Establishment of a RAA-CRISPR Cas12a based diagnostic method for peste des petits ruminants virus N gene and M gene.

Peste des petis ruminants (PPR) is an acute, highly contagious fatal disease affecting both domestic and wild small ruminants, caused by Morbillivirus caprinae (also known as peste des petis ruminants virus (PPRV)). Herein, a rapid method based on recombinase aided amplification-clustered regularly interspaced short palindromic repeats-Cas12a (RAA-CRISPR Cas12a) to detect PPRV was developed. CRISPR RNAs and RAA primers for PPRV-N (nucleocapsid) and PPRV-M (matrix) fragments were designed. The reaction system was constructed following screening and optimization. Detection could be completed within in 50 minutes at 37°C. Detection of gradient dilutions of plasmids carrying of PPRV N and M gene fragments indicated a minimum limit of detection of 10 copies/µL. There were no cross-reactions with related viruses and all tested lineages of PPRV were detected successfully. The method also showed good repeatability. The detection of clinical samples (previously detected using reverse transcription polymerase chain reaction (RT-PCR)) indicated good consistency between the RAA-CRISPR Cas12a method and RT-PCR. Thus, the RAA-CRISPR Cas12a method for rapid PPRV diagnosis has strong specificity, high sensitivity, and stable repeatability. Moreover, the results can be observed visually under blue or UV light or using lateral flow strips without complex instruments.

Biocompatible Perovskite Nanocrystals with Enhanced Stability for White Light-Emitting Diodes.

Recently emerged lead halide perovskite CsPbX3 (X = Cl, Br, and I) nanocrystals (PNCs) have attracted tremendous attention due to their excellent optical properties. However, the poor water stability, unsatisfactory luminescence efficiency, disappointing lead leakage, and toxicity have restricted their practical applications in photoelectronics and biomedical fields. Herein, a controllable encapsulated strategy is investigated to realize CsPbX3 PNCs/PVP @PMMA composites with superior luminescence properties and excellent biocompatibility. Additionally, the synthesized CsPbBr3 and CsPbBr0.6I2.4 PNCs/PVP@PMMA structures exhibit green and red emissions with a maximal photoluminescence quantum yield (PLQY) of about 70.24% and 98.26%, respectively. These CsPbX3 PNCs/PVP@PMMA structures show high emission efficiency, excellent stability after water storage for 18 months, and low cytotoxicity at the PNC concentration at 500 µg mL-1. Moreover, white light-emitting diode (WLED) devices based on mixtures of CsPbBr3 and CsPbBr0.6I2.4 PNCs/PVP@PMMA perovskite structures are investigated, which exhibit excellent warm-white light emissions at room temperature. A flexible manipulation method is used to fabricate the white light emitters based on these perovskite composites, providing a fantastic platform for fabricating solid-state white light sources and full-color displays.

Discovery of Highly Potent Small-Molecule PD-1/PD-L1 Inhibitors with a Novel Scaffold for Cancer Immunotherapy.

Inhibition of the PD-1/PD-L1 interaction through small-molecule inhibitors is a promising therapeutic approach in cancer immunotherapy. Herein, we utilized BMS-202 as the lead compound to develop a series of novel PD-1/PD-L1 small-molecule inhibitors with a naphthyridin scaffold. Among these compounds, X14 displayed the most potent inhibitory activity for the PD-1/PD-L1 interaction (IC50 = 15.73 nM). Furthermore, X14 exhibited good binding affinity to both human PD-L1 (KD = 14.62 nM) and mouse PD-L1 (KD = 392 nM). In particular, X14 showed favorable pharmacokinetic properties (oral bioavailability, F = 58.0%). In the 4T1 (mouse breast cancer cells) syngeneic mouse model, intragastric administration of X14 at 10 mg/kg displayed significant antitumor efficacy (TGI = 66%). Mechanistic investigations revealed that X14 effectively enhanced T-cell infiltration within the tumor microenvironment. Our study demonstrates that compound X14 exhibits potential as a candidate compound for the development of orally effective small-molecule inhibitors targeting PD-1/PD-L1.

Discovery of the novel and potent histamine H1 receptor antagonists for treatment of allergic diseases.

