Mechanistic Research for the Student or Educator (Part II of II).

Mechanistic Research for the Student or Educator (Part II of II).
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DOI:
10.3389/fphar.2022.741492
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发表时间:
2022
影响因子:
5.6
通讯作者:
--
中科院分区:
医学2区
文献类型:
--
作者:

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这两部分的系列介绍了如何测试假设的分子机制,生物现象的基础上,使用临床前药物测试作为一个简化的例子。在临床前研究中进行药物测试时,学生需要了解描述性和机制性研究的局限性。前者并不确定两个或多个变量之间的任何因果关系;它确定相关性的存在或不存在。本教育系列的第一部分和第二部分鼓励学生1)确保其测量的灵敏度和特异性,2)建立或优化适当的疾病模型,3)找到干扰实验疾病过程的药物剂量/浓度,4)利用文献和探索性数据集来构建药物结合和下游效应的机制导向假设,5)在勾勒出潜在结果并想象其解释后,设计一个全因子实验来检验假设。这些创造性目标有助于选择适当的阳性和阴性对照,以避免错误的数据解释。在这里,第二部分详细描述了如何测试药物诱导的生物靶点激活和治疗结果之间的因果关系。在完成这两部分的系列课程后,新学生将掌握一些工具来设计机械研究,解释他们的研究成果,并避免技术和理论陷阱,否则会减缓科学进步并浪费人力和财力。
This two-part series describes how to test hypotheses on molecular mechanisms that underlie biological phenomena, using preclinical drug testing as a simplified example. While pursuing drug testing in preclinical research, students will need to understand the limitations of descriptive as well as mechanistic studies. The former does not identify any causal links between two or more variables; it identifies the presence or absence of correlations. Parts I and II of this educational series encourage the student to 1) ensure the sensitivity and specificity of their measurements, 2) establish or optimize an appropriate disease model, 3) find pharmaceutical drug doses/concentrations that interfere with experimental disease processes, 4) leverage the literature and exploratory datasets to craft a mechanism-oriented hypothesis on drug binding and downstream effects, 5) and design a full-factorial experiment to test the hypothesis after sketching potential outcomes and imagining their interpretations. These creative goals facilitate the choice of the appropriate positive and negative controls to avoid false data interpretations. Here, Part II describes in detail how to test for a causal link between drug-induced activation of biological targets and therapeutic outcomes. Upon completion of this two-part series, the new student will have some of the tools in hand to design mechanistic studies, interpret the outcomes of their research, and avoid technical and theoretical pitfalls, which can otherwise decelerate scientific progress and squander human and financial resources.
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