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Summary: Programmable metasurfaces have garnered significant attention for their capacity to dynamically manipulate electromagnetic (EM) waves. In particular, the programmable metasurfaces offer to generate a wide range of EM beams when the appropriate digital coding patterns are designed. Traditionally, optimizing the coding patterns involves time-consuming nonlinear optimization algorithms due to the high computational complexity. In this study, we propose a physics-assisted deep learning (DL) model that can calculate the coding pattern in milliseconds, requiring only a simple depiction of the desired beam. An extended version of the macroscopic model for digital coding metasurface is introduced as the physics-driven component, which can compute the radiation pattern rapidly based on the provided coding pattern. The integration of the macroscopic model ensures to generate the physics-compliant coding designs. We validate the proposed method experimentally by measuring several coding patterns for both single-beam and dual-beam scenarios, which demonstrate good performance of beamforming.

BackgroundToxoplasma gondii (T. gondii) is a widespread, zoonotic protozoan intracellular parasite with a complex life cycle, which can cause toxoplasmosis, a potentially serious disease. During the invasion process, T. gondii proteins first bind to the relevant host cell receptors, such as glycosaminoglycan molecule (GAG-binding motif), which is one of the main receptors for parasites or virus to infect host cells. However, research on TGME49_216510 (T. gondii Trx21), a protein from Toxoplasma gondii, is limited.MethodsBioinformatics analysis of the Trx21 protein was performed firstly. And specific primers were then designed using the conserved domain and GAG-binding motif to amplify, express, and purify a fragment of the Trx21 protein. The purified Trx21-GST protein was used for antioxidant and cell adhesion experiments. Simultaneously, mice were immunized with Trx21-His to generate specific polyclonal antibodies for subcellular localization analysis.ResultsThe Trx21 protein, consisting of 774 amino acids, included a transmembrane region, three GAG-binding motifs, and a Thioredoxin-like domain. The recombinant Trx21-His protein had a molecular mass of about 31 kDa, while the Trx21-GST protein had a molecular mass of about 55 kDa, which was analyzed by SDS-PAGE and Western blot. Subcellular localization analysis by IFA revealed that Trx21 is predominantly distributed in the cytoplasm of T. gondii. Furthermore, Trx21 exhibited a protective effect on supercoiled DNA against metal-catalyzed oxidation (MCO) and demonstrated adhesion abilities to Vero cells.ConclusionsThese results indicate that Trx21 plays an important role in host cell interaction and oxidative damage.

Abstract The poor prognosis observed in elderly individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) remains a serious clinical burden and the underlying mechanism is unclear, which necessities detailed investigation of disease characteristics and research for efficient countermeasures. To simulate lethal coronavirus disease 2019 (COVID‐19) in senescent human patients, 80‐week‐old male hamsters are intranasally inoculated with different doses of SARS‐CoV‐2 Omicron BA.5 variant. Exposure to a low dose of the Omicron BA.5 variant results in early activation of the innate immune response, followed by rapid viral clearance and minimal lung damage. However, a high dose of BA.5 results in impaired interferon signaling, cytokine storm, uncontrolled viral replication, and severe lung injury. To decrease viral load and reverse the deterioration of COVID‐19, a new bio‐mimic decoy called CoVR‐MV is used as a preventive or therapeutic agent. Administration of CoVR‐MV as a preventive or therapeutic intervention in the early stages of infection can effectively suppress viral load, regulate the immune response, and rescue animals from death and critical illness. These findings underscore the risk associated with SARS‐CoV‐2 Omicron BA.5 exposure in senescent hamsters and highlight the importance of early intervention to prevent disease progression.

Due to their remarkable capabilities of generation, deep-learning-based (DL) generative models have been widely applied in the field of synthetic aperture radar (SAR) image synthesis. This kind of data-driven DL methods usually requires abundant training samples to guarantee the performance. However, the number of SAR images for training is often insufficient because of expensive acquisitions. This typical few-shot image generation (FSIG) task still remains not fully investigated. In this article, we propose an optical-to-SAR (O2S) image translation model with a pairwise distance (PD) loss to enhance the diversity of generation. First, we replace the semantic maps used as the input of network in previous studies with more easily available optical images and apply the popular pix2pix model in image-to-image translation tasks as the foundation network. Second, inspired by the FSIG works in the traditional computer vision field, we propose a similarity preservation term in the loss function, which encourages the generated images to inherit the similarity relationship of the corresponding simulated SAR images. Third, the data augmentation experiments on the MSTAR dataset indicates the effectiveness of our model. With only five samples for each target category and six categories in total, the basic O2S network boosts the classification accuracy by 4.81% and 2.27% for data of depression angle of 15° and 17°, respectively. The PD loss is capable of bringing additional 2.23% and 1.78% improvement. The investigation on similarity curves also suggests that the generated images enhanced by the PD loss have closer similarity behaviors to the real SAR images.

