Academic literature on the topic 'Disease propagation'

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Journal articles on the topic "Disease propagation"

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Nagaprasad, S., T. Pushpalatha, and S. Naga Lakshmi. "Heart Disease Prediction Propagation approach." International Journal of Machine Learning and Networked Collaborative Engineering 4, no. 2 (October 24, 2020): 72–77. http://dx.doi.org/10.30991/ijmlnce.2020v04i02.003.

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Brightman, B. K., Q. X. Li, D. J. Trepp, and H. Fan. "Differential disease restriction of Moloney and Friend murine leukemia viruses by the mouse Rmcf gene is governed by the viral long terminal repeat." Journal of Experimental Medicine 174, no. 2 (August 1, 1991): 389–96. http://dx.doi.org/10.1084/jem.174.2.389.

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Neonatal CxD2 (Rmcfr) and Balb/c (Rmcfs) mice inoculated with Moloney murine leukemia virus (M-MuLV) exhibited approximately equivalent time course and pathology for disease. CxD2 mice showed only slightly reduced presence of Moloney mink cell focus-forming virus (M-MCF) provirus as seen by Southern blot analysis compared to Balb/c mice. This lack of restriction for disease and spread of MCF was in sharp contrast to that seen for CxD2 mice inoculated with Friend murine leukemia virus (F-MuLV), where incidence of disease and propagation of MCFs were severely restricted, as previously reported. Inoculation of CxD2 mice with FM-MuLV, a recombinant F-MuLV virus containing M-MuLV LTR sequences (U3 and R), resulted in T cell disease of time course equal to that seen in Balb/c mice; there also was little restriction for propagation of MCFs. This indicated that presence of the M-MuLV long terminal repeat (LTR) was sufficient for propagation of MCFs in CxD2 mice. Differing restriction for F-MuLV vs. M-MuLV in CxD2 mice was explained on the basis of different "MCF propagator cells" for the two viruses. It was suggested that cells propagating F-MCF (e.g., erythroid progenitors) are blocked by endogenous MCF-like gp70env protein, whereas cells propagating M-MCF (e.g., lymphoid) do not express this protein on their surface. F-MuLV disease in CxD2 mice was greatly accelerated when neonates were inoculated with a F-MuLV/F-MCF pseudotypic mixture. However, F-MCF provirus was not detectable or only barely detectable in F-MuLV/F-MCF-induced tumors, suggesting that F-MCF acted indirectly in induction of these tumors.
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Rajna, Zalán, Heli Mattila, Niko Huotari, Timo Tuovinen, Johanna Krüger, Sebastian C. Holst, Vesa Korhonen, et al. "Cardiovascular brain impulses in Alzheimer’s disease." Brain 144, no. 7 (March 31, 2021): 2214–26. http://dx.doi.org/10.1093/brain/awab144.

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Abstract Accumulation of amyloid-β is a key neuropathological feature in brain of Alzheimer’s disease patients. Alterations in cerebral haemodynamics, such as arterial impulse propagation driving the (peri)vascular CSF flux, predict future Alzheimer’s disease progression. We now present a non-invasive method to quantify the three-dimensional propagation of cardiovascular impulses in human brain using ultrafast 10 Hz magnetic resonance encephalography. This technique revealed spatio-temporal abnormalities in impulse propagation in Alzheimer’s disease. The arrival latency and propagation speed both differed in patients with Alzheimer’s disease. Our mapping of arterial territories revealed Alzheimer’s disease-specific modifications, including reversed impulse propagation around the hippocampi and in parietal cortical areas. The findings imply that pervasive abnormality in (peri)vascular CSF impulse propagation compromises vascular impulse propagation and subsequently glymphatic brain clearance of amyloid-β in Alzheimer’s disease.
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Wilson, Spencer, Abdullah Alabdulkarim, and David Goldsman. "Green Simulation of Pandemic Disease Propagation." Symmetry 11, no. 4 (April 22, 2019): 580. http://dx.doi.org/10.3390/sym11040580.

