Increased migration of olfactory ensheathing cells secreting the Nogo receptor ectodomain over inhibitory substrates and lesioned spinal cord

Olfactory ensheathing cell (OEC) transplantation emerged some years ago as a promising therapeutic strategy to repair injured spinal cord. However, inhibitory molecules are present for long periods of time in lesioned spinal cord, inhibiting both OEC migration and axonal regrowth. Two families of these molecules, chondroitin sulphate proteoglycans (CSPG) and myelin-derived inhibitors (MAIs), are able to trigger inhibitory responses in lesioned axons. Mounting evidence suggests that OEC migration is inhibited by myelin. Here we demonstrate that OEC migration is largely inhibited by CSPGs and that inhibition can be overcome by the bacterial enzyme Chondroitinase ABC. In parallel, we have generated a stable OEC cell line overexpressing the Nogo receptor (NgR) ectodomain to reduce MAI-associated inhibition in vitro and in vivo. Results indicate that engineered cells migrate longer distances than unmodified OECs over myelin or oligodendrocyte-myelin glycoprotein (OMgp)-coated substrates. In addition, they also show improved migration in lesioned spinal cord. Our results provide new insights toward the improvement of the mechanisms of action and optimization of OEC-based cell therapy for spinal cord lesion.     

一种新数值工具在车辆气动声学开发中的应用

为了优化车辆开发过程的有效性，数值气动声学分析法的实施和应用对汽车制造商来说变得越来越重要。提出了一种结合延迟分离涡流模拟和基于Lighthill方程及声学扰动方程的有限元模型混合数值工具，应用OpenFOAM和Actran软件实现了基于声学有限元法的近场声源区提取及声学压力脉动计算，并尝试应用于车顶扰流板及后视镜区域的气动噪声计算及分析。在兰博基尼Urus车型上，研究了不同车顶扰流板设计的气动声学行为，将仿真结果与斯图加特大学气动声学全尺寸风洞的实验结果进行比较，发现了令人信服的相关性。此外，探讨了扰流板上的主要噪声产生机制，研究了汽车表面压力波动水平随几何形状改变的变化情况。     

SIRT1 modulates MAPK pathways in ischemic–reperfused cardiomyocytes

SIRT1, an ubiquitous NAD(+)-dependent deacetylase that plays a role in biological processes such as longevity and stress response, is significantly activated in response to reactive oxygen species (ROS) production. Resveratrol (Resv), an important activator of SIRT1, has been shown to exert major health benefits in diseases associated with oxidative stress. In ischemia-reperfusion (IR) injury, a major role has been attributed to the mitogen-activated protein kinase (MAPK) pathway, which is upregulated in response to a variety of stress stimuli, including oxidative stress. In neonatal rat ventricular cardiomyocytes subjected to simulated IR, the effect of Resv-induced SIRT1 activation and the relationships with the MAPK pathway were investigated. Resv-induced SIRT1 overexpression protected cardiomyocytes from oxidative injury, mitochondrial dysfunction, and cell death induced by IR. For the first time, we demonstrate that SIRT1 overexpression positively affects the MAPK pathway-via Akt/ASK1 signaling-by reducing p38 and JNK phosphorylation and increasing ERK phosphorylation. These results reveal a new protective mechanism elicited by Resv-induced SIRT1 activation in IR tissues and suggest novel potential therapeutic targets to manage IR-induced cardiac dysfunction.     

A New Dimension Reduction Method: Factor Discriminant K-means

Reduced K-means (RKM) and Factorial K-means (FKM) are two data reduction techniques incorporating principal component analysis and K-means into a unified methodology to obtain a reduced set of components for variables and an optimal partition for objects. RKM finds clusters in a reduced space by maximizing the between-clusters deviance without imposing any condition on the within-clusters deviance, so that clusters are isolated but they might be heterogeneous. On the other hand, FKM identifies clusters in a reduced space by minimizing the within-clusters deviance without imposing any condition on the between-clusters deviance. Thus, clusters are homogeneous, but they might not be isolated. The two techniques give different results because the total deviance in the reduced space for the two methodologies is not constant; hence the minimization of the within-clusters deviance is not equivalent to the maximization of the between-clusters deviance. In this paper a modification of the two techniques is introduced to avoid the afore mentioned weaknesses. It is shown that the two modified methods give the same results, thus merging RKM and FKM into a new methodology. It is called Factor Discriminant K-means (FDKM), because it combines Linear Discriminant Analysis and K-means. The paper examines several theoretical properties of FDKM and its performances with a simulation study. An application on real-world data is presented to show the features of FDKM.     