Since the introduction of Maxwell’s equations in the 19th century, computational electromagnetics has dramatically increased development. This growth can be attributed to the evolution of numerical algorithms, such as the finite difference method, finite element method, method of moments, and high-frequency approximation methods. These numerical techniques have become a crucial foundation of modern electronic and information engineering. Artificial intelligence has recently witnessed considerable development in electromagnetics; the rapid growth within this field owes itself to its robust modeling and inferential capability. This advancement has given rise to the emerging field of intelligent electromagnetic computing, which has captured the attention of numerous researchers. Remarkable achievements include electromagnetic modeling and simulation, analysis and synthesis of new electromagnetic materials and devices, and detection and perception. These contributions have injected fresh insights into the realm of electromagnetics. This paper discusses recent advances in intelligent electromagnetic computing to highlight new perspectives and avenues in research in this emerging field.

Rhinoviruses (RVs) are major causes of the common cold and are related to severe respiratory tract diseases, leading to a considerable economic burden and impacts on public health. Available and stable viral resources of rhinoviruses for laboratory use are important for promoting studies on rhinoviruses and further vaccine or therapeutic drug development. Reverse genetic technology can be useful to produce rhinoviruses and will help to promote studies on their pathogenesis and virulence. In this study, rhinovirus A89, an RV-A species that has been found to be highly involved in hospitalization triggered by RV infections, was selected to construct an infectious clone based on its sequence as a representative. The viral mRNA produced by a T7 RNA transcript system was transfected into H1-HeLa cells, and the rescued RV-A89 viruses were harvested and confirmed by sequencing. The rescued RV-A89 induced a similar cytopathic effect (CPE) and shared almost identical growth kinetics curves with parental RV-A89. Moreover, 9A7, a prescreened monoclonal antibody against the parental RV-A89, had a good and specific reaction with the rescued RV-A89, and further characterization showed almost the same morphology and protein composition of both viruses; thus, recombinant RV-A89 with similar biological characterization and virulence to the parental virus was obtained. In summary, the infectious clone of RV-A89 was successfully established, and the development of reverse genetic technology for rhinovirus will provide a framework for further studies on rhinoviruses.

BackgroundPlasmodium falciparum is a protozoan parasite that causes the most severe form of malaria in humans worldwide, which is predominantly found in sub-Saharan Africa, where it is responsible for the majority of malaria-related deaths. Plasmodium helical interspersed subtelomeric (PHIST) proteins are a family of proteins, with a conserved PHIST domain, which are typically located at the subtelomeric regions of the Plasmodium falciparum chromosomes and play crucial roles in the interaction between the parasite and its human host, such as cytoadherence, immune evasion, and host cell remodeling. However, the specific utilization of synonymous codons by PHIST proteins in Plasmodium falciparum is still unknown.MethodsCodon usage bias (CUB) refers to the unequal usage of synonymous codons during translation, resulting in over- or underrepresentation of certain nucleotide patterns. This imbalance in CUB can impact various cellular processes, including protein expression levels and genetic variation. To investigate this, the CUB of 88 PHIST protein coding sequences (CDSs) from 5 subgroups were analyzed in this study.ResultsThe results showed that both codon base composition and relative synonymous codon usage (RSCU) analysis identified a higher occurrence of AT-ended codons (AGA and UUA) in PHIST proteins of Plasmodium falciparum. The average effective number of codons (ENC) for these PHIST proteins was 36.69, indicating a weak codon preference among them, as it was greater than 35. Additionally, the correlation analysis among codon base composition (GC1, GC2, GC3, GCs), codon adaptation index (CAI), codon bias index (CBI), frequency of optimal codons (FOP), ENC, general average hydropathicity (GRAVY), aromaticity (AROMO), length of synonymous codons (L_sym), and length of amino acids (L_aa) revealed the influence of base composition and codon usage indices on codon usage bias, with GC1 having a significant impact in this study. Furthermore, the neutrality plot analysis, PR2-bias plot analysis, and ENC-GC3 plot analysis provided additional evidence that natural selection plays a crucial role in determining codon bias in PHIST proteins.ConclusionIn conclusion, this study has enhanced our understanding of the characteristics of codon usage and genetic evolution in PHIST proteins, thereby providing data foundation for further research on antimalarial drugs or vaccines.

