641 research outputs found

    Fluorescent Labeling, Co-Tracking, and Quantification of RNA In Cellulo.

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    RNA plays a fundamental, pervasive role in cellular physiology, through the maintenance and controlled readout of all genetic information, a functional landscape we are only beginning to understand. In particular, the cellular mechanisms for the spatiotemporal control of the plethora of RNAs are still poorly understood. Intracellular single-molecule fluorescence microscopy provides a powerful emerging tool for probing the pertinent biophysical and biochemical parameters that govern cellular RNA functions, including those of protein-encoding mRNAs. Yet progress has been hampered by the scarcity of high-yield, efficient methods to fluorescently label RNA molecules without the need to drastically increase their molecular weight through artificial appendages that may result in altered behavior. Herein, we employ a series of in vitro enzymatic techniques to efficiently, extensively and in high-yield, incorporate chemically modified nucleoside triphosphates into a transcribed messenger RNA body, between its body and tail (BBT), or randomly throughout the poly(A) tail (tail). Of these, BBT and tail modified strategies proved the most promising methods to functionally label messenger RNA and single-particle track their behaviors using our in-house single-molecule assay: intracellular single-molecule high resolution localization and counting (iSHiRLoC). From this research also was spawned a novel method to anchor an RNA to the actin cytoskeleton for the study of long-term interactions within a cellular context, termed: Gene-Actin Tethered Intracellular Co-tracking Assay (GATICA). Here, biotinylated RNA is tethered to the actin surface, either through complexation with a streptavidin coupled to a biotinylated phalloidin molecule or actin protein. Taken together, this body of work represents strategies for the labeling and visualizing, both freely diffusing and actin tethered, long-RNAs and their interactome in real-time.PHDChemical BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135832/1/tcuster_1.pd

    Speeding up Adaboost object detection with motion segmentation and Haar feature acceleration

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    A key challenge in a surveillance system is the object detection task. Object detection in general is a non-trivial problem. A sub-problem within the broader context of object detection which many researchers focus on is face detection. Numerous techniques have been proposed for face detection. One of the better performing algorithms is proposed by Viola et. al. This algorithm is based on Adaboost and uses Haar features to detect objects. The main reason for its popularity is very low false positive rates and the fact that the classifier network can be trained for any detection task. The use of Haar basis functions to represent key object features is the key to its success. The basis functions are organized as a network to form a strong classifier. To detect objects, this technique divides each input image into non-overlapping sub-windows and the strong classifier is applied to each sub-window to detect the presence of an object. The process is repeated at multiple scales of the input image to detect objects of various sizes. In this thesis we propose an object detection system that uses object segmentation as a preprocessing step. We use Mixture of Gaussians (MoG) proposed by Staffer et. al. for object segmentation. One key advantage with using segmentation to extract image regions of interest is that it reduces the number of search windows sent to detection task, thereby reducing the computational complexity and the execution time. Moreover, owing to the computational complexity of both the segmentation and detection algorithms we used in the system, we propose hardware architectures for accelerating key computationally intensive blocks. In this thesis we propose hardware architecture for MoG and also for a key compute intensive block within the adaboost algorithm corresponding to the Haar feature computation

