p21WAF1/Cip1 expression is associated with cell differentiation but not with p53 mutations in squamous cell carcinomas of the larynx

The anti-metastatic effect of Z-100, an immunomodulatory arabinomannan extracted from Mycobacterium tuberculosis, was investigated in mice bearing B16 melanoma cells. Treatment of BF10 mice implanted with high metastatic B16F10 melanoma cells with a 10 mg/kg dose of Z-100 resulted in the reduction of experimental pulmonary metastasis as compared with that of BF10 mice treated with saline. The number of pulmonary metastatic colonies in BF1 mice (mice implanted with low metastatic B16F1 melanoma cells) was greatly increased after the inoculation of CD4+ CD11b+ CD281+ TCR alphabeta+ type 2 T cells (F10-Th2 cells) derived from BF10 mice, while only a few metastatic colonies were demonstrated in lungs of BF1 mice inoculated with naive CD4+ T cells. However, the numbers of metastatic colonies in BF1 mice were not increased when they were inoculated with the F10-Th2 cell fraction derived from Z-100-treated BF10 mice and the generation of F10-Th2 cells in BF10 mice was effectively suppressed by the Z-100 treatment. These results suggest that Z-100 inhibits pulmonary metastasis of B16 melanoma through the regulation of tumor-associated Th2 cells, which are a key cell in the acceleration of tumor metastasis.     

A numerical study of a semi‐algebraic multilevel preconditioner for the local discontinuous Galerkin method

In this work, we consider the local discontinuous Galerkin (LDG) method applied to second‐order elliptic problems arising in the modeling of single‐phase flows in porous media. It has been recently proven that the spectral condition number of the stiffness matrix exhibits an asymptotic behavior of ??(h^?2) on structured and unstructured meshes, where h is the mesh size. Thus, efficient preconditioners are mandatory. We present a semi‐algebraic multilevel preconditioner for the LDG method using local Lagrange‐type interpolatory basis functions. We show, numerically, that its performance does not degrade, or at least the number of iterations increases very slowly, as the number of unknowns augments. The preconditioner is tested on problems with high jumps in the coefficients, which is the typical scenario of problems arising in porous media. Copyright © 2007 John Wiley & Sons, Ltd.     

Can porous polymeric scaffolds be functionalized by stem cells leading to osteogenic differentiation? A systematic review of in vitro studies

The aim of this study was to analyze the influence of nanoporous structure of polymeric biomaterials on the in vitro osteogenic induction of human stem cells. An electronic search in three databases (MEDLINE, SCOPUS, and Web of Science) was performed for articles that were published before May 2018. In vitro studies were included if they met the following criteria: (1) the use of polymeric scaffolds (natural or synthetic); (2) the co-culture of human stem cells with the scaffold; and (3) cell viability, proliferation, and osteogenic differentiation assays. The main characteristics of the published studies were summarized, and a quality assessment tool was used to analyze methodological features. Eighty-eight potential articles were firstly retrieved. Thirteen were eligible for qualitative analysis. Only three studies characterized cell stemness. Nanostructure of the scaffolds showed a significant influence on viability, proliferation, and osteogenic differentiation of human stem cells. Combination of porosity between 72 and 93% and a large range diameter between 50 and 224 μm resulted in more remarkable cellular proliferation and differentiation. Porous polymeric scaffolds can be functionalized by stem cells leading to osteogenic induction. High standards of laboratory practice and accurate methodological reporting are essential for the credibility of the results.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.     

Kinetics of the Hydrolysis of some alkyl halides in aqueous ethyl alcohol

A comparison of the rates of substitution and elimination reactions occuring simultaneously in alkaline hydrolysis of n-amyl chloride, isoamyl chloride, n-amyl iodide and n-hexyl iodide at different temperatures and in varying alcohol-water mixtures, has been made. Under the same conditions the rates of solvolysis of these halides have also been reported. In the case of n-amyl halides there is a much larger rate difference between chloride and bromide than between bromide and iodide.     

Peeling dynamics of fluid membranes bridged by molecular bonds: moving or breaking

Biological adhesion is a critical mechanical function of complex organisms. At the scale of cell–cell contacts, adhesion is remarkably tunable to enable both cohesion and malleability during development, homeostasis and disease. It is physically supported by transient and laterally mobile molecular bonds embedded in fluid membranes. Thus, unlike specific adhesion at solid–solid or solid–fluid interfaces, peeling at fluid–fluid interfaces can proceed by breaking bonds, by moving bonds or by a combination of both. How the additional degree of freedom provided by bond mobility changes the mechanics of peeling is not understood. To address this, we develop a theoretical model coupling diffusion, reactions and mechanics. Mobility and reaction rates determine distinct peeling regimes. In a diffusion-dominated Stefan-like regime, bond motion establishes self-stabilizing dynamics that increase the effective fracture energy. In a reaction-dominated regime, peeling proceeds by travelling fronts where marginal diffusion and unbinding control peeling speed. In a mixed reaction–diffusion regime, strengthening by bond motion competes with weakening by bond breaking in a force-dependent manner, defining the strength of the adhesion patch. In turn, patch strength depends on molecular properties such as bond stiffness, force sensitivity or crowding. We thus establish the physical rules enabling tunable cohesion in cellular tissues and in engineered biomimetic systems.     

Localization-limited exciton oscillator strength in colloidal CdSe nanoplatelets revealed by the optically induced stark effect

2D materials are considered for applications that require strong light-matter interaction because of the apparently giant oscillator strength of the exciton tra...     

From latex specifications to parallel codes

The advent of multicore systems, joined to the potential acceleration of the graphics processing units, has given us a low cost computation capability unprecedented. The new systems alleviate some well-known important architectural problems at the expense of a considerable increment of the programmability wall. Heterogeneity, at both the architectural and programming levels, poses a great challenge to programmers. As a contribution, we propose a development methodology for the automatic source-to-source transformation on specific domains. This methodology is successfully instantiated as a framework to solve Dynamic Programming problems. As a result of applying our framework, the end user (a physicist, a mathematician or a biologist) can express her problem through a latex equation and automatically derive efficient parallel codes for current homogeneous or heterogeneous architectures. The approach allows an easy portability to new emergent architectures.     

Collective intelligence as mechanism of medical diagnosis: The iPixel approach

Collective intelligence (CI) is an active field of research, which capitalizes the knowledge of human collectives in order to create, to innovate and to invent. There are two important mechanisms to implement CI: recommender and reputation systems. Recommender systems are used to provide filtered information from a large amount of elements. The recommendations are intended to provide interesting elements to users. Recommendation systems can be developed using different techniques and algorithms where the selection of these techniques depends on the area in which they will be applied. This work presents iPixel Recommender Engine, which is focused on the medical field. iPixel Recommendation Engine supports the process of differential diagnosis by recommending mammographic evaluations. Each mammogram is collectively tagged by the users’ community with a semantic sense; this feature allows iPixel acquires collective knowledge. iPixel can associate more than one feature with each mammogram. This work also presents a qualitative evaluation, where the basic features that a recommendation system should have in the medical field were obtained. Finally, a comparison was carried out with other similar recommender systems in order to know the Pixel advantages.     

Control of attendance applied in higher education through mobile NFC technologies

This paper presents an improved attendance control system, required for continuous evaluation which has become compulsory following the Bologna Process. It provides a solution based on NFC technology and is based on a real project developed and pilot tested at the “Universidad Pontificia de Salamanca, Campus Madrid”.