1,115 research outputs found
Identification of novel DNA methylation inhibitors via a two-component reporter gene system
<p>Abstract</p> <p>Background</p> <p>Targeting abnormal DNA methylation represents a therapeutically relevant strategy for cancer treatment as demonstrated by the US Food and Drug Administration approval of the DNA methyltransferase inhibitors azacytidine and 5-aza-2'-deoxycytidine for the treatment of myelodysplastic syndromes. But their use is associated with increased incidences of bone marrow suppression. Alternatively, procainamide has emerged as a potential DNA demethylating agent for clinical translation. While procainamide is much safer than 5-aza-2'-deoxycytidine, it requires high concentrations to be effective in DNA demethylation in suppressing cancer cell growth. Thus, our laboratories have embarked on the pharmacological exploitation of procainamide to develop potent DNA methylation inhibitors through lead optimization.</p> <p>Methods</p> <p>We report the use of a DNA methylation two-component enhanced green fluorescent protein reporter system as a screening platform to identify novel DNA methylation inhibitors from a compound library containing procainamide derivatives.</p> <p>Results</p> <p>A lead agent IM25, which exhibits substantially higher potency in <it>GSTp1 </it>DNA demethylation with lower cytotoxicity in MCF7 cells relative to procainamide and 5-aza-2'-deoxycytidine, was identified by the screening platform.</p> <p>Conclusions</p> <p>Our data provide a proof-of-concept that procainamide could be pharmacologically exploited to develop novel DNA methylation inhibitors, of which the translational potential in cancer therapy/prevention is currently under investigation.</p
Transcriptional regulation of human eosinophil RNases by an evolutionary- conserved sequence motif in primate genome
Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: a structural equation modeling of an extended technology acceptance model
In this study, we examine the effects of individual-level culture on the adoption and acceptance of e-learning tools by students in Lebanon using a theoretical framework based on the Technology Acceptance Model (TAM). To overcome possible limitations of using TAM in developing countries, we extend TAM to include subjective norms (SN) and quality of work life constructs as additional constructs and a number of cultural variables as moderators. The four cultural dimensions of masculinity/femininity (MF), individualism/collectivism, power distance and uncertainty avoidance were measured at the individual level to enable them to be integrated into the extended TAM as moderators and a research model was developed based on previous literature. To test the hypothesised model, data were collected from 569 undergraduate and postgraduate students using e-learning tools in Lebanon via questionnaire. The collected data were analysed using the structural equation modelling technique in conjunction with multi-group analysis. As hypothesised, the results of the study revealed perceived usefulness (PU), perceived ease of use (PEOU), SN and quality of work life to be significant determinants of students’ behavioural intention (BI) towards e-learning. The empirical results also demonstrated that the relationship between SN and BI was particularly sensitive to differences in individual-cultural values, with significant moderating effects observed for all four of the cultural dimensions studied. Some moderating effects of culture were also found for both PU and PEOU, however, contrary to expectations the effect of quality of work life was not found to be moderated by MF as some previous authors have predicted. The implications of these results to both theory and practice are explored in the paper
A Single-Walled Carbon Nanotube Network Gas Sensing Device
The goal of this research was to develop a chemical gas sensing device based on single-walled carbon nanotube (SWCNT) networks. The SWCNT networks are synthesized on Al2O3-deposted SiO2/Si substrates with 10 nm-thick Fe as the catalyst precursor layer using microwave plasma chemical vapor deposition (MPCVD). The development of interconnected SWCNT networks can be exploited to recognize the identities of different chemical gases by the strength of their particular surface adsorptive and desorptive responses to various types of chemical vapors. The physical responses on the surface of the SWCNT networks cause superficial changes in the electric charge that can be converted into electronic signals for identification. In this study, we tested NO2 and NH3 vapors at ppm levels at room temperature with our self-made gas sensing device, which was able to obtain responses to sensitivity changes with a concentration of 10 ppm for NO2 and 24 ppm for NH3
Identifying efficient solutions via simulation: myopic multi-objective budget allocation for the bi-objective case
Simulation optimisation offers great opportunities in the design and optimisation of complex systems. In the presence of multiple objectives, there is usually no single solution that performs best on all objectives. Instead, there are several Pareto-optimal (efficient) solutions with different trade-offs which cannot be improved in any objective without sacrificing performance in another objective. For the case where alternatives are evaluated on multiple stochastic criteria, and the performance of an alternative can only be estimated via simulation, we consider the problem of efficiently identifying the Pareto-optimal designs out of a (small) given set of alternatives. We present a simple myopic budget allocation algorithm for multi-objective problems and propose several variants for different settings. In particular, this myopic method only allocates one simulation sample to one alternative in each iteration. This paper shows how the algorithm works in bi-objective problems under different settings. Empirical tests show that our algorithm can significantly reduce the necessary simulation budget
The DArk Matter Particle Explorer mission
The DArk Matter Particle Explorer (DAMPE), one of the four scientific space
science missions within the framework of the Strategic Pioneer Program on Space
Science of the Chinese Academy of Sciences, is a general purpose high energy
cosmic-ray and gamma-ray observatory, which was successfully launched on
December 17th, 2015 from the Jiuquan Satellite Launch Center. The DAMPE
scientific objectives include the study of galactic cosmic rays up to
TeV and hundreds of TeV for electrons/gammas and nuclei respectively, and the
search for dark matter signatures in their spectra. In this paper we illustrate
the layout of the DAMPE instrument, and discuss the results of beam tests and
calibrations performed on ground. Finally we present the expected performance
in space and give an overview of the mission key scientific goals.Comment: 45 pages, including 29 figures and 6 tables. Published in Astropart.
Phy
Online platform for applying space–time scan statistics for prospectively detecting emerging hot spots of dengue fever
Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics
A detailed study is presented of the expected performance of the ATLAS
detector. The reconstruction of tracks, leptons, photons, missing energy and
jets is investigated, together with the performance of b-tagging and the
trigger. The physics potential for a variety of interesting physics processes,
within the Standard Model and beyond, is examined. The study comprises a series
of notes based on simulations of the detector and physics processes, with
particular emphasis given to the data expected from the first years of
operation of the LHC at CERN
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