM to improve the performance and generalization of the network on our small-scale dataset. Experiments show promising results of our method, which outperforms state-of-the-art low-light image enhancement algorithms. The dataset and codes will be open-sourced.

A large amount of data has been accumulated. with the development of the Internet industry. Many problems have been exposed with data explosion: 1. The contradiction between data privacy and data collaborations; 2. The contradiction between data ownership and the right of data usage; 3. The legality of data collection and data usage; 4. The relationship between the governance of data and the governance of rules; 5. Traceability of evidence chain. In order to face such a complicated situation, many algorithms were proposed and developed. This article tries to build a model from the perspective of blockchain to make some breakthroughs.Internet Of Rights(IOR) model uses multi-chain technology to logically break down the consensus mechanism into layers, including storage consensus, permission consensus, role consensus, transaction consensus etc. thus to build a new infrastructure, which enables data sources with complex organizational structures and interactions to collaborate smoothly on the premise of protecting data privacy. With blockchain's nature of decentralization, openness, autonomy, immutability, and controllable anonymity, Internet Of Rights(IOR) model registers the ownership of data, enables applications to build ecosystem based on responsibilities and rights. It also provides cross-domain processing with privacy protection, as well as the separation of data governance and rule governance. With the processing capabilities of artificial intelligence and big data technology, as well as the ubiquitous data collection capabilities of the Internet of Things, Internet Of Rights(IOR) model may provide a new infrastructure concept for realizing swarm intelligence and building a new paradigm of the Internet, i.e. intelligent governance.

The fusion of images taken by heterogeneous sensors helps to enrich the information and improve the quality of imaging. In this article, we present a hybrid model consisting of a convolutional encoder and a Transformer-based decoder to fuse multimodal images. In the encoder, a non-local cross-modal attention block is proposed to capture both local and global dependencies of multiple source images. A branch fusion module is designed to adaptively fuse the features of the two branches. We embed a Transformer module with linear complexity in the decoder to enhance the reconstruction capability of the proposed network. Qualitative and quantitative experiments demonstrate the effectiveness of the proposed method by comparing it with existing state-of-the-art fusion models. The source code of our work is available at https://github.com/pandayuanyu/HCFusion.

3D scene stylization aims at generating stylized images of the scene from arbitrary novel views following a given set of style examples, while ensuring consistency when rendered from different views. Directly applying methods for image or video stylization to 3D scenes cannot achieve such consistency. Thanks to recently proposed neural radiance fields (NeRF), we are able to represent a 3D scene in a consistent way. Consistent 3D scene stylization can be effectively achieved by stylizing the corresponding NeRF. However, there is a significant domain gap between style examples which are 2D images and NeRF which is an implicit volumetric representation. To address this problem, we propose a novel mutual learning framework for 3D scene stylization that combines a 2D image stylization network and NeRF to fuse the stylization ability of 2D stylization network with the 3D consistency of NeRF. We first pre-train a standard NeRF of the 3D scene to be stylized and replace its color prediction module with a style network to obtain a stylized NeRF. It is followed by distilling the prior knowledge of spatial consistency from NeRF to the 2D stylization network through an introduced consistency loss. We also introduce a mimic loss to supervise the mutual learning of the NeRF style module and fine-tune the 2D stylization decoder. In order to further make our model handle ambiguities of 2D stylization results, we introduce learnable latent codes that obey the probability distributions conditioned on the style. They are attached to training samples as conditional inputs to better learn the style module in our novel stylized NeRF. Experimental results demonstrate that our method is superior to existing approaches in both visual quality and long-range consistency., Comment: Accepted by CVPR 2022

Implicit neural rendering, especially Neural Radiance Field (NeRF), has shown great potential in novel view synthesis of a scene. However, current NeRF-based methods cannot enable users to perform user-controlled shape deformation in the scene. While existing works have proposed some approaches to modify the radiance field according to the user's constraints, the modification is limited to color editing or object translation and rotation. In this paper, we propose a method that allows users to perform controllable shape deformation on the implicit representation of the scene, and synthesizes the novel view images of the edited scene without re-training the network. Specifically, we establish a correspondence between the extracted explicit mesh representation and the implicit neural representation of the target scene. Users can first utilize well-developed mesh-based deformation methods to deform the mesh representation of the scene. Our method then utilizes user edits from the mesh representation to bend the camera rays by introducing a tetrahedra mesh as a proxy, obtaining the rendering results of the edited scene. Extensive experiments demonstrate that our framework can achieve ideal editing results not only on synthetic data, but also on real scenes captured by users., Comment: Accepted by CVPR 2022