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This paper is concerned with the efficient stochastic simulation of multiple scenarios of an infectious disease as it propagates through a population. In particular, we propose a simple “green” method to speed up the simulation of disease transmission as we vary the probability of infection of the disease from scenario to scenario. After running a baseline scenario, we incrementally increase the probability of infection, and use the common random numbers variance reduction technique to avoid re-simulating certain events in the new scenario that would not otherwise have changed from the previous scenario. A set of Monte Carlo experiments illustrates the effectiveness of the procedure. We also propose various extensions of the method, including its use to estimate the sensitivity of propagation characteristics in response to small changes in the infection probability.
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Yates, Darran. "Propagation of disease pathology in PD." Nature Reviews Neurology 5, no. 10 (October 2009): 522. http://dx.doi.org/10.1038/nrneurol.2009.142.

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MAGDOŃ-MAKSYMOWICZ, M. S., A. Z. MAKSYMOWICZ, and J. GOŁDASZ. "SIMULATION OF MAD COW DISEASE PROPAGATION." International Journal of Modern Physics C 17, no. 02 (February 2006): 213–22. http://dx.doi.org/10.1142/s0129183106008935.

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Computer simulation of dynamic of BSE disease is presented. Both vertical (to baby) and horizontal (to neighbor) mechanisms of the disease spread are considered. The game takes place on a two-dimensional square lattice Nx×Ny = 1000×1000 with initial population randomly distributed on the net. The disease may be introduced either with the initial population or by a spontaneous development of BSE in an item, at a small frequency. Main results show a critical probability of the BSE transmission above which the disease is present in the population. This value is vulnerable to possible spatial clustering of the population and it also depends on the mechanism responsible for the disease onset, evolution and propagation. A threshold birth rate below which the population is extinct is seen. Above this threshold the population is disease free at equilibrium until another birth rate value is reached when the disease is present in population. For typical model parameters used for the simulation, which may correspond to the mad cow disease, we are close to the BSE-free case.
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Soto, Claudio, and Gabriela P. Saborı́o. "Prions: disease propagation and disease therapy by conformational transmission." Trends in Molecular Medicine 7, no. 3 (March 2001): 109–14. http://dx.doi.org/10.1016/s1471-4914(01)01931-1.

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Luk, Kelvin C., and Virginia M. Y. Lee. "Modeling Lewy pathology propagation in Parkinson's disease." Parkinsonism & Related Disorders 20 (January 2014): S85—S87. http://dx.doi.org/10.1016/s1353-8020(13)70022-1.

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Potterat, J. J., R. B. Rothenberg, and S. Q. Muth. "Network structural dynamics and infectious disease propagation." International Journal of STD & AIDS 10, no. 3 (March 1999): 182–85. http://dx.doi.org/10.1258/0956462991913853.

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Qian, Yu, Søren Besenbacher, Thomas Mailund, and Mikkel Heide Schierup. "Identifying disease associated genes by network propagation." BMC Systems Biology 8, Suppl 1 (2014): S6. http://dx.doi.org/10.1186/1752-0509-8-s1-s6.

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Dissertations / Theses on the topic "Disease propagation"

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Ferreira, Rodrigues Sara [Verfasser]. "Propagation of Tau pathology in Alzheimer disease / Sara Ferreira Rodrigues." Bonn : Universitäts- und Landesbibliothek Bonn, 2020. http://d-nb.info/121914049X/34.