    Hardware dedicado para sistemas empotrados de visión

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    La constante evolución de las Tecnologías de la Información y las Comunicaciones no solo ha permitido que más de la mitad de la población mundial esté actualmente interconectada a través de Internet, sino que ha sido el caldo de cultivo en el que han surgido nuevos paradigmas, como el ‘Internet de las cosas’ (IoT) o la ‘Inteligencia ambiental’ (AmI), que plantean la necesidad de interconectar objetos con distintas funcionalidades para lograr un entorno digital, sensible y adaptativo, que proporcione servicios de muy distinta índole a sus usuarios. La consecución de este entorno requiere el desarrollo de dispositivos electrónicos de bajo coste que, con tamaño y peso reducido, sean capaces de interactuar con el medio que los rodea, operar con máxima autonomía y proporcionar un elevado nivel de inteligencia. La funcionalidad de muchos de estos dispositivos incluirá la capacidad para adquirir, procesar y transmitir imágenes, extrayendo, interpretando o modificando la información visual que resulte de interés para una determinada aplicación. En el marco de este desafío surge la presente Tesis Doctoral, cuyo eje central es el desarrollo de hardware dedicado para la implementación de algoritmos de procesamiento de imágenes y secuencias de vídeo usados en sistemas empotrados de visión. El trabajo persigue una doble finalidad. Por una parte, la búsqueda de soluciones que, por sus prestaciones y rendimiento, puedan ser incorporadas en sistemas que satisfagan las estrictas exigencias de funcionalidad, tamaño, consumo de energía y velocidad de operación demandadas por las nuevas aplicaciones. Por otra, el diseño de una serie de bloques funcionales implementados como módulos de propiedad intelectual, que permitan aliviar la carga computacional de las unidades de procesado de los sistemas en los que se integren. En la Tesis se proponen soluciones específicas para la implementación de dos tipos de operaciones habitualmente presentes en muchos sistemas de visión artificial: la sustracción de fondo y el etiquetado de componentes conexos. Las distintas alternativas surgen como consecuencia de aplicar una adecuada relación de compromiso entre funcionalidad y coste, entendiendo este último criterio en términos de recursos de cómputo, velocidad de operación y potencia consumida, lo que permite cubrir un amplio espectro de aplicaciones. En algunas de las soluciones propuestas se han utilizado además, técnicas de inferencia basadas en Lógica Difusa con idea de mejorar la calidad de los sistemas de visión resultantes. Para la realización de los diferentes bloques funcionales se ha seguido una metodología de diseño basada en modelos, que ha permitido la realización de todo el ciclo de desarrollo en un único entorno de trabajo. Dicho entorno combina herramientas informáticas que facilitan las etapas de codificación algorítmica, diseño de circuitos, implementación física y verificación funcional y temporal de las distintas alternativas, acelerando con ello todas las fases del flujo de diseño y posibilitando una exploración más eficiente del espacio de posibles soluciones. Asimismo, con el objetivo de demostrar la funcionalidad de las distintas aportaciones de esta Tesis Doctoral, algunas de las soluciones propuestas han sido integradas en sistemas de vídeo reales, que emplean buses estándares de uso común. Los dispositivos seleccionados para llevar a cabo estos demostradores han sido FPGAs y SoPCs de Xilinx, ya que sus excelentes propiedades para el prototipado y la construcción de sistemas que combinan componentes software y hardware, los convierten en candidatos ideales para dar soporte a la implementación de este tipo de sistemas.The continuous evolution of the Information and Communication Technologies (ICT), not only has allowed more than half of the global population to be currently interconnected through Internet, but it has also been the breeding ground for new paradigms such as Internet of Things (ioT) or Ambient Intelligence (AmI). These paradigms expose the need of interconnecting elements with different functionalities in order to achieve a digital, sensitive, adaptive and responsive environment that provides services of distinct nature to the users. The development of low cost devices, with small size, light weight and a high level of autonomy, processing power and ability for interaction is required to obtain this environment. Attending to this last feature, many of these devices will include the capacity to acquire, process and transmit images, extracting, interpreting and modifying the visual information that could be of interest for a certain application. This PhD Thesis, focused on the development of dedicated hardware for the implementation of image and video processing algorithms used in embedded systems, attempts to response to this challenge. The work has a two-fold purpose: on one hand, the search of solutions that, for its performance and properties, could be integrated on systems with strict requirements of functionality, size, power consumption and speed of operation; on the other hand, the design of a set of blocks that, packaged and implemented as IP-modules, allow to alleviate the computational load of the processing units of the systems where they could be integrated. In this Thesis, specific solutions for the implementation of two kinds of usual operations in many computer vision systems are provided. These operations are background subtraction and connected component labelling. Different solutions are created as the result of applying a good performance/cost trade-off (approaching this last criteria in terms of area, speed and consumed power), able to cover a wide range of applications. Inference techniques based on Fuzzy Logic have been applied to some of the proposed solutions in order to improve the quality of the resulting systems. To obtain the mentioned solutions, a model based-design methodology has been applied. This fact has allowed us to carry out all the design flow from a single work environment. That environment combines CAD tools that facilitate the stages of code programming, circuit design, physical implementation and functional and temporal verification of the different algorithms, thus accelerating the overall processes and making it possible to explore the space of solutions. Moreover, aiming to demonstrate the functionality of this PhD Thesis’s contributions, some of the proposed solutions have been integrated on real video systems that employ common and standard buses. The devices selected to perform these demonstrators have been FPGA and SoPCs (manufactured by Xilinx) since, due to their excellent properties for prototyping and creating systems that combine software and hardware components, they are ideal to develop these applications