In this work, the support vector machine (SVM) method is adopted to separate BL Lacertae objects (BL Lacs) and flat spectrum radio quasars (FSRQs) in the plots of photon spectrum index against the photon flux, $\alpha_{\rm ph} \sim {\rm log}\,F$, that of photon spectrum index against the variability index, $\alpha_{\rm ph} \sim {\rm log}\, \textit{V\!I}$, and that of variability index against the photon flux, ${\rm log}\,{V\!I} \sim {\rm log}\,F$. Then we used the dividing lines to tell BL Lacs from FSRQs in the blazars candidates of uncertain types from \textit{Fermi}/LAT catalogue. Our main conclusions are: 1. We separate BL Lacs and FSRQs by $\alpha_{\rm ph} = -0.123\,{\rm log}\,F + 1.170$ in the $\alpha_{\rm ph} \sim {\rm log}\,F$ plot, $\alpha_{\rm ph} = -0.161\,{\rm log}\,{V\!I} + 2.594$ in the $\alpha_{\rm ph} \sim {\rm log}\,{V\!I}$ plot, and ${\rm log}\,{V\!I} = 0.792\,{\rm log}\,F + 9.203$ in the ${\rm log}\,{V\!I} \sim {\rm log}\,F$ plot. 2. We obtained 932 BL Lac candidates and possible BL Lac candidates, and 585 FSRQ candidates and possible FSRQ candidates. 3. Some discussions are given for comparisons with those in literature., Comment: Accepted to Universe

Ling-Ling Xu,1– 4,* Yao Yan,1– 3,* Yu-Min Yuan,1– 3 Ying Li,1– 3 Jun Jiang,1– 3 Li-Cai Zhang1– 3 1Jiangsu Province Key Laboratory of Anesthesiology, Xuzhou Medical University, Xuzhou, People’s Republic of China; 2Jiangsu Province Key Laboratory of Anesthesia and Analgesia Application Technology, Xuzhou Medical University, Xuzhou, People’s Republic of China; 3NMPA Key Laboratory for Research and Evaluation of Narcotic and Psychotropic Drugs, Xuzhou, People’s Republic of China; 4Department of Anesthesiology, Nanjing Gaochun People’s Hospital, Nanjing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Li-Cai Zhang, Email licaizhang001@163.comObjective: To assess the receptors of TRPV1 and GABAB1 receptors that were colocalized in cerebrospinal fluid contacting nucleus (CSF-contact nucleus) of chronic inflammatory pain (CIP) rats bringing inspiration for reducing chronic pain.Methods: A rat model of CIP was constructed by plantar injection of complete Freund’s adjuvant (CFA), and the paw withdrawal mechanical threshold (PWMT) and paw withdrawal thermal latency (PWTL) were measured 1, 3, 5, 7, 10, and 14 days after plantar injection. In the first part of the experiment, rats with CIP were divided into the immunofluorescence group and the coimmunoprecipitation (Co-IP) group (n = 6). Rats in the immunofluorescence group were injected with the retrograde tracer CB conjugated with Alexa Fluor 594 into the lateral ventricle two days before the injection of CFA into the plantar surface of the left paw. Three days later, rats that exhibited hyperalgesia were perfused, and their brains were extracted and used for double immunofluorescence staining of the CSF-contacting nucleus. Rats in the Co-IP group were anesthetized and dissected 3 days after CFA injection, and fresh brain segments containing the CSF-contacting nucleus were collected for Co-IP to assess the colocalization of TRPV1 and GABAB

Muscle loss and impairment resulting from traumatic injury can be alleviated by therapies using muscle stem cells. However, collecting sufficient numbers of autologous myogenic stem cells and expanding them efficiently has been challenging. Here we show that myogenic stem cells (predominantly Pax7+ cells)-which were selectively expanded from readily obtainable dermal fibroblasts or skeletal muscle stem cells using a specific cocktail of small molecules and transplanted into muscle injuries in adult, aged or dystrophic mice-led to functional muscle regeneration in the three animal models. We also show that sustained release of the small-molecule cocktail in situ through polymer nanoparticles led to muscle repair by inducing robust activation and expansion of resident satellite cells. Chemically induced stem cell expansion in vitro and in situ may prove to be advantageous for stem cell therapies that aim to regenerate skeletal muscle and other tissues.

