Training in the Multiscale and Multimodal Analysis of Biomarkers in Alzheimer’s Disease

项目总结/摘要 认识到迫切需要在几个分析层次上进行生物标志物分析的广泛专门知识， 我们提出了一个独特的博士后培训计划，题为“培训的多尺度和多模态分析的 阿尔茨海默病的生物标志物”（AD）。南加州大学是在工作中利用生物标志物的领先专家的所在地 通过各种方法和分析来调查AD。利用南加州大学的杰出资源， 专业知识，这项建议将侧重于准备调查人员在多尺度的独立研究生涯 和AD生物标志物的多模式分析，通过整合分子和细胞方法，成像工具和 信息学、临床试验研究的定量方法和大规模人口分析。我们提出的 培训项目吸引了南加州大学12所学校、系、研究所和中心的教师和教员， 履行这些专业知识的方法领域：南加州大学马克和玛丽史蒂文斯神经成像和信息学 凯克医学院（KSoM）的Zilkha神经遗传研究所（ZNI）; KSoM神经内科; KSoM神经外科; KSoM放射学; KSoM阿尔茨海默氏症治疗研究所;人口和 公共卫生科学在KSoM;经济学系在达纳和大卫Dornsife学院 达娜和大卫多恩西夫学院经济和社会研究中心 技术和医疗系统创新研究所（ITEMS），一项联合倡议 凯克医学院和维特比工程学院之间;伦纳德D. Schaeffer健康中心 政策与经济学，南加州大学索尔普莱斯公共政策学院和 药学;和伦纳德戴维斯老年学学院。学员将完成课程作业，实验室轮换， 职业发展活动，如系列研讨会，解决问题的指导，沟通，时间 管理和领导技能，以及指导和培训的赠款写作。学员将熟悉 在所有专题领域，并将能够有效地合作以外的自己的特定专业领域。 具体而言，南加州大学AD生物标志物多尺度和多模式分析培训旨在： 具有综合技能的学员，通过以下方式对AD生物标志物进行多尺度和多模式分析： 提供量身定制的教学研究教育机会，以促进学员的研究潜力;促进 在AD生物标志物的多尺度和多模式分析方面的杰出研究，包括 发展研究思路，执行研究项目，传播研究成果;建立 在受训人员中，采用协作和多学科团队方法，以推进多尺度和 AD生物标志物的多模式分析;并成功地将受训者转变为独立的研究职业， 包括确保他们自己的研究资金。

PROJECT SUMMARY/ABSTRACT Recognizing the critical need for a broad range of expertise in biomarker analysis at several levels of analysis, we propose a unique postdoctoral training program titled “Training for the Multiscale and Multimodal Analysis of Biomarkers in Alzheimer’s Disease” (AD). USC is home to leading experts who utilize biomarkers in their work investigating AD through a myriad of methods and analyses. Drawing from USC’s eminent resources and expertise, this proposal will focus on preparing investigators for independent research careers in the multiscale and multimodal analysis of biomarkers in AD, by integrating molecular and cellular methods, imaging tools and informatics, quantitative methods for clinical trials research, and large-scale population analyses. Our proposed training program draws preceptors and faculty from 12 schools, departments, institutes, and centers at USC, fulfilling these methodological areas of expertise: USC Mark and Mary Stevens Neuroimaging and Informatics Institute (INI) in the Keck School of Medicine (KSoM); Zilkha Neurogenetic Institute (ZNI) in the KSoM; Department of Neurology in the KSoM; Department of Neurological Surgery in the KSoM; Department of Radiology in KSoM; Alzheimer's Therapeutic Research Institute in the KSoM; Department of Population and Public Health Sciences at the KSoM; Department of Economics in the Dana and David Dornsife College of Letters, Arts and Sciences; Center for Economic and Social Research in the Dana and David Dornsife College of Letters, Arts and Sciences; Institute for Technology and Medical Systems Innovation (ITEMS), a joint initiative between Keck School of Medicine and Viterbi School of Engineering; Leonard D. Schaeffer Center for Health Policy and Economics, a unique collaboration between the USC Sol Price School of Public Policy and School of Pharmacy; and Leonard Davis School of Gerontology. Trainees will complete coursework, lab rotations, and career development activities, such as seminar series, instruction for problem solving, communication, time management, and leadership skills, and instruction and training in grant writing. Trainees will become conversant in all thematic areas and will be able to effectively collaborate outside of their own particular area of expertise. Specifically, the USC Training for the Multiscale and Multimodal Analysis of Biomarkers in AD will aim to: equip trainees with a combination of skills to conduct multiscale and multimodal analyses of biomarkers in AD by providing tailored, didactic research education opportunities to further the research potential of trainees; facilitate eminent research in the multiscale and multimodal analysis of biomarkers in AD by trainees, including the development of research ideas, execution of research projects, and dissemination of research findings; establish among trainees a collaborative and multidisciplinary team approach to advance research in the multiscale and multimodal analysis of biomarkers in AD; and successfully transition trainees to independent research careers, including securing their own research funding.