Synthetic Vector Research Articles

Use of an adeno‐associated virus serotype Anc80 to provide durable cure of phenylketonuria in a mouse model

Phenylketonuria (PKU) is the most common inborn error of metabolism of the liver, and results from mutations of both alleles of the phenylalanine hydroxylase gene (PAH). As such, it is a suitable target for gene therapy via gene delivery with a recombinant adeno‐associated virus (AAV) vector. Here we use the synthetic AAV vector Anc80 via systemic administration to deliver a functional copy of a codon‐optimized human PAH gene, with or without an intron spacer, to the Pah enu2 mouse model of PKU. Dose‐dependent transduction of the liver and expression of PAH mRNA were present with both vectors, resulting in significant and durable reduction of circulating phenylalanine, reaching near control levels in males. Coat color of treated Pah enu2 mice reflected an increase in pigmentation from brown to the black color of control animals, further indicating functional restoration of phenylalanine metabolism and its byproduct melanin. There were no adverse effects associated with administration of AAV up to 5 × 1012 VG/kg, the highest dose tested. Only minor and/or transient variations in some liver enzymes were observed in some of the AAV‐dosed animals which were not associated with pathology findings in the liver. Finally, there was no impact on cell turnover or apoptosis as evaluated by Ki‐67 and TUNEL staining, further supporting the safety of this approach. This study demonstrates the therapeutic potential of AAV Anc80 to safely and durably cure PKU in a mouse model, supporting development for clinical consideration.

Spontaneous quantum superradiant emission in atomic Bose-Einstein condensates subject to a synthetic vector potential

We theoretically investigate the spontaneous quantum emission of phonon pairs by superradiant processes in an atomic Bose-Einstein condensate subject to a synthetic vector potential. Within the analog gravity perspective, this effect corresponds to the spontaneous emission of radiation from the ergosurface of rotating black holes. A general input-output formalism is built and used to characterize the spectral and correlation properties of the emission. Experimentally accessible signatures of the emission are pointed out in the correlation functions of the atomic gas.

Efficient cardiac gene transfer and early-onset expression of a synthetic adeno-associated viral vector, Anc80L65, after intramyocardial administration

ObjectiveGene therapy is a promising approach in the treatment of cardiovascular diseases. Preclinical and clinical studies have demonstrated that adeno-associated viral vectors are the most attractive vehicles for gene transfer. However, preexisting immunity, delayed gene expression, and postinfection immune response limit the success of this technology. The aim of this study was to investigate the efficacy of the first synthetic adeno-associated viral lineage clone, Anc80L65, for cardiac gene therapy. MethodsBy combining 2 different reporter approaches by fluorescence with green fluorescent protein and bioluminescence (Firefly luciferase), we compared transduction efficiency of Anc80L65 and adeno-associated virus, serotype 9 in neonatal rat cardiomyocytes ex vivo and rat hearts in vivo after intramyocardial and intracoronary administration. ResultsIn cardiomyocytes, Anc80L65 provided a green fluorescent protein expression of 28.9% (36.4 ± 3.34 cells/field) at 24 hours and approximately 100% on day 7. In contrast, adeno-associated virus, serotype 9 green fluorescent protein provided minimal green fluorescent protein expression of 5.64% at 24 hours and 11.8% on day 7. After intramyocardial injection, vector expression peaked on day 7 with Anc80L65; however, with adeno-associated virus, serotype 9 the peak expression was during week 6. Administration of Anc80L65 demonstrated significantly more efficient expression of reporter gene than after adeno-associated virus, serotype 9 at 6 weeks (6.81 ± 0.64 log10 gc/100 ng DNA vs 6.49 ± 0.28 log10 gc/100 ng DNA, P < .05). These results were consistent with the amount of genome copy per cell observed in the heart. ConclusionsAnc80L65 vector allows fast and robust gene transduction compared with adeno-associated virus, serotype 9 vector in cardiac gene therapy. Anc80L65 did not adversely affect cardiac function and caused no inflammatory response or toxicity.