    A Future for Integrated Diagnostic Helping

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    International audienceMedical systems used for exploration or diagnostic helping impose high applicative constraints such as real time image acquisition and displaying. A large part of computing requirement of these systems is devoted to image processing. This chapter provides clues to transfer consumers computing architecture approaches to the benefit of medical applications. The goal is to obtain fully integrated devices from diagnostic helping to autonomous lab on chip while taking into account medical domain specific constraints.This expertise is structured as follows: the first part analyzes vision based medical applications in order to extract essentials processing blocks and to show the similarities between consumer’s and medical vision based applications. The second part is devoted to the determination of elementary operators which are mostly needed in both domains. Computing capacities that are required by these operators and applications are compared to the state-of-the-art architectures in order to define an efficient algorithm-architecture adequation. Finally this part demonstrates that it's possible to use highly constrained computing architectures designed for consumers handled devices in application to medical domain. This is based on the example of a high definition (HD) video processing architecture designed to be integrated into smart phone or highly embedded components. This expertise paves the way for the industrialisation of intergraded autonomous diagnostichelping devices, by showing the feasibility of such systems. Their future use would also free the medical staff from many logistical constraints due the deployment of today’s cumbersome systems

    Characterization of cell uptake and intracellular trafficking of exosomes by quantitative live cell imaging: towards biomimetic delivery vehicles of therapeutic RNA

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    Exosomes are biological nanoparticles which play a role in long distance cell-to cell communication. These 40-100 nm sized vesicles are released by virtually all cells and derive from the multivesicular bodies within their parent cells. They modulate their target cell fate by induction of cell signaling as well as RNA and protein cargo transfer. Exosomes have also moved into the spotlight of clinical research, with potential use as biomarkers or next generation therapeutic delivery agents. Exosomes are thought to be highly efficient intercellular messengers but quantitative characterization is lacking. Also, their routes of cell uptake and subcellular fate within recipient cells remain elusive. This work introduces an in depth and quantitative characterization of exosome cargo, physicochemical properties, labeling, isolation and their recipient cell interaction at the single cell – single vesicle level. Basic protocols for exosome purification were revisited in order to allow for isolation of exosomes with sufficient yields and in as native state as possible to enable functional studies. Since exosome integrity and recovery yields after differential ultracentrifugation (UC), the most commonly used protocol for exosome isolation, turned out to be poor and unreproducible, we describe an alternative protocol based on ultrafiltration (UF) with subsequent gel filtration (GF) for recovering exosomes relatively selectively, with intact biophysical and functional properties and significantly higher yields. Next we establish methods for specific exosome labeling using fluorescent marker proteins transiently expressed in parent cells, which led to a focus on FP tagged CD63 constructs. CD63-emGFP labeled exosomes were extensively characterized and showed identical properties compared to unlabeled exosomes based on sucrose density gradient, CryoTEM microscopy and proteomics analysis. Furthermore, we successfully adapted fluctuation correlation spectroscopy for characterization of fluorescently labeled exosomes. In another part of this work we describe a high content screen for exosome uptake which we use to provide a first systematic and quantitative profiling of exosome uptake across a panel of exosome parent recipient cells, including HEK293, Huh7, B16F10 as parental cells and additional primary fibroblasts, primary keratinocytes, iPS derived motor neurons and HUVEC primary human endothelial cells as recipient cell lines. These quantitative profiling data reveals preferences in exosome internalization by different cell types and suggests that specific receptor ligand interactions may determine tissue specificity. Finally, we address one of the fundamental questions in the field of cellular communication: how exosomes released by one cell enter and interact with their recipient cell. Our data quantifies for the first time the cell uptake dynamics of exosomes at the single vesicle and single cell level and reveals a quantitative efficiency paralleling that of infective pathogens rather than artificial delivery vehicles. We demonstrate that exosome uptake is largely mediated by active recruitment and surfing on filopodia to reach endocytic hotspots for their internalization at the filopodia base. This provides a cell biological explanation for the remarkably high efficiency of exosomes in targeting recipient cells and discovers a new parallel to some viruses and other pathogens. We propose that the process of filopodia surfing may have evolved as a highway for exosomes into the cell, being hijacked by certain pathogens for host cell interaction. This data does not support the previously reported exosome uptake by vesicle fusion with the plasma membrane or cargo release by endosomal escape. Instead we observe intact exosome uptake to enter endocytic vesicles, which then scan along the endoplasmic reticulum (ER) and end up in lysosomes. Our data suggest a model of controlled cargo delivery to defined subcellular localizations like the ER, rather than vesicle fusion and free release into the cytoplasm

