Increased levels of intracellular calcium are not required for the formation of attaching and effacing lesions by enteropathogenic and enterohemorrhagic Escherichia coli

Elevated concentrations of intracellular calcium ([Ca]i) have been implicated as an important signalling event during attaching and effacing (A/E) lesion formation by enteropathogenic Escherichia coli (EPEC). The highly localized nature of the cytoskeletal and cell surface alterations occurring during A/E lesion formation suggests that there should be equally localized EPEC-induced signalling events. To analyze further the calcium responses to infection of HEp-2 cells by EPEC, we employed calcium-imaging fluorescence microscopy, which allows both temporal and spatial measurements of [Ca]i in live cells. Using this imaging technique, not only were we unable to detect any significant elevation in [Ca]i at sites of A/E EPEC adhesion, but, with several different classical EPEC and enterohemorrhagic E. coli (EHEC) strains and three different infection procedures, each of which resulted in extensive A/E bacterial adhesion, we were unable to detect any significant alterations in [Ca]i in infected cells compared to uninfected cells. In addition, chelation of intracellular free calcium with bis-(aminophenoxy)-ethane-N,N,N',N'-tetraacetic acid (BAPTA) did not, as previously reported, prevent A/E lesion formation. We conclude that increased [Ca]i are not required for A/E lesion formation by EPEC and EHEC.     

Childhood personality influences on social-cognitive development: a longitudinal study

The relation of childhood personality to the development of friendship understanding and moral judgment in adolescence was considered in a longitudinal study. Personality at age 7, assessed with the California Child Q-Set, was characterized in terms of ego-resiliency and ego-control. IQ and social class were also measured. Friendship understanding was assessed when the participants were ages 7, 9, 12, 15, and 19, and moral judgment was elicited when the participants were 12, 15, and 19. Ego-resiliency was found to predict social-cognitive development in adolescence, even after the effects of IQ and childhood measures of social-cognitive development were controlled for. Analyses indicate that the effects of ego-resiliency on social-cognitive development are largely unmediated by the ability to focus attention or by social participation.     

EXTENSION OF THE RELATIONAL DATABASE AND ITS ALGEBRA WITH ROUGH SET TECHNIQUES

This paper describes a database model based on the original rough sets theory. Its rough relations permit the representation of a rough set of tuples not definable in terms of the elementary classes, except through use of lower and upper approximations. The rough relational database model also incorporates indiscernibility in the representation and in all the operators of the rough relational algebra. This indiscernibility is based strictly on equivalence classes which must be defined for every attribute domain. There are several obvious applications for which the rough relational database model can more accurately model an enterprise than does the standard relational model. These include systems involving ambiguous, imprecise, or uncertain data. Retrieval over mismatched domains caused by the merging of one or more applications can be facilitated by the use of indiscernibility, and naive system users can achieve greater recall with the rough relational database. In addition, applications inherently “rough” could be more easily implemented and maintained in the rough relational database.     

Networking,Storytelling and Knowledge Production in First-Year Writing

As writing teachers, we seek to validate the knowledge that students bring to the classroom while introducing and cultivating new methods, strategies, techniques and technologies that may serve them now and in the future. In this article we describe an approach we take that integrates curricular and extracurricular co-apprenticeship strategies using public writing models in conjunction with social networking tools. With publication as a final goal, we urge students to move from expressing personal problems to addressing social issues, using a private, non-commercial learning network NoDiff <http://NoDiff.com> as a safe zone for skills development, knowledge production and social inquiry. In taking this approach, we resist dichotomies that place professional skills training in strict opposition to critical pedagogy. We argue that many of the so-called “extracurricular” composing activities that most of today's students engage in lay the groundwork for both professional and civic participation. Acknowledging that we as composition teachers are also beginners in the world of 21^st century communication, we emphasize both (1) the continual transference of skills and knowledge among teachers and learners; and (2) the importance of providing what is often lacking in skills-based ‘new literacy’ training, namely a critical pedagogical approach to learning as social engagement and critical intervention.     