Understanding superradiant phenomena with synthetic vector potentials in atomic Bose-Einstein condensates

We theoretically investigate superradiance effects in quantum field theories in curved space-times by proposing an analogue model based on Bose--Einstein condensates subject to a synthetic vector potential. The breaking of the irrotationality constraint of superfluids allows to study superradiance in simple planar geometries and obtain intuitive insight in the amplified scattering processes at ergosurfaces. When boundary conditions are modified allowing for reflections, dynamical instabilities are found, similar to the ones of ergoregions in rotating space-times. Their stabilization by horizons in black hole geometries is discussed. All these phenomena are reinterpreted through an exact mapping with the physics of one-dimensional relativistic charged scalar fields in electrostatic potentials. Our study provides a deeper understanding on the basic mechanisms of superradiance: by disentangling the different ingredients at play, it shines light on some misconceptions on the role of dissipation and horizons and on the competition between superradiant scattering and instabilities.

Computationally Directed Discovery of MoBi2.

Incorporating bismuth, the heaviest element stable to radioactive decay, into new materials enables the creation of emergent properties such as permanent magnetism, superconductivity, and nontrivial topology. Understanding the factors that drive Bi reactivity is critical for the realization of these properties. Using pressure as a tunable synthetic vector, we can access unexplored regions of phase space to foster reactivity between elements that do not react under ambient conditions. Furthermore, combining computational and experimental methods for materials discovery at high-pressures provides broader insight into the thermodynamic landscape than can be achieved through experiment alone, informing our understanding of the dominant chemical factors governing structure formation. Herein, we report our combined computational and experimental exploration of the Mo-Bi system, for which no binary intermetallic structures were previously known. Using the ab initio random structure searching (AIRSS) approach, we identified multiple synthetic targets between 0-50 GPa. High-pressure in situ powder X-ray diffraction experiments performed in diamond anvil cells confirmed that Mo-Bi mixtures exhibit rich chemistry upon the application of pressure, including experimental realization of the computationally predicted CuAl2-type MoBi2 structure at 35.8(5) GPa. Electronic structure and phonon dispersion calculations on MoBi2 revealed a correlation between valence electron count and bonding in high-pressure transition metal-Bi structures as well as identified two dynamically stable ambient pressure polymorphs. Our study demonstrates the power of the combined computational-experimental approach in capturing high-pressure reactivity for efficient materials discovery.

Combining Regression and Clustering for Financial Analysis

Abstract Artificial Intelligence is used in business through machine learning algorithms. Machine learning is a part of computer science focused on computer systems learning to perform a specific task without using explicit instructions, relying on patterns and inference instead. Though it might seem like we’ve come a long way in the last ten years, which is true from a research perspective, the adoption of AI among corporations is still relatively low. Over time it became possible to automate more tasks and business processes than ever before. The benefit of using artificial intelligence is that does not require to program every step of the process, predicting at each step what could happen and how to resolve it. The algorithms decide for themselves in each case how the problems should be solved, based on the data that is used. I apply Python language to create a synthetic feature vector that allows visualizations in two dimensions for EDIBTA financial ratio. I use Mean-Square Error in order to evaluate the success, having the optimal parameters. In this section, I also mentioned about the purpose, goals, and applications of cluster analysis. I indicated about the basics of cluster analysis and how to do it and also did a demonstration on how to use K-Means.

RANC: Reconfigurable Architecture for Neuromorphic Computing

Neuromorphic architectures have been introduced as platforms for energy efficient spiking neural network execution. The massive parallelism offered by these architectures has also triggered interest from non-machine learning application domains. In order to lift the barriers to entry for hardware designers and application developers we present RANC: a Reconfigurable Architecture for Neuromorphic Computing, an open-source highly flexible ecosystem that enables rapid experimentation with neuromorphic architectures in both software via C++ simulation and hardware via FPGA emulation. We present the utility of the RANC ecosystem by showing its ability to recreate behavior of the IBM's TrueNorth and validate with direct comparison to IBM's Compass simulation environment and published literature. RANC allows optimizing architectures based on application insights as well as prototyping future neuromorphic architectures that can support new classes of applications entirely. We demonstrate the highly parameterized and configurable nature of RANC by studying the impact of architectural changes on improving application mapping efficiency with quantitative analysis based on Alveo U250 FPGA. We present post routing resource usage and throughput analysis across implementations of Synthetic Aperture Radar classification and Vector Matrix Multiplication applications, and demonstrate a neuromorphic architecture that scales to emulating 259K distinct neurons and 73.3M distinct synapses.