Since the 90s, keyword-based search engines have been helping people locate relevant web content via a simple query, so have the recent full-text-based search engines mainly used for plagiarism detection following an article upload. However, these "free" or paid services operate by storing users' search queries and preferences for personal profiling and targeted ads delivery, while user-uploaded articles can further profit the service providers as part of their expanding databases. In short, search engine privacy has not been an option for web exploration in the past decades. Here we demonstrate that a database or internet search, provided with the entire article as a query, can be correctly carried out without revealing users' sensitive queries by an irreversible encoding scheme and an efficient FM-index search routine that is generally used in the NGS of genomes. In our solution, Sapiens Aperio Veritas Engine (S.A.V.E.), every word in the query is encoded into one of 12 "amino acids" (a.a.) comprising a pseudo-biological sequence (PBS) at users' local machines. The PBS-mediated plagiarism detection is done by users' submission of locally encoded PBS through our cloud service to locate identical duplicates in the collected web contents which had been encoded in the same way as the query. It is found that PBSs with a length longer than 12 a.a., can return correct results with a false positive rate <0.8%. S.A.V.E. runs at a similar speed as Bowtie and is 4 orders faster than BLAST. S.A.V.E., functioning in both regular and in-private search modes, provides a new option for efficient internet search and plagiarism detection in a compressed search space without a chance of storing and revealing users' confidential contents. We expect that future privacy-aware search engines can reference the ideas proposed herein. S.A.V.E. is made available at https://dyn.life.nthu.edu.tw/SAVE, Comment: 21 pages, 5 figures, 3 tables

3D shape editing is widely used in a range of applications such as movie production, computer games and computer aided design. It is also a popular research topic in computer graphics and computer vision. In past decades, researchers have developed a series of editing methods to make the editing process faster, more robust, and more reliable. Traditionally, the deformed shape is determined by the optimal transformation and weights for an energy term. With increasing availability of 3D shapes on the Internet, data-driven methods were proposed to improve the editing results. More recently as the deep neural networks became popular, many deep learning based editing methods have been developed in this field, which is naturally data-driven. We mainly survey recent research works from the geometric viewpoint to those emerging neural deformation techniques and categorize them into organic shape editing methods and man-made model editing methods. Both traditional methods and recent neural network based methods are reviewed.

3D shape analysis is an important research topic in computer vision and graphics. While existing methods have generalized image-based deep learning to meshes using graph-based convolutions, the lack of an effective pooling operation restricts the learning capability of their networks. In this paper, we propose a novel pooling operation for mesh datasets with the same connectivity but different geometry, by building a mesh hierarchy using mesh simplification. For this purpose, we develop a modified mesh simplification method to avoid generating highly irregularly sized triangles. Our pooling operation effectively encodes the correspondence between coarser and finer meshes in the hierarchy. We then present a variational auto-encoder (VAE) structure with the edge contraction pooling and graph-based convolutions, to explore probability latent spaces of 3D surfaces and perform 3D shape generation. Our network requires far fewer parameters than the original mesh VAE and thus can handle denser models thanks to our new pooling operation and convolutional kernels. Our evaluation also shows that our method has better generalization ability and is more reliable in various applications, including shape generation and shape interpolation. © 2020 IEEE.

Bioresorbable electronic stimulators are of rapidly growing interest as unusual therapeutic platforms, i.e., bioelectronic medicines, for treating disease states, accelerating wound healing processes and eliminating infections. Here, we present advanced materials that support operation in these systems over clinically relevant timeframes, ultimately bioresorbing harmlessly to benign products without residues, to eliminate the need for surgical extraction. Our findings overcome key challenges of bioresorbable electronic devices by realizing lifetimes that match clinical needs. The devices exploit a bioresorbable dynamic covalent polymer that facilitates tight bonding to itself and other surfaces, as a soft, elastic substrate and encapsulation coating for wireless electronic components. We describe the underlying features and chemical design considerations for this polymer, and the biocompatibility of its constituent materials. In devices with optimized, wireless designs, these polymers enable stable, long-lived operation as distal stimulators in a rat model of peripheral nerve injuries, thereby demonstrating the potential of programmable long-term electrical stimulation for maintaining muscle receptivity and enhancing functional recovery.

The exact relationship between the long gamma-ray burst (LGRB) rate and the cosmic star formation rate (CSFR) is essential for using LGRBs as cosmological probes. In this work, we collect a large sample composed of 371 Swift LGRBs with known redshifts and prompt emission properties. We first compare the rest-frame prompt properties of these bursts in different redshift bins, finding negligible redshift evolution of the luminosity of LGRBs with $L_{\mathrm{iso}}\gtrsim10^{51}\,\mathrm{erg\, s^{-1}}$ between $z\sim1$ and $z\sim4$. Then, by utilizing the CSFR obtained from the large-scale cosmological hydrodynamical simulation, the Illustris simulation, we calculate the cumulative redshift distribution of LGRBs under different metallicity thresholds. After comparing with our sample, we find that the predictions with a moderate threshold between $0.3\,Z_{\odot}\leqslant Z_{\mathrm{th}}\leqslant1.0\,Z_{\odot}$ are consistent with the sample between redshift $0

Cell reprogramming is a revolutionized biotechnology that offers a powerful tool to engineer cell fate and function for regenerative medicine, disease modeling, drug discovery, and beyond. Leveraging advances in biomaterials and micro/nanotechnologies can enhance the reprogramming performance in vitro and in vivo through the development of delivery strategies and the control of biophysical and biochemical cues. In this review, we present an overview of the state-of-the-art technologies for cell reprogramming and highlight the recent breakthroughs in engineering biomaterials with micro/nanotechnologies to improve reprogramming efficiency and quality. Finally, we discuss future directions and challenges for reprogramming technologies and clinical translation.