Desloratadine, a second-generation histamine H1 receptor antagonist, has established itself as a first-line drug for the treatment of allergic diseases. Despite its effectiveness, desloratadine exhibits an antagonistic effect on muscarinic M3 receptor, which can cause side effects such as dry mouth and urinary retention, ultimately limiting its clinical application. Herein, we describe the discovery of compound Ⅲ-4, a novel H1 receptor antagonist with significant H1 receptor antagonistic activity (IC50 = 24.12 nM) and enhanced selectivity towards peripheral H1 receptor. In particular, Ⅲ-4 exhibits reduced M3 receptor inhibitory potency (IC50 > 10,000 nM) and acceptable hERG inhibitory activity (17.6 ± 2.1 µM) compare with desloratadine. Additionally, Ⅲ-4 exhibits favorable pharmacokinetic properties, as well as in vivo efficacy and safety profiles. All of these reveal that Ⅲ-4 has potential to emerge as a novel H1 receptor antagonist for the treatment of allergic diseases. More importantly, the compound Ⅲ-4 (HY-078020) has recently been granted clinical approval.

Transformation of crystal structure induced by the temperatures in carbon dots (CDs)-based composites with multicolor fluorescence for white Light-Emitting-Diode (WLED).

Regulation of the fluorescence through crystalizing from the matrix in the Carbon dots (CDs)-based solid-state materials has been verified to be one of the effective methods, yet there are not only challenges in preparing such materials efficiently, but also insufficient insight into their regulation mechanisms. Here, a one-pot solvothermal route to synthesize a series of CDs-based composites with crystalline matrix is reported. These crystals exhibited multicolor fluorescence with the feature of multi-peaks emissions with increasing temperatures from 140 ℃ to 220 ℃, in which the orange emitting O-CDs@PA and the yellow emitting Y-CDs@PA crystals obtained the FLQYs of 22% and 68% respectively due to relatively stable crystalline structures. After comparative analysis to both crystals in detail, the core and the groups associated with them on the interface between CDs and matrix were adjusted in size and species during structural transformation of the crystal matrix, which changes radically the energy band structures to influence fluorescent emitting of both crystals ultimately. In addition, the reasons resulting in higher FLQY for Y-CDs@PA were provided leveraging the schematic illustration presumed based on the PL properties of both crystals. Because of the optimal optical performances, these fluorescent materials promised to fabricate WLED devices and obtained a number of photometric parameters endowed these WLED devices with the feature of warm-white light.

Broadband free space 2 × 4 90° optical hybrid for satellite laser communication.

We design a broadband free space 2×4 90° optical hybrid over a spectral window of 1000-1200 nm and 1470-1650 nm and verify the feasibility of the scheme experimentally. The hybrid consists of three broadband polarization beam splitters, an achromatic λ/4 wave plate, and three achromatic λ/2 wave plates. The fabricated hybrid exhibits a good quadrature phase response with an interchannel imbalance of 0.93-1.07 and a low phase deviation of less than 0.2° under the typical communication wavelengths of 1064 nm and C-band. The experimental results of the heterodyne method show that the proposed hybrid can effectively solve the wavelength incompatibility problem in satellite laser communication and realize interconnection at different wavelengths. The designed hybrid (without coupling) has a measured insertion loss of no more than 7.34 dB at 1064 nm and C-band. A high-speed transmission experiment with BPSK format has been conducted to verify the performance of the assembled device.

Hybrid integrated Si3N4 external cavity laser with high power and narrow linewidth.

We have designed and fabricated a hybrid integrated laser source with full C-band wavelength tunability and high-power output. The external cavity laser is composed of a gain chip and a dual micro-ring narrowband filter integrated on the silicon nitride photonic chip to achieve a wavelength tuning range of 55 nm and a SMSR higher than 50 dB. Through the integration of the semiconductor optical amplifier in the miniaturized package, the laser exhibits an output power of 220 mW and linewidth narrower than 8 kHz over the full C-band. Such a high-power, narrow-linewidth laser diode with a compact and low-cost design could be applied whenever coherence and interferometric resolutions are needed, such as silicon optical coherent transceiver module for space laser communication, light detection and ranging (LiDAR).

Sensitivity Deterioration of Free-Space Optical Coherent/Non-Coherent OOK Modulation Receiver by Ambient Light Noise.

In free-space optical (FSO) communication systems, on-off keying (OOK) is a widely used modulation format. Coherent and non-coherent OOK receivers with sensitivities of -54.60 dBm and -51.25 dBm, respectively, were built with a communication rate of 1 Gbit/s and a bit error rate of 10-3. In an FSO communication system, the parameters must be designed to ensure a sufficient link margin. In contrast to optical fiber systems, FSO systems have ambient light (AL) noise such as sunlight. The efficiency of sunlight coupling in the single-mode fiber (SMF) of the receivers was calculated in this study. For a signal light with AL, the change in the main components of noise and the sensitivity deterioration were theoretically analyzed and experimentally verified in conditions of coherent reception and non-coherent reception with a preamplifier. For coherent reception, the theoretical sensitivity deterioration results are consistent with the experimental results which indicate that coherent reception exhibits better anti-AL noise performance than non-coherent reception when the power spectral density of the AL is the same. Coherent and non-coherent receivers coupled with SMF can work in direct sunlight. When the receiver lens diameter is greater than 4.88 × 10-4 m, the anti-AL noise performance of the receiver can be improved by increasing the receiver lens diameter.