The HaLoop approach to large-scale iterative data analysis

The growing demand for large-scale data mining and data analysis applications has led both industry and academia to design new types of highly scalable data-intensive computing platforms. MapReduce has enjoyed particular success. However, MapReduce lacks built-in support for iterative programs, which arise naturally in many applications including data mining, web ranking, graph analysis, and model fitting. This paper (This is an extended version of the VLDB 2010 paper “HaLoop: Efficient Iterative Data Processing on Large Clusters” PVLDB 3(1):285–296, 2010.) presents HaLoop, a modified version of the Hadoop MapReduce framework, that is designed to serve these applications. HaLoop allows iterative applications to be assembled from existing Hadoop programs without modification, and significantly improves their efficiency by providing inter-iteration caching mechanisms and a loop-aware scheduler to exploit these caches. HaLoop retains the fault-tolerance properties of MapReduce through automatic cache recovery and task re-execution. We evaluated HaLoop on a variety of real applications and real datasets. Compared with Hadoop, on average, HaLoop improved runtimes by a factor of 1.85 and shuffled only 4 % as much data between mappers and reducers in the applications that we tested.     

Incorporating fuzzy membership functions into the perceptron algorithm

The perceptron algorithm, one of the class of gradient descent techniques, has been widely used in pattern recognition to determine linear decision boundaries. While this algorithm is guaranteed to converge to a separating hyperplane if the data are linearly separable, it exhibits erratic behavior if the data are not linearly separable. Fuzzy set theory is introduced into the perceptron algorithm to produce a ``fuzzy algorithm' which ameliorates the convergence problem in the nonseparable case. It is shown that the fuzzy perceptron, like its crisp counterpart, converges in the separable case. A method of generating membership functions is developed, and experimental results comparing the crisp to the fuzzy perceptron are presented.     

Characteristics of natural scenes related to the fractal dimension

Many objects in images of natural scenes are so complex and erratic, that describing them by the familiar models of classical geometry is inadequate. In this paper, we exploit the power of fractal geometry to generate global characteristics of natural scenes. In particular we are concerned with the following two questions: 1) Can we develop a measure which can distinguish between different global backgrounds (e.g., mountains and trees)? and 2) Can we develop a measure that is sensitive to change in distance (or scale)? We present a model based on fractional Brownian motion which will allow us to recover two characteristics related to the fractal dimension from silhouettes. The first characteristic is an estimate of the fractal dimension based on a least squares linear fit. We show that this feature is stable under a variety of real image conditions and use it to distinguish silhouettes of trees from silhouettes of mountains. Next we introduce a new theoretical concept called the average Holder constant and relate it mathematically to the fractal dimension. It is shown that this measurement is sensitive to scale in a predictable manner, and hence, provides the potential for use as a range indicator. Corroborating experimental results are presented.     

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

Biflavonoid-Induced Disruption of Hydrogen Bonds Leads to Amyloid-β Disaggregation

Deposition of amyloid β (Aβ) fibrils in the brain is a key pathologic hallmark of Alzheimer’s disease. A class of polyphenolic biflavonoids is known to have anti-amyloidogenic effects by inhibiting aggregation of Aβ and promoting disaggregation of Aβ fibrils. In the present study, we further sought to investigate the structural basis of the Aβ disaggregating activity of biflavonoids and their interactions at the atomic level. A thioflavin T (ThT) fluorescence assay revealed that amentoflavone-type biflavonoids promote disaggregation of Aβ fibrils with varying potency due to specific structural differences. The computational analysis herein provides the first atomistic details for the mechanism of Aβ disaggregation by biflavonoids. Molecular docking analysis showed that biflavonoids preferentially bind to the aromatic-rich, partially ordered N-termini of Aβ fibril via the π–π interactions. Moreover, docking scores correlate well with the ThT EC₅₀ values. Molecular dynamic simulations revealed that biflavonoids decrease the content of β-sheet in Aβ fibril in a structure-dependent manner. Hydrogen bond analysis further supported that the substitution of hydroxyl groups capable of hydrogen bond formation at two positions on the biflavonoid scaffold leads to significantly disaggregation of Aβ fibrils. Taken together, our data indicate that biflavonoids promote disaggregation of Aβ fibrils due to their ability to disrupt the fibril structure, suggesting biflavonoids as a lead class of compounds to develop a therapeutic agent for Alzheimer’s disease.     

Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

Neurodegenerative diseases (NDs) including Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and Huntington’s disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.