Human iPSC-derived astrocytes transplanted into the mouse brain undergo morphological changes in response to amyloid-beta plaques

BACKGROUND: Increasing evidence for a direct contribution of astrocytes to neuroinflammatory and neurodegenerative processes causing Alzheimer’s disease comes from molecular and functional studies in rodent models. However, these models may not fully recapitulate human disease as human and rodent astrocytes differ considerably in morphology, functionality, and gene expression. RESULTS: To address these challenges, we established an approach to study human astrocytes within the mouse brain by transplanting human induced pluripotent stem cell (hiPSC)-derived astrocyte progenitors into neonatal brains. Xenografted hiPSC-derived astrocyte progenitors differentiated into astrocytes that integrated functionally within the mouse host brain and matured in a cell-autonomous way retaining human-specific morphologies, unique features, and physiological properties. In Alzheimer´s chimeric brains, transplanted hiPSC-derived astrocytes responded to the presence of amyloid plaques undergoing morphological changes that seemed independent of the APOE allelic background. CONCLUSIONS: In sum, we describe here a promising approach that consist of transplanting patient-derived and genetically modified astrocytes into the mouse brain to study human astrocyte pathophysiology in the context of Alzheimer´s disease

Computer simulations of VANETs using realistic city topologies

Researchers in vehicular ad hoc networks (VANETs) commonly use simulation to test new algorithms and techniques. This is the case because of the high cost and labor involved in deploying and testing vehicles in real outdoor scenarios. However, when determining the factors that should be taken into account in these simulations, some factors such as realistic road topologies and presence of obstacles are rarely addressed. In this paper, we first evaluate the packet error rate (PER) through actual measurements in an outdoor road scenario, and deduce a close model of the PER for VANETs. Secondly, we introduce a topology-based visibility scheme such that road dimension and geometry can be accounted for, in addition to line-of-sight. We then combine these factors to determine when warning messages (i.e., messages that warn drivers of danger and hazards) are successfully received in a VANET. Through extensive simulations using different road topologies, city maps, and visibility schemes, we show these factors can impact warning message dissemination time and packet delivery rate.This work was partially supported by the Ministerio de Educacion y Ciencia, Spain, under Grant TIN2011-27543-C03-01, and by the Diputacion General de Aragon, under Grant "subvenciones destinadas a la formacion y contratacion de personal investigador".Martínez, FJ.; Fogue, M.; Toh, C.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2013). Computer simulations of VANETs using realistic city topologies. Wireless Personal Communications. 69(2):639-663. https://doi.org/10.1007/s11277-012-0594-6S639663692Martinez F. J., Toh C.-K., Cano J.-C., Calafate C. T., Manzoni P. (2011) A survey and comparative study of simulators for vehicular ad hoc networks (VANETs). Wireless Communications and Mobile Computing Journal 11(7): 813–828Toh C.-K. 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J., Fogue, M., Coll, M., Cano, J.-C., Calafate, C. T., & Manzoni, P. (2010). Assessing the impact of a realistic radio propagation model on VANET scenarios using real maps. In 9th IEEE international symposium on network computing and applications (NCA), Boston, USA, pp. 132–139.Fall, K., & Varadhan, K. (2000). “ns notes and documents,” The VINT project. UC Berkeley, LBL, USC/ISI, and Xerox PARC, February 2000. Available at http://www.isi.edu/nsnam/ns/ns-documentation.html .Marinoni, S., & Kari, H. H. (2006). Ad hoc routing protocol performance in a realistic environment. In Proceedings of the international conference on networking, international conference on systems and international conference on mobile communications and learning technologies (ICN/ICONS/MCL 2006), Washington, DC, USA.Mahajan, A., Potnis, N., Gopalan, K., & Wang, A. (2007). Modeling VANET deployment in urban settings. In International workshop on modeling analysis and simulation of wireless and mobile systems (MSWiM 2007), Crete Island, Greece.Suriyapaiboonwattana, K., Pornavalai, C., & Chakraborty, G. (2009). An adaptive alert message dissemination protocol for VANET to improve road safety. In IEEE intlernational conference on fuzzy systems, 2009. FUZZ-IEEE 2009, pp. 1639–1644.Bako, B., Schoch, E., Kargl, F., & Weber, M. (2008). Optimized position based gossiping in VANETs. In Vehicular technology conference, 2008. VTC 2008-Fall. IEEE 68th, pp. 1–5.Martinez, F. J., Cano, J.-C., Calafate, C. T., & Manzoni, P. (2008). Citymob: A mobility model pattern generator for VANETs. In IEEE vehicular networks and applications workshop (Vehi-Mobi, held with ICC), Beijing, China.Torrent-Moreno, M., Santi, P., & Hartenstein, H. (2007). Inter-vehicle communications: Assessing information dissemination under safety constraints. In Proceedings of the 4th annual conference on wireless on demand network systems and services (WONS), Oberguyrgl, Austria.Martinez, F. J., Toh, C.-K., Cano, J.-C., Calafate, C. T., & Manzoni, P. (2009). Realistic radio propagation models (RPMs) for VANET simulations. In IEEE wireless communications and networking conference (WCNC), Budapest, Hungary.Martinez, F. J., Toh, C.-K., Cano, J.-C., Calafate, C. T., & Manzoni, P. (2010). A street broadcast reduction scheme (SBR) to mitigate the broadcast storm problem in VANETs. Wireless personal communications, pp. 1–14. doi: 10.1007/s11277-010-9989-4Ni, S.-Y., Tseng, Y.-C., Chen, Y.-S., & Sheu, J.-P. (1999). The broadcast storm problem in a mobile ad hoc network. In ACM/IEEE international conference on mobile computing and networking (MobiCom 1999), Seattle Washington.Krajzewicz, D., & Rossel, C. (2007). “Simulation of urban mobility (SUMO),” Centre for Applied Informatics (ZAIK) and the Institute of Transport Research at the German Aerospace Centre. Available at http://sumo.sourceforge.net/index.shtml .OpenStreetMap Team. (2009). OpenStreetMap, collaborative project to create a free editable map of the world. Available at http://www.openstreetmap.org .U.S. Census Bureau. (2009). TIGER, topologically integrated geographic encoding and referencing. Available at http://www.census.gov/geo/www/tiger .Krauss S., Wagner P., Gawron C. (1997) Metastable states in a microscopic model of traffic flow. Physical Review E 55(5): 5597–5602Krajzewicz, D., Hertkorn, G., Rossel, C., & Wagner, P. (2002). SUMO (Simulation of Urban MObility)—An open-source traffic simulation. In Proceedings of the 4th middle east symposium on simulation and modelling (MESM2002), Sharjah, United Arab Emirates, pp. 183–187

An Intelligent Transportation System Application for Smartphones Based on Vehicle Position Advertising and Route Sharing in Vehicular Ad-Hoc Networks

