Molecular Dynamics Simulation of Chain Folding for Polyethylene Subjected to Vibration Excitation

We propose a molecular dynamics method with vibration excitation, named as VEMD, to investigate the vibration effect on chain folding for polymer molecule. The VEMD method is based on the introduction of periodic force, the amplitude and frequency of which can be adjusted, and the method was applied to the folding simulation of a polyethylene chain. Simulation results show that the vibration excitation significantly affects the folding of the polyethylene, and frequency and amplitude of the vibration excitation play key roles in VEMD. Different frequencies and amplitudes will determine how and to what extent does the vibration excitation affect the folding process of the polyethylene structure

A New Race (X12) of Soybean Cyst Nematode in China

The soybean cyst nematode (SCN), Heterodera glycines, is a serious economic threat to soybean-producing regions worldwide. A new SCN population (called race X12) was detected in Shanxi province, China. Race X12 could reproduce on all the indicator lines of both race and Heterodera glycines (HG) type tests. The average number of females on Lee68 (susceptible control) was 171.40 with the lowest Female Index (FI) 61.31 on PI88788 and the highest FI 117.32 on Pickett in the race test. The average number of females on Lee68 was 323.17 with the lowest FI 44.18 on PI88788 and the highest FI 97.83 on PI548316 in the HG type test. ZDD2315 and ZDD24656 are elite resistant germplasms in China. ZDD2315 is highly resistant to race 4, the strongest infection race in the 16 races with FI 1.51 while being highly sensitive to race X12 with FI 64.32. ZDD24656, a variety derived from PI437654 and ZDD2315, is highly resistant to race 1 and race 2. ZDD24656 is highly sensitive to race X12 with FI 99.12. Morphological and molecular studies of J2 and cysts confirmed the population as the SCN H. glycines. This is a new SCN race with stronger virulence than that of race 4 and is a potential threat to soybean production in China

Direct measurement of the Raman enhancement factor of rhodamine 6G on graphene under resonant excitation

Graphene substrates have recently been found to generate Raman enhancement. Systematic studies using different Raman probes have been implemented, but one of the most commonly used Raman probes, rhodamine 6G (R6G), has yielded controversial results for the enhancement effect on graphene. Indeed, the Raman enhancement factor of R6G induced by graphene has never been measured directly under resonant excitation because of the presence of intense fluorescence backgrounds. In this study, a polarization-difference technique is used to suppress the fluorescence background by subtracting two spectra collected using different excitation laser polarizations. As a result, enhancement factors are obtained ranging between 1.7 and 5.6 for the four Raman modes of R6G at 611, 1,183, 1,361, and 1,647 cm[superscript −1] under resonant excitation by a 514.5 nm laser. By comparing these results with the results obtained under non-resonant excitation (632.8 nm) and pre-resonant excitation (593 nm), the enhancement can be attributed to static chemical enhancement (CHEM) and tuning of the molecular resonance. Density functional theory simulations reveal that the orbital energies and densities for R6G are modified by graphene dots.National Natural Science Foundation (China) (Nos. 21233001, 50972001, and 21129001)China. Ministry of Science and Technology (Nos. 2011YQ0301240201 and 2011CB932601)Beijing Natural Science Foundation (No. 2132056

Drug Release Analysis and Optimization for Drug-Eluting Stents

The drug release analysis and optimization for drug-eluting stents in the arterial wall are studied, which involves mechanics, fluid dynamics, and mass transfer processes and design optimization. The Finite Element Method (FEM) is used to analyze the process of drug release in the vessels for drug-eluting stents (DES). Kriging surrogate model is used to build an approximate function relationship between the drug distribution and the coating parameters, replacing the expensive FEM reanalysis of drug release for DES in the optimization process. The diffusion coefficients and the coating thickness are selected as design variables. An adaptive optimization approach based on kriging surrogate model is proposed to optimize the lifetime of the drug in artery wall. The adaptive process is implemented by an infilling sampling criterion named Expected Improvement (EI), which is used to balance local and global search and tends to find the global optimal design. The effect of coating diffusivity and thickness on the drug release process for a typical DES is analyzed by means of FEM. An implementation of the optimization method for the drug release is then discussed. The results demonstrate that the optimized design can efficiently improve the efficacy of drug deposition and penetration into the arterial walls

Immunogenicity and therapeutic effects of a Mycobacterium tuberculosis rv2190c DNA vaccine in mice

