30,252 research outputs found

    The effects of subcurative praziquantel treatment on life-history traits and trade-offs in drug-resistant Schistosoma mansoni

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    Natural selection acts on all organisms, including parasites, to maximize reproductive fitness. Drug resistance traits are often associated with life-history costs in the absence of treatment. Schistosomiasis control programmes rely on mass drug administration to reduce human morbidity and mortality. Although hotspots of reduced drug efficacy have been reported, resistance is not widespread. Using Bayesian state-space models (SSMs) fitted to data from an in vivo laboratory system, we tested the hypothesis that the spread of resistant Schistosoma mansoni may be limited by life-history costs not present in susceptible counterparts. S. mansoni parasites from a praziquantel-susceptible (S), a praziquantel-resistant (R) or a mixed line of originally resistant and susceptible parasites (RS) were exposed to a range of praziquantel doses. Parasite numbers at each life stage were quantified in their molluscan intermediate and murine definitive hosts across four generations, and SSMs were used to estimate key life-history parameters for each experimental group over time. Model outputs illustrated that parasite adult survival and fecundity in the murine host decreased across all lines, including R, with increasing drug pressure. Trade-offs between adult survival and fecundity were observed in all untreated lines, and these remained strong in S with praziquantel pressure. In contrast, trade-offs between adult survival and fecundity were lost under praziquantel pressure in R. As expected, parasite life-history traits within the molluscan host were complex, but trade-offs were demonstrated between parasite establishment and cercarial output. The observed trade-offs between generations within hosts, which were modified by praziquantel treatment in the R line, could limit the spread of R parasites under praziquantel pressure. Whilst such complex life-history costs may be difficult to detect using standard empirical methods, we demonstrate that SSMs provide robust estimates of life-history parameters, aiding our understanding of costs and trade-offs of resistant parasites within this system and beyond

    The effects of subcurative praziquantel treatment on life-history traits and trade-offs in drug-resistant Schistosoma mansoni

    Get PDF
    Natural selection acts on all organisms, including parasites, to maximise reproductive fitness. Drug resistance traits are often associated with life-history costs in the absence of treatment. Schistosomiasis control programmes rely on mass drug administration to reduce human morbidity and mortality. Although hotspots of reduced drug efficacy have been reported, resistance is not widespread. Using Bayesian State-Space Models (SSMs) fitted to data from an in vivo laboratory system, we tested the hypothesis that the spread of resistant Schistosoma may be limited by life-history costs not present in susceptible counterparts. Schistosoma mansoni parasites from a praziquantel–susceptible (S), a praziquantel–resistant (R) or a mixed line of originally resistant and susceptible parasites (RS) were exposed to a range of praziquantel doses. Parasite numbers at each life stage were quantified in their molluscan intermediate and murine definitive hosts across four generations, and SSMs were used to estimate key life-history parameters for each experimental group over time. Model outputs illustrated that parasite adult survival and fecundity in the murine host decreased across all lines, including R, with increasing drug pressure. Trade-offs between adult survival and fecundity were observed in all untreated lines, and these remained strong in S with praziquantel pressure. In contrast, trade-offs between adult survival and fecundity were lost under praziquantel pressure in R. As expected, parasite life-history traits within the molluscan host were complex, but trade-offs were demonstrated between parasite establishment and cercarial output. The observed trade-offs between generations within hosts, which were modified by praziquantel treatment in the R line, could limit the spread of R parasites under praziquantel pressure. Whilst such complex life-history costs may be difficult to detect using standard empirical methods, we demonstrate that SSMs provide robust estimates of life history parameters, aiding our understanding of costs and trade-offs of resistant parasites within this system and beyond