[EN] Alerting drivers about incoming emergency vehicles and their routes can greatly improve their travel times in congested cities, while reducing the risk of accidents due to distractions. This paper contributes to this goal by proposing Messiah, an Android application capable of informing regular vehicles about incoming emergency vehicles like ambulances, police cars and fire brigades. This is made possible by creating a network of vehicles capable of directly communicating between them. The user can, therefore, take driving decisions in a timely manner by considering incoming alerts. Using the support of our GRCBox hardware, the application can rely on vehicular ad-hoc network communications in the 5 GHz band, being V2V (vehicle-to-vehicle) communication provided through a combination of Android-based smartphone and our GRCBox device. The application was tested in three different scenarios with different levels of obstruction, showing that it is capable of providing alerts up to 300 meters, and notifying vehicles within less than one secondThis work was partially supported by the "Ministerio de Economia y Competividad, Programa Estatal de Investigacion, Desarollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014", Spain, under Grant Nos. TEC2014-52690-R and BES-2015-075988.Hadiwardoyo, SA.; Patra, S.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P. (2018). An Intelligent Transportation System Application for Smartphones Based on Vehicle Position Advertising and Route Sharing in Vehicular Ad-Hoc Networks. Journal of Computer Science and Technology. 33(2):249-262. https://doi.org/10.1007/s11390-018-1817-4S249262332Papadimitratos P, De La Fortelle A, Evenssen K, Brignolo R, Cosenza S. Vehicular communication systems: Enabling technologies, applications, and future outlook on intelligent transportation. IEEE Communications Magazine, 2009, 47(11): 84-95.Gerla M, Kleinrock L. Vehicular networks and the future of the mobile Internet. Computer Networks, 2011, 55(2): 457-469.Vegni A M, Loscrí V. A survey on vehicular social networks. IEEE Communications Surveys & Tutorials, 2015, 17(4): 2397-2419.Eze E C, Zhang S J, Liu E J. Vehicular ad hoc networks (VANETs): Current state, challenges, potentials and way forward. In Proc. the 20th Int. Conf. Automation and Computing, September 2014, pp.176-181.Qi L. Research on intelligent transportation system technologies and applications. In Proc. Workshop on Power Electronics and Intelligent Transportation System, August 2008, pp.529-531.Gozalvez J. First Google’s Android phone launched [Mobile Radio]. IEEE Vehicular Technology Magazine, 2008, 3(4): 3-69.Haklay M,Weber P. OpenStreetMap: User-generated street maps. IEEE Pervasive Computing, 2008, 7(4): 12-18.Hadiwardoyo S A, Patra S, Calafate C T, Cano J C, Manzoni P. An Android ITS driving safety application based on vehicle-to-vehicle (V2V) communications. In Proc. the 26th Int. Conf. Computer Communication and Networks, July 31-August 3, 2017.Eriksson J, Balakrishnan H, Madden S. Cabernet: Vehicular content delivery using WiFi. In Proc. the 14th ACM Int. Conf. Mobile Computing and Networking, September 2008, pp.199-210.Gerla M, Weng J T, Giordano E, Pau G. Vehicular testbeds-validating models and protocols before large scale deployment. In Proc. Int. Conf. Computing Networking and Communications, January 30-February 2, 2012, pp.665-669.Wahlström J, Skog I, Händel