The Excel data file [FOLT] Figshare, [DOI: 10.6084/m9.figshare.4668148 and https://figshare.com/s/bd46c22986c673579bb6 ] includes all datasets supporting the conclusions of this article: IFN-Îł in spleen lymphocyte culture supernatants, IL-4 in spleen lymphocyte culture supernatants, CD4+ T cell subsets expressing intracellular IFN-Îł or IL-4, CFU in the lungs and spleens.. (XLS 143 kb

Newcastle disease virus-vectored Nipah encephalitis vaccines induce B and T cell responses in mice and long-lasting neutralizing antibodies in pigs

AbstractNipah virus (NiV), a member of the Paramyxoviridae family, causes deadly encephalitis in humans and huge economic losses to the pig industry. Here, we generated recombinant avirulent Newcastle disease virus (NDV) LaSota strains expressing the NiV G and F proteins respectively (designated as rLa-NiVG and rLa-NiVF), and evaluated their immunogenicity in mice and pigs. Both rLa-NiVG and rLa-NiVF displayed growth properties similar to those of LaSota virus in chicken eggs. Co-infection of rLa-NiVG and rLa-NiVF caused marked syncytia formation, while intracerebral co-inoculation of these viruses in mice showed they were safe in at least one mammalian species. Animal immunization studies showed rLa-NiVG and rLa-NiVF induced NiV neutralizing antibody responses in mice and pigs, and F protein-specific CD8+ T cell responses in mice. Most importantly, rLa-NiVG and rLa-NiVF administered alone or together, induced a long-lasting neutralizing antibody response in pigs. Recombinant rLa-NiVG/F thus appear to be promising NiV vaccine candidates for pigs and potentially humans

Urine Metabolomics Profiling of Lumbar Disc Herniation and its Traditional Chinese Medicine Subtypes in Patients Through Gas Chromatography Coupled With Mass Spectrometry

Lumbar disc herniation (LDH) possesses complex pathogenesis, which has not been well elucidated yet. To date, specific or early diagnosis of LDH remains unavailable, resulting in missed opportunity for effective treatment. According to Traditional Chinese medicine (TCM) theory, LDH can be divided into two subtypes (reality syndrome and deficiency syndrome). The purpose of this study was to analyze the metabolic disorders of LDH and its TCM subtypes and screen out potential biomarkers for LDH diagnosis. Gas chromatography coupled with mass spectrometry (GC-MS) was applied to test the urine samples from 66 participants (30 healthy volunteers, 18 LDH patients with deficiency syndrome and 18 patients with reality syndrome). PCA analysis showed a distinct separation tendency between the healthy subjects and LDH patients but no obvious separation between the different syndromes (reality syndrome and deficiency syndrome) of LDH patients. As a result, 23 metabolites were identified significantly altered in the LDH patients, as compared with the healthy subjects. The altered metabolites belong to amino acid metabolism, nucleic acid metabolism, carbohydrate metabolism, and vitamin metabolism, which are related to osteoporosis and inflammation. Our results indicate metabolic disorders of LDH and thereby propose a group of metabolic biomarkers for potential application in early diagnosis of LDH in clinic, which provide a reasonable explanation for the pathogenesis of LDH

AI of Brain and Cognitive Sciences: From the Perspective of First Principles

Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation. Despite these powerful applications, there are still many tasks in our daily life that are rather simple to humans but pose great challenges to AI. These include image and language understanding, few-shot learning, abstract concepts, and low-energy cost computing. Thus, learning from the brain is still a promising way that can shed light on the development of next-generation AI. The brain is arguably the only known intelligent machine in the universe, which is the product of evolution for animals surviving in the natural environment. At the behavior level, psychology and cognitive sciences have demonstrated that human and animal brains can execute very intelligent high-level cognitive functions. At the structure level, cognitive and computational neurosciences have unveiled that the brain has extremely complicated but elegant network forms to support its functions. Over years, people are gathering knowledge about the structure and functions of the brain, and this process is accelerating recently along with the initiation of giant brain projects worldwide. Here, we argue that the general principles of brain functions are the most valuable things to inspire the development of AI. These general principles are the standard rules of the brain extracting, representing, manipulating, and retrieving information, and here we call them the first principles of the brain. This paper collects six such first principles. They are attractor network, criticality, random network, sparse coding, relational memory, and perceptual learning. On each topic, we review its biological background, fundamental property, potential application to AI, and future development.Comment: 59 pages, 5 figures, review articl