    Developing preclinical devices for neuroscience research in the fields of animal tracking, fMRI acquisition, and 3D histology cutting

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    [ES] La neurociencia es un campo que abarca muchas especialidades. El objetivo de esta tesis es subsanar algunas carencias tecnológicas que existen en los métodos actuales de experimentación animal en neurociencia. En esta tesis, se presentan seis proyectos, que tendrán como objetivo mejorar el "Principio de las tres R", el cual fue enunciado por los biólogos ingleses W. M. S. Russell y R. L. Burch, durante la experimentación animal. El comportamiento es uno de los aspectos más importantes de la vida animal. Depende de los vínculos entre los animales, sus sistemas nerviosos y sus entornos. Para estudiar el comportamiento de los animales de laboratorio, se necesitan varias herramientas, pero una herramienta de seguimiento es esencial para llevar a cabo un estudio de comportamiento exhaustivo. Varias herramientas de seguimiento visual están actualmente disponibles. Sin embargo, todas tienen algunos inconvenientes. Por ejemplo, en una situación en la que un animal está dentro de una madriguera o cerca de otros animales, las cámaras de rastreo (tracking) no siempre pueden detectar la ubicación precisa o el movimiento del animal. Por esta razón, los entornos enriquecidos para intentar recrear el hábitat natural de los animales en experimentación no pueden utilizarse, ya que los datos recopilados son insuficientes/inexactos. Con la finalidad de mejorar los experimentos de tracking RFID Assisted Tracking Tile (RATT) es presentado en esta tesis. RATT es un sistema de seguimiento basado en tecnología de identificación pasiva de radiofrecuencia (RFID) y está compuesto por baldosas electrónicas con las que se puede construir una gran superficie, sobre la cual los animales pueden moverse libremente. Esto permite la identificación más precisa de los animales, así como el seguimiento de sus movimientos. Este sistema, que también se puede combinar con un sistema de seguimiento con cámaras, allana el camino para estudios completos de comportamiento en entornos enriquecidos. Dada la capacidad de rastrear animales y, por lo tanto, realizar experimentos de comportamiento exhaustivos, es posible observar cómo se comportan los sujetos desde un punto de vista externo. Sin embargo, si queremos comprender lo que sucede en el cerebro de estos sujetos, es necesario aplicar otras técnicas de análisis, por ejemplo, el estudio de señales dependientes del nivel de oxígeno en la sangre (BOLD, por sus siglas en inglés). Las señales BOLD se basan en las respuestas vasculares a la activación neuronal y se utilizan ampliamente en estudios de investigación clínicos y preclínicos. En entornos preclínicos, los animales suelen ser anestesiados. Sin embargo, los anestésicos causan cambios en la fisiología de los animales, p. Ej. hipotermia, y esto tiene el potencial de alterar las señales funcionales de MRI (fMRI). Para evitar la hipotermia en roedores anestesiados, se presenta TherMouseDuino. Este es un sistema de control automático de temperatura de código abierto, que reduce las fluctuaciones de la temperatura, lo que proporciona condiciones sólidas para realizar experimentos de resonancia magnética funcional. En los cursos de biología y neurociencia, la anatomía del cerebro se enseña generalmente utilizando imágenes de resonancia magnética (IRM) o secciones histológicas de diferentes planos. Estos muestran las áreas macroscópicas más importantes en el cerebro de un animal. Sin embargo, este método no es dinámico ni intuitivo. En esta tesis se presenta un cerebro de rata impreso en 3D con fines educativos. La manipulación manual de la estructura, facilitada por la ampliación de sus dimensiones, junto con la capacidad de desmontar el "cerebro" en algunas de sus partes principales, facilita la comprensión de la organización 3D del sistema nervioso. Este es un método alternativo y mejorado para enseñar a los estudiantes en general y a los biólogos, en particular, la anatomía del cerebro de rata.