Global dynamics of a stage-structured hantavirus infection model with seasonality

In this paper, we study a time-periodic model, which incorporates seasonality and host stage-structure. This model describes the propagation of Puumala hantavirus within the bank vole population of Clethrionomys glareolus. The basic reproduction number R0 is obtained. By appealing to the theory of monotone dynamical systems and chain transitive sets, we establish a threshold-type result on the global dynamics in terms of R0, that is, the virus-free periodic solution is globally attractive, and the virus dies out if R0 ≤ 1, while there exists a unique positive periodic solution, which is globally attractive, and the virus persists if R0 > 1. Numerical simulations are given to confirm our theoretical results and to show that cleaning environment and controlling the grow of mice population are essential control strategies to reduce hantavirus infection

In Vitro

Chitosan/collagen composite nanofibrous scaffold has been greatly concerned in recent years for its favorable physicochemical properties which mimic the native extracellular matrix (ECM) both morphologically and chemically. In a previous study, we had successfully fabricated nanofibrous chitosan/collagen composite by electrospinning. In the present study, we further investigate the biocompatibility of such chitosan/collagen composite nanofiber to be used as scaffolds in vascular tissue engineering. The porcine iliac artery endothelial cells (PIECs) were employed for morphogenesis, attachment, proliferation, and phenotypic studies. Four characteristic EC markers, including two types of cell adhesion molecules, one proliferation molecule (PCNA), and one function molecule (p53), were studied by semiquantitative RT-PCR. Results showed that the chitosan/collagen composite nanofibrous scaffold could enhance the attachment, spreading, and proliferation of PIECs and preserve the EC phenotype. Our work provides profound proofs for the applicable potency of scaffolds made from chitosan/collagen composite nanofiber to be used in vascular tissue engineering

Elucidating the regulation of complex signalling systems in plant cells

The pollen tube represents a model system for the study of tip growth, and the root provides a valuable system to study gene and signalling networks in plants. In the present article, using the two systems as examples, we discuss how to elucidate the regulation of complex signalling systems in plant cells. First, we discuss how hormones and related genes in plant root development form a complex interacting network, and their activities are interdependent. Therefore their roles in root development must be analysed as an integrated system, and elucidation of the regulation of each component requires the adaptation of a novel modelling methodology: regulation analysis. Secondly, hydrodynamics, cell wall and ion dynamics are all important properties that regulate plant cell growth. We discuss how regulation analysis can be applied to study the regulation of hydrodynamics, cell wall and ion dynamics, using pollen tube growth as a model system. Finally, we discuss future prospects for elucidating the regulation of complex signalling systems in plant cells

Design principles for decoding calcium signals to generate specific gene expression via transcription

The second messenger calcium plays a key role in conveying specificity of signalling pathways in plant cells. Specific calcium signatures are decoded to generate correct gene expression responses and amplification of calcium signatures is vital to this process. It is not known: (1) if this amplification is an intrinsic property of all calcium-regulated gene expression responses and whether all calcium signatures have the potential to be amplified, and (2) how does a given calcium signature maintain specificity in cells containing a great number of transcription factors (TFs) and other proteins with the potential to be calcium-regulated? The work presented here uncovers the design principle by which it is possible to decode calcium signals into specific changes in gene transcription in plant cells. Regarding the first question, we found that the binding mechanism between protein components possesses an intrinsic property that will nonlinearly amplify any calcium signal. This nonlinear amplification allows plant cells to effectively distinguish the kinetics of different calcium signatures to produce specific and appropriate changes in gene expression. Regarding the second question, we found that the large number of calmodulin (CaM)-binding transcription factors (TFs) or proteins in plant cells form a buffering system such that the concentration of an active CaM-binding TF is insensitive to the concentration of any other CaM-binding protein, thus maintaining specificity. The design principle revealed by this work can be used to explain how any CaM-binding TF decodes calcium signals to generate specific gene expression responses in plant cells via transcription

One-step hydrothermal synthesis of fluorescence carbon quantum dots with high product yield and quantum yield

A one-step hydrothermal synthesis of nitrogen and silicon co-doped fluorescence carbon quantum dots (N,Si-CQDs), from citric acid monohydrate and silane coupling agent KH-792 with a high product yield (PY) of 52.56% and high quantum yield (QY) of 97.32%, was developed. This greatly improves both the PY and QY of CQDs and provides a new approach for a large-scale production of high-quality CQDs. Furthermore, N,Si-CQDs were employed as phosphors without dispersants to fabricate white light-emitting diodes (WLEDs) with the color coordinates at (0.29, 0.32). It is suggested that N,Si-CQDs have great potential as promising fluorescent materials to be applied in WLEDs.Peer reviewe

Behavior Analysis and Recognition of Hidden Populations in Online Social Network Based on Big Data Method

Hidden populations refer to the minority groups that not well-known to the public. Traditional statistical survey methods are difficult to apply in the study of hidden populations because of that the hidden populations individuals are very troublesome to be found and they are not willing to share the inner opinion with the others. On the other hand, with the development of the Web 2.0, the hidden populations gather and share their views in online social networks due to the openness and anonymity of the Internet. So, this paper analyzes the behavioral characteristics of the hidden populations based on their data in online social networks. This paper uses the lesbian population as an example and analyzes the behavioral characteristics of lesbian by analyzing the data of the lesbian population in Douban Group. First, the activity data on lesbian are collected from Douban Group. Second, behavior characteristics of lesbian are analysed, the regional characteristic, temporal characteristic and text characteristic are mined out by big data method. Third, a lesbian recognition model is proposed based on the above analytical characteristics, and the effectiveness of the recognition model is varified by experiment study. The research of this paper is helpful to understand the behavioral characteristics of hidden populations deeply, and provides decision-making basis of management and service for hidden populations