Nonlinear dynamical response of interacting bosons to synthetic electric field

We theoretically study the non-linear response of interacting neutral bosonic gas in a synthetically driven one-dimensional optical lattice. In particular, we examine the bosonic analogue of electronic higher harmonic generation in a strong time-dependent synthetic vector potential manifesting itself as the synthetic electric field. We show that the vector potential can generate reasonably high harmonics in the insulating regime, while the superfluid regime exhibits only a few harmonics. In the insulating regime, the number of harmonics increases with the increase in the strength of the vector potential. This originates primarily due to the field-driven resonant and non-resonant excitations in the neutral Mott state and their recombination with the ground state. If the repulsive interaction between two atoms ($U$) is close to the strength of the gauge potential ($A_0$), the resonant quasiparticle-quasihole pairs on nearest-neighbor sites, namely dipole states are found to a play a dominant role in the generating higher harmonics. However, in the strong-field limit $A_0\gg U$, the nonresonant states where quasiparticle-quasihole pairs are not on nearest-neighbor sites give rise to higher harmonics.

Galactose Functionalized Mesoporous Silica Nanoparticles As Delivery Vehicle in the Treatment of Hepatitis C Infection.

DNA and RNA based antiviral strategies using nonviral vectors have shown better potential over the viral pathway due to the fewer chances of gene recombination and immunogenicity. In this work a mesoporous silica nanoparticle (MSN) based carrier system has been used for targeted delivery of shDNA molecule against the conserved 5'-untranslated region (UTR) in the RNA of a hepatitis C virus to inhibit its replication. The MSNs coated with amine and galactose could specifically target liver cells. Significant reduction (about 94%) of viral RNA level was achieved in HCV-JFH1 infectious cell culture compared to the control RNA levels directed the successful delivery and action of the shDNA. This study showed that Gal-AMSN can be used as a synthetic delivery vector to deliver the shDNA effectively for the treatment of HCV infection.

Deep learning for non-rigid 3D shape classification based on informative images

In order to enhance the discernment of features in view-based 3D shape recognition, we propose a joint convolutional neural network (CNN) learning model based on informative images. It learns deep features from intrinsic feature images and extrinsic 2D views, and generates a synthetic feature vector via weighted aggregation and refinement process, which has achieved remarkable improvement in non-rigid 3D shape classification. Our joint CNNs model contains three parts: the first part is the geometry-based feature generation unit. We provide a discriminative BoF (bag of features) image descriptor and construct CNN framework to learn the geometric features of the model. The second part is the view-based feature generation unit. We establish a parallel CNN to extract spatial features from optimized 2D views. The third part is a score generation and refinement unit, which automatically learns the weighted scores of geometric features and spatial features. Finally, the aggregated feature is refined in a CNN framework and serves as an informative shape descriptor for recognition task. The experimental results demonstrate that our deep features have the strong discerning ability. Thus, better performance and robustness can be obtained compared to state-of-the-art methods.

Electromagnetic wave absorbing performance of 3D printed wave-shape copper solid cementitious element

Electromagnetic wave (EMW) pollution impairs the performance of equipment, facilities, information security, and human health. Ordinary, plain cementitious composite has limited EMW-reflecting capacity. To correct this, a macrostructure EMW absorbing element has been developed to reduce EMW pollution. As conventional casting of macrostructures is not cost-effective and lacks quality because of the demand for special formwork, 3D printing technology offers greater design flexibility, higher efficiency, and improved mechanical properties. Moreover, the surface texture of 3D-printed material exhibits natural corrugation to enhance EMW reflection further. In this study, novel wave-shaped EMW absorbing elements were fabricated using 3D cementitious printing technology. The EMW absorbing performance was analyzed by the naval research laboratory (NRL) system in the range of 1 GHz–18 GHz. Significant improvement of reflectivity was observed, especially in the low-frequency range. The optimum configuration was identified through effectiveness evaluation to be a K3 sample with 45 mm of heave height and 2/3 tan(θ), exhibiting a minimum reflectivity −43.7 dB, mean reflectivity −25 dB, and an absorbing bandwidth of 18 GHz. The experimental reflectivity was also simulated by the finite element method, which agrees with the experimental results. The synthetic vector electromagnetic field distribution was also studied to explore space impedance characteristics. Moreover, the finite element method attempted to correct drawbacks in experiments, including multiple direction reflection measurement and wave-number interruption. Based on simulation calibration, the influence of wave-shaped parameters (heave height and tangent value) upon EMW absorbing capacity was induced accurately.