[CA] La neurociència és un camp que abasta moltes especialitats. L'objectiu d'aquesta tesi és esmenar algunes manques tecnològiques que existeixen en els mètodes actuals d'experimentació animal en neurociència. En aquesta tesi, es presenten sis projectes, que tindran com a objectiu millorar el "Principi de les tres R", el qual va ser enunciat pels biòlegs anglesos W. M. S. Russell i R. L. Burch, durant l'experimentació animal. El comportament és un dels aspectes m'és importants de la vida animal. Depèn dels vincles entre els animals, els seus sistemes nerviosos i els seus entorns. Per estudiar el comportament dels animals de laboratori, es necessiten diverses eines, però` una eina de seguiment és essencial per a dur a terme un estudi de comportament exhaustiu. Diverses eines de seguiment visual estan actualment disponibles. No obstant això, totes tenen alguns inconvenients. Per exemple, en una situació en la qual un animal esta` dins d'un cau o prop d'altres animals, les cambres de rastreig (tracking) no sempre poden detectar la ubicació precisa o el moviment de l'animal. Per aquesta raó, els entorns enriquits per a intentar recrear l'hàbitat natural dels animals en experimentació no poden utilitzar-se, ja que les dades recopilades són insuficients/inexactes. Amb la finalitat de millorar els experiments de tracking/seguiment RFID Assisted Tracking Tile (RATT) és presentat en aquesta tesi. RATT es un sistema de seguiment basat en tecnologia d'identificació passiva de radiofreqüència (RFID) i esta` compost per rajoles electròniques amb les quals es pot construir una gran superfície, sobre la qual els animals poden moures lliurement. Això permet la identificació més precisa dels animals, així com el seguiment dels seus moviments. Aquest sistema, que també es pot combinar amb un sistema de seguiment amb cambres, aplana el camí per a estudis complets de comportament en entorns enriquits. Donada la capacitat de rastrejar animals i, per tant, realitzar experiments de comportament exhaustius, és possible observar com es comporten els subjectes des d'un punt de vista extern. No obstant això, si volem comprendre el que succeeix en el cervell d'aquests subjectes, és necessari aplicar altres tècniques d'anàlisis, per exemple, l'estudi de senyals dependents del nivell d'oxigen en la sang (BOLD, per les seues sigles en anglès). Els senyals BOLD es basen en les respostes vasculars a l'activació neuronal i s'utilitzen àmpliament en estudis d'investigació clínics i preclínics. En entorns preclínics, els animals solen ser anestesiats. No obstant això, els anestèsics causen canvis en la fisiologia de els animals, per exemple hipotèrmia, i això te el potencial d'alterar els senyals funcionals de MRI (fMRI). Per a evitar la hipotèrmia en rosegadors anestesiats, es presenta TherMouseDuino. Aquest és un sistema de control automàtic de temperatura de codi obert, que redueix les fluctuacions de la temperatura, la qual cosa proporciona condicions solides per a realitzar experiments de ressonància magnètica funcional. En els cursos de biologia i neurociència, l'anatomia del cervell s'ensenya generalment utilitzant imatges de ressonància magnètica (IRM) o seccions histològiques de diferents plans. Aquests mostren les àrees macroscòpiques més importants en el cervell de un animal. No obstant això, aquest mètode no és dinàmic ni intuïtiu. En aquesta tesi es presenta un cervell de rata imprès en 3D amb finalitats educatius. La manipulació manual de l'estructura, facilitada per l'ampliació de les seues dimensions, juntament amb la capacitat de desmuntar el "cervell" en algunes de les seues parts principals, facilita la comprensió de l'organització 3D del sistema nerviós. Aquest és un mètode alternatiu i millorat per a ensenyar a els estudiants en general i als biòlegs, en particular, l'anatomia del cervell de rata.