P. Smartphone-based vehicle telematics: A ten-year anniversary. IEEE Trans. Intelligent Transportation Systems, 2017, 18(10): 2802-2825.Whipple J, Arensman W, Boler M S. A public safety application of GPS-enabled smartphones and the Android operating system. In Proc. IEEE Int. Conf. Systems Man and Cybernetics, October 2009, pp.2059-2061.Meseguer J E, Calafate C T, Cano J C, Manzoni P. DrivingStyles: A smartphone application to assess driver behavior. In Proc. IEEE Symp. Computers and Communications, July 2013, pp.000535-000540.You C W, Lane N D, Chen F L, Wang R, Chen Z Y, Bao T J, Montes-De-Oca M, Cheng Y T, Lin M, Torresani L, Campbell A T. CarSafe app: Alerting drowsy and distracted drivers using dual cameras on smartphones. In Proc. the 11th Annual Int. Conf. Mobile Systems Applications and Services, June 2013, pp.461-462.Patra S, Arnanz J H, Calafate C T, Cano J C, Manzoni P. EYES: A novel overtaking assistance system for vehicular networks. In Proc. the 14th Int. Conf. Ad-Hoc Networks and Wireless, June 2015, pp.375-389.Togneri M C, Deriaz M. On-board navigation system for smartphones. In Proc. Int. Conf. Indoor Positioning and Indoor Navigation, October 2013.Dancu A, Franjcic Z, Fjeld M. Smart flashlight: Map navigation using a bike-mounted projector. In Proc. the SIGCHI Conf. Human Factors in Computing Systems, April 2014, pp.3627-3630.Yamabe T, Ikegami S, Ishizaki A, Kitagami S, Kiyohara R. Car navigation user interface based on a smartphone. In Proc. the 7th Int. Conf. Mobile Computing and Ubiquitous Networking, January 2014, pp.85-86.Matsuyama S, Yamabe T, Takahashi N, Kiyohara R. Intelligent user interface of smartphones for on-vehicle information devices. Procedia Computer Science, 2014, 35: 1635-1643.Kovacevic B, Kovacevic M, Maruna T, Papp I. A java application programming interface for in-vehicle infotainment devices. IEEE Trans. Consumer Electronics, 2017, 63(1): 68-76.Liu R L, Liu H Z, Kwak D, Xiang Y, Borcea C, Nath B, Iftode L. Themis: A participatory navigation system for balanced traffic routing. In Proc. IEEE Vehicular Networking Conf., December 2014, pp.159-166.Liu R L, Liu H Z, Kwak D, Xiang Y, Borcea C, Nath B, Iftode L. Balanced traffic routing: Design, implementation, and evaluation. Ad Hoc Networks, 2016, 37: 14-28.Vochin M, Zoican S, Borcoci E. Intelligent system for vehicle navigation assistance. In Proc. World Conf. Information Systems and Technologies, April 2017, pp.142-148.Sha W J, Kwak D, Nath B, Iftode L. Social vehicle navigation: Integrating shared driving experience into vehicle navigation. In Proc. the 14th Workshop on Mobile Computing Systems and Applications, February 2013, Article No. 16.Kwak D, Liu R L, Kim D, Nath B, Iftode L. Seeing is believing: Sharing real-time visual traffic information via vehicular clouds. IEEE Access, 2016, 4: 3617-3631.Djajadi A, Putra R J. Inter-cars safety communication system based on Android smartphone. In Proc. IEEE Conf. Open Systems, October 2014, pp.12-17.Dorairaj P, Mohammed A, Grbic N. Location-Aware services using Android mobile operating platform for safety, emergency and health applications. In Mobile Health, Adibi S (ed.), Springer, 2015, pp.283-298.Dorairaj P, Ramamoorthy S, Ramalingam A K. 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Early alterations in the MCH system link aberrant neuronal activity and sleep disturbances in a mouse model of Alzheimer’s disease