This paper explores the use of Deep Learning methods for automatic estimation of quality of human translations. Automatic estimation can provide useful feedback for translation teaching, examination and quality control. Conventional methods for solving this task rely on manually engineered features and external knowledge. This paper presents an end-to-end neural model without feature engineering, incorporating a cross attention mechanism to detect which parts in sentence pairs are most relevant for assessing quality. Another contribution concerns of prediction of fine-grained scores for measuring different aspects of translation quality. Empirical results on a large human annotated dataset show that the neural model outperforms feature-based methods significantly. The dataset and the tools are available.

We introduce TM-NET, a novel deep generative model for synthesizing textured meshes in a part-aware manner. Once trained, the network can generate novel textured meshes from scratch or predict textures for a given 3D mesh, without image guidance. Plausible and diverse textures can be generated for the same mesh part, while texture compatibility between parts in the same shape is achieved via conditional generation. Specifically, our method produces texture maps for individual shape parts, each as a deformable box, leading to a natural UV map with minimal distortion. The network separately embeds part geometry (via a PartVAE) and part texture (via a TextureVAE) into their respective latent spaces, so as to facilitate learning texture probability distributions conditioned on geometry. We introduce a conditional autoregressive model for texture generation, which can be conditioned on both part geometry and textures already generated for other parts to achieve texture compatibility. To produce high-frequency texture details, our TextureVAE operates in a high-dimensional latent space via dictionary-based vector quantization. We also exploit transparencies in the texture as an effective means to model complex shape structures including topological details. Extensive experiments demonstrate the plausibility, quality, and diversity of the textures and geometries generated by our network, while avoiding inconsistency issues that are common to novel view synthesis methods.

Rui Xiong, 1 Tao Yin, 2, 3 Jian-long Gao, 2, 3 Yu-feng Yuan 1 1Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, Hubei Province, People’s Republic of China; 2Department of Hepatobiliary and Pancreatic Surgery, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, People’s Republic of China; 3Seventh Clinical Medical College, Huazhong University of Science and Technology, Wuhan 430079, Hubei Province, People’s Republic of ChinaCorrespondence: Yu-feng YuanZhongnan Hospital of Wuhan University, No. 169 of Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, People’s Republic of ChinaEmail znyuanyufeng@163.comBackground: Gastric cancer (GC) is the most common malignant tumor of the digestive tract and its molecular mechanism is not clear. HOXD9 plays an important role in tumor progression as transcription factor. In the current study, we explored the role of HOXD9 in GC.Methods: We predicted the expression and potential mechanism of HOXD9 in GC through an online database. The expression of HOXD9 was detected in GC and adjacent tissues, and then we analyzed the relationship between HOXD9 and the prognosis of patients with GC. In vitro, we investigated the effects of HOXD9 on malignant biological behaviors such as proliferation, migration, and invasion of the GC cell line MCG-803. In addition, we have initially studied the underlying mechanism by Western blot.Results: High expression of HOXD9 in GC was predicted by online database prediction and implied poor prognosis. In the clinical sample, we confirmed the above predictions. In vitro, we found that knockdown of HOXD9 could effectively inhibit the proliferation, migration, and invasion of GC cells. In terms of mechanism, HOXD9 may activate the TGF-β/Smad signaling pathway.Conclusion: HOXD9 promotes the malignant biological process of GC, whi

Lichen planus (LP) of the eyelid is an under-reportedmanifestation of a common inflammatory condition.To the best of our knowledge fewer than 20 cases ofeyelid LP have been described in the English literature.We report a case of a 29-year-old woman whopresented with 3-month history of bilateral eyelidpruritic violaceous papules and similar lesions on herchest and lower extremity. Histology examinationrevealed characteristic findings and a diagnosisof LP was established. This report further reviewsthe previously reported 18 cases and discussesmanagement strategies.