[EN] Neuroscience is a field that covers many specialties. The objective of this thesis is to correct some technological deficiencies that exist in current methods of animal experimentation in neuroscience. In this thesis, six projects are presented, which will aim to improve the "Principle of the three Rs" in animal experimentation enunciated by the English biologists W. M. S. Russell and R. L. Burch. In the present era of impressive progress in neuroscience, it is still not arguable that a complete understanding of the brain cannot be possible without a comparable understanding of animal behavior. In order to study the behavior of laboratory animals, various tools are needed, being a reliable tracking system one of the most important to follow large populations of individual subjects that interact in complex manners. Several visual tracking tools are currently available. However, they all have some drawbacks. For example, in a situation where an animal is inside a cave, or is in close proximity to other animals, tracking cameras cannot always detect the precise location or movement of the animal. For this reason, environments that have been enriched in order to attempt to recreate the natural habitat of the animals under experiment, cannot be used, as the data gathered is insufficient/inaccurate. In order to improve the current tracking systems , the RATT is presented. RATT is a tracking system based on passive RFID technology and it is composed of electronic tiles. Using several tiles, a large surface area, on which the animals can move freely, can be built. This enables the more accurate identification of the animals, as well as the tracking of their movements. This system, which can also be combined with a visual tracking system, paves the way for complete behavioral studies in enriched environments. Given the ability to track animals and thus conduct thorough behavioral experiments, it is possible to observe how the subjects behave from an external viewpoint. However, if we want to understand what is going on in the brains of these subjects, it is necessary to apply other analysis techniques, for example the study of BOLD signals. BOLD signals are based on vascular responses to neuronal activation and are used extensively in clinical and preclinical research studies. In preclinical settings, animals are usually anesthetized. However, anesthetics cause changes in the physiology of the animals, e.g. hypothermia, and this has the potential to disrupt fMRI signals. In order to avoid hypothermia in anesthetized rodents, TherMouseDuino is presented. This is an Open-Source automatic temperature control system, which reduces temperature fluctuations, thus providing robust conditions in which to perform fMRI experiments. In biology and neuroscience courses, brain anatomy is generally taught using MRI or histological sections of different planes. These show the most important macroscopic areas in an animals' brain. However, this method is neither dynamic nor intuitive. An anatomical 3D printed rat brain with educative purposes is presented in this thesis. Hand manipulation of the structure, facilitated by the scaling up of its dimensions, together with the ability to dismantle the "brain" into some of main its constituent parts, facilitates the understanding of the 3D organization of the nervous system. This is an alternative and improved method for teaching students in general and biologists, in particular, the rat brain anatomy.This work was supported in part by the Spanish Ministerio de Economía y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-2-R (D.M.) and BFU2015-64380-C2-1-R, by EU Horizon 2020 Program 668863-SyBil-AA grant (S.C.). S.C. acknowledges financial support from the Spanish State Research Agency, through the “Severo Ochoa” Programme for Centres of Excellence in R&D (ref. SEV-2013-0317) and by a grant “Ayudas para la formación de personal investigador (FPI)” from the Vicerrectorado de Investigación, Innovación y Transferencia of the Universitat Politècnica de València.Quiñones Colomer, DR. (2019). Developing preclinical devices for neuroscience research in the fields of animal tracking, fMRI acquisition, and 3D histology cutting [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/118795TESI