Early Alzheimer’s disease (AD) is associated with hippocampal hyperactivity and decreased sleep quality. Here we show that homeostatic mechanisms transiently counteract the increased excitatory drive to CA1 neurons in App NL-G-F mice, but that this mechanism fails in older mice. Spatial transcriptomics analysis identifies Pmch as part of the adaptive response in App NL-G-F mice. Pmch encodes melanin-concentrating hormone (MCH), which is produced in sleep–active lateral hypothalamic neurons that project to CA1 and modulate memory. We show that MCH downregulates synaptic transmission, modulates firing rate homeostasis in hippocampal neurons and reverses the increased excitatory drive to CA1 neurons in App NL-G-F mice. App NL-G-F mice spend less time in rapid eye movement (REM) sleep. App NL-G-F mice and individuals with AD show progressive changes in morphology of CA1-projecting MCH axons. Our findings identify the MCH system as vulnerable in early AD and suggest that impaired MCH-system function contributes to aberrant excitatory drive and sleep defects, which can compromise hippocampus-dependent functions

Flying ad-hoc network application scenarios and mobility models

[EN] Flying ad-hoc networks are becoming a promising solution for different application scenarios involving unmanned aerial vehicles, like urban surveillance or search and rescue missions. However, such networks present various and very specific communication issues. As a consequence, there are several research studies focused on analyzing their performance via simulation. Correctly modeling mobility is crucial in this context and although many mobility models are already available to reproduce the behavior of mobile nodes in an ad-hoc network, most of these models cannot be used to reliably simulate the motion of unmanned aerial vehicles. In this article, we list the existing mobility models and provide guidance to understand whether they could be actually adopted depending on the specific flying ad-hoc network application scenarios, while discussing their advantages and disadvantages.Bujari, A.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P.; Palazzi, CE.; Ronzani, D. (2017). Flying ad-hoc network application scenarios and mobility models. International Journal of Distributed Sensor Networks. 13(10):1-17. doi:10.1177/1550147717738192S117131