Hierarchical Echo State Network With Sparse Learning: A Method for Multidimensional Chaotic Time Series Prediction.

Echo state network (ESN), a type of special recurrent neural network with a large-scale randomly fixed hidden layer (called a reservoir) and an adaptable linear output layer, has been widely employed in the field of time series analysis and modeling. However, when tackling the problem of multidimensional chaotic time series prediction, due to the randomly generated rules for input and reservoir weights, not only the representation of valuable variables is enriched but also redundant and irrelevant information is accumulated inevitably. To remove the redundant components, reduce the approximate collinearity among echo-state information, and improve the generalization and stability, a new method called hierarchical ESN with sparse learning (HESN-SL) is proposed. The HESN-SL mines and captures the latent evolution patterns hidden from the dynamic system by means of layer-by-layer processing in stacked reservoirs, and leverage monotone accelerated proximal gradient algorithm to train a sparse output layer with variable selection capability. Meanwhile, we further prove that the HESN-SL satisfies the echo state property, which guarantees the stability and convergence of the proposed model when applied to time series prediction. Experimental results on two synthetic chaotic systems and a real-world meteorological dataset illustrate the proposed HESN-SL outperforms both original ESN and existing hierarchical ESN-based models for multidimensional chaotic time series prediction.

Multi-dimensional and large-sized optical phased array for space laser communication.

In this study, we propose a novel multi-dimensional and large-sized optical phased array theory for space laser communication that addresses the theoretical limitations of the conventional optical phased array. We theoretically analyzed the principle of this phased array technology. The results of simulation and laboratory experiment clearly showed it can realize the large scanning angle and high optical gain required for communication. The novel optical phased array theory is of great significance to the revolution of miniaturization and networking in the field of space laser communication.

Learning Both Dynamic-Shared and Dynamic-Specific Patterns for Chaotic Time-Series Prediction.

In the real world, multivariate time series from the dynamical system are correlated with deterministic relationships. Analyzing them dividedly instead of utilizing the shared-pattern of the dynamical system is time consuming and cumbersome. Multitask learning (MTL) is an effective inductive bias method to utilize latent shared features and discover the structural relationships from related tasks. Base on this concept, we propose a novel MTL model for multivariate chaotic time-series prediction, which could learn both dynamic-shared and dynamic-specific patterns. We implement the dynamic analysis of multiple time series through a special network structure design. The model could disentangle the complex relationships among multivariate chaotic time series and derive the common evolutionary trend of the multivariate chaotic dynamical system by inductive bias. We also develop an efficient Crank-Nicolson-like curvilinear update algorithm based on the alternating direction method of multipliers (ADMM) for the nonconvex nonsmooth Stiefel optimization problem. Simulation results and analysis demonstrate the effectiveness on dynamic-shared pattern discovery and prediction performance.

Modified BBO-Based Multivariate Time-Series Prediction System With Feature Subset Selection and Model Parameter Optimization.

Multivariate time-series prediction is a challenging research topic in the field of time-series analysis and modeling, and is continually under research. The echo state network (ESN), a type of efficient recurrent neural network, has been widely used in time-series prediction, but when using ESN, two crucial problems have to be confronted: 1) how to select the optimal subset of input features and 2) how to set the suitable parameters of the model. To solve this problem, the modified biogeography-based optimization ESN (MBBO-ESN) system is proposed for system modeling and multivariate time-series prediction, which can simultaneously achieve feature subset selection and model parameter optimization. The proposed MBBO algorithm is an improved evolutionary algorithm based on biogeography-based optimization (BBO), which utilizes an S -type population migration rate model, a covariance matrix migration strategy, and a Lévy distribution mutation strategy to enhance the rotation invariance and exploration ability. Furthermore, the MBBO algorithm cannot only optimize the key parameters of the ESN model but also uses a hybrid-metric feature selection method to remove the redundancies and distinguish the importance of the input features. Compared with the traditional methods, the proposed MBBO-ESN system can discover the relationship between the input features and the model parameters automatically and make the prediction more accurate. The experimental results on the benchmark and real-world datasets demonstrate that MBBO outperforms the other traditional evolutionary algorithms, and the MBBO-ESN system is more competitive in multivariate time-series prediction than other classic machine-learning models.