Leukemia cutis (LC) is an extramedullary manifestationof leukemia owing to cutaneous infiltration ofneoplastic cells resulting in characteristic firm,erythematous nodules. Most cases of LC occur inpatients with acute myelogenous leukemia andchronic myelogenous leukemia. However in rarecases, LC has presented in patients with acutelymphoblastic leukemia (ALL). In these rare ALLassociatedcases, only 10 cases of precursor-B-ALL(pre-B-ALL) have been described in the literature.We report a case of a 22-year-old man with relapsingpre-B-ALL who presented with a 4-day history ofmultiple asymptomatic, soft, dome-shaped, lipomalikemounds on his scalp and chin, which exhibitedcutaneous involvement by leukemic cells. To date, thisis the first case of pre-B-ALL associated leukemia cutispresenting as soft, dome-shaped mounds resemblinglipomas.

We introduce SDM-NET, a deep generative neural network which produces structured deformable meshes. Specifically, the network is trained to generate a spatial arrangement of closed, deformable mesh parts, which respects the global part structure of a shape collection, e.g., chairs, airplanes, etc. Our key observation is that while the overall structure of a 3D shape can be complex, the shape can usually be decomposed into a set of parts, each homeomorphic to a box, and the finer-scale geometry of the part can be recovered by deforming the box. The architecture of SDM-NET is that of a two-level variational autoencoder (VAE). At the part level, a PartVAE learns a deformable model of part geometries. At the structural level, we train a Structured Parts VAE (SP-VAE), which jointly learns the part structure of a shape collection and the part geometries, ensuring the coherence between global shape structure and surface details. Through extensive experiments and comparisons with the state-of-the-art deep generative models of shapes, we demonstrate the superiority of SDM-NET in generating meshes with visual quality, flexible topology, and meaningful structures, benefiting shape interpolation and other subsequent modeling tasks. © 2019 Association for Computing Machinery.

Tomato fruit are especially susceptible to chilling injury (CI) when continuously exposed to temperatures below 12 °C. In this study, integrative comparative analyses of transcriptomics and metabolomics data were performed to uncover the regulatory network in CI tomato fruit. Metabolite profiling analysis found that 7 amino acids, 27 organic acids, 16 of sugars and 22 other compounds had a significantly different content while transcriptomics data showed 1735 differentially expressed genes (DEGs) were down-regulated and 1369 were up-regulated in cold-stored fruit. We found that the contents of citrate, cis-aconitate and succinate were increased, which were consistent with the expression of ATP-citrate synthase (ACS) and isocitrate dehydrogenase (IDH) genes in cold-treated tomato fruit. Cold stress promotes the expression of ACS and IDH which may increase the synthesis of citrate, cis-aconitate and succinate. Alanine and leucine had increased contents, which may result from alanine aminotransferase (ALT) and branched-chain amino acid aminotransferase (BcAT)'s high expression levels, respectively. Overall the transcriptomics and metabolomics data in our study explain the molecular mechanisms of the chilling injury and expands our understanding of the complex regulatory mechanisms of a metabolic network in response to chilling injury in tomato fruit.

BackgroundNeurovascular unit restoration is crucial for nerve regeneration, especially in critical gaps of injured peripheral nerve. Multipotent vascular stem cells (MVSCs) harvested from an adult blood vessel are involved in vascular remodeling; however, the therapeutic benefit for nerve regeneration is not clear.MethodsMVSCs were isolated from rats expressing green fluorescence protein (GFP), expanded, mixed with Matrigel matrix, and loaded into the nerve conduits. A nerve autograft or a nerve conduit (with acellular matrigel or MVSCs in matrigel) was used to bridge a transected sciatic nerve (10-mm critical gap) in rats. The functional motor recovery and cell fate in the regenerated nerve were investigated to understand the therapeutic benefit.ResultsMVSCs expressed markers such as Sox 17 and Sox10 and could differentiate into neural cells in vitro. One month following MVSC transplantation, the compound muscle action potential (CMAP) significantly increased as compared to the acellular group. MVSCs facilitated the recruitment of Schwann cell to regenerated axons. The transplanted cells, traced by GFP, differentiated into perineurial cells around the bundles of regenerated myelinated axons. In addition, MVSCs enhanced tight junction formation as a part of the blood-nerve barrier (BNB). Furthermore, MVSCs differentiated into perivascular cells and enhanced microvessel formation within regenerated neurovascular bundles.ConclusionsIn rats with peripheral nerve injuries, the transplantation of MVSCs into the nerve conduits improved the recovery of neuromuscular function; MVSCs differentiated into perineural cells and perivascular cells and enhanced the formation of tight junctions in perineural BNB. This study demonstrates the in vivo therapeutic benefit of adult MVSCs for peripheral nerve regeneration and provides insight into the role of MVSCs in BNB regeneration.

In this paper, we proposed a deep learning-based end-to-end method on the domain specified automatic term extraction (ATE), it considers possible term spans within a fixed length in the sentence and predicts them whether they can be conceptual terms. In comparison with current ATE methods, the model supports nested term extraction and does not crucially need extra (extracted) features. Results show that it can achieve high recall and a comparable precision on term extraction task with inputting segmented raw text.