The authors present an intelligent metasurface system that uses a target detection algorithm combined with a depth camera, to automatically detect the position of moving targets and achieve real-time wireless communications. The system can operate for multiple targets in limited ambient light, outdoor and other realistic environments.

Electromagnetic inverse scattering (EMIS) is uniquely positioned among many inversion methods because it enables to image the scene in a contactless, quantitative and super-resolution way. Although many EMIS approaches have been proposed to date, they usually suffer from two important challenges, i.e., time-consuming data acquisition and computationally -prohibitive data post processing, especially for large-scale objects with high and even moderate contrasts. To tackle the challenges, we here propose a framework of intelligent EMIS with the aid of deep learning techniques and information metasurfaces, enabling to the efficient data acquisition and instant data processing in a smart way. Towards this goal, as illustrative examples, we considerably extend the canonical contrast source inversion (CSI) algorithm, a canonical EMIS method by updating the contrast via the generative adversarial network (GAN), an unsupervised deep learning approach, leading to a novel physics-informed unsupervised deep learning method for EMIS, referred to as CSI-GAN in short. Compared with existing deep learning solutions for EMIS, our method relies on the supervision of physical law instead of the labeled training dataset, beating the bottleneck arising from the collection of labeled training datasets. Furthermore, we propose a scheme of adaptive data acquisition with the use of information metasurface in a cost-efficiency way, remarkably reducing the number of measurements and thus speeding up the data acquisition but maintaining the reconstruction's quality. Illustrative examples are provided to demonstrate the performance gain in terms of reconstruction quality, showing the promising potentials for providing the intelligent scheme for the EMIS problems.

Current varicella vaccines retain neurovirulence and can establish latency and reactivate. Here, the authors present preclinical results of a rationally-designed, skin- and neuro-attenuated varicella vaccine candidate, v7D, showing its attenuation in human skin and neuronal cells and its immunogenicity in small animal models and nonhuman primates

Wireless ultraviolet communication uses the atmospheric scattering effect for signal transmission, and this paper improves the partially important sampling model (MCI-PIS) in the Monte Carlo integration method, and the improved model is used to simulate the influence of multiple system parameters such as communication distance, transceiver tilt angle, transceiver divergence angle on the path loss and impulse response of ultraviolet light communication.The simulation results show that the path loss of the improved model for multiple scattering of ultraviolet light is increased by 0.2- $2~dB$ , and the impulse response is almost the same as that of MCI-PIS, but the calculation effect is increased by 20% compared with the MCI-PIS model.

Aiming at the problem of uneven illuminance distribution in traditional indoor optical communication systems, this paper proposes a square + elliptical layout, using simulated annealing particle swarm algorithm to optimize the spacing of LED light sources, and optimize the uniformity of system illuminance and signal-to-noise ratio. The simulation results show that the optimized square + elliptical layout illumination ranges from 359.25 lx to 451.05 lx, and the mean square error reaches 12.66 lx. Signal noise ratio is between 18.54 dB and 20.75 dB, and the mean square error is 0.39 dB. Compared with the traditional square and elliptical layout, the illumination performance and communication performance are improved clearly, which provides a new reference scheme for indoor light source layout.

