碳酸酐酶Ⅲ在疾病和肌肉疲劳发生发展中的作用

碳酸酐酶（carbonic anhydrases,CAs）是一种广泛存在的含锌的金属蛋白酶,能可逆性地高效催化CO2的水合反应,参与调节胞内pH值、离子运输和生物合成反应等多种生理过程。在哺乳动物体内已发现13种CA同工酶和3种CA相关蛋白,其中CAⅢ与其他CA同工酶相比,在组织分布、分子结构和生物学功能上均有其独特之处。CAⅢ表达异常可能与多种临床疾病的发生和发展有关,还可能参与了肌肉疲劳的发生。     

具有多时变分布时滞的Lurie控制系统的绝对稳定性

研究了一类具有多时变分布时滞的Lurie控制系统的绝对稳定性.通过构造合适的Lyapunov函数,并利用矩阵不等式技术,获得了该控制系统绝对稳定性的充分条件.     

Differentiation,polarization, and migration of human induced pluripotent stem cell-derived neural progenitor cells co-cultured with a human glial cell line with radial glial-like characteristics

Here we established a unique human glial cell line, GDC90, derived from a human glioma and demonstrated its utility as a glial scaffold for the polarization and differentiation of human induced pluripotent stem cell-derived neural progenitor cells (iPSC-NPCs). When co-cultured with GDC90 cells, iPSC-NPCs underwent rapid polarization and neurite extension along the radially spreading processes of the GDC90 cells, and showed migratory behavior. This method is potentially useful for detailed examination of neurites or for controlling neurites behavior for regenerative medicine.     

How to catch the patch? A dendrometer study of the radial increment through successive cambia in the mangrove Avicennia

Background and Aims

Successive vascular cambia are involved in the secondary growth of at least 200 woody species from >30 plant families. In the mangrove Avicennia these successive cambia are organized in patches, creating stems with non-concentric xylem tissue surrounded by internal phloem tissue. Little is known about radial growth and tree stem dynamics in trees with this type of anatomy. This study aims to (1) clarify the process of secondary growth of Avicennia trees by studying its patchiness; and (2) study the radial increment of Avicennia stems, both temporary and permanent, in relation to local climatic and environmental conditions. A test is made of the hypothesis that patchy radial growth and stem dynamics enable Avicennia trees to better survive conditions of extreme physiological drought.

Methods

Stem variations were monitored by automatic point dendrometers at four different positions around and along the stem of two Avicennia marina trees in the mangrove forest of Gazi Bay (Kenya) during 1 year.

Key Results

Patchiness was found in the radial growth and shrinkage and swelling patterns of Avicennia stems. It was, however, potentially rather than systematically present, i.e. stems reacted either concentrically or patchily to environment triggers, and it was fresh water availability and not tidal inundation that affected radial increment.

Conclusions

It is concluded that the ability to develop successive cambia in a patchy way enables Avicennia trees to adapt to changes in the prevailing environmental conditions, enhancing its survival in the highly dynamic mangrove environment. Limited water could be used in a more directive way, investing all the attainable resources in only some locations of the tree stem so that at least at these locations there is enough water to, for example, overcome vessel embolisms or create new cells. As these locations change with time, the overall functioning of the tree can be maintained.     

A global machine learning based scoring function for protein structure prediction

We present a knowledge‐based function to score protein decoys based on their similarity to native structure. A set of features is constructed to describe the structure and sequence of the entire protein chain. Furthermore, a qualitative relationship is established between the calculated features and the underlying electromagnetic interaction that dominates this scale. The features we use are associated with residue–residue distances, residue–solvent distances, pairwise knowledge‐based potentials and a four‐body potential. In addition, we introduce a new target to be predicted, the fitness score, which measures the similarity of a model to the native structure. This new approach enables us to obtain information both from decoys and from native structures. It is also devoid of previous problems associated with knowledge‐based potentials. These features were obtained for a large set of native and decoy structures and a back‐propagating neural network was trained to predict the fitness score. Overall this new scoring potential proved to be superior to the knowledge‐based scoring functions used as its inputs. In particular, in the latest CASP (CASP10) experiment our method was ranked third for all targets, and second for freely modeled hard targets among about 200 groups for top model prediction. Ours was the only method ranked in the top three for all targets and for hard targets. This shows that initial results from the novel approach are able to capture details that were missed by a broad spectrum of protein structure prediction approaches. Source codes and executable from this work are freely available at http://mathmed.org /#Software and http://mamiris.com/ . Proteins 2014; 82:752–759. © 2013 Wiley Periodicals, Inc.     