Random Fourier feature kernel recursive maximum mixture correntropy algorithm for online time series prediction.

In the paper, a novel kernel recursive least-squares (KRLS) algorithm named random Fourier feature kernel recursive maximum mixture correntropy (RFF-RMMC) algorithm is proposed, which improves the prediction efficiency and robustness of the KRLS algorithm. Random Fourier feature (RFF) method as well as maximum mixture correntropy criterion (MMCC) are combined and applied into KRLS algorithm afterwards. Using RFF to approximate the kernel function in KRLS with a fixed cost can greatly reduce the computational complexity and simultaneously improve the prediction efficiency. In addition, the MMCC maintains the robustness like the maximum correntropy criterion (MCC). More importantly, it can enhance the accuracy of the similarity measurement between predicted and true values by more flexible parameter settings, and then make up for the loss of prediction accuracy caused by RFF to a certain extent. The performance of the RFF-RMMC algorithm for online time series prediction is verified by the simulation results based on three datasets.

Inhibition of Histone Deacetylase 6 (HDAC6) as a therapeutic strategy for Alzheimer's disease: A review (2010-2020).

Alzheimer's disease (AD) is one of the most common neurodegenerative disorders, which is characterized by the primary risk factor, age. Several attempts have been made to treat AD, while most of them end in failure. However, with the deepening study of pathogenesis of AD, the expression of HDAC6 in the hippocampus, which plays a major role of the memory formation, is becoming worth of notice. Neurofibrillary tangles (NFTs), a remarkable lesion in AD, has been characterized in association with the abnormal accumulation of hyperphosphorylated Tau, which is mainly caused by the high expression of HDAC6. On the other hand, the hypoacetylated tubulin induced by HDAC6 is also fatal for the neuronal transport, which is the key impact of the formation of axons and dendrites. Overall, the significantly increased expression of HDAC6 in brain regions is deleterious to neuron survival in AD patients. Based on the above research, the inhibition of HDAC6 seems to be a potential therapeutic method for the treatment of AD. Up to now, various types of HDAC6 inhibitors have been discovered. This review mainly analyzes the HDAC6 inhibitors reported amid 2010-2020 in terms of their structure, selectivity and pharmacological impact towards AD. And we aim at facilitating the design and development of better HDAC6 inhibitors in the future.

Contralateral S1 nerve root transfer for motor function recovery in the lower extremity among patients with central nervous system injury: study protocol for a randomized controlled trial.

BACKGROUND: Central nervous system injury (CNSI) comprises a series of common diseases that severely affect patients' motor function and quality of life and is associated with high disability and mortality rates. Previous studies have shown that contralateral lumbosacral nerve root transfer significantly improved the function of the paralyzed limb in rat models of CNSI. These studies showed that severing the sacral 1 nerve root (S1) did not damage the function of the ipsilateral lower extremity. Thus, we speculate that contralateral S1 nerve root transfer can improve the recovery of a paralyzed limb. Because no associated rigorously designed randomized controlled trial has evaluated the effectiveness of contralateral S1 nerve transfer thus far, we designed this clinical trial to compare the effects of this new treatment approach with those of traditional treatments in paralyzed patients after chronic CNSI. METHODS: This is a single-center, prospective, randomized controlled trial. Forty patients, who meet the inclusion criteria and have hemiplegia caused by chronic CNSI, will be randomly divided into the surgical or non-surgical group. The treatment effect in the 2 groups will be assessed before and 3, 6, 9, 12, 18, and 24 months after intervention by using numerous scales and resting-state functional magnetic resonance imaging. The primary outcome will be the Fugl-Meyer score for the lower limbs 24 months after treatment. The secondary outcomes include the modified Ashworth spasm scale, the modified Barthel scale, 10-m walking speed measurement results, three-dimensional gait analysis, muscle strength testing, electromyography, and resting-state functional magnetic resonance imaging findings. Safety outcomes and adverse events will be observed simultaneously. DISCUSSION: We expect that the surgery will improve the sensorimotor functions of the paralyzed limb, and the results of this trial will provide high-quality clinical evidence for a new efficient treatment strategy for disability after CNSI. TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR1800014414, registration date: 12 January 2018.

A colloidal gold test strip assay for the detection of African swine fever virus based on two monoclonal antibodies against P30.