Human Rhinoviruses (RVs) are dominant pathogens causing a wide range of respiratory tract diseases, posing a huge threat to public health worldwide. Viruses belonging to the RV-C species are more likely to cause severe illnesses and are strongly associated with asthma onset or exacerbations than RV-A or RV-B. Rapid and sensitive detection of neutralizing antibodies (NAbs) against RV-C can promote the development of vaccines and antiviral drugs and help in the diagnosis of viral infection. In this study, a rapid neutralization testing system for RV-C15, based on an enzyme-linked immunospot assay (Nt-ELISPOT) was developed. A monoclonal antibody (MAb), named 9F9, with high binding efficacy for RV-C15 conjugated to horseradish peroxidase (HRP), was used to detect RV-C15-infected cells at a concentration of 2 μg/ml. The optimal infectious dose of RV-C15 was set at 1 × 104 TCID50/well and the cells were fixed with 0.5% formaldehyde diluted in PBS after incubation for 20 h. Compared with the traditional cytopathic effect (CPE)-based neutralization assay (Nt-CPE), Nt-ELISPOT significantly shortened the detection period and showed good consistency with the detection of neutralizing titers of both sera and NAbs. Using Nt-ELISPOT, three anti-RV-C15 NAbs were obtained with IC50 values of 0.16, 0.27, and 11.8 μg/ml, respectively. Moreover, 64 human serum samples collected from a wide range of age groups were tested for NAb against RV-C15 by Nt-ELISPOT. The total seroprevalence was 48.4% (31/64) and the positive rate was lowest in the group under 6 years old. Thus, the Nt-ELISPOT established in this study can be used as a high-throughput and rapid neutralization assay for the screening of NAbs and for seroepidemiological investigation against RV-C15.

Abstract Epidemiological studies of the COVID-19 patients have suggested the male bias in outcomes of lung illness. To experimentally demonstrate the epidemiological results, we performed animal studies to infect male and female Syrian hamsters with SARS-CoV-2. Remarkably, high viral titer in nasal washings was detectable in male hamsters who presented symptoms of weight loss, weakness, piloerection, hunched back and abdominal respiration, as well as severe pneumonia, pulmonary edema, consolidation, and fibrosis. In contrast with the males, the female hamsters showed much lower shedding viral titers, moderate symptoms, and relatively mild lung pathogenesis. The obvious differences in the susceptibility to SARS-CoV-2 and severity of lung pathogenesis between male and female hamsters provided experimental evidence that SARS-CoV-2 infection and the severity of COVID-19 are associated with gender.

Regeneration of existing buildings and abandoned areas is a governmental and European key objective. This research focuses on Poveglia: an abandoned island in the Venetian lagoon, Italy. The underpinning idea concerns the upgrade of Poveglia to a zero energy Cognitive University Campus, connected to other educational institutions in the lagoon. The vision aims at reusing abandoned islands combining architecture, learning environments and digital networks, to demonstrate the potential of new technologies for the transformation of abandoned areas. The case study demonstrates the effectiveness of employing improved and revised systems and tools, developed in eLUX lab at the University of Brescia, for the regeneration of the island. The inclusion of the island in a smart campus network results in triggering positive synergies both enhancing energy efficiency and the learning environment. A further development concerns the setup of strategies for historical preservation, energy efficiency and renewable energy production.

Recently, programmable metasurfaces have aroused great attention for various applications such as beam manipulation, wireless communication, and holograms by modulating the spatial phase or amplitude. However, programmable amplitude‐coding modulations have rarely been investigated due to the difficulty in realizing dynamic control of amplitude. Herein, a real‐time programmable amplitude‐coding metasurface with multifrequency modulation is proposed by integrating PIN diodes and chip attenuators to the metaelement. The element is encoded as “11,” “10,” and “00,” corresponding to the ON/OFF states of two diodes. By switching the two states of the PIN diode, the metaelement exhibits distinctly reflected amplitude responses in three frequencies (2.98, 4.11, and 5.73 GHz). For the whole metasurface, the magnitude of the reflected beam can be modulated with some specific coding patterns. To verify the performance, six coding patterns with 10 × 10 metaelements are designed, and four of them are measured. Experimental results are fundamentally consistent with theoretical designs and simulations. Further a wireless communication demonstration is designed and implemented to perform direct modulation of digital signals without using mixers required in the conventional wireless communication systems. It is envisioned that this work will find applications in new architecture encrypted communication and imaging systems.

Conventional imagers require time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing. Here, the authors demonstrate a real-time digital-metasurface imager that can be trained in-situ to show high accuracy image coding and recognition for various image sets.

In this study, the circular Gaussian spot emitted by a laser light source is shaped into a rectangular flat-top beam to improve the scanning efficiency of a selective laser sintering scanning system. A CO2 laser with a power of 200 W, wavelength of 10.6 μm, and spot diameter of 9 mm is shaped into a flat-top spot with a length and width of 0.5 × 0.1 mm, and the mapping function and flat-top Lorentzian function are calculated. We utilize ZEMAX to optimize the aspherical cylindrical lens of the shaping system and the cylindrical lens of the focusing system. We then calculate the energy uniformity of the flat-top line-shaped beam at distances from 500 to 535 mm and study the zoom displacement of the focusing lens system. The results indicated that the energy uniformity of the flat-top beam was greater than 80% at the distances considered, and the focusing system must precisely control the displacement of the cylindrical lens in the Y-direction to achieve precise zooming.