Speed Sensor-Less Predictive Torque Control for Five-Phase Induction Motor Drive Using Synthetic Voltage Vectors

The predictive torque control (PTC) is researched extensively for control of electrical drives because of its fast-dynamic response and robust control. In multiphase motors, it is mandatory to design a multiobjective cost function with more than two terms for controlling xy-subspace current and common-mode voltage (CMV). However, selecting the weighting factor for multiple control variables is time penalizing and increases the computational burden. Using a noisy speed input from the speed sensor in the prediction model reduces the steady-state performance in terms of higher torque ripple, flux ripple, and phase current total harmonic distortion (THD), especially during low speeds. In this article, PTC for a five-phase induction motor (IM) drive without speed sensor [sensorless PTC (PTC-S)] is presented. The adaptive full observer is incorporated to estimate the stator flux, stator resistance, and rotor speed. The proposed algorithm is capable to eliminate CMV and xy-current harmonics having advantages over the conventional PTC (PTC-C) algorithm. The elimination of CMV is achieved by the selection of set of voltage vectors from available 243 voltage vectors. The proposed speed sensor-less control is implemented with a three-level neutral-point clamped (NPC) inverter using synthetic voltage vectors. The use of a synthetic voltage vector eliminates the xy-subspace current and reduces the computational burden. The PTC-S is implemented with a seven-level hysteresis torque comparator, which reduces the torque ripple significantly. To further improve the effectiveness of the control algorithm, two-step delay compensation is implemented. The discussed algorithms are tested on a laboratory prototype for experimental evaluation. The proposed study also highlights the effect of torque ripple reduction on the speed adaptive flux observer for sensor-less operation. The experimental results show the effectiveness and applicability by comparing the steady-state and dynamic performances of PTC.

List Viterbi Decoding of PAC Codes

Polarization-adjusted convolutional (PAC) codes are special concatenated codes in which we employ a one-to-one convolutional transform as a pre-coding step before the polar transform. In this scheme, the polar transform (as a mapper) and the successive cancellation process (as a demapper) present a synthetic vector channel to the convolutional transformation. The numerical results show that this concatenation improves the Hamming distance properties of polar codes. Motivated by the fact that the parallel list Viterbi algorithm (LVA) sorts the candidate paths locally at each trellis node, in this work, we adapt the trellis, path metric, and the local sorter of LVA to PAC codes and show how the error correction performance moves from the poor performance of the Viterbi algorithm (VA) to the superior performance of list decoding by changing the constraint length, list size, and the sorting strategy (local sorting and global sorting) in the LVA. Also, we analyze the complexity of the local sorting of the paths in LVA relative to the global sorting in the list decoding and we show that LVA has a significantly lower sorting complexity compared with list decoding.

Efficient In Utero Gene Transfer to the Mammalian Inner Ears by the Synthetic Adeno-Associated Viral Vector Anc80L65

Sensorineural hearing loss is one of the most common sensory disorders worldwide. Recent advances in vector design have paved the way for investigations into the use of adeno-associated vectors (AAVs) for hearing disorder gene therapy. Numerous AAV serotypes have been discovered to be applicable to inner ears, constituting a key advance for gene therapy for sensorineural hearing loss, where transduction efficiency of AAV in inner ear cells is critical for success. One such viral vector, AAV2/Anc80L65, has been shown to yield high expression in the inner ears of mice treated as neonates or adults. Here, to evaluate the feasibility of prenatal gene therapy for deafness, we assessed the transduction efficiency of AAV2/Anc80L65-eGFP (enhanced green fluorescent protein) after microinjection into otocysts in utero. This embryonic delivery method achieved high transduction efficiency in both inner and outer hair cells of the cochlea. Additionally, the transduction efficiency was high in the hair cells of the vestibules and semicircular canals and in spiral ganglion neurons. Our results support the potential of Anc80L65 as a gene therapy vehicle for prenatal inner ear disorders.