    A Microcontroller Based System for Controlling Patient Respiratory Guidelines

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    The need of making improvements in obtaining (in a non-invasive way) and monitoring the breathing rate parameters in a patient emerges due to (1) the great amount of breathing problems our society suffer, (2) the problems that can be solved, and (3) the methods used so far. Non-specific machines are usually used to carry out these measures or simply calculate the number of inhalations and exhalations within a particular timeframe. These methods lack of effectiveness and precision thus, influencing the capacity of getting a good diagnosis. This proposal focuses on drawing up a technology composed of a mechanism and a user application which allows doctors to obtain the breathing rate parameters in a comfortable and concise way. In addition, such parameters are stored in a database for potential consultation as well as for the medical history of the patients. For this, the current approach takes into account the needs, the capacities, the expectations and the user motivations which have been compiled by means of open interviews, forum discussions, surveys and application uses. In addition, an empirical evaluation has been conducted with a set of volunteers. Results indicate that the proposed technology may reduce cost and improve the reliability of the diagnosis.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Economía y Competitividad TIN2015-71938-RED

    Screening Homes to Prevent Malaria: A Randomised Controlled Trial

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    Surveillance guidelines for disease elimination: a case study of canine rabies

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    Surveillance is a critical component of disease control programmes but is often poorly resourced, particularly in developing countries lacking good infrastructure and especially for zoonoses which require combined veterinary and medical capacity and collaboration. Here we examine how successful control, and ultimately disease elimination, depends on effective surveillance. We estimated that detection probabilities of <0.1 are broadly typical of rabies surveillance in endemic countries and areas without a history of rabies. Using outbreak simulation techniques we investigated how the probability of detection affects outbreak spread, and outcomes of response strategies such as time to control an outbreak, probability of elimination, and the certainty of declaring freedom from disease. Assuming realistically poor surveillance (probability of detection <0.1), we show that proactive mass dog vaccination is much more effective at controlling rabies and no more costly than campaigns that vaccinate in response to case detection. Control through proactive vaccination followed by 2 years of continuous monitoring and vaccination should be sufficient to guarantee elimination from an isolated area not subject to repeat introductions. We recommend that rabies control programmes ought to be able to maintain surveillance levels that detect at least 5% (and ideally 10%) of all cases to improve their prospects of eliminating rabies, and this can be achieved through greater intersectoral collaboration. Our approach illustrates how surveillance is critical for the control and elimination of diseases such as canine rabies and can provide minimum surveillance requirements and technical guidance for elimination programmes under a broad-range of circumstances

    Moving forward in circles: challenges and opportunities in modelling population cycles

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    Population cycling is a widespread phenomenon, observed across a multitude of taxa in both laboratory and natural conditions. Historically, the theory associated with population cycles was tightly linked to pairwise consumer–resource interactions and studied via deterministic models, but current empirical and theoretical research reveals a much richer basis for ecological cycles. Stochasticity and seasonality can modulate or create cyclic behaviour in non-intuitive ways, the high-dimensionality in ecological systems can profoundly influence cycling, and so can demographic structure and eco-evolutionary dynamics. An inclusive theory for population cycles, ranging from ecosystem-level to demographic modelling, grounded in observational or experimental data, is therefore necessary to better understand observed cyclical patterns. In turn, by gaining better insight into the drivers of population cycles, we can begin to understand the causes of cycle gain and loss, how biodiversity interacts with population cycling, and how to effectively manage wildly fluctuating populations, all of which are growing domains of ecological research

    Dynamic mode decomposition with control

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    We develop a new method which extends Dynamic Mode Decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, complex systems. DMD finds spatial-temporal coherent modes, connects local-linear analysis to nonlinear operator theory, and provides an equation-free architecture which is compatible with compressive sensing. In actuated systems, DMD is incapable of producing an input-output model; moreover, the dynamics and the modes will be corrupted by external forcing. Our new method, Dynamic Mode Decomposition with control (DMDc), capitalizes on all of the advantages of DMD and provides the additional innovation of being able to disambiguate between the underlying dynamics and the effects of actuation, resulting in accurate input-output models. The method is data-driven in that it does not require knowledge of the underlying governing equations, only snapshots of state and actuation data from historical, experimental, or black-box simulations. We demonstrate the method on high-dimensional dynamical systems, including a model with relevance to the analysis of infectious disease data with mass vaccination (actuation).Comment: 10 pages, 4 figure

    Face Transplantation

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