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Canter, Rebecca Gail. "4D mapping of network-specific pathological propagation in Alzheimer's disease." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107868.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 113-132).
Alzheimer's disease (AD) causes a devastating loss of memory and cognition for which there is no cure. Without effective treatments that slow or reverse the course of the disease, the rapidly aging population will require astronomical investment from society to care for the increasing numbers of AD patients. Additionally, the financial and emotional burden on families of affected individuals will be profound. Traditional approaches to the study of AD use either biochemical assays to probe cellular pathophysiology or non-invasive imaging platforms to investigate brain-wide network alterations. Though decades of research using these tools have advanced the field significantly, our increased understanding of AD has not led to successful interventions. One reason for this impediment may be that the tools used in neither approach can achieve the spatial and temporal precision necessary to study the consequences of molecular insults across the brain over time. In this thesis, I capitalize on recent advances in tissue processing technologies to gain a network-level perspective on the molecular and cellular progression of AD. First, I present optimized methods for in situ proteomic phenotyping of large-volume tissue specimens. Then, I use the techniques to map amyloid-beta (A[beta]) aggregates at the whole-brain scale across disease stages in a mouse model of AD. The spatially-unbiased, temporally-precise map demonstrates hierarchical susceptibility of increasingly large, memory-related brain networks to A[beta] deposition. Importantly, the 4D nature of the map reveals that subcortical nodes and white matter tracts of the Papez memory circuit exhibit unique, early vulnerability to A[beta] aggregates. Finally, using large-volume labeling approaches, I confirm the molecular findings by showing disease-specific A[beta] aggregation in human samples from the early hub regions. Together, this data unites desperate observations of network-level deficits and identifies critical locations of early A[beta] deposition in the brain. By linking molecular and network observations, I begin to provide biological explanations for the clinical manifestation of AD. This perspective can guide earlier patient identification and refine experimental approaches to developing cognitively efficacious treatments. These discoveries emphasize the necessity of multi-level investigations in neuroscience research and highlight the potential impacts of tools that enable researchers to bridge the gap.
by Rebecca Gail Canter.
Ph. D.
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Elizabeth, Murphy A. "UTILIZING DROSOPHILA PRIMARY NEURONS TO STUDY HUMAN TAU PROPAGATION: AN IN VITRO MODEL OF ALZHEIMER'S DISEASE." Ohio University Honors Tutorial College / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ouhonors1524831015975217.

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Domert, Jakob. "Neuron-to-neuron propagation of neurodegenerative proteins; relation to degradative systems." Doctoral thesis, Linköpings universitet, Avdelningen för neuro- och inflammationsvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-134667.

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Alzheimer’s disease (AD) and Parkinson’s disease (PD) are defined by neurodegeneration and accumulations of misfolded proteins that spread through the brain in a well characterized manner. In AD these accumulations consist mainly of β-amyloid (Aβ) and tau, while in PD, α-synuclein (α-syn) make up the characteristic lewy pathology.     The general aim of this thesis was to investigate mechanisms associated with neurotoxic peptide activity by Aβ, tau and α-syn in relation to cellular degradation and transfer with a cell-to-cell transfer model system.    We found that intercellular transfer of oligomeric Aβ occurs independently of isoform. However, the amount of transfer correlates with each isoforms ability to resist degradation or cellular clearance. The Aβ1-42 isoform showed particular resistance to clearance, which resulted in higher levels of cell-to-cell transfer of the isoform and lysosomal stress caused by accumulation.    As Aβ accumulations can inhibit the proteasomal degradation we investigated how reduced proteasomal degradation affected neuron-like cells. We found increased levels of phosphorylated tau protein, disturbed microtubule stability and impaired neuritic transport after reduced proteasomal activity. These changes was partly linked to c-Jun and ERK 1/2 kinase activity.    We could also show that α-syn transferred from cell-to-cell in our model system, with a higher degree of transfer for the larger oligomer and fibrillar species. Similar to Aβ, α-syn mainly colocalized with lysosomes, before and after transfer.     Lastly, we have developed our cell-to-cell transfer system into a model suitable for high throughput screening (HTS). The type of cells have been upgraded from SH-SY5Y cells to induced pluripotent stem cells (iPSCs), with a differentiation profile more similar to mature neurons. The next step will be screening a small molecular library for substances with inhibitory effect on cell-to-cell transfer of Aβ peptides.     The importance of the degradative systems in maintaining protein homeostasis and prevent toxic accumulations in general is well known. Our findings shows the importance of these systems for neurodegenerative diseases and also highlight the link between degradation and cell-to-cell transfer. To restore or enhance the degradative systems would be an interesting avenue to treat neurodegenerative diseases. Another way would be to inhibit the transfer of misfolded protein aggregates. By using the HTS model we developed, a candidate substance with good inhibitory effect on transfer can hopefully be found.
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Davidson, Andrew Doran. "Fundamental Principles of Tremor Propagation in the Upper Limb." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6509.