African swine fever (ASF), caused by African swine fever virus (ASFV), was first reported in Kenya in 1921, but an effective vaccine or antiviral drug is still not available for ASFV control. Rapid and effective diagnostics are key steps in managing ASF. We generated two monoclonal antibodies (MAbs) against the ASFV phosphoprotein P30 and designated these as 3H7A7 and 6H9A10. Epitope mapping revealed that MAb 3H7A7 and 6H9A10 recognized aa 144-154 and aa 12-18 of P30, respectively. A signal-amplified sandwich colloidal gold test strip for rapid detection of ASFV was developed based using these MAbs. Sensitivity and specificity analysis showed that the detection limit of the strip was 2.16 ng of P30. The strip only reacted with ASFV and did not react with other common porcine viruses. In detection tests using 153 clinical field samples including sera, plasma, anticoagulant-treated blood, and tissue, the strip had 95.42% concordance with real-time PCR. The new MAbs specific for P30 and the rapid colloidal gold test strip helped to reveal novel B cell epitopes in P30 and provide an efficient diagnostic test for on-site clinical detection of ASF.

Rapid and visual detection of African swine fever virus antibody by using fluorescent immunochromatography test strip.

African swine fever virus (ASFV) is a large and complex DNA virus that causes a highly contagious and often lethal swine viral disease, for which no vaccine and effective treatments are available yet. Hence, ASFV presents significant economic consequences for the swine industry. A rapid and simple diagnostic method is urgently needed to monitor ASFV-specific antibodies for controlling the spread of ASFV. In this study, we chose the truncated p54 protein as an antigen and combined it with Eu-doped fluorescent microspheres as tracers to detect anti-ASFV antibodies specifically. Results showed that the truncated p54 protein had high specificity to ASFV antibody and had no cross-reactions with other swine virus antibodies. The results between our fluorescent immunochromatography test strip (FICTS) and commercial ELISA kits showed high consistency. The proposed FICTS offers a rapid, sensitive, specific, and visual method for ASFV antibody detection and shows great potential for ASF epidemic surveillance and control.

A new feature selection method based on symmetrical uncertainty and interaction gain.

Defining important information from complex biological data is of great significance in biological study. It is known that the physiological and pathological changes in an organism are usually influenced by molecule interactions. Analyzing biological data by fusing the evaluation of the individual molecules and molecule interactions could induce a more accurate and comprehensive understanding of the organism. This study proposes an Interaction Gain - Recursive Feature Elimination (IG-RFE) method which evaluates the feature importance by combining the relevance between feature and class label and the interaction among features. Symmetrical uncertainty is adopted to measure the relevance between feature and the class label. The average normalized interaction gain of feature f, every other features and the class label is calculated to reflect the interaction of feature f with other features in the feature set F. Based on the combination of symmetrical uncertainty and normalized interaction gain, less important features are removed iteratively. To show the performance of IG-RFE, it was compared with seven efficient feature selection methods, MIFS, mRMR, CMIM, ReliefF, FCBF, PGVNS and SVM-RFE, on eleven public datasets. The experiment results showed the superiority of IG-RFE in accuracy, sensitivity, specificity and stability. Hence, integrating feature individual discriminative ability and the interaction among features could better evaluate feature importance in biological data analysis.

An extra insertion of tandem repeat sequence in African swine fever virus, China, 2019.

On 7 March 2019, African swine fever in a domestic pig farm was detected in Guangxi Province of China. The phylogenetic analysis showed that its causative strain contained two tandem repeat sequence insertions in the intergenic region between the I73R and the I329L genes, and was different from previously reported strains in China and other countries.

Robust manifold broad learning system for large-scale noisy chaotic time series prediction: A perturbation perspective.

Noises and outliers commonly exist in dynamical systems because of sensor disturbations or extreme dynamics. Thus, the robustness and generalization capacity are of vital importance for system modeling. In this paper, the robust manifold broad learning system(RM-BLS) is proposed for system modeling and large-scale noisy chaotic time series prediction. Manifold embedding is utilized for chaotic system evolution discovery. The manifold representation is randomly corrupted by perturbations while the features not related to low-dimensional manifold embedding are discarded by feature selection. It leads to a robust learning paradigm and achieves better generalization performance. We also develop an efficient solution for Stiefel manifold optimization, in which the orthogonal constraints are maintained by Cayley transformation and curvilinear search algorithm. Furthermore, we discuss the common thoughts between random perturbation approximation and other mainstream regularization methods. We also prove the equivalence between perturbations to manifold embedding and Tikhonov regularization. Simulation results on large-scale noisy chaotic time series prediction illustrates the robustness and generalization performance of our method.