Synthetic Internal Voltage Phase–Amplitude Dynamics Investigation for Electric Drivetrain Small-Signal Model in Electromechanical Control Timescale for a Wound Rotor Induction Machine-Based Shipboard Power System

With less fragile power electronics integrated, the overall shipboard power system (SPS) safety level is prone to increase. In this article, the motion equation concept of a less power electronics-based more-electric ship is proposed to study the SPS dynamics. A wound rotor induction machine (WRIM) acts as the propulsion load, whose stator and power converter are regarded as a synthetic internal voltage vector (SIVV). The small-signal model of a WRIM-based electric drivetrain (WRIM-ED) is established in the electromechanical control timescale. Besides, the external dynamic behaviors of the propulsion load are investigated in detail according to the phase and amplitude of SIVV. The control effects of phase-locked loop (PLL), rotor speed control (RSC), and reactive power control (RPC) are taken into account. In addition, the control schemes by applying the traditional PLL-based vector control (PLL-VC) and an emulated stator voltage-oriented VC (ESVO-VC) for WRIM-ED are described. Moreover, with ESVO-VC, the expression of equivalent inertia for WRIM-ED is much simplified, and there is no need to tune the PLL controller gains. MATLAB/Simulink is applied to carry out simulations to investigate the control effects of both PLL-VC and ESVO-VC on the system dynamic performance.

Quality prediction and control of cable harness wiring using extension theory and a backpropagation neural network

Given that the cable harness wiring quality (CHWQ) of complex mechatronic products is affected by multiple factors and it is difficult to solve the resulting control problems, this paper proposes a quality prediction method for cable harness wiring using extension theory and a backpropagation (BP) neural network. First, a quality prediction framework is designed based on the factors influencing the composition and analysis of the CHWQ. Second, we establish a quality evaluation index system based on five aspects and design a first-level factor set and a second-level factor set. Based on the single factor index for various parameters and evaluation of data after dimensionless parameter processing, we use extension theory and the entropy weight method to determine the membership matrix and the fuzzy weight vector for the first-level evaluation. Additionally, the single factor and the synthetic fuzzy weight vector are determined using the entropy weight method and the analytic hierarchy process (AHP), respectively, and quality grade evaluation based on the fuzzy synthetic evaluation (FSE) method is completed. Finally, we use a three-layer feedforward neural network to predict the quality status of a specific phased array radar system. The results demonstrate that the proposed method can produce increased prediction accuracy.

Synthetic Aperture Imaging in Cylindrical Component Using Ultrasonic Immersion Forward Vector Algorithm

Abstract—Ultrasonic nondestructive testing has been widely used in the detection and evaluation of fatigue cracks and defects of high-speed railway. In order to improve the detection speed of cylindrical components such as rims, a theoretical model of the forward vector algorithm of ultrasonic immersion curved surface is established. For improving image quality, an averaging correction factor is introduced in this paper to avoid multiple irradiation of the same pixel by the same element, and the visualization of cylindrical components with internal defects is realized by simulation and experiment. The traditional synthetic aperture focusing technique (SAFT), Newton iterative synthetic aperture (NISA) and ultrasonic forward vector algorithm (UFVA) are compared and analyzed on the aspects of imaging effect, array performance index (API) and imaging efficiency. Compared with the other two algorithms, the ultrasonic forward vector algorithm can effectively overcome the iteration of calculation of the refraction point and improve the imaging efficiency. The efficiency is improved by 2 and 1 orders of magnitude respectively while imaging quality is guaranteed. At the same time, this algorithm plays an important role on the measurement of the inner and outer diameter of the rim, the defect detection, and the quantitative analysis of the surface wear, which provides an effective means for the rapid detection of internal defects of the regular curved parts.