3D shape analysis is an important research topic in computer vision and graphics. While existing methods have generalized image-based deep learning to meshes using graph-based convolutions, the lack of an effective pooling operation restricts the learning capability of their networks. In this paper, we propose a novel pooling operation for mesh datasets with the same connectivity but different geometry, by building a mesh hierarchy using mesh simplification. For this purpose, we develop a modified mesh simplification method to avoid generating highly irregularly sized triangles. Our pooling operation effectively encodes the correspondence between coarser and finer meshes in the hierarchy. We then present a variational auto-encoder structure with the edge contraction pooling and graph-based convolutions, to explore probability latent spaces of 3D surfaces. Our network requires far fewer parameters than the original mesh VAE and thus can handle denser models thanks to our new pooling operation and convolutional kernels. Our evaluation also shows that our method has better generalization ability and is more reliable in various applications, including shape generation, shape interpolation and shape embedding.

The contributions of this paper are: (1) a taxonomy of the "Realities" (Virtual, Augmented, Mixed, Mediated, etc.), and (2) some new kinds of "reality" that come from nature itself, i.e. that expand our notion beyond synthetic realities to include also phenomenological realities. VR (Virtual Reality) replaces the real world with a simulated experience (virtual world). AR (Augmented Reality) allows a virtual world to be experienced while also experiencing the real world at the same time. Mixed Reality provides blends that interpolate between real and virtual worlds in various proportions, along a "Virtuality" axis, and extrapolate to an "X-axis". Mediated Reality goes a step further by mixing/blending and also modifying reality. This modifying of reality introduces a second axis. Mediated Reality is useful as a seeing aid (e.g. modifying reality to make it easier to understand), and for psychology experiments like Stratton's 1896 upside-down eyeglasses experiment. We propose Multimediated Reality as a multidimensional multisensory mediated reality that includes not just interactive multimedia-based reality for our five senses, but also includes additional senses (like sensory sonar, sensory radar, etc.), as well as our human actions/actuators. These extra senses are mapped to our human senses using synthetic synesthesia. This allows us to directly experience real (but otherwise invisible) phenomena, such as wave propagation and wave interference patterns, so that we can see radio waves and sound waves and how they interact with objects and each other. Multimediated reality is multidimensional, multimodal, multisensory, and multiscale. It is also multidisciplinary, in that we must consider not just the user, but also how the technology affects others, e.g. how its physical appearance affects social situations., Comment: 14 pages, 20 figures, expanded version of a much shorter paper submitted to ACM Multimedia 2018

Using the 1.56m telescope at the Shanghai Observatory (ShAO), China, we monitored two sources, BL Lac object S5 0716+714 and Flat Spectrum Radio Quasar (FSRQ) 3C 273. For S5 0716+714, we report 4969 sets of CCD (Charge-coupled Device) photometrical optical observations (1369 for V band, 1861 for R band and 1739 for I band) in the monitoring time from Dec.4, 2000 to Apr.5, 2014. For 3C 273, we report 460 observations (138 for V band, 146 for R band and 176 for I band) in the monitoring time from Mar. 28, 2006 to Apr. 9, 2014. The observations provide us with a large amount of data to analyze the short-term and long-term optical variabilities. Based on the variable timescales, we can estimate the central black hole mass and the Doppler factor. An abundance of multi-band observations can help us to analyze the relations between the brightness and spectrum. We use Gaussian fitting to analyze the intra-day light curves and obtain the intra-day variability (IDV) timescales. We use the discrete correlation function (DCF) method and Jurkevich method to analyze the quasi-periodic variability. Based on the VRI observations, we use the linear fitting to analyze the relations between brightness and spectrum. The two sources both show IDV properties for S5 0716+714. The timescales are in the range from 17.3 minutes to 4.82 hours; for 3C273, the timescale is 35.6 minutes. Based on the periodic analysis methods, we find the periods P(V) = 24.24 days, P(R)=24.12 days, P(I)=24.82 days for S5 0716+714, and P = 12.99, 21.76 yr for 3C273. The two sources displayed the "bluer-when-brighter" spectral evolution properties. S5 0716+714 and 3C 273 are frequently studied objects. The violent optical variability and IDV may come from the jet. Gaussian fitting can be used to analyze IDVs. The relations between brightness (flux density) and spectrum are strongly influenced by the frequency., Comment: 28 pages, 3 tables

