Role of CD4 T Cell in Relapsing-Remitting Experimental Autoimmune Encephalomyelitis.

Multiple sclerosis (MS) is an autoimmune disease characterized by the infiltration of immune cells and demyelination in the central nervous system (CNS). Experimental autoimmune encephalomyelitis (EAE) serves as a prototypic animal model for studying MS. In this study, we aimed to investigate the role of CD4 T cells in the initiation and relapse of EAE, focusing on the activation phase and immune response. To create the EAE mice model, female mice were immunized with myelin oligodendrocyte glycoprotein (MOG)35-55 emulsified with complete Freund's adjuvant (CFA). Clinical scores were assessed daily, and results demonstrated that mice in the EAE group exhibited a classic relapsing-remitting pattern. Hematoxylin-eosin (H&E) and luxol fast blue (LFB) staining analysis revealed significant infiltration of inflammatory cells in the CNS and demyelination in EAE mice. Regarding the activation phase, both CD4+CD69+ effector T (Teff) cells and CD4+CD44+CD62L- effector memory T (Tem) cells may contribute to the initiation of EAE, however, the relapse stage was probably dominated by CD4+CD44+CD62L- Tem cells. Additionally, in terms of immune function, helper T (Th)1 cells are primarily involved in initiating the EAE. However, both Th1 and Th17 cells contribute to the relapse stage, and the immunosuppressive function of regulatory T (Treg) cells was inhibited during the EAE pathological process.

Superconductivity Above 100 K Predicted in Carbon-Cage Network.

To explore carbide superconductors with higher transition temperature, two novel carbon structures of cage-network are designed and their superconductivity is studied by doping metals. MC6 and MC10 are respectively identified as C24 and C32 cage-network structures. This study finds that both carbon structures drive strong electron-phonon interaction and can exhibit superconductivity above liquid nitrogen temperature. Importantly, the superconducting transition temperatures above 100 K are predicted to be achieved in C24 -cage-network systems doped by Na, Mg, Al, In, and Tl at ambient pressure, which is far higher than those in graphite, fullerene, and other carbides. Meanwhile, the superconductivity of cage-network carbides is also found to be sensitive to the electronegativity and concentration of dopant M. The result indicates that the higher transition temperatures can be obtained by optimizing the carbon-cage-network structures and the doping conditions. The study suggests that the carbon-cage-network structure is a direction to explore high-temperature superconducting carbides.

A Deep Neural Network-Based Model for Quantitative Evaluation of the Effects of Swimming Training.

This paper analyzes the quantitative assessment model of the swimming training effect based on the deep neural network by constructing a deep neural network model and designing a quantitative assessment model of the swimming training effect. This paper addresses the problem of not considering the influence of the uncertainties existing in the virtual environment when evaluating swimming training and adds the power of the delays in the actual training operation environment, which is used to improve the objectivity and usability of swimming training evaluation results. To better measure the degree of influence of uncertainties, a training evaluation software module is developed to validate the usability of the simulated training evaluation method using simulated case data and compare it with the data after training evaluation using the unimproved evaluation method to verify the correctness and objectivity of the evaluation method in this paper. In the experiments, the feature extractor is a deep neural network, and the classifier is a gradient-boosting decision tree with integrated learning advantages. In the experimental comparison, we can achieve more than 60% accuracy and no more than a 1.00% decrease in recognition rate on DBPNN + GBDT, 78.5% parameter reduction, and 54.5% floating-point reduction on DPBNN. We can effectively reduce 32.1% of video memory occupation. It can be concluded from the experiments that deep neural network models are more effective and easier to obtain relatively accurate experimental results than shallow learning when facing high-dimensional sparse features. At the same time, deep neural networks can also improve the prediction results of external learning models. Therefore, the experimental results of this model are most intuitively accurate when combining deep neural networks with gradient boosting decision trees.

Selenium Vacancies and Synergistic Effect of Near- and Far-Field-Enabled Ultrasensitive Surface-Enhanced Raman-Scattering-Active Substrates for Malaria Detection.

Defect engineering with the active control of defect states brings remarkable enhancement on surface-enhanced Raman scattering (SERS) by magnifying semiconductor-molecule interaction. Such light-trapping architectures can increase the light path length, which promotes photon-analytes interactions and further improves the SERS sensitivity. However, by far the reported semiconductor SERS-active substrates based on these strategies are often nonuniform and commonly in the form of isolated laminates or random clusters, which limit their reliability and stability for practical applications. Herein, we develop self-grown single-crystalline "V-shape" SnSe2-x (SnSe1.5, SnSe1.75, SnSe2) nanoflake arrays (SnSe2-x NFAs) with controlled selenium vacancies over large-area (10 cm × 10 cm) for ultrahigh-sensitivity SERS. First-principles density functional theory (DFT) is used to calculate the band gap and the electronic density of states (DOS). Based on the Herzberg-Teller theory regarding the vibronic coupling, the results of theoretical calculation reveal that the downshift of band edge and high DOS of SnSe1.75 can effectively enhance the vibronic coupling within the SnSe1.75-R6G system, which in turn enhances the photoinduced charge transfer resonance and contributes to the SERS activity with a remarkable enhancement factor of 1.68 × 107. Furthermore, we propose and demonstrate ultrasensitive (10-15 M for R6G), uniform, and reliable SERS substrates by forming SnSe1.75 NFAs/Au heterostructures via a facile Au evaporation process. We attribute the superior performance of our SnSe1.75 NFAs/Au heterostructures to the following reasons: (1) selenium vacancies and (2) synergistic effect of the near and far fields. In addition, we successfully build a detection platform to achieve rapid (∼15 min for the whole process), antibody-free, in situ, and reliable early malaria detection (100% detection rate for 10 samples with 160 points) in whole blood, and molecular hemozoin (<100/mL) can be detected. Our approach not only provides an efficient technique to obtain large-area, uniform, and reliable SERS-active substrates but also offers a substantial impact on addressing practical issues in many application scenarios such as the detection of insect-borne infectious diseases.