A network analysis of the 2010 FIFA world cup champion team play

This paper analyzes the network of passes among the players of the Spanish team during the last FIFA World Cup 2010, where they emerged as the champion, with the objective of explaining the results obtained from the behavior at the complex network level. The team is considered a network with players as nodes and passes as (directed) edges. A temporal analysis of the resulting passes network is also done, looking at the number of passes, length of the chain of passes, and to network measures such as player centrality and clustering coefficient. Results of the last three matches (the decisive ones) indicate that the clustering coefficient of the pass network remains high, indicating the elaborate style of the Spanish team. The effectiveness of the opposing team in negating the Spanish game is reflected in the change of several network measures over time, most importantly in drops of the clustering coefficient and passing length/speed, as well as in their being able in removing the most talented players from the central positions of the network. Spain’s ability to restore their combinative game and move the focus of the game to offensive positions and talented players is shown to tilt the balance in favor of the Spanish team.     

Predictability of Plastic Parts Behaviour Made from Rapid Manufacturing

One of the most important issues to resolve in parts manufactured from rapid manufacturing (RM) technologies is to know their behavior working under real conditions. Total quality manufacturing (TQM) is only possible if mechanical properties are well known in the design stage depending on the processing parameters. This work is mainly focused on testing of several samples made with different selective laser sintering (SLS) parameters and technologies. This procedure is the starting point to establish a basis for designing for RM and the standardization of RM testing. The experiments and the analysis of variance (ANOVA) analyzed the effects of several factors on mechanical properties. The SLS technologies were 3DSystem and EOS. The results show which factor has a large effect on the variables and the interaction between them. The conclusions are very useful for developing rules for designing (designing for RM) and creating new standard rules (ISO, AISI, and DIN) for RM materials and parts testing. The ANOVA gives a better knowledge of the effects of these factors and eliminates unimportant parameters.     

An open environment for cooperative equational solving

We describe a system called CFLP which aims at the integration of the best features of functional logic programming (FLP), cooperative constraint solving (CCS), and distributed computing. FLP provides support for defining one’s own abstractions over a constraint domain in an easy and comfortable way, whereas CCS is employed to solve systems of mixed constraints by iterating specialized constraint solving methods in accordance with a well defined strategy. The system is a distributed implementation of a cooperative constraint functional logic programming scheme that combines higher-order lazy narrowing with cooperative constraint solving. The model takes advantage of the existence of several constraint solving resources located in a distributed environment (e. g., a network of computers), which communicate asynchronously via message passing. To increase the openness of the system, we are redesigning CFLP based on CORBA. We discuss some design and implementation issues of the system.     

Requirements for leukocyte transmigration via the transmembrane chemokine CX3CL1

The surface-expressed transmembrane CX3C chemokine ligand 1 (CX3CL1/fractalkine) induces firm adhesion of leukocytes expressing its receptor CX3CR1. After shedding by the disintegrins and metalloproteinases (ADAM) 10 and 17, CX3CL1 also acts as soluble leukocyte chemoattractant. Here, we demonstrate that transmembrane CX3CL1 expressed on both endothelial and epithelial cells induces leukocyte transmigration. To investigate the underlying mechanism, we generated CX3CR1 variants lacking the intracellular aspartate-arginine-tyrosine (DRY) motif or the intracellular C-terminus which led to a defect in intracellular calcium response and impaired ligand uptake, respectively. While both variants effectively mediated firm cell adhesion, they failed to induce transmigration and rather mediated retention of leukocytes on the CX3CL1-expressing cell layer. Targeting of ADAM10 led to increased adhesion but reduced transmigration in response to transmembrane CX3CL1, while transmigration towards soluble CX3CL1 was not affected. Thus, transmembrane CX3CL1 mediates leukocyte transmigration via the DRY motif and C-terminus of CX3CR1 and the activity of ADAM10.     

Accurate Tree-based Missing Data Imputation and Data Fusion within the Statistical Learning Paradigm

Framework of this paper is statistical data editing, specifically how to edit or impute missing or contradictory data and how to merge two independent data sets presenting some lack of information. Assuming a missing at random mechanism, this paper provides an accurate tree-based methodology for both missing data imputation and data fusion that is justified within the Statistical Learning Theory of Vapnik. It considers both an incremental variable imputation method to improve computational efficiency as well as boosted trees to gain in prediction accuracy with respect to other methods. As a result, the best approximation of the structural risk (also known as irreducible error) is reached, thus reducing at minimum the generalization (or prediction) error of imputation. Moreover, it is distribution free, it holds independently of the underlying probability law generating missing data values. Performance analysis is discussed considering simulation case studies and real world applications.