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Although tremor is the most common movement disorder, there exist few effective tremor-suppressing devices, in part because the characteristics of tremor throughout the upper limb are unknown. To clarify, optimally suppressing tremor requires a knowledge of the mechanical origin, propagation, and distribution of tremor throughout the upper limb. Here we present the first systematic investigation of how tremor propagates between the shoulder, elbow, forearm, and wrist. We simulated tremor propagation using a linear, time-invariant, lumped-parameter musculoskeletal model relating joint torques and the resulting joint displacements. The model focused on the seven main degrees of freedom (DOF) from the shoulder to the wrist and included coupled joint inertia, damping, and stiffness. We deliberately implemented a simple model to focus first on the most basic effects. Simulating tremorogenic joint torque as a sinusoidal input, we used the model to establish fundamental principles describing how input parameters (torque location and frequency) and joint impedance (inertia, damping, and stiffness) affect tremor propagation. We expect that the methods and principles presented here will serve as the groundwork for future refining studies to understand the origin, propagation, and distribution of tremor throughout the upper limb in order to enable the future development of optimal tremor-suppressing devices.
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Kim, Louis Y. (Louis Yongchul). "Estimating network structure and propagation dynamics for an infectious disease : towards effective vaccine allocation." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91397.

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Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2014.
76
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 67-72).
In the event of a pandemic influenza outbreak, such as the 2009-2010 H1N1 "Swine Flu" episode, it is crucial to effectively allocate limited resources in order to minimize the casualties. Design of effective resource allocation strategies requires good understanding of the underlying contact network and of the propagation dynamics. In this thesis we develop a parameter estimation method that learns the network structure, among a family of graphs, and disease dynamics from the recorded infection curve, assuming that the disease dynamics follow an SIR process. We apply the method to data collected during the 2009-2010 H1N1 epidemic and show that the best-fit model, among a scale-free network and a small-world network, indicates the scale-free network. Given the knowledge of the network structure we evaluate different vaccination strategies. As a benchmark, we allow the vaccination decisions to depend on the state of the epidemic and we show that random vaccination (which is the current practice), does not efficiently halt the spread of influenza. Instead, we propose vaccine allocation strategies that exploit the underlying network structure and provide a reduction in the number of infections by over 6 times compared to the current practice. In addition, more realistic scenario involves random encounters between agents. To test this hypothesis, we introduced a dynamic network formation on top of the static network model. We apply the estimation method to the dynamic network model and show a small improvement in estimating the infection dynamics of the 2009-2010 H1N1 influenza.
by Louis Y. Kim.
S.M.
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Wann, Steven R. "In vitro isolation and propagation of mammatoxin-resistant aspen." Diss., Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/5742.

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Chen, Chien-Hung. "Optimization and decision strategies for medical preparedness and emergency response." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/52939.

