414 research outputs found

    Environmental responses of virally infected respiratory epithelial cells

    Full text link
    Background: Rhinovirus, airborne pollution, and allergens are thought to contribute to epithelial dysfunction in chronic airway disease. Objectives were to determine whether these factors act in synergism to induce inflammation and chronic airway disease. Methods: Respiratory mucosa from chronic rhinosinusitis with nasal polyps (CRSwNP) (n=7) or healthy (n=6) patients were cultured at air-liquid interface (ALI) (culture wells n=204). Cells were infected with rhinovirus, then exposed to combinations of vehicle, diesel particulate matter (DPM), and house dust mite (HDM). Ciliary beating frequency (CBF), interleukin (IL)-6 release, and cytotoxicity were assessed by Sisson-Ammons Video Analysis (SAVA) software, flow cytometry, and LDH assays. Results: Compared with healthy cultures, CRSwNP culture groups had lower baseline CBF. The CBF of virally infected ALI cultures was higher than healthy cultures. Challenges tended to impair CBF more in cells that were also virally infected. There was an elevation in IL-6 with viral infection. Challenge combinations did not cause a different IL-6 or CBF response within groups. Conclusions: An inherent mucosal dysfunction and environmental exposures can worsen sinus disease. Synergism in CBF impairment or IL-6 release was not seen

    A spatio‑temporal model of homicide in El Salvador

    Get PDF
    This paper examines the spatio-temporal evolution of homicide across the municipalities of El Salvador. It aims at identifying both temporal trends and spatial clusters that may contribute to the formation of time-stable corridors lying behind a historically (recurrent) high homicide rate. The results from this study reveal the presence of significant clusters of high homicide municipalities in the Western part of the country that have remained stable over time, and a process of formation of high homicide clusters in the Eastern region. The results show an increasing homicide trend from 2002 to 2013 with significant municipality-specific differential trends across the country. The data suggests that links may exist between the dynamics of homicide rates, drug trafficking and organized crime

    Anti-angiogenic therapies for the treatment of angiosarcoma: a clinical update

    Get PDF
    Summary: Angiosarcomas are rare aggressive endothelial tumours, and are associated with a poor prognosis. Due to their vascular nature, there is great interest in their response to anti-angiogenic agents. A number of small prospective studies have reported angiosarcoma response to vascular-targeted agents, including agents that target vascular endothelial growth factor. To date, the response to these agents has been disappointing, and similar to the response observed in other soft tissue sarcoma subtypes. This short review will summarise the recent data in this field

    Trabecular Meshwork Gene Expression after Selective Laser Trabeculoplasty

    Get PDF
    BACKGROUND: Trabecular meshwork and Schlemm's canal are the tissues appointed to modulate the aqueous humour outflow from the anterior chamber. The impairment of their functions drives to an intraocular pressure increase. The selective laser trabeculoplasty is a laser therapy of the trabecular meshwork able to decrease intraocular pressure. The exact response mechanism to this treatment has not been clearly delineated yet. The herein presented study is aimed at studying the gene expression changes induced in trabecular meshwork cells by selective laser trabeculoplasty (SLT) in order to better understand the mechanisms subtending its efficacy. METHODOLOGY/PRINCIPAL FINDINGS: Primary human trabecular meshwork cells cultured in fibroblast medium underwent selective laser trabeculoplasty treatment. RNA was extracted from a pool of cells 30 minutes after treatment while the remaining cells were further cultured and RNA was extracted respectively 2 and 6 hours after treatment. Control cells stored in incubator in absence of SLT treatment were used as reference samples. Gene expression was evaluated by hybridization on miRNA-microarray and laser scanner analysis. Scanning electron microscopic examination was performed on 2 Trabecular meshwork samples after SLT at 4(th) and 6(th) hour from treatment. On the whole, selective laser trabeculoplasty modulates in trabecular meshwork the expression of genes involved in cell motility, intercellular connections, extracellular matrix production, protein repair, DNA repair, membrane repair, reactive oxygen species production, glutamate toxicity, antioxidant activities, and inflammation. CONCLUSIONS/SIGNIFICANCE: SLT did not induce any phenotypic alteration in TM samples. TM is a complex tissue possessing a great variety of function pivotal for the active regulation of aqueous humour outflow from the anterior chamber. SLT is able to modulate these functions at the postgenomic molecular level without inducing damage either at molecular or phenotypic levels

    Multisensory information facilitates reaction speed by enlarging activity difference between superior colliculus hemispheres in rats