Yu-Guo Yuan,1,2 Sangiliyandi Gurunathan3 1College of Veterinary Medicine/Animal Science and Technology/Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, Jiangsu, China; 2Jiangsu Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Treatment of Senile Diseases, Yangzhou University, Yangzhou, China; 3Department of Stem Cell and Regenerative Biotechnology, Konkuk University, Seoul, Republic of Korea Background: Cisplatin (Cis) is a widely used chemotherapeutic drug for treating a variety of cancers, due to its ability to induce cell death in cancer cells significantly. Recently, graphene and its modified nanocomposites have gained much interest in cancer therapy, due to their unique physicochemical properties. The objective of this study was to investigate the combination effect of Cis and a reduced graphene oxide–silver nanoparticle nanocomposite (rGO-AgNPs) in human cervical cancer (HeLa) cells.Materials and methods: We synthesized AgNPs, rGO, and rGO-AgNP nanocomposites using C-phycocyanin. The synthesized nanomaterials were characterized using various analytical techniques. The anticancer properties of the Cis, rGO-AgNPs, and combination of Cis and rGO-AgNPs were evaluated using a series of cellular assays, such as cell viability, cell proliferation, LDH leakage, reactive oxygen species generation, and cellular levels of oxidative and antioxidative stress markers such as malondialdehyde, glutathione, SOD, and CAT. The expression of proapoptotic, antiapoptotic, and autophagy genes were measured using real-time reverse-transcription polymerase chain reaction.Results: The synthesized AgNPs were well dispersed, homogeneous, and spherical, with an average size of 10 nm and uniformly distributed on graphene sheets. Cis, GO, rGO, AgNPs, and rGO-AgNPs inhibited cell viability in a dose-dependent manner. The combination of Cis and

Yu-Guo Yuan,1 Qiu-Ling Peng,2 Sangiliyandi Gurunathan3 1College of Veterinary Medicine/Animal Science and Technology/Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, 2College of Chemistry and Bioengineering, Yichun University, Yichun, People’s Republic of China; 3Department of Stem cell and Regenerative Biotechnology, Konkuk University, Seoul, Republic of Korea Background: Breast cancer is the most common malignant disease that occurs in women. Histone deacetylase (HDAC) inhibition has recently emerged as an effective and attractive target for the treatment of cancer. The aim of this study was to investigate the efficacy of a combined treatment of tubastatin A (TUB-A) and palladium nanoparticles (PdNPs) against MDA-MB-231 human breast cancer cells using two different cytotoxic agents that work by two different mechanisms, thereby decreasing the probability of chemoresistance in cancer cells and increasing the efficacy of toxicity, to provide efficient therapy for advanced stage of cancer without any undesired side effects. Methods: PdNPs were synthesized using a novel biomolecule called R-phycoerythrin and characterized using various analytical techniques. The combinatorial effect of TUB-A and PdNPs was assessed by various cellular and biochemical assays and also by gene expression analysis. Results: The biologically synthesized PdNPs had an average size of 25 nm and were spherical in shape. Treatment of MDA-MB-231 human breast cancer cells with TUB-A or PdNPs showed a dose-dependent effect on cell viability. The combination of 4 µM TUB-A and 4 µM PdNPs had a significant inhibitory effect on cell viability compared with either TUB-A or PdNPs alone. The combinatorial treatment also had a more pronounced effect on the inhibition of HDAC activity and enhanced apoptosis by regulating various cellular and biochemical changes. Conclusion: Our results s

Yu-Guo Yuan,1 Qiu-Ling Peng,2 Sangiliyandi Gurunathan3 1College of Veterinary Medicine/Animal Science and Technology/Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, Jiangsu, People’s Republic of China; 2College of Chemistry and Bioengineering, Yichun University, Yichun, Jiangxi, People’s Republic of China; 3Department of Stem cell and Regenerative Biotechnology, Konkuk University, Seoul, Republic of Korea Background: Gemcitabine (GEM) is widely used as an anticancer agent in several types of solid tumors. Silver nanoparticles (AgNPs) possess unique cytotoxic features and can induce apoptosis in a variety of cancer cells. In this study, we investigated whether the combination of GEM and AgNPs can exert synergistic cytotoxic effects in the human ovarian cancer cell line A2780.Methods: We synthesized AgNPs using resveratrol as a reducing and stabilizing agent. The synthesized nanomaterials were characterized using various analytical techniques. The anticancer effects of a combined treatment with GEM and AgNPs were evaluated using a series of cellular assays. The expression of pro- and antiapoptotic genes was measured using real-time reverse transcription polymerase chain reaction. Apoptosis was confirmed by TUNEL assay.Results: In this study, combined treatment with GEM and AgNPs significantly inhibited viability and proliferation in A2780 cells. Moreover, the levels of apoptosis in cells treated with a combination of GEM and AgNPs were significantly higher compared with those in cells treated with GEM or AgNPs alone. Our data suggest that GEM and AgNPs exhibit potent apoptotic activity in human ovarian cancer cells. Combined treatment with GEM and AgNPs showed a significantly higher cytotoxic effect in ovarian cancer cells compared with that induced by either of these agents alone.Conclusion: Our study demonstrated that the interaction between GEM and AgNPs