    Methods and techniques for analyzing human factors facets on drivers

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    Mención Internacional en el título de doctorWith millions of cars moving daily, driving is the most performed activity worldwide. Unfortunately, according to the World Health Organization (WHO), every year, around 1.35 million people worldwide die from road traffic accidents and, in addition, between 20 and 50 million people are injured, placing road traffic accidents as the second leading cause of death among people between the ages of 5 and 29. According to WHO, human errors, such as speeding, driving under the influence of drugs, fatigue, or distractions at the wheel, are the underlying cause of most road accidents. Global reports on road safety such as "Road safety in the European Union. Trends, statistics, and main challenges" prepared by the European Commission in 2018 presented a statistical analysis that related road accident mortality rates and periods segmented by hours and days of the week. This report revealed that the highest incidence of mortality occurs regularly in the afternoons during working days, coinciding with the period when the volume of traffic increases and when any human error is much more likely to cause a traffic accident. Accordingly, mitigating human errors in driving is a challenge, and there is currently a growing trend in the proposal for technological solutions intended to integrate driver information into advanced driving systems to improve driver performance and ergonomics. The study of human factors in the field of driving is a multidisciplinary field in which several areas of knowledge converge, among which stand out psychology, physiology, instrumentation, signal treatment, machine learning, the integration of information and communication technologies (ICTs), and the design of human-machine communication interfaces. The main objective of this thesis is to exploit knowledge related to the different facets of human factors in the field of driving. Specific objectives include identifying tasks related to driving, the detection of unfavorable cognitive states in the driver, such as stress, and, transversely, the proposal for an architecture for the integration and coordination of driver monitoring systems with other active safety systems. It should be noted that the specific objectives address the critical aspects in each of the issues to be addressed. Identifying driving-related tasks is one of the primary aspects of the conceptual framework of driver modeling. Identifying maneuvers that a driver performs requires training beforehand a model with examples of each maneuver to be identified. To this end, a methodology was established to form a data set in which a relationship is established between the handling of the driving controls (steering wheel, pedals, gear lever, and turn indicators) and a series of adequately identified maneuvers. This methodology consisted of designing different driving scenarios in a realistic driving simulator for each type of maneuver, including stop, overtaking, turns, and specific maneuvers such as U-turn and three-point turn. From the perspective of detecting unfavorable cognitive states in the driver, stress can damage cognitive faculties, causing failures in the decision-making process. Physiological signals such as measurements derived from the heart rhythm or the change of electrical properties of the skin are reliable indicators when assessing whether a person is going through an episode of acute stress. However, the detection of stress patterns is still an open problem. Despite advances in sensor design for the non-invasive collection of physiological signals, certain factors prevent reaching models capable of detecting stress patterns in any subject. This thesis addresses two aspects of stress detection: the collection of physiological values during stress elicitation through laboratory techniques such as the Stroop effect and driving tests; and the detection of stress by designing a process flow based on unsupervised learning techniques, delving into the problems associated with the variability of intra- and inter-individual physiological measures that prevent the achievement of generalist models. Finally, in addition to developing models that address the different aspects of monitoring, the orchestration of monitoring systems and active safety systems is a transversal and essential aspect in improving safety, ergonomics, and driving experience. Both from the perspective of integration into test platforms and integration into final systems, the problem of deploying multiple active safety systems lies in the adoption of monolithic models where the system-specific functionality is run in isolation, without considering aspects such as cooperation and interoperability with other safety systems. This thesis addresses the problem of the development of more complex systems where monitoring systems condition the operability of multiple active safety systems. To this end, a mediation architecture is proposed to coordinate the reception and delivery of data flows generated by the various systems involved, including external sensors (lasers, external cameras), cabin sensors (cameras, smartwatches), detection models, deliberative models, delivery systems and machine-human communication interfaces. Ontology-based data modeling plays a crucial role in structuring all this information and consolidating the semantic representation of the driving scene, thus allowing the development of models based on data fusion.I would like to thank the Ministry of Economy and Competitiveness for granting me the predoctoral fellowship BES-2016-078143 corresponding to the project TRA2015-63708-R, which provided me the opportunity of conducting all my Ph. D activities, including completing an international internship.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: José María Armingol Moreno.- Secretario: Felipe Jiménez Alonso.- Vocal: Luis Mart

    Histone Deacetylase 8 Is Required for Centrosome Cohesion and Influenza A Virus Entry

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    Influenza A virus (IAV) enters host cells by endocytosis followed by acid-activated penetration from late endosomes (LEs). Using siRNA silencing, we found that histone deacetylase 8 (HDAC8), a cytoplasmic enzyme, efficiently promoted productive entry of IAV into tissue culture cells, whereas HDAC1 suppressed it. HDAC8 enhanced endocytosis, acidification, and penetration of the incoming virus. In contrast, HDAC1 inhibited acidification and penetration. The effects were connected with dramatic alterations in the organization of the microtubule system, and, as a consequence, a change in the behavior of LEs and lysosomes (LYs). Depletion of HDAC8 caused loss of centrosome-associated microtubules and loss of directed centripetal movement of LEs, dispersing LE/LYs to the cell periphery. For HDAC1, the picture was the opposite. To explain these changes, centrosome cohesion emerged as the critical factor. Depletion of HDAC8 caused centrosome splitting, which could also be induced by depleting a centriole-linker protein, rootletin. In both cases, IAV infection was inhibited. HDAC1 depletion reduced the splitting of centrosomes, and enhanced infection. The longer the distance between centrosomes, the lower the level of infection. HDAC8 depletion was also found to inhibit infection of Uukuniemi virus (a bunyavirus) suggesting common requirements among late penetrating enveloped viruses. The results established class I HDACs as powerful regulators of microtubule organization, centrosome function, endosome maturation, and infection by IAV and other late penetrating viruses
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