Age-related effects on whole-tree hydraulics are one of the key challenges to better predicting the production and growth of old-growth forests. Previous models have described the optimal state of stomatal behaviour, and field studies have implied on age/size-induced trends in tree ecophysiology related to hydraulics. On these bases, we built a Bayesian hierarchical model to link sap flow density and drivers of transpiration directly. The model included parameters with physiological meanings and accounted for variations in leaf-sapwood area ratio and the time lag between sap flow and transpiration. The model well-simulated the daily pattern of sap flow density and the variation between tree age groups. The results of parameterization show that (1) the usually higher stomatal conductance in young than old trees during mid-summer was mainly because the sap flow of young trees were more activated at low to medium light intensity, and (2) leaf-sapwood area ratio linearly decreased while time lag linearly increased with increasing tree height. Uncertainty partitioning and cross-validation, respectively, indicated a reliable and fairly robust parameter estimation. The model performance may be further improved by higher data quality and more process-based expressions of the internal dynamics of trees.

Metasurfaces have been developed as a promising approach for manipulating electromagnetic waves. Recently, deep learning algorithms have been introduced to design metasurfaces, but the network can only output one solution for each desired input and suffers from nonunique issue. To overcome the aforementioned challenges, a deep neural network model for inverse designs of anisotropic metasurfaces with full phase properties in ultrawideband is proposed. Given the target reflection spectra as inputs, the candidate metasurface patterns are generated through a generative adversarial network (GAN), and the corresponding predictions are simply achieved by the accurate forward neural network model to match the target spectra in the whole band with high fidelity. By training the generator and discriminator in GAN in an alternating order combined with setting a threshold of discriminator loss to trigger the phase prediction, the proposed method is much more efficient and consumes less time in the training process. Numerical simulations and experimental results demonstrate that the reflection phases of the generated meta‐atoms have excellent agreements with the given targets, providing an efficient way in automatically designing metasurfaces. The most important advantage of this approach over the previous schemes is to improve the design speed significantly with very good accuracy.

Self-reconfiguration of modular self-reconfigurable robots is a fundamental function that can be used as part of higher-level functionality. Interaction with the environment is a key factor affecting the self-reconfiguration process of modular robots. In this article, a modeling framework that makes it possible to simulate and visualize the interactions at the level of decentralized modules will be introduced. The framework extends the formalism of Lindenmayer systems (L-systems) with constructs needed to model robotic information exchanged between decentralized modules and their surrounding environments. Both the construction of target configurations and environmental sensitive adaption can be handled by extending L-system symbols and reproduction rules. The proposed method is illustrated with simulations capturing the development of branching structures while adapting to environmental obstacles.

ABSTRACT Glioblastoma multiforme (GBM) is the most common brain tumor in adults. Human cytomegalovirus (HCMV) genomes are present in GBM tumors, yielding hope that antiviral treatments could prove therapeutic and improve the poor prognosis of GBM patients. We discovered that GBM cells infected in vitro with HCMV display properties of cancer stem cells. HCMV-infected GBM cells grow more slowly than mock-infected controls, demonstrate a higher capacity for self-renewal determined by a sphere formation assay, and display resistance to the chemotherapeutic drug temozolomide. Our data suggest that HCMV, while present in only a minority of the cells within a tumor, could contribute to the pathogenesis of GBMs by promoting or prolonging stem cell-like phenotypes, thereby perpetuating tumors in the face of chemotherapy. Importantly, we show that temozolomide sensitivity is restored by the antiviral drug ganciclovir, indicating a potential mechanism underlying the positive effects observed in GBM patients treated with antiviral therapy. IMPORTANCE A role for HCMV in GBMs remains controversial for several reasons. Some studies find HCMV in GBM tumors, while others do not. Few cells within a GBM may harbor HCMV, making it unclear how the virus could be contributing to the tumor phenotype without infecting every cell. Finally, HCMV does not overtly transform cells in vitro. However, tumors induced by other viruses can be treated with antiviral remedies, and initial results indicate that this may be true for anti-HCMV therapies and GBMs. With such a poor prognosis for GBM patients, any potential new intervention deserves exploration. Our work here describes an evidence-based model for how HCMV could contribute to GBM biology while infecting very few cells and without transforming them. It also illuminates why anti-HCMV treatments may be beneficial to GBM patients. Our observations provide blueprints for future in vitro studies examining how HCMV manipulates stem cell-specific pathways and future clinical studies of anti-HCMV measures as GBM therapeutics.