Yu-Guo Yuan,1 Yan-Hong Wang,1 Hui-Hui Xing,1 Sangiliyandi Gurunathan2 1Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, College of Veterinary Medicine, Yangzhou University, Yangzhou, Jiangsu, People’s Republic of China; 2Department of Stem Cell and Regenerative Biotechnology, Konkuk University, Seoul, Republic of Korea Background: Graphene and graphene-related materials have gained substantial interest from both academia and industry for the development of unique nanomaterials for biomedical applications. Graphene oxide (GO) and silver nanoparticles (AgNPs) are a valuable platform for the development of nanocomposites, permitting the combination of nanomaterials with different physical and chemical properties to generate novel materials with improved and effective functionalities in a single platform. Therefore, this study was conducted to synthesize a graphene oxide–silver nanoparticle (GO-AgNPs) nanocomposite using the biomolecule quercetin and evaluate the potential cytotoxicity and mechanism of GO-AgNPs in human neuroblastoma cancer cells (SH-SY5Y).Methods: The synthesized GO-AgNPs were characterized using various analytical techniques. The potential toxicities of GO-AgNPs were evaluated using a series of biochemical and cellular assays. The expression of apoptotic and anti-apoptotic genes was measured by quantitative real-time reverse transcription polymerase chain reaction. Further, apoptosis was confirmed by caspase-9/3 activity and a terminal deoxynucleotidyl transferase dUTP nick end labeling assay, and GO-AgNPs-induced autophagy was also confirmed by transmission electron microscopy.Results: The prepared GO-AgNPs exhibited significantly higher cytotoxicity toward SH-SY5Y cells than GO. GO-AgNPs induced significant cytotoxicity in SH-SY5Y cells by the loss of cell viability, inhibition of cell proliferation, increased leakage of lactate dehydrogenase, decreased level of mitocho

Low power and high density requires scaling of MOSFETs in VLSI. As the Si based bulk MOSFETs scale down to the limit imposed by gate oxide tunneling induced gate leakage, short channel effects (SCEs) induced loss of control on electrostatic integrity, high body doping induced high Vt variation, and band-to-band tunneling induced high substrate leakage, etc., two categories of novel MOSFETs are being intensively investigated: Si multiple gate MOSFETs and high mobility III-V material based MOSFETs. Among all types of Si multiple gate MOSFETs, nanowire MOSFET is drawing quite a few attentions for its superior electrostatic control through all-around gate structure. High mobility III-V MOSFETs are considered as a principal candidate to achieve high speed without too aggressive scaling, which can keep good control of electrostatic integrity. This dissertation is primarily devoted to modeling and characterization of challenges and features which are becoming pronounced in aggressively scaled MOSFETs and high mobility material based MOSFETs. High-k dielectric on III-V MOS capacitors are intensively characterized and modeled with the focus on defects at insulator- semiconductor interface as well as inside the oxide, which are grand challenges for III-V MOSFETs. A distributed bulk-oxide trap model is developed to account for the commonly observed frequency dispersion of small signal capacitance-voltage and conductance-voltage data in accumulation and near flat band region. The observed C-V humps in depletion to strong inversion are modeled by interface states model. For III-V MOSFETs design, SCEs and raised source/drain issues are studied using TCAD simulation. Fabricated III-V MOSFETs are characterized and mobility is extracted through experimental current voltage data and multiple frequency gate to channel capacitance measurement and data. For multiple gate Si MOSFETs, this dissertation focuses on nanowire MOSFETs. SCEs based on generalized scale length theory are discusse

Little is known regarding the interplays between the mechanical and molecular bases for vein graft restenosis. We elucidated the stenosis initiation using a high-frequency ultrasonic (HFU) echogenicity platform and estimated the endothelium yield stress from von-Mises stress computation to predict the damage locations in living rats over time. The venous-arterial transition induced the molecular cascades for autophagy and apoptosis in venous endothelial cells (ECs) to cause neointimal hyperplasia, which correlated with the high echogenicity in HFU images and the large mechanical stress that exceeded the yield strength. The ex vivo perfusion of arterial laminar shear stress to isolated veins further confirmed the correlation. EC damage can be rescued by inhibiting autophagy formation using 3-methyladenine (3-MA). Pretreatment of veins with 3-MA prior to grafting reduced the pathological increases of echogenicity and neointima formation in rats. Therefore, this platform provides non-invasive temporal spatial measurement and prediction of restenosis after venous-arterial transition as well as monitoring the progression of the treatments.