DockRank: Ranking docked conformations using partner‐specific sequence homology‐based protein interface prediction

Selecting near‐native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner‐specific sequence homology‐based protein–protein interface predictor (PS‐HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state‐of‐the‐art docking scoring functions using Success Rate (the percentage of cases that have at least one near‐native conformation among the top m conformations) and Hit Rate (the percentage of near‐native conformations that are included among the top m conformations). In cases where it is possible to obtain partner‐specific (PS) interface predictions from PS‐HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state‐of‐the‐art energy‐based scoring functions (improving Success Rate by up to 4‐fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39‐fold). The latter result underscores the importance of using partner‐specific interface residues in scoring docked conformations. We show that DockRank, when used to re‐rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/ . Proteins 2014; 82:250–267. © 2013 Wiley Periodicals, Inc.     

On the structure of molecularly imprinted polymers by modifying charge on functional groups through molecular dynamics simulations

Molecularly imprinted polymers (MIPs) have been widely applied in many fields owing to their advantages. The recognition mechanism between target molecules and MIPs and the influence of dominant factor on the recognition process are still poorly understood. In this paper, a cubic methacrylate-based MIP model was constructed, and the charge on carboxyl group atoms was changed artificially to investigate the recognition process. It is found that the diffusion coefficients of the target molecules (cholesterol) are not affected by polymer network structure. The recognition process is mainly determined by the mesh sizes of the polymer network. In addition, the structure of modified MIP systems was also discussed from the viewpoints of radial distribution function and hydrogen bonds system. These results suggest that the polymer matrix structure would be enhanced with an increase in charge. Thus, it influences the structure of the water molecules in the system a little.     

胶质类芽孢杆菌功能及基因组学研究进展

胶质类芽孢杆菌(Paenibacillus mucilaginosus)因其具有多功能、强抗逆等特点而成为微生物肥料的首选菌种,它在农业生产中表现出提高土壤速效钾与速效磷含量、促进作物生长、提高作物产量和品质等多方面的效应,一直是研究的重点和热点。首次从P.mucilaginosus的系统发育地位及快速检测技术、生物学功能、基因组学研究进展等方面进行综述,以期进一步拓宽对该细菌生物学特征及其功能的认识,推动其在生态农业中的应用。     

Self-expanding stent modelling and radial force accuracy

Computational simulations using finite element analysis are a tool commonly used to analyse stent designs, deployment geometries and interactions between stent struts and arterial tissue. Such studies require large computational models and efforts are often made to simplify models in order to reduce computational time while maintaining reasonable accuracy. The objective of the study is focused on computational modelling and specifically aims to investigate how different methods of modelling stent–artery interactions can affect the results, computational time taken and computational size of the model. Various different models, each with increasing levels of complexity, are used to simulate this analysis, representing the many assumptions and simplifications used in other similar studies in order to determine what level of simplification will still allow for an accurate representation of stent radial force and resulting stress concentrations on the inner lining of the vessel during self-expanding stent deployment. The main conclusions of the study are that methods used in stent crimping impact on the resulting predicted radial force of the stent; that accurate representation of stent–artery interactions can only be made when modelling the full length of the stent due to the incorporation of end effects; and that modelling self-contact of the stent struts greatly impacts on the resulting stress concentrations within the stent, but that the effect of this on the unloading behaviour and resulting radial force of the stent is negligible.