While the aging process is central to the pathogenesis of age-dependent diseases, it is poorly understood at the molecular level. We identified a mouse mutant with accelerated aging in the retina as well as pathologies observed in age-dependent retinal diseases, suggesting that the responsible gene regulates retinal aging, and its impairment results in age-dependent disease. We determined that a mutation in the transmembrane 135 (Tmem135) is responsible for these phenotypes. We observed localization of TMEM135 on mitochondria, and imbalance of mitochondrial fission and fusion in mutant Tmem135 as well as Tmem135 overexpressing cells, indicating that TMEM135 is involved in the regulation of mitochondrial dynamics. Additionally, mutant retina showed higher sensitivity to oxidative stress. These results suggest that the regulation of mitochondrial dynamics through TMEM135 is critical for protection from environmental stress and controlling the progression of retinal aging. Our study identified TMEM135 as a critical link between aging and age-dependent diseases.

To assess wavefront derived refraction and full eye biometry including ciliary muscle dimension and full eye axial geometry in pseudophakic eyes using spectral domain OCT equipped with a Shack-Hartmann wavefront sensor.Twenty-eight adult subjects (32 pseudophakic eyes) having recently undergone cataract surgery were enrolled in this study. A custom system combining two optical coherence tomography systems with a Shack-Hartmann wavefront sensor was constructed to image and monitor changes in whole eye biometry, the ciliary muscle and ocular aberration in the pseudophakic eye. A Badal optical channel and a visual target aligning with the wavefront sensor were incorporated into the system for measuring the wavefront-derived refraction. The imaging acquisition was performed twice. The coefficients of repeatability (CoR) and intraclass correlation coefficient (ICC) were calculated.Images were acquired and processed successfully in all patients. No significant difference was detected between repeated measurements of ciliary muscle dimension, full-eye biometry or defocus aberration. The CoR of full-eye biometry ranged from 0.36% to 3.04% and the ICC ranged from 0.981 to 0.999. The CoR for ciliary muscle dimensions ranged from 12.2% to 41.6% and the ICC ranged from 0.767 to 0.919. The defocus aberrations of the two measurements were 0.443 ± 0.534 D and 0.447 ± 0.586 D and the ICC was 0.951.The combined system is capable of measuring full eye biometry and refraction with good repeatability. The system is suitable for future investigation of pseudoaccommodation in the pseudophakic eye.

Dynamic axial compression (DAC) columns are key elements in simulated moving bed, which is a chromatography process in drug industry and chemical engineering. In this study, rules for designing distributors are proposed based on mass conservation and validated by experiments, the computer aided design (CAD) and the computational fluid dynamics (CFD). Experimental works are conducted to choose feasible numerical parameters for simulations. In CFD, the transient laminar flow fields are governed by the momentum and species transport equations with Darcy's law to model the porous zone in the packed bed. Results show that CFD combined with CAD solid modelling is a good approach to explore detailed flow fields in DAC columns and carry out parameter analysis for innovative designs. For further testing and evaluation, a new model of compound distributor is designed, 3D printed and processed in factory for practical applications in preparative chromatography.

Zika virus (ZIKV) has been defined as a teratogenic pathogen behind the increased number of cases of microcephaly in French Polynesia, Brazil, Puerto Rico, and other South American countries. Experimental studies using animal models have achieved tremendous insight into understanding the viral pathogenesis, transmission, teratogenic mechanisms, and virus–host interactions. However, the animals used in published investigations are mostly interferon (IFN)-compromised, either genetically or via antibody treatment. Herein, we studied ZIKV infection in IFN-competent mice using African (MR766) and Asian strains (PRVABC59 and SZ-WIV01). After testing four different species of mice, we found that BALB/c neonatal mice were resistant to ZIKV infection, that Kunming, ICR and C57BL/6 neonatal mice were fatally susceptible to ZIKV infection, and that the fatality of C57BL/6 neonates from 1 to 3 days old were in a viral dose-dependent manner. The size and weight of the brain were significantly reduced, and the ZIKV-infected mice showed neuronal symptoms such as hind-limb paralysis, tremor, and poor balance during walking. Pathologic and immunofluorescent experiments revealed that ZIKV infected different areas of the central nervous system (CNS) including gray matter, hippocampus, cerebral cortex, and spinal cord, but not olfactory bulb. Interestingly, ZIKV replicated in multiple organs and resulted in pathogenesis in liver and testis, implying that ZIKV infection may engender a high health risk in neonates by postnatal infection. In summary, we investigated ZIKV pathogenesis using an animal model that is not IFN-compromised.

