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Intra-host mathematical model of chronic wasting disease dynamics in deer (Odocoileus)

机译:鹿(Odocoileus)慢性浪费疾病动态的主机内数学模型

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Bioassays of native cervid hosts have established the presence of infectious chronic wasting disease (CWD) prions in saliva, blood, urine, and feces of clinically diseased and pre-clinical infected deer. The intra-host trafficking of prions from the time of initial infection to shedding has been less well defined. We created a discrete-time compartmentalized model to simulate the misfolding catalysis, trafficking, and shedding of infectious prions throughout the organ systems of CWD-infected cervids. Using parameter values derived from experimental infections of North American deer (Odocoileus spp.), the exponential-based model predicts prion deposition over time with: 1) nervous tissues containing the highest deposition of prions at 20months post-infection and 2) excreted fluids containing low levels of prions throughout infection with the highest numbers of prions predicted to be shed in saliva and feces (as high as 10 lethal doses (1.34 x 10(29) prions) in 11-15months). These findings are comparable to prion deposition described in literature as assayed by conventional and ultrasensitive amplification assays. The comparison of our model to published data suggests that highly sensitive assays (sPMCA, RT-QuIC, and bioassay) are appropriate for early prion detection in bodily fluids and secretions. The model provides a view of intra-host prion catalysis leading to pre-clinical shedding and provides a framework for continued development of antemortem diagnostic methods.
机译:本土Cervid宿主的生物测定已经建立了唾液,血液,尿液和临床感染鹿的唾液中的传染性慢性浪费疾病(CWD)朊病毒的存在。从初始感染到脱落时,宿主贩卖朊病毒的贩运人数不太明确。我们创建了一个离散时间的分区化模型,以模拟在CWD感染的CervIDS的器官系统中的错误折叠催化剂,贩运和脱落。使用源自北美鹿(Odocoileus SPP)的实验感染的参数值,基于指数的模型随时间预测朊病毒沉积:1)含有最高沉积的朊病毒局部在感染后的最高沉积和2)含有的排泄液体在唾液和粪便中脱落的朊病毒数量最多的朊病毒(高达10个致命剂量(1.34×10(29)个朊病毒),11-15个月)。这些发现与文献中描述的朊病毒沉积相当,如常规和超敏扩增测定的测定。我们的模型对公布数据的比较表明,高度敏感的测定(SPMCA,RT-QUIC和生物测定)适用于体液和分泌物中的早期朊病毒检测。该模型提供了对宿主朊病毒催化催化剂的视图,导致临床前脱落,并提供了持续发展的持久性诊断方法的框架。

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