Human AlphoidtetO Artificial Chromosome as a Gene Therapy Vector for the Developing Hemophilia A Model in Mice.

Human artificial chromosomes (HACs), including the de novo synthesized alphoidtetO-HAC, are a powerful tool for introducing genes of interest into eukaryotic cells. HACs are mitotically stable, non-integrative episomal units that have a large transgene insertion capacity and allow efficient and stable transgene expression. Previously, we have shown that the alphoidtetO-HAC vector does not interfere with the pluripotent state and provides stable transgene expression in human induced pluripotent cells (iPSCs) and mouse embryonic stem cells (ESCs). In this study, we have elaborated on a mouse model of ex vivo iPSC- and HAC-based treatment of hemophilia A monogenic disease. iPSCs were developed from FVIIIY/− mutant mice fibroblasts and FVIII cDNA, driven by a ubiquitous promoter, was introduced into the alphoidtetO-HAC in hamster CHO cells. Subsequently, the therapeutic alphoidtetO-HAC-FVIII was transferred into the FVIIIY/– iPSCs via the retro-microcell-mediated chromosome transfer method. The therapeutic HAC was maintained as an episomal non-integrative vector in the mouse iPSCs, showing a constitutive FVIII expression. This study is the first step towards treatment development for hemophilia A monogenic disease with the use of a new generation of the synthetic chromosome vector—the alphoidtetO-HAC.

Construction of a Chimeric Plasmid Vector and Its Investigation for Usage as an Internal Control for Detection of Shiga Toxin-Producing Escherichia coli by Polymerase Chain Reaction and Real-Time PCR

Background: Shiga-toxigenic Escherichia coli (STEC) is an important foodborne pathogen and considered a worldwide problem. The infection can cause severe illnesses, including hemolytic uremic syndrome. Traditional methods for STEC detection are currently not done in clinical laboratories due to the cost and related long turnaround time, which necessitates the development of quick and reliable alternative detection methods. Objectives: In this study, the application of PCR and real-time PCR methods for rapid detection of STEC in DNA extracts of stool samples was investigated. Methods: A synthetic control DNA vector, containing target genes of stx1, stx2, EhxA, and eae, was designed to evaluate the validity of these methods. Moreover, efficiency of primers targeting the genes, limit of detection, repeatability, sensitivity, and specificity of real-time PCR assay was compared with PCR results. Results: Repeatability of real-time PCR assay showed percent coefficient of variation of 3.3% - 16.1% and sensitivity of 66% to 100%. Efficiency of all the primers was 100% with a detection limit of 103 copies of DNA per reaction for both of the two assays. Comparison of the results showed that real-time PCR was more sensitive than conventional PCR. The chimeric vector interfered with template DNA when it was used as an internal control in PCR and real-time PCR assays; however, its application as external control was approved for detection of all targeted genes in STEC. Conclusions: These results confirmed application of the chimeric vector as an external control in detection of STEC by both PCR and real-time PCR assays, but its usage as an internal control was not approved in this study.

In Vivo Delivery of Nucleic Acid-Encoded Monoclonal Antibodies.

Antibody immunotherapy is revolutionizing modern medicine. The field has advanced dramatically over the past 40 years, driven in part by major advances in isolation and manufacturing technologies that have brought these important biologics to the forefront of modern medicine. However, the global uptake of monoclonal antibody (mAb) biologics is impeded by biophysical and biochemical liabilities, production limitations, the need for cold-chain storage and transport, as well as high costs of manufacturing and distribution. Some of these hurdles may be overcome through transient in vivo gene delivery platforms, such as non-viral synthetic plasmid DNA and messenger RNA vectors that are engineered to encode optimized mAb genes. These approaches turn the body into a biological factory for antibody production, eliminating many of the steps involved in bioprocesses and providing several other significant advantages, and differ from traditional gene therapy (permanent delivery) approaches. In this review, we focus on nucleic acid delivery of antibody employing synthetic plasmid DNA vector platforms, and RNA delivery, these being important approaches that are advancing simple, rapid, in vivo expression and having an impact in animal models of infectious diseases and cancer, among others.