Neuronal lysosomal dysfunction releases exosomes harboring APP C-terminal fragments and unique lipid signatures

Defects in endolysosomal and autophagic functions are increasingly viewed as key pathological features of neurodegenerative disorders. A master regulator of these functions is phosphatidylinositol-3-phosphate (PI3P), a phospholipid synthesized primarily by class III PI 3-kinase Vps34. Here we report that disruption of neuronal Vps34 function in vitro and in vivo impairs autophagy, lysosomal degradation as well as lipid metabolism, causing endolysosomal membrane damage. PI3P deficiency also promotes secretion of unique exosomes enriched for undigested lysosomal substrates, including amyloid precursor protein C-terminal fragments (APP-CTFs), specific sphingolipids, and the phospholipid bis(monoacylglycero)phosphate (BMP), which normally resides in the internal vesicles of endolysosomes. Secretion of these exosomes requires neutral sphingomyelinase 2 and sphingolipid synthesis. Our results reveal a homeostatic response counteracting lysosomal dysfunction via secretion of atypical exosomes eliminating lysosomal waste and define exosomal APP-CTFs and BMP as candidate biomarkers for endolysosomal dysfunction associated with neurodegenerative disorders.Fan Wang for the kind gift of the Pi3kc3flox/flox mice. We thank Basant Abdulrahman and Hermann Schaetzl for providing the gene-edited Atg5 KO N2a cells. We are also grateful to Zhenyu Yue, Ralph Nixon, and Jean Gruenberg for the kind gift of anti-Atg14L, Cathepsin D, and BMP antibodies, respectively. We thank Thomas Südhof for sharing Cre recombinase lentiviruses. We thank the OCS Microscopy Core of New York University Langone Medical Center for the support of the EM work and Rocio Perez-Gonzalez and Efrat Levy of New York University for their support during optimization of the brain exosome isolation technique. We thank Elizabeta Micevska for the maintenance and genotyping of the animal colony and Bowen Zhou for the preliminary lipidomic analysis of conditional Pi3kc3 cKO mice. We also thank Rebecca Williams and Catherine Marquer for critically reading the manuscript. This work was supported by grants from the Fundação para a Ciência e Tecnologia (PD/BD/105915/2014 to A.M.M.); the National Institute of Health (R01 NS056049 to G.D.P., transferred to Ron Liem, Columbia University; T32-MH015174 to Rene Hen (Z.M.L.)). Z.M.L. and R.B.C. received pilot grants from ADRC grant P50 AG008702 to S.A.S.info:eu-repo/semantics/publishedVersio

Evaluation of the H.264 scalable video coding in error prone IP networks

The Joint Video Team, composed by the ISO/IEC Moving Picture Experts Group (MPEG) and the ITU-T Video Coding Experts Group (VCEG), has standardized a scalable extension of the H.264/AVC video coding standard called Scalable Video Coding (SVC). H.264/SVC provides scalable video streams which are composed by a base layer and one or more enhancement layers. Enhancement layers may improve the temporal, the spatial or the signal-to-noise ratio resolutions of the content represented by the lower layers. One of the applications, of this standard is related to video transmission in both wired and wireless communication systems, and it is therefore important to analyze in which way packet losses contribute to the degradation of quality, and which mechanisms could be used to improve that quality. This paper provides an analysis and evaluation of H.264/SVC in error prone environments, quantifying the degradation caused by packet losses in the decoded video. It also proposes and analyzes the consequences of QoS-based discarding of packets through different marking solutions