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The public health emergencies, such as bioterrorist attacks or pandemic outbreaks, have gained serious public and government attentions since the 2001 anthrax attacks and the SARS outbreak in 2003. These events require large-scale and timely dispensing of critical medical countermeasures for protection of the general population. This thesis research focuses on developing mathematical models, real-time algorithms, and computerized decision support systems that enable (1) systematic coordination to tackle multifaceted nature of mass dispensing, (2) fast disease propagation module to allow immediate mitigation response to on-site uncertainties, and (3) user-friendly platform to facilitate modeling-solution integration and cross-domain collaboration. The work translates operations research methodologies into practical decision support tools for public health emergency professionals. Under the framework of modeling and optimizing the public health infrastructure for biological and pandemic emergency responses, the task first determines adequate number of point-of-dispensing sites (POD), by placing them strategically for best possible population coverage. Individual POD layout design and associated staffing can thus be optimized to maximize throughput and/or minimize resource requirement for an input throughput. Mass dispensing creates a large influx of individuals to dispensing facilities, thus raising the risk of high degree of intra-facility infections. Our work characterizes the interaction between POD operations and disease propagation. Specifically, fast genetic algorithm-based heuristics were developed for solving the integer-programming-based facility location instances. The approach has been applied to the metro-Atlanta area with a population of 5.2 million people spreading over 11 districts. Among the 2,904 instances, the state-of-the-art specialized integer programming solver solved all except one instance to optimality within 300,000 CPU seconds and solved all except 5 to optimality within 40,000 CPU seconds. Our fast heuristic algorithm returns good feasible solutions that are within 8 percent to optimality in 15 minutes. This algorithm was embedded within an interactive web-based decision support system, RealOpt-Regional©. The system allows public health users to contour the region of interest and determine the network of PODs for their affected population. Along with the fast optimization engine, the system features geographical, demographical, and spatial visualization that facilitate real-time usage. The client-server architecture facilities front-end user interactive design on Google Maps© while the facility location mathematical instances are generated and solved in the back-end server. In the analysis of disease propagation and mitigation strategies, we first extended the 6-stage ordinary differential equation-based (ODE) compartmental model to accommodate POD operations. This allows us to characterize the intra-facility infections of highly contagious diseases during local outbreak when large dispensing is in process. The disease propagation module was then implemented into the CDC-RealOpt-POD© discrete-event-simulation-optimization. CDC-RealOpt-POD is a widely used emergency response decision support system that includes simulation-optimization for determining optimal staffing and operations. We employed the CDC-RealOpt-POD environment to analyze the interactions between POD operations and disease parameters and identified effective mitigation strategies. The disease propagation module allows us to analyze the efficient frontier between operational efficiencies and intra-POD infections. Emergency response POD planners and epidemiologists can collaborate under the familiar CDC-RealOpt-POD environment, e.g., design the most efficient plan by designing and analyzing both POD operations and disease compartmental model in a unified platform. Corresponding problem instances are formed automatically by combining and transforming graphical inputs and numerical parameters from users. To facilitate the operations of receiving, staging and storage (RSS) of medical countermeasures, we expanded the CDC-RealOpt-POD layout design functions by integrating it with the process flow. The resulting RSS system allows modeling of both system processes along with spatial constraints for optimal operations and process design. In addition, agent-based simulation was incorporated inside where integrated process flow and layout design allow analysis of crowd movement and congestion. We developed the hybrid agent behavior where individual agents make decision through system-defined process flow and autonomous discretion. The system was applied successfully to determine guest movement strategies for the new Georgia Aquarium Dolphin Tales exhibit. The goal was to enhance guest experience while mitigating overall congestion.
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Gibb, Matthew Michael James. "Myocardial microstructure and its role in propagation dynamics." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:69a1a65e-9a71-422c-86e8-c347cfabf21a.

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Computational modelling and simulation, in close interaction with experiments, has provided invaluable insight into the biochemical, mechanical and electrophysiological function and dysfunction of the heart. However, limitations in imaging techniques and computing resources have precluded the analysis of tissue architecture near the cellular scale and the effect of this architecture on cardiac function. It is the wider aim of this thesis to develop a framework to characterise cardiac microstructure and to investigate the role of microstructure in cardiac propagation dynamics and arrhythmogenesis. An initial modelling study elucidates the effect of blood vessels in sustaining arrhythmic episodes, and how the accurate modelling of fibre direction in the vicinity of the vessels mitigates this detrimental mechanism. A mathematical model of fibre orientation in a simple geometry around blood vessels has been developed, based on information obtained from highly detailed histological and MRI datasets. A simulation regime was chosen, guided by the vasculature extracted from whole heart MRI images, to analyse ventricular wavefront propagation for different orientations and positions of blood vessels. Our results demonstrate not only that the presence of the blood vessels encourages curvature in the activation wavefront around the blood vessels, but further that vessels act to restrict and prolong phase singularities. When compared to a more simplistic implementation of fibre orientation, the model is shown to weaken wavefront curvature and reduce phase singularity anchoring. Having established the importance of microstructural detail in computational models, it seems expedient to generate accurate data in this regard. An automated registration toolchain is developed to reconstruct histological slices based on coherent block face volumes, in order to present the first 3-D sub-cellular resolution images of cardiac tissue. Although mesoscopic geometry is faithfully reproduced throughout much of the dataset, low levels of transformational noise obfuscate tissue microstructure. These distortions are all but eradicated by a novel transformational diffusion algorithm, with characteristics that outperform any previous method in the literature in this domain, with respect to robustness, conservation of geometry and extent of information transfer. Progress is made towards extracting microstructural models from the resultant histological volumes, with a view to incorporating this detail into simulations and yielding a deeper understanding of the role of microstructure in arrhythmia.
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Eusebio, A. "Mechanisms and consequences of beta oscillatory activity propagation in the basal ganglia-cortical network in Parkinson's disease." Thesis, University College London (University of London), 2012. http://discovery.ucl.ac.uk/1356885/.