The fact that piezoelectric ceramic transducer (PZT) precision drive systems in 3D printing are faced with nonlinear problems with respect to positioning, such as hysteresis and creep, has had an extremely negative impact on the precision of laser focusing systems. To eliminate the impact of PZT nonlinearity during precision drive movement, mathematical modeling and theoretical analyses of each module comprising the system were carried out in this study, a micro-displacement measurement circuit based on Position Sensitive Detector (PSD) is constructed, followed by the establishment of system closed-loop control and creep control models. An XL-80 laser interferometer (Renishaw, Wotton-under-Edge, UK) was used to measure the performance of the precision drive system, showing that system modeling and control algorithms were correct, with the requirements for precision positioning of the drive system satisfied.

Enterovirus 71 (EV71) is a neurotropic virus capable of inducing severe neurological symptoms and death. No direct targeting antivirals are useful in the treatment of severe EV71 infection. Because of low toxicity and good specificity, monoclonal antibodies (MAb) are a potential candidate for the treatment of viral infections. Therefore, we developed an EV71-specific conformational MAb with high in vitro cross-neutralization activity to heterologous EV71 subgenotypes. The in vivo treatment experiment at different days post-infection indicated that a single treatment of MAb CT11F9 within day 3 post-infection fully protected mice from morbidity and mortality (0% PBS vs. 100% at 10 µg/g per body weight ***P

Quantum logic gates differ from classical logic gates as the former involves quantum operators. The conventional gates such as AND, OR, NOT etc., are generally classified as classical gates, however, some of the quantum gates are known as Pauli gates, Toffoli gates and Hadamard gates, respectively. Normally classical states only involve 0 and 1, whereas quantum states involve the superpositions of 0 and 1. Hence, underlying principles of algorithm implementation for classical logic gate and quantum logic gate are indeed different. In this paper, we introduce significant concepts of quantum computations, analyse the discrepancy between classical and quantum gates, compare quantum algorithms using Qiskit against equivalent classical algorithms and analyse their performance in terms of runtime.

Glioblastoma (GBM) is the most common primary brain tumor in adults. The poor prognosis and minimally successful treatments of these tumors indicates a need to identify new therapeutic targets. Therapy resistance of GBMs is attributed to heterogeneity of the glioblastoma due to genetic alterations and functional subpopulations. Chemokine receptors CXCR4 and CXCR7 play important roles in progression of various cancers although the specific functions of the CXCL12-CXCR4-CXCR7 axis in GBM are less characterized. In this study we examined the expression and function of CXCR4 and CXCR7 in four primary patient-derived GBM cell lines of the proliferative subclass, investigating their roles in in vitro growth, migration, sphere and tube formation. CXCR4 and CXCR7 cell surface expression was heterogeneous both between and within each cell line examined, which was not reflected by RT-PCR analysis. Variable percentages of CXCR4+CXCR7- (CXCR4 single positive), CXCR4-CXCR7+ (CXCR7 single positive), CXCR4+CXCR7+ (double positive), and CXCR4-CXCR7- (double negative) subpopulations were evident across the lines examined. A subpopulation of slow cell cycling cells was enriched in CXCR4 and CXCR7. CXCR4+, CXCR7+, and CXCR4+/CXCR7+ subpopulations were able to initiate intracranial tumors in vivo. CXCL12 stimulated in vitro cell growth, migration, sphere formation and tube formation in some lines and, depending on the response, the effects were mediated by either CXCR4 or CXCR7. Collectively, our results indicate a high level of heterogeneity in both the surface expression and functions of CXCR4 and CXCR7 in primary human GBM cells of the proliferative subclass. Should targeting of CXCR4 and CXCR7 provide clinical benefits to GBM patients, a personalized treatment approach should be considered given the differential expression and functions of these receptors in GBM.