A Label-Free Fluorescent Aptasensor for Detection of Staphylococcal Enterotoxin A Based on Aptamer-Functionalized Silver Nanoclusters.

Staphylococcal enterotoxin A (SEA) is a worldwide public health problem accounting for the majority of food poisoning which is produced by Staphylococcus aureus, threatening human health and leading to various foodborne diseases. Therefore, it is of great significance to develop a sensitive detection method for SEA to ensure food safety and prevent foodborne diseases in humans. In this study, an adaptive fluorescence biosensor for the detection of staphylococcal enterotoxin A (SEA) was designed and developed by combining DNA silver nanoclusters (DNA-AgNCs) with polypyrrole nanoparticles (PPyNPs). Fluorescent AgNCs, synthesized using aptamers as templates, were used as fluorescence probes, whose fluorescence was quenched by PPyNPs. In the presence of the target SEA, DNA-AgNCs were forced to desorb from the surface of PPyNPs through the binding of SEA with the aptamer-DNA-AgNCs, thereby resulting in fluorescence recovery. Under the optimized conditions, the relative fluorescence intensity (FI) showed a linear relationship with the SEA concentration in the range from 0.5 to 1000 ng/mL (Y = 1.4917X + 0.9100, R2 = 0.9948) with a limit of detection (LOD) of 0.3393 ng/mL. The sensor was successfully used to evaluate the content of SEA in milk samples, and the recovery efficiency of SEA was between 87.70% and 94.65%. Thus, the sensor shows great potential for application in food analysis. In short, the proposed platform consisted of an aptamer fluorescent sensor that can be used for the ultrasensitive detection of various toxins by taking advantage of the excellent affinity and specificity of corresponding aptamers.

Selection and application of ssDNA aptamers against spermine based on Capture-SELEX.

Spermine contamination ranks as one of the food safety issues, it will cause some adverse reactions if the intake of spermine is excessive in human body. So it is of great significance to establish fast and efficient analysis method to detect spermine in foods. In this study, the spermine aptamers with high affinity and specificity were obtained by the capture systematic evolution of ligands by exponential enrichment (Capture-SELEX) technique. Forty-one aptamer sequences were obtained by cloning and sequencing, and were divided into eight families based on homology and secondary structure analysis. The affinity and specificity of candidate aptamers was analyzed by isothermal titration calorimetry (ITC) and fluorescence assay. The aptamers named APJ-6 was picked out as the optimal aptamer that recognizes spermine specifically with the Kd value of 9.648 ±â€¯0.896 nM. In order to verify the practicability of the selected aptamers, the sensitive aptamer-based fluorescene assay was designed. Under optimized conditions, this aptasensor exhibited a low detection limit of 0.052 nM, as well as a linear within the range of 0.1-20 nM. Besides, it has been further applied for the determination of spermine in pork samples and the recoveries ranged from 86.45% to 98.15%, showing its great potential for sensitive analysis in food safety control.

[Development of indel markers for molecular authentication of Panax ginseng and P. quinquefolius].

Panax ginseng and P. quinquefolius are two kinds of important medicinal herbs. They are morphologically similar but have different pharmacological effects. Therefore, botanical origin authentication of these two ginsengs is of great importance for ensuring pharmaceutical efficacy and food safety. Based on the fact that intron position in orthologous genes is highly conserved across plant species, intron length polymorphisms were exploited from unigenes of ginseng. Specific primers were respectively designed for these two species based on their insertion/deletion sequences of cytochrome P450 and glyceraldehyde 3-phosphate dehydrogenase, and multiplex PCR was conducted for molecular authentication of P.ginseng and P. quinquefolius. The results showed that the developed multiplex PCR assay was effective for molecular authentication of P.ginseng and P. quinquefolius without strict PCR condition and the optimization of reaction system.This study provides a preferred ideal marker system for molecular authentication of ginseng,and the presented method can be employed in origin authentication of other herbal preparations.

[A simulation study of the effects of ischemia on spiral waves in 2D human ventricular tissue].

Based on human ventricular single cell mathematical model, a two-dimensional mesh of ventricular wall tissue was constructed. Through the increasing of the concentration of extracellular K+, we simulated the propagation of spiral wave in a condition under the influence of ischemia in 2-D human ventricular tissue. The results showed that along with the increase of ischemic level and size, the instability of spiral waves increased, and under the influence of certain ischemic level and size, spiral waves broke up. Through this simulation study of the effects of ischemia on spiral waves in 2-D human ventricular tissue, we explained the corresponding mechanism of the maintenance of ventricular tachycardia and the cause of ventricular fibrillation under the influence of ischemia.