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Excessive neural synchronisation in the beta frequency band (10-35 Hz) is a hallmark of Parkinson’s disease (PD) but the mechanisms underlying the generation and propagation of such oscillatory activity and its links with movement impairment remain partly unclear. Patients receiving deep brain stimulation of the subthalamic nucleus (STN DBS) provide a unique opportunity to address these issues by either recording the neuronal activity from the implanted electrodes or driving the network to study the behavioural and neurophysiological effects of stimulation. The studies outlined in this thesis bring further understanding into the mechanisms by which beta oscillations pervade every level of the basal ganglia – cortical network, how they impair movement and how they are modified by the usual treatments of PD such as dopamine or STN DBS. We performed a series of experiments involving PD patients either in the post-operative phase of DBS or chronically stimulated, and in an animal model of PD to study the effect of beta frequency STN stimulation on movement, the effect of high frequency STN stimulation on beta oscillations and the network properties underlying its vulnerability to beta frequencies. The findings of these studies suggest the existence of anatomically segregated subthalamo-cortical networks, with specific properties and susceptibility to resonate variably impaired in PD patients. We propose that excessive beta oscillations in PD are primarily due to a failing damping system rather than a net increase in their generation, and that dopaminergic drugs act to partially restore this damping system, while high frequency DBS suppresses pathological local beta activity. / Abstract in French: Les oscillations neuronales dans la bande beta (10-35 Hz) sont caractéristiques de la maladie de Parkinson (MP). Toutefois, les mécanismes qui sous-tendent la genèse et la propagation des ces activités et leurs liens avec les troubles moteurs restent obscurs. La chirurgie de stimulation des noyaux sous-thalamiques (NST) permet d’enregistrer l’activité neuronale par l’électrode implantée et d’étudier les effets moteurs et neurophysiologiques de la stimulation. Les travaux présentés dans cette thèse ont pour but d’améliorer la compréhension de l’origine de la diffusion des oscillations beta dans le réseau subthalamo-cortical, de leur retentissement sur la motricité et de l’influence des traitements de la MP sur celles-ci. Nous avons effectué une série d’expériences chez des patients parkinsoniens et chez un modèle animal de la MP pour étudir les effets de la stimulation du NST dans la bande beta sur la motricité, ceux de la stimulation à haute fréquence du NST sur les oscillations beta et les propriétés de réseau à l’origine de sa vulnérabilité aux fréquences beta. Les résultats de ces travaux suggèrent l’existence de réseaux subthalamo-corticaux distincts, présentant des propriétés et une susceptibilité à la résonance propres, et qui seraient atteints de façon variable selon les patients, possiblement en rapport avec la variabilité clinique de la MP. Nous proposons que les oscillations beta dans la MP sont principalement dues à la faillite du système d’atténuation plutôt qu’à une augmentation de leur genèse, que les traitements dopaminergiques restaurent partiellement ce système d’atténuation alors que la stimulation à haute fréquence du NST supprime cette activité.
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Books on the topic "Disease propagation"

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De Mello, Walmor C., and Michiel J. Janse. Heart Cell Coupling and Impulse Propagation in Health and Disease. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1155-7.

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Grape and Wine Research and Development Corporation (Australia), ed. Using grapevine rootstocks: The Australian perspective. Adelaide: Winetitles, 1994.

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Mitra, Sisir, ed. Guava: botany, production and uses. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789247022.0000.

