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项目摘要 虽然在识别与自闭症风险相关的新生基因突变方面取得了重大进展,但许多 对环境风险以及这些风险导致自闭症病理的程度关注较少 在易感人群中。环境因素,包括妊娠期暴露于拟除虫菊酯类农药, 丙戊酸与自闭症风险有关。产前暴露于拟除虫菊酯也与以下风险有关: 发育迟缓和注意力缺陷多动障碍(ADHD)-最常见的 神经发育障碍然而,这些环境风险是在一个 大量的人受到感染。数千种化学品被注册用于环境, 人类可能会在不同程度上接触到许多这些化学品,包括塑料中的化学品 和建筑材料。我们目前缺乏一种方法来系统地评估哪些环境使用化学品 最有可能伤害发育中的大脑无法确定环境威胁, 在它们导致疾病之前早期发现大脑代表了我们这个时代的主要公共卫生挑战之一。 这一挑战与自闭症尤其相关,现在美国每59个人中就有1个受到影响, 遗传性研究表明,遗传和环境因素有助于自闭症的风险。我们的研究 该计划的指导假设,“候选人”环境风险自闭症和其他 神经发育障碍可以通过识别化学品和混合物来合理地识别, 靶向与这些疾病有关的分子途径。我们的长期目标是:1)确定 靶向神经发育相关分子通路的环境用化学品和混合物 紊乱这些研究将利用原代人神经祖细胞(phNPC)、原代神经元和神经元。 与高通量筛选相容的端点。2)评估真实的世界暴露于这些 化学品/混合物。如果没有这些国家的环境采样和生物监测数据, 化学品/混合物,我们将与环境健康科学(EHS)研究人员网络合作,收集 这些数据。3)使用野生型和CRISPR/Cas9工程小鼠评估体内暴露风险, 人类新生自闭症相关突变。我们将优先考虑以下化学品/混合物:a)影响一种或多种 phNPC/神经元测定终点,B)是经验证的人类暴露风险,和c)进入胎盘和/或 母亲接触后大脑发育。虽然具体项目将随着时间的推移而发展,但我们计划 最初集中在个人和联合暴露于拟除虫菊酯和嗜球果伞素-一类新的杀真菌剂, 抑制线粒体。这两种化学物质都会损害神经元功能,并在家庭环境中共存。 我们将评估产前暴露于这些和其他优先化学品和混合物的程度 加剧与自闭症和其他神经发育障碍相关的大脑和行为表型 在整个生命周期中。
英文摘要
PROJECT SUMMARY While significant progress has been made in identifying de novo gene mutations linked to autism risk, much less attention has been paid to environmental risks and the extent to which these risks cause autism pathology in susceptible individuals. Environmental factors, including gestational exposure to pyrethroid pesticides and valproic acid, are implicated in risk for autism. Prenatal exposure to pyrethroids is also linked to risk for developmental delay and attention deficit hyperactivity disorder (ADHD)—one of the most common neurodevelopmental disorders. However, these environmental risks were identified retrospectively, after a large number of people were exposed. Thousands of chemicals are registered for use in the environment, and humans are potentially exposed to many of these chemicals to varying degrees, including chemicals in plastics and building materials. We currently lack a way to systematically evaluate which environmental-use chemicals have the greatest potential to harm the developing brain. The inability to identify environmental threats to the brain early—before they cause disease—represents one of the major public health challenges of our time. This challenge is particularly relevant to autism, which now affects 1 in 59 individuals in America, and where heritability studies indicate that genetic and environmental factors contribute to autism risk. Our research program is guided by the hypothesis that “candidate” environmental risks for autism and other neurodevelopmental disorders can be identified rationally, by identifying chemicals and mixtures that target molecular pathways implicated in these disorders. Our long term goals are to 1) identify environmental-use chemicals and mixtures that target molecular pathways implicated in neurodevelopmental disorders. These studies will utilize primary human neural progenitor cells (phNPCs), primary neurons, and endpoints that are compatible with high-throughput screening. 2) Assess real world exposure to these chemicals/mixtures. If environmental sampling and biomonitoring data are not available for these chemicals/mixtures, we will work with a network of Environmental Health Science (EHS) researchers to collect these data. 3) Evaluate exposure risk in vivo using wild-type and CRISPR/Cas9-engineered mice that model human de novo autism-linked mutations. We will prioritize chemicals/mixtures that a) impact one or more phNPC/neuron assay endpoints, b) are verified exposure risks to humans, and c) enter the placenta and/or developing brain following maternal exposure. While the specific projects will evolve over time, we plan to initially focus on individual and joint exposures to pyrethroids and strobilurins—a new class of fungicides that inhibits mitochondria. Both chemical classes impair neuronal functions and co-occur in the home environment. We will evaluate the extent to which prenatal exposure to these and other prioritized chemicals and mixtures exacerbate brain and behavioral phenotypes associated with autism and other neurodevelopmental disorders across the lifespan.
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Development of a deep neural network to measure spontaneous pain from mouse facial expressions
Development of a deep neural network to measure spontaneous pain from mouse facial expressions
Development of a deep neural network to measure spontaneous pain from mouse facial expressions
Development of a deep neural network to measure spontaneous pain from mouse facial expressions
国内基金
海外基金
多模态超声VisTran-Attention网络评估早期子宫颈癌保留生育功能手术可行性
  • 批准号:
    --
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    30万元
  • 批准年份:
    2022
  • 负责人:
    郑巧
  • 依托单位:
Ultrasomics-Attention孪生网络早期精准评估肝内胆管癌免疫治疗的研究
  • 批准号:
    --
  • 项目类别:
    面上项目
  • 资助金额:
    52万元
  • 批准年份:
    2022
  • 负责人:
    陈立达
  • 依托单位: