The effect of cytokines, including IL4, IL7, stem cell factor, insulin-like growth factor on childhood acute lymphoblastic leukemia

We have investigated the effects of some interleukins, such as interleukin (IL) 4, IL7, stem cell factor (SCF) and insulin-like growth factor (IGF-1), known to be involved in human lymphopoiesis, on proliferation, clonal growth and differentiation of cells from two acute lymphoblastic leukemia (ALL) derived pre-B cell lines, that is, Nalm 1, Nalm 6 and purified blasts from 37 childhood ALL. IL4 did not display any promoting activity, an inhibitory effect being observed in two patients. IL7 showed an heterogeneous responsiveness, not related to immunophenotype or cytogenetic features, proliferation and clonal growth being observed in a minority of ALL. In other patients no or even inhibitory effects on proliferation were observed. In one case this inhibition of DNA synthesis was accompanied by maturation of the cells, as demonstrated by the induced expression of surface immunoglobulins (slg); other IL7 treated samples failed to express slg, but showed a decreased expression of terminal deoxynucleotidyl transferase and cALL antigen, suggesting that the cells have a potential of limited maturation by IL7. SCF, known to synergize with IL7 in the most primitive stages of normal B cell development, did not enhance the IL7 response in B cell precursor ALL. Finally IGF-1 failed to induce a proliferative response and clonal growth in BCP ALL either alone or in combination with IL7.     

A characterization of (regular) circular languages generated by monotone complete splicing systems

Circular splicing systems are a formal model of a generative mechanism of circular words, inspired by a recombinant behaviour of circular DNA. Some unanswered questions are related to the computational power of such systems, and finding a characterization of the class of circular languages generated by circular splicing systems is still an open problem. In this paper we solve this problem for monotone complete systems, which are finite circular splicing systems with rules of a simpler form. We show that a circular language L is generated by a monotone complete system if and only if the set Lin(L) of all words corresponding to L is a pure unitary language generated by a set closed under the conjugacy relation. The class of pure unitary languages was introduced by A. Ehrenfeucht, D. Haussler, G. Rozenberg in 1983, as a subclass of the class of context-free languages, together with a characterization of regular pure unitary languages by means of a decidable property. As a direct consequence, we characterize (regular) circular languages generated by monotone complete systems. We can also decide whether the language generated by a monotone complete system is regular. Finally, we point out that monotone complete systems have the same computational power as finite simple systems, an easy type of circular splicing system defined in the literature from the very beginning, when only one rule of a specific type is allowed. From our results on monotone complete systems, it follows that finite simple systems generate a class of languages containing non-regular languages, showing the incorrectness of a longstanding result on simple systems.     

Estimation of predictive accuracy in survival analysis using R and S-PLUS

When the purpose of a survival regression model is to predict future outcomes, the predictive accuracy of the model needs to be evaluated before practical application. Various measures of predictive accuracy have been proposed for survival data, none of which has been adopted as a standard, and their inclusion in statistical software is disregarded. We developed the surev library for R and S-PLUS, which includes functions for evaluating the predictive accuracy measures proposed by Schemper and Henderson. The library evaluates the predictive accuracy of parametric regression models and of Cox models. The predictive accuracy of the Cox model can be obtained also when time-dependent covariates are included because of non-proportional hazards or when using Bayesian model averaging. The use of the library is illustrated with examples based on a real data set.     

Diet supplementation with donkey milk upregulates liver mitochondrial uncoupling,reduces energy efficiency and improves antioxidant and antiinflammatory defences in rats

Dietary PUFA, mainly those of the n‐3 family, are known to play essential roles in the maintenance of energy balance and in the reduction of body fat deposition through the upregulation of mitochondrial uncoupling that is the main source of reactive oxygen species. We hypothesized that rat supplementation with raw donkey's milk (DM), characterized by low‐fat content and higher n3:n6 ratio, may affect energy balance, lipid metabolism, and prooxidant status as compared to animals treated with cow's milk. In the present study, the effects of drinking raw DM (for 4 weeks) on energy balance, lipid metabolism, antiinflammatory, and antioxidant/detoxifying defences was compared to that produced by rat intake of an iso‐energetic amount of raw cow's milk. The hypolipidemic effect produced by DM paralleled with the enhanced mitochondrial activity/proton leakage and with the increased activity or expression of mitochondrial markers namely, carnitine palmitoyl transferase and uncoupling protein 2. The association of decreased energy efficiency with reduced proinflammatory signs (TNF‐α and LPS levels) with the significant increase antioxidant (total thiols) and detoxifying enzyme activities (glutathione‐S‐transferase NADH quinone oxidoreductase) in DM‐treated animals, indicated that beneficial effects were attributable, at least in part, to the activation of nuclear factor 2 erythroid‐related factor 2 pathway.     

Investigation of Microstructures,Mechanical Properties of AZ91E Hybrid Composite Reinforced with Silicon Carbide and Fly Ash

Silicon - In this study, the stir casting processing technique was used to produce the AZ91E hybrid composite reinforced with Silicon Carbide (SiC) and Fly ash (FA) particles in different weight...     

Intrinsic Ferromagnetic Impurity Phases in SmFeAsO1−x F x Detected by μSR

We report μSR measurements on SmFeAsO_1−x F _x which helped us to identify the signature of diluted ferromagnetic inclusions, ubiquitous in the iron pnictides. These impurities are characterized by a Curie temperature close to room temperature and they seem responsible for a non negligible magnetic relaxation of the implanted muons, which should not be confused with intrinsic pnictide properties.      

Growth/no growth interfaces of Bacillus cereus, Staphylococcus aureus and Salmonella enteritidis in model systems based on water activity, pH, temperature and ethanol concentration

This study focuses its attention on the boundary between the growth and no growth of three strains ofSalmonella enteritidis , Bacillus cereus and Staphylococcus aureus in the presence of growth controlling factors such as temperature, pH, water activity (A_w) and ethanol concentration. Preliminarly, the minimal values of pH, A_wand temperature, and the maximum ethanol concentrations allowing the growth of the considered micro-organisms were determined. The calculation of these values enabled the use of logistic model to evaluate the growth/no growth boundary for the bacteria in relation to the considered independent variables. The location of the growth/no-growth boundaries for S. enteritidis and Staph. aureus were strongly affected, at the same ethanol concentration, by temperature, pH and A_w. Among the considered species, Staph. aureus was endowed with the highest sensitivity to low pH values whileB. cereus's growth/no growth interface, was quite unaffected by the combination of the stresses, when the physico–chemical conditions were above the minimum for growth. The effects of temperature, A_wand ethanol on the limitation of growth of the considered species were not merely additive. It was possible to identify the combinations of such factors preventing the growth of Salmonella enteritidis, Staph. aureus and B. cereus.     

Optical properties of high-density dispersions of particles: application to intralipid solutions

We propose to study the scattering properties of dense distributions of spherical scatterers by resorting to an iterative solution of the Foldy-Twersky equation for the propagation of the coherent field. As a result of the first step of the iterative procedure, the host medium is substituted by an effective medium of complex refractive index to account for the multiple-scattering processes that occur among the particles. Although we truncate the above-mentioned iterative procedure to the second step, the results of our calculations are in excellent agreement with previous experimental results of Zaccanti et al. ("Measurement of optical properties of high-density media," to be published in Applied Optics) for the scattering coefficient of Intralipid solutions up to a volume density of 15% and show a limited disagreement at a volume density of 22%.     

Synthesis of an Al-ZrO2 composite by infiltration of Zr-chelates into an Al matrix

Aluminium-based matrix composites were prepared by infiltration with an ammoniacal zirconium chelate within an Al matrix synthesized via Aluminium powder compactation. After infiltration, this chelate can be transformed in situ by sol-gel method that leads to tetragonal phases in zirconia, which in turn, transforms to monoclinic structure on heating. Based on Differential Thermal Analysis (DTA), Fourier Transformed Infrared (FTIR), X-Ray Diffraction (XRD), and Scanning Electron Microscopy (SEM), we confirm the reaction sequence to obtain the tetramer, the phase transformation sequence within the Al matrix, and the development of phases that leads to the synthesis of the Al-ZrO₂ composite.     

Enhancing density-based clustering: Parameter reduction and outlier detection

Clustering is a widely used unsupervised data mining technique. It allows to identify structures in collections of objects by grouping them into classes, named clusters, in such a way that similarity of objects within any cluster is maximized and similarity of objects belonging to different clusters is minimized. In density-based clustering, a cluster is defined as a connected dense component and grows in the direction driven by the density. The basic structure of density-based clustering presents some common drawbacks: (i) parameters have to be set; (ii) the behavior of the algorithm is sensitive to the density of the starting object; and (iii) adjacent clusters of different densities could not be properly identified. In this paper, we address all the above problems. Our method, based on the concept of space stratification, efficiently identifies the different densities in the dataset and, accordingly, ranks the objects of the original space. Next, it exploits such a knowledge by projecting the original data into a space with one more dimension. It performs a density based clustering taking into account the reverse-nearest-neighbor of the objects. Our method also reduces the number of input parameters by giving a guideline to set them in a suitable way. Experimental results indicate that our algorithm is able to deal with clusters of different densities and outperforms the most popular algorithms DBSCAN and OPTICS in all the standard benchmark datasets.