    Get PDF
    Animals can make faster behavioral responses to multisensory stimuli than to unisensory stimuli. The superior colliculus (SC), which receives multiple inputs from different sensory modalities, is considered to be involved in the initiation of motor responses. However, the mechanism by which multisensory information facilitates motor responses is not yet understood. Here, we demonstrate that multisensory information modulates competition among SC neurons to elicit faster responses. We conducted multiunit recordings from the SC of rats performing a two-alternative spatial discrimination task using auditory and/or visual stimuli. We found that a large population of SC neurons showed direction-selective activity before the onset of movement in response to the stimuli irrespective of stimulation modality. Trial-by-trial correlation analysis showed that the premovement activity of many SC neurons increased with faster reaction speed for the contraversive movement, whereas the premovement activity of another population of neurons decreased with faster reaction speed for the ipsiversive movement. When visual and auditory stimuli were presented simultaneously, the premovement activity of a population of neurons for the contraversive movement was enhanced, whereas the premovement activity of another population of neurons for the ipsiversive movement was depressed. Unilateral inactivation of SC using muscimol prolonged reaction times of contraversive movements, but it shortened those of ipsiversive movements. These findings suggest that the difference in activity between the SC hemispheres regulates the reaction speed of motor responses, and multisensory information enlarges the activity difference resulting in faster responses

    Multilocus Bayesian Estimates of Intra-Oceanic Genetic Differentiation, Connectivity, and Admixture in Atlantic Swordfish (Xiphias gladius L.)

    Get PDF
    Versión del editor

    Inhibition of N1-Src kinase by a specific SH3 peptide ligand reveals a role for N1-Src in neurite elongation by L1-CAM

    Get PDF
    In the mammalian brain the ubiquitous tyrosine kinase, C-Src, undergoes splicing to insert short sequences in the SH3 domain to yield N1- and N2-Src. We and others have previously shown that the N-Srcs have altered substrate specificity and kinase activity compared to C-Src. However, the exact functions of the N-Srcs are unknown and it is likely that N-Src signalling events have been misattributed to C-Src because they cannot be distinguished by conventional Src inhibitors that target the kinase domain. By screening a peptide phage display library, we discovered a novel ligand (PDN1) that targets the unique SH3 domain of N1-Src and inhibits N1-Src in cells. In cultured neurons, PDN1 fused to a fluorescent protein inhibited neurite outgrowth, an effect that was mimicked by shRNA targeting the N1-Src microexon. PDN1 also inhibited L1-CAM-dependent neurite elongation in cerebellar granule neurons, a pathway previously shown to be disrupted in Src(−/−) mice. PDN1 therefore represents a novel tool for distinguishing the functions of N1-Src and C-Src in neurons and is a starting point for the development of a small molecule inhibitor of N1-Src

