Self-dual centroaffine surfaces of codimension two with constant affine mean curvature

We explicitly determine the minimal, self-dual centroaffine surfaces in JR.4 \ {O} by giving a representation formula. Moreover, we describe the self-dual centroaffine surfaces with affine mean curvature -1

Multi-Hamiltonian Structures on Spaces of Closed Equicentroaffine Plane Curves Associated to Higher KdV Flows

Higher KdV flows on spaces of closed equicentroaffine plane curves are studied and it is shown that the flows are described as certain multi-Hamiltonian systems on the spaces. Multi-Hamiltonian systems describing higher mKdV flows are also given on spaces of closed Euclidean plane curves via the geometric Miura transformation

Supporting User-Defined Functions on Uncertain Data

Uncertain data management has become crucial in many sensing and scientific applications. As user-defined functions (UDFs) become widely used in these applications, an important task is to capture result uncertainty for queries that evaluate UDFs on uncertain data. In this work, we provide a general framework for supporting UDFs on uncertain data. Specifically, we propose a learning approach based on Gaussian processes (GPs) to compute approximate output distributions of a UDF when evaluated on uncertain input, with guaranteed error bounds. We also devise an online algorithm to compute such output distributions, which employs a suite of optimizations to improve accuracy and performance. Our evaluation using both real-world and synthetic functions shows that our proposed GP approach can outperform the state-of-the-art sampling approach with up to two orders of magnitude improvement for a variety of UDFs. 1

Discovery and cardioprotective effects of the first non-peptide agonists of the G protein-coupled prokineticin receptor-1

Prokineticins are angiogenic hormones that activate two G protein-coupled receptors: PKR1 and PKR2. PKR1 has emerged as a critical mediator of cardiovascular homeostasis and cardioprotection. Identification of non-peptide PKR1 agonists that contribute to myocardial repair and collateral vessel growth hold promises for treatment of heart diseases. Through a combination of in silico studies, medicinal chemistry, and pharmacological profiling approaches, we designed, synthesized, and characterized the first PKR1 agonists, demonstrating their cardioprotective activity against myocardial infarction (MI) in mice. Based on high throughput docking protocol, 250,000 compounds were computationally screened for putative PKR1 agonistic activity, using a homology model, and 10 virtual hits were pharmacologically evaluated. One hit internalizes PKR1, increases calcium release and activates ERK and Akt kinases. Among the 30 derivatives of the hit compound, the most potent derivative, IS20, was confirmed for its selectivity and specificity through genetic gain- and loss-of-function of PKR1. Importantly, IS20 prevented cardiac lesion formation and improved cardiac function after MI in mice, promoting proliferation of cardiac progenitor cells and neovasculogenesis. The preclinical investigation of the first PKR1 agonists provides a novel approach to promote cardiac neovasculogenesis after MI

Variability in organ-specific EGFR mutational spectra in tumour epithelium and stroma may be the biological basis for differential responses to tyrosine kinase inhibitors

Organ-specific differences in epidermal growth factor receptor (EGFR) mutational spectra and frequencies were found in lung cancer and sporadic and BRCA1/2-related breast cancers. Additionally, we found a high frequency of EGFR mutations in the tumour stroma of these invasive breast carcinomas. Those organ-specific mutational spectra and potential targets in the cancer-associated stroma might influence the efficacy of TKI therapy

High-throughput genomic technology in research and clinical management of breast cancer. Molecular signatures of progression from benign epithelium to metastatic breast cancer

It is generally accepted that early detection of breast cancer has great impact on patient survival, emphasizing the importance of early diagnosis. In a widely recognized model of breast cancer development, tumor cells progress through chronological and well defined stages. However, the molecular basis of disease progression in breast cancer remains poorly understood. High-throughput molecular profiling techniques are excellent tools for the study of complex molecular alterations. By accurately mapping changes in the genome and subsequent biological/molecular pathways, the chances of finding potential novel treatment targets as well as intervention strategies are enhanced, and ultimately lives can be saved. This review provides a brief summary of recent progress in identifying molecular markers for invasiveness in early breast lesions

A hop-count based positioning algorithm for wireless ad-hoc networks

We propose a range-free localization algorithm for a wireless ad-hoc network utilizing the hop-count metric’s ability to indicate proximity to anchors (i.e., nodes with known positions). In traditional sense, hop-count generally means the number of intermediate routers a datagram has to go through between its source and the destination node. We analytically show that hop-count could be used to indicate proximity relative to an anchor node. Our proposed algorithm is computationally feasible for resource constrained wireless ad-hoc nodes, and gives reasonable accuracy. We perform both real experiments and simulations to evaluate the algorithm’s performance. Experimental results show that our algorithm outperforms similar proximity based algorithms utilizing received signal strength and expected transmission count. We also analyze the impact of various parameters like the number of anchor nodes, placements of anchor nodes and varying transmission powers of the nodes on the hop-count based localization algorithm’s performance through simulation

Harmonic oscillator model of the insulin and IGF1 receptors' allosteric binding and activation

The insulin and insulin-like growth factor 1 receptors activate overlapping signalling pathways that are critical for growth, metabolism, survival and longevity. Their mechanism of ligand binding and activation displays complex allosteric properties, which no mathematical model has been able to account for. Modelling these receptors' binding and activation in terms of interactions between the molecular components is problematical due to many unknown biochemical and structural details. Moreover, substantial combinatorial complexity originating from multivalent ligand binding further complicates the problem. On the basis of the available structural and biochemical information, we develop a physically plausible model of the receptor binding and activation, which is based on the concept of a harmonic oscillator. Modelling a network of interactions among all possible receptor intermediaries arising in the context of the model (35, for the insulin receptor) accurately reproduces for the first time all the kinetic properties of the receptor, and provides unique and robust estimates of the kinetic parameters. The harmonic oscillator model may be adaptable for many other dimeric/dimerizing receptor tyrosine kinases, cytokine receptors and G-protein-coupled receptors where ligand crosslinking occurs

On the Suitability of Estelle for Multimedia Systems

Formal Description Techniques have been widely used for the specification of traditional networked applications. They have not been applied to the specification of new applications such as multimedia systems yet. In this paper, we examine the FDT Estelle with respect to its suitability for multimedia system specification and automatic derivation of efficient implementations. We show that it is possible to specify certain aspects of multimedia systems, but that Estelle is not sufficient for others. The derived implementations often perform badly. We show the reasons and propose to use a slightly modified Estelle syntax and semantics to solve the problems. The implemented solution was tested successfully