Effects of cytomegalovirus infection in human neural precursor cells depend on their differentiation state

© 2015, Journal of NeuroVirology, Inc. Cytomegalovirus (CMV) is the most common cause of congenital infection in developed countries and a major cause of neurological disability in children. Although CMV can affect multiple organs, the most important sequelae of intrauterine infection are related to lesions of the central nervous system. However, little is known about the pathogenesis and the cellular events responsible for neuronal damage in infants with congenital infection. Some studies have demonstrated that neural precursor cells (NPCs) show the greatest susceptibility to CMV infection in the developing brain. We sought to establish an in vitro model of CMV infection of the developing brain in order to analyze the cellular events associated with invasion by this virus. To this end, we employed two cell lines as a permanent source of NPC, avoiding the continuous use of human fetal tissue, the human SK-N-MC neuroblastoma cell line, and an immortalized cell line of human fetal neural origin, hNS-1. We also investigated the effect of the differentiation stage in relation to the susceptibility of these cell lines by comparing the neuroblastoma cell line with the multipotent cell line hNS-1. We found that the effects of the virus were more severe in the neuroblastoma cell line. Additionally, we induced hNS-1 to differentiate and evaluated the effect of CMV in these differentiated cells. Like SK-N-MC cells, hNS-1-differentiated cells were also susceptible to infection. Viability of differentiated hNS-1 cells decreased after CMV infection in contrast to undifferentiated cells. In addition, differentiated hNS-1 cells showed an extensive cytopathic effect whereas the effect was scarce in undifferentiated cells. We describe some of the effects of CMV in neural stem cells, and our observations suggest that the degree of differentiation is important in the acquisition of susceptibility.CONACYT (CB16782 and #120452), PROMEP (103.5/10/7697), and FAI-UASLP (C12-FAI-03-62.62).Peer Reviewe

Synthetic lethal interaction of cetuximab with MEK1/2 inhibition in NRAS-mutant metastatic colorectal cancer

KRAS mutations are an established predictor of lack of response to EGFR-targeted therapies in patients with metastatic colorectal cancer (mCRC). However, little is known about the role of the rarer NRAS mutations as a mechanism of primary resistance to the anti-EGFR monoclonal antibody cetuximab in wild-type KRAS mCRC. Using isogenic mCRC cells with a heterozygous knock-in of the NRAS activating mutation Q61K, we aimed to elucidate the mechanism(s) by which mutant NRAS blocks cetuximab from inhibiting mCRC growth. NRASQ61K/+ cells were refractory to cetuximab-induced growth inhibition. Pathway-oriented proteome profiling revealed that cetuximab-unresponsive ERK1/2 phosphorylation was the sole biomarker distinguishing cetuximab-refractory NRASQ61K/+ from cetuximab-sensitive NRAS+/+ cells. We therefore employed four representative MEK1/2 inhibitors (binimetinib, trametinib, selumetinib, and pimasertib) to evaluate the therapeutic value of MEK/ERK signaling in cetuximab-refractory NRAS mutation-induced mCRC. Co-treatment with an ineffective dose of cetuximab augmented, up to more than 1,300-fold, the cytotoxic effects of pimasertib against NRASQ61K/+ cells. Simultaneous combination of MEK1/2 inhibitors with cetuximab resulted in extremely high and dose-dependent synthetic lethal effects, which were executed, at least in part, by exacerbated apoptotic cell death. Dynamic monitoring of real-time cell growth rates confirmed that cetuximab synergistically sensitized NRASQ61K/+ cellsto MEK1/2 inhibition. Our discovery of a synthetic lethal interaction of cetuximab in combination with MEK1/2 inhibition for the NRAS mutant subgroup of mCRC underscores the importance of therapeutic intervention both in the MEK-ERK and EGFR pathways to achieve maximal therapeutic efficacy against NRAS-mutant mCRC tumors

APLICACIÓN MÓVIL PARA LA DETECCIÓN DE DIFICULTADES DURANTE LA EJECUCIÓN DE EVALUACIONES FORMATIVAS

This paper presents the production of graphical interfaces for Health Simulator project. The article discusses the possibility of using agile methods combined with design methodology to improve the preparation of game and administrative interfaces. It chose a methodology based on Project E (Meurer and Szabluk, 2008). The final product will be validated with users regarding the use of this

The Large Aperture GRB Observatory

The Large Aperture GRB Observatory (LAGO) is aiming at the detection of the high energy (around 100 GeV) component of Gamma Ray Bursts, using the single particle technique in arrays of Water Cherenkov Detectors (WCD) in high mountain sites (Chacaltaya, Bolivia, 5300 m a.s.l., Pico Espejo, Venezuela, 4750 m a.s.l., Sierra Negra, Mexico, 4650 m a.s.l). WCD at high altitude offer a unique possibility of detecting low gamma fluxes in the 10 GeV - 1 TeV range. The status of the Observatory and data collected from 2007 to date will be presented.Comment: 4 pages, proceeding of 31st ICRC 200

Water Cherenkov Detectors response to a Gamma Ray Burst in the Large Aperture GRB Observatory

In order to characterise the behaviour of Water Cherenkov Detectors (WCD) under a sudden increase of 1 GeV - 1 TeV background photons from a Gamma Ray Burst (GRB), simulations were conducted and compared to data acquired by the WCD of the Large Aperture GRB Observatory (LAGO). The LAGO operates arrays of WCD at high altitude to detect GRBs using the single particle technique. The LAGO sensitivity to GRBs is derived from the reported simulations of the gamma initiated particle showers in the atmosphere and the WCD response to secondaries.Comment: 5 pages, proceeding of the 31st ICRC 200

Decomposition techniques with mixed integer programming and heuristics for home healthcare planning

We tackle home healthcare planning scenarios in the UK using decomposition methods that incorporate mixed integer programming solvers and heuristics. Home healthcare planning is a difficult problem that integrates aspects from scheduling and routing. Solving real-world size instances of these problems still presents a significant challenge to modern exact optimization solvers. Nevertheless, we propose decomposition techniques to harness the power of such solvers while still offering a practical approach to produce high-quality solutions to real-world problem instances. We first decompose the problem into several smaller sub-problems. Next, mixed integer programming and/or heuristics are used to tackle the sub-problems. Finally, the sub-problem solutions are combined into a single valid solution for the whole problem. The different decomposition methods differ in the way in which subproblems are generated and the way in which conflicting assignments are tackled (i.e. avoided or repaired). We present the results obtained by the proposed decomposition methods and compare them to solutions obtained with other methods. In addition, we conduct a study that reveals how the different steps in the proposed method contribute to those results. The main contribution of this paper is a better understanding of effective ways to combine mixed integer programming within effective decomposition methods to solve real-world instances of home healthcare planning problems in practical computation time