    New prioritized value iteration for Markov decision processes

    Full text link
    The problem of solving large Markov decision processes accurately and quickly is challenging. Since the computational effort incurred is considerable, current research focuses on finding superior acceleration techniques. For instance, the convergence properties of current solution methods depend, to a great extent, on the order of backup operations. On one hand, algorithms such as topological sorting are able to find good orderings but their overhead is usually high. On the other hand, shortest path methods, such as Dijkstra's algorithm which is based on priority queues, have been applied successfully to the solution of deterministic shortest-path Markov decision processes. Here, we propose an improved value iteration algorithm based on Dijkstra's algorithm for solving shortest path Markov decision processes. The experimental results on a stochastic shortest-path problem show the feasibility of our approach. © Springer Science+Business Media B.V. 2011.García Hernández, MDG.; Ruiz Pinales, J.; Onaindia De La Rivaherrera, E.; Aviña Cervantes, JG.; Ledesma Orozco, S.; Alvarado Mendez, E.; Reyes Ballesteros, A. (2012). New prioritized value iteration for Markov decision processes. Artificial Intelligence Review. 37(2):157-167. doi:10.1007/s10462-011-9224-zS157167372Agrawal S, Roth D (2002) Learning a sparse representation for object detection. In: Proceedings of the 7th European conference on computer vision. Copenhagen, Denmark, pp 1–15Bellman RE (1954) The theory of dynamic programming. Bull Amer Math Soc 60: 503–516Bellman RE (1957) Dynamic programming. Princeton University Press, New JerseyBertsekas DP (1995) Dynamic programming and optimal control. Athena Scientific, MassachusettsBhuma K, Goldsmith J (2003) Bidirectional LAO* algorithm. In: Proceedings of indian international conferences on artificial intelligence. p 980–992Blackwell D (1965) Discounted dynamic programming. Ann Math Stat 36: 226–235Bonet B, Geffner H (2003a) Faster heuristic search algorithms for planning with uncertainty and full feedback. In: Proceedings of the 18th international joint conference on artificial intelligence. Morgan Kaufmann, Acapulco, México, pp 1233–1238Bonet B, Geffner H (2003b) Labeled RTDP: improving the convergence of real-time dynamic programming. In: Proceedings of the international conference on automated planning and scheduling. Trento, Italy, pp 12–21Bonet B, Geffner H (2006) Learning depth-first search: a unified approach to heuristic search in deterministic and non-deterministic settings and its application to MDP. In: Proceedings of the 16th international conference on automated planning and scheduling. Cumbria, UKBoutilier C, Dean T, Hanks S (1999) Decision-theoretic planning: structural assumptions and computational leverage. J Artif Intell Res 11: 1–94Chang I, Soo H (2007) Simulation-based algorithms for Markov decision processes Communications and control engineering. Springer, LondonDai P, Goldsmith J (2007a) Faster dynamic programming for Markov decision processes. Technical report. Doctoral consortium, department of computer science and engineering. University of WashingtonDai P, Goldsmith J (2007b) Topological value iteration algorithm for Markov decision processes. In: Proceedings of the 20th international joint conference on artificial intelligence. Hyderabad, India, pp 1860–1865Dai P, Hansen EA (2007c) Prioritizing bellman backups without a priority queue. In: Proceedings of the 17th international conference on automated planning and scheduling, association for the advancement of artificial intelligence. Rhode Island, USA, pp 113–119Dibangoye JS, Chaib-draa B, Mouaddib A (2008) A Novel prioritization technique for solving Markov decision processes. In: Proceedings of the 21st international FLAIRS (The Florida Artificial Intelligence Research Society) conference, association for the advancement of artificial intelligence. Florida, USAFerguson D, Stentz A (2004) Focused propagation of MDPs for path planning. In: Proceedings of the 16th IEEE international conference on tools with artificial intelligence. pp 310–317Hansen EA, Zilberstein S (2001) LAO: a heuristic search algorithm that finds solutions with loops. Artif Intell 129: 35–62Hinderer K, Waldmann KH (2003) The critical discount factor for finite Markovian decision processes with an absorbing set. Math Methods Oper Res 57: 1–19Li L (2009) A unifying framework for computational reinforcement learning theory. PhD Thesis. The state university of New Jersey, New Brunswick. NJLittman ML, Dean TL, Kaelbling LP (1995) On the complexity of solving Markov decision problems.In: Proceedings of the 11th international conference on uncertainty in artificial intelligence. Montreal, Quebec pp 394–402McMahan HB, Gordon G (2005a) Fast exact planning in Markov decision processes. In: Proceedings of the 15th international conference on automated planning and scheduling. Monterey, CA, USAMcMahan HB, Gordon G (2005b) Generalizing Dijkstra’s algorithm and gaussian elimination for solving MDPs. Technical report, Carnegie Mellon University, PittsburghMeuleau N, Brafman R, Benazera E (2006) Stochastic over-subscription planning using hierarchies of MDPs. In: Proceedings of the 16th international conference on automated planning and scheduling. Cumbria, UK, pp 121–130Moore A, Atkeson C (1993) Prioritized sweeping: reinforcement learning with less data and less real time. Mach Learn 13: 103–130Puterman ML (1994) Markov decision processes. Wiley Editors, New YorkPuterman ML (2005) Markov decision processes. Wiley Inter Science Editors, New YorkRussell S (2005) Artificial intelligence: a modern approach. Making complex decisions (Ch-17), 2nd edn. Pearson Prentice Hill Ed., USAShani G, Brafman R, Shimony S (2008) Prioritizing point-based POMDP solvers. IEEE Trans Syst Man Cybern 38(6): 1592–1605Sniedovich M (2006) Dijkstra’s algorithm revisited: the dynamic programming connexion. Control Cybern 35: 599–620Sniedovich M (2010) Dynamic programming: foundations and principles, 2nd edn. Pure and Applied Mathematics Series, UKTijms HC (2003) A first course in stochastic models. Discrete-time Markov decision processes (Ch-6). Wiley Editors, UKVanderbei RJ (1996) Optimal sailing strategies. Statistics and operations research program, University of Princeton, USA ( http://www.orfe.princeton.edu/~rvdb/sail/sail.html )Vanderbei RJ (2008) Linear programming: foundations and extensions, 3rd edn. Springer, New YorkWingate D, Seppi KD (2005) Prioritization methods for accelerating MDP solvers. J Mach Learn Res 6: 851–88
    • …
    corecore