CounterAct Administrative Supplement to NS114020 Automated Phenotyping in Epilepsy
CounterAct Administrative Supplement to NS114020 Automated Phenotyping in Epilepsy
批准号:
10227611
负责人:
Sandeep R Datta
金额:
$12.38万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-10-01 至 2021-06-30
关键词:
3-DimensionalAcuteAddressAdministrative SupplementAnimal BehaviorAnimalsAntiepileptic AgentsArtificial IntelligenceBehaviorBehavioralCannabidiolChronicCognitiveCommunitiesComplexDataDetectionDevelopmentDrug ScreeningElectroencephalographyEpilepsyExposure toGoalsHumanIntoxicationIsoflurophateLong-Term EffectsLongitudinal StudiesMethodsModelingMonitorMotionMusNeurologic EffectObserver VariationPesticidesPharmaceutical PreparationsPhenotypePlayProbabilityPublic HealthReproducibilityResearchRestSeizuresStatus EpilepticusStereotypingStructureTechniquesTechnologyTestingThree-dimensional analysisTimeacquired epilepsyautomated algorithmcomorbidityimprovedinnovationmedical countermeasurenerve agentneuroinflammationneuronal circuitrynovel therapeuticsparent grantpre-clinical researchscreeningtoolvalproate
中文摘要
急性有机磷农药中毒是一个严重的公共卫生问题
关注和长期的神经影响还没有得到很好的理解。的主要障碍
在OP的长期作用方面,朝着可重复的、严格的临床前研究方向取得进展,
诱发癫痫持续状态是目前的实验方法往往需要禁止
时间和劳动密集型24/7视频脑电图监测和固有的主观评分,
人类观察者的癫痫发作(如广泛使用的拉辛量表)。虽然算法
EEG中的自动癫痫发作检测正在改进,
获得性癫痫的临床表现及其认知共病的评估仍然很差
量化。我们的母基金专注于开发一种客观、高通量的技术,
使用称为运动测序(MoSeq)的新方法来表征癫痫表型,
将其应用于自动抗癫痫药物(AED)筛选。MoSeq的核心思想在于
发现复杂的动物行为是以刻板的模块(“音节”)结构化的
在亚秒级的时间尺度上,根据特定的规则(“语法”)来安排,
通过人工智能(AI)辅助的3D视频分析,在没有观察者偏见的情况下检测到。在这
行政补充项目,我们建议使用和完善MoSeq,以解决关键问题,
新的医学对策(MCM)的发展研究面临的挑战,
神经毒剂和OP杀虫剂。这包括测试是否有可能客观地研究
OP中毒的长期影响,并通过确定癫痫特异性
急性OP暴露后小鼠的行为模块和相关转移概率。在
此外,鉴于神经炎症可能在OP诱导的持续性炎症中起关键作用,
神经元回路障碍,我们将测试小胶质细胞耗竭是否可以挽救OP诱导的
行为音节和转换概率的慢性变化。总之,这一目标
行政补助金将受益于并有助于我们的父母补助金的目标,
为研究界开发一个可靠的、可共享的工具,以研究癫痫发作和认知功能。
癫痫的并发症。
英文摘要
Acute intoxication with organophosphorus (OP) pesticides is a significant public health
concern and long-term neurological effects are not well understood. A major obstacle to
progress towards reproducible, rigorous preclinical research in the long-term effects of OP-
induced status epilepticus is that current experimental approaches often require prohibitively
time and labor-intensive 24/7 video-EEG monitoring and inherently subjective scoring of
seizures by human observers (like the widely used Racine scale). While algorithms for
automated seizure detection in EEG are improving, the critically important behavioral
manifestations of acquired epilepsy and assessment of its cognitive comorbidities remain poorly
quantified. Our parent grant focuses on developing an objective, high-throughput technique to
characterize epileptic phenotypes using a new method called motion sequencing (MoSeq) and
apply it to automated anti-epileptic drugs (AED) screening. The central idea of MoSeq rests on
the discovery that complex animal behaviors are structured in stereotyped modules (“syllables”)
at sub-second timescales that are arranged according to specific rules (“grammar”) that can be
detected without observer bias by artificial intelligence (AI)-assisted 3D video analysis. In this
administrative supplement project, we propose to employ and refine MoSeq to address key
challenges in research into the development of new medical countermeasures (MCM) against
nerve agents and OP pesticides. This includes testing if it is possible to objectively study the
long-term effects of OP intoxication and evaluate MCMs at scale by determine epilepsy-specific
behavioral modules and associated transition probabilities in mice after acute OP exposure. In
addition, given that neuroinflammation is likely to play a key role in OP-induced persistent
neuronal circuit disturbance, we will test if microglial depletion can rescue the OP-induced
chronic changes in behavioral syllables and transition probabilities. Together, the aims in this
administrative supplement will both benefit from and contribute to our parent grant’s goal to
develop a reliable, sharable tool for the research community to study seizures and cognitive
comorbidities of epilepsy.
期刊论文(0)
专著(0)
科研奖励(0)
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