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Abstract This publication presents the current state of knowledge concerning the origin, history, culture and trade of guava throughout the world. The fruit composition and processing, as well as fruit set, development and maturation are described. The propagation, biotechnology, nutrition, irrigation, orchard management, flowering, physiological disorders, photosynthesis, productivity, pests (including nematodes), diseases, postharvest physiology and storage of guava are also discussed. The book is mainly targeted at guava researchers, teachers and academics, students, advisors and industry support personnel.
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McDonald, G. I. Armillaria in the northern Rockies: Delineation of isolates into clones. [Ogden, Utah]: U.S. Dept. of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, 1988.

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McDonald, G. I. Armillaria in the northern Rockies: Delineation of isolates into clones. Ogden, UT: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1988.

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McDonald, G. I. Armillaria in the northern Rockies: Delineation of isolates into clones. Ogden, UT: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1988.

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Roth, Lewis F. Response of dwarf mistletoe-infested ponderosa pine to thinning. [Portland, Or.]: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station, 1985.

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McDonald, G. I. Armillaria in the northern Rockies: Pathogenicity and host susceptibility on pristine and disturbed sites. Ogden, UT: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1987.

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McDonald, G. I. Armillaria in the northern Rockies: Pathogenicity and host susceptibility on pristine and disturbed sites. Ogden, UT: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1987.

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McDonald, G. I. Armillaria in the northern Rockies: Pathogenicity and host susceptibility on pristine and disturbed sites. Ogden, UT: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1987.

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Book chapters on the topic "Disease propagation"

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Babiuk, Shawn. "Propagation of the Virus In Vitro." In Lumpy Skin Disease, 41–44. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92411-3_10.

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Kapp, Ursula, Jürgen Wolf, Christof von Kalle, and Volker Diehl. "Propagation of Hodgkin and Reed-Sternberg Cells." In Etiology of Hodgkin’s Disease, 173–86. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4613-0339-8_14.

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Kumar, Vivek, Manoj Kumar, Shivesh Sharma, Ajit Varma, and Neera Bhalla-Sarin. "Procedural Insights on In Vitro Propagation of Litchi chinensis (Sonn.)." In Lychee Disease Management, 217–35. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4247-8_13.

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Zhu, Jiefan, Wenjie Tang, and Yiping Yao. "Message Transmission-Driven Infectious Disease Propagation Model." In Advances in Intelligent Systems and Computing, 284–90. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34387-3_35.

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Winfree, A. T. "Are Cardiac Waves Relevant to Epileptic Wave Propagation?" In Epilepsy as a Dynamic Disease, 165–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05048-4_10.

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Milton, J. "Insights into Seizure Propagation from Axonal Conduction Times." In Epilepsy as a Dynamic Disease, 15–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05048-4_2.

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Rao, Srinath, and H. Sandhya. "In Vitro Selection of Disease-Resistant Plants." In Plant Tissue Culture: Propagation, Conservation and Crop Improvement, 395–417. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1917-3_17.

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Ducrot, Arnaud, and Hiroshi Matano. "Plant Disease Propagation in a Striped Periodic Medium." In Applied Analysis in Biological and Physical Sciences, 121–64. New Delhi: Springer India, 2016. http://dx.doi.org/10.1007/978-81-322-3640-5_8.

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Hu, Mingsheng, Suimin Jia, Qiaoling Chen, Zhijuan Jia, and Liu Hong. "The Analysis of Epidemic Disease Propagation in Competition Environment." In Lecture Notes in Electrical Engineering, 227–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38466-0_26.

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Vomberg, Zoë L., Megan Robinson, Thomas Fellner, and Karl Willert. "Maintenance, Propagation, and Differentiation of Human Embryonic Stem Cells and Induced Pluripotent Stem Cells." In Textbook of Pulmonary Vascular Disease, 613–20. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-87429-6_42.

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Conference papers on the topic "Disease propagation"

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Joseph, Richard, Yohan Mahajan, Sanjib Naha Biswas, Karan Patowary, and Dhanashri Asai. "Contagious Disease Propagation Study Using Machine Learning." In 2018 3rd International Conference on Inventive Computation Technologies (ICICT). IEEE, 2018. http://dx.doi.org/10.1109/icict43934.2018.9034328.

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Hwang, TaeHyun, and Rui Kuang. "A Heterogeneous Label Propagation Algorithm for Disease Gene Discovery." In Proceedings of the 2010 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2010. http://dx.doi.org/10.1137/1.9781611972801.51.

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"ARTIFICIAL LIFE MODEL OF DENGUE HOST-VECTOR DISEASE PROPAGATION." In International Conference on Evolutionary Computation. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0002324102430247.

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Shahzamal, Md, Raja Jurdak, Reza Arablouei, Minkyoung Kim, Kanchana Thilakarathna, and Bernard Mans. "Airborne Disease Propagation on Large Scale Social Contact Networks." In CPS Week '17: Cyber Physical Systems Week 2017. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3055601.3055604.

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Faragó, István, and Róbert Horváth. "Qualitatively adequate numerical modelling of spatial SIRS-type disease propagation." In The 10'th Colloquium on the Qualitative Theory of Differential Equations. Szeged: Bolyai Institute, SZTE, 2016. http://dx.doi.org/10.14232/ejqtde.2016.8.12.

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Kurtah, Pratima, Yusrah Takun, and Leckraj Nagowah. "Disease Propagation Prediction using Machine Learning for Crowdsourcing Mobile Applications." In 2019 7th International Conference on Information and Communication Technology (ICoICT). IEEE, 2019. http://dx.doi.org/10.1109/icoict.2019.8835381.

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Ravindra, B. V., N. Sriraam, and M. Geetha. "Chronic Kidney Disease Detection Using Back Propagation Neural Network Classifier." In 2018 International Conference on Communication, Computing and Internet of Things (IC3IoT). IEEE, 2018. http://dx.doi.org/10.1109/ic3iot.2018.8668110.

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Gromov, Dmitry. "Stuctural analysis of a controlled compartmental model of disease propagation." In 2019 SICE International Symposium on Control Systems (SICE ISCS). IEEE, 2019. http://dx.doi.org/10.23919/siceiscs.2019.8758777.

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Hua, Ting, Chandan K. Reddy, Lei Zhang, Lijing Wang, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. "Social Media based Simulation Models for Understanding Disease Dynamics." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/528.

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Abstract:
In this modern era, infectious diseases, such as H1N1, SARS, and Ebola, are spreading much faster than any time in history. Efficient approaches are therefore desired to monitor and track the diffusion of these deadly epidemics. Traditional computational epidemiology models are able to capture the disease spreading trends through contact network, however, one unable to provide timely updates via real-world data. In contrast, techniques focusing on emerging social media platforms can collect and monitor real-time disease data, but do not provide an understanding of the underlying dynamics of ailment propagation. To achieve efficient and accurate real-time disease prediction, the framework proposed in this paper combines the strength of social media mining and computational epidemiology. Specifically, individual health status is first learned from user's online posts through Bayesian inference, disease parameters are then extracted for the computational models at population-level, and the outputs of computational epidemiology model are inversely fed into social media data based models for further performance improvement. In various experiments, our proposed model outperforms current disease forecasting approaches with better accuracy and more stability.
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Tayyab, M., M. S. Sharawi, and A. Shamim. "Inkjet Printed RF Sensor Array For Lung Disease Detection." In 12th European Conference on Antennas and Propagation (EuCAP 2018). Institution of Engineering and Technology, 2018. http://dx.doi.org/10.1049/cp.2018.1224.

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Reports on the topic "Disease propagation"

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Ibáñez, Ana María, Sandra Rozo, and Maria J. Urbina. Forced Migration and the Spread of Infectious Diseases. Inter-American Development Bank, November 2020. http://dx.doi.org/10.18235/0002894.

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We examine the role of Venezuelan forced migration on the propagation of 15 infectious dis-eases in Colombia. For this purpose, we use rich municipal-monthly panel data. We exploit the fact that municipalities closer to the main migration entry points have a disproportionate ex-posure to infected migrants when the cumulative migration flows increase. We find that higher refugee inflows are associated with increments in the incidence of vaccine-preventable dis-eases, such as chickenpox and tuberculosis, as well as sexually transmitted diseases, including AIDS and syphilis. However, we find no significant effects of migration on the propagation of vector-borne diseases. Contact with infected migrants upon arrival seems to be the main driving mechanism.
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