Severity assessment in neuroscientific research: generalisability of multidimensional approaches and application to refinement

在资助阶段1和2期间，在神经儿科和神经系统疾病的各种诱导和遗传小鼠和大鼠模型中评估了一套全面的行为，生化和遥测分析的生理参数。交叉年龄，模型，物种和性别验证提供了有价值的信息，所选参数候选人的普遍性。在设计和验证试验组合时考虑了相应的信息，以评估幼龄转基因小鼠发育轨迹中的累积严重程度。此外，我们还进一步开发和优化了生物信息学工作流程，用于多维复合测量方案的参数选择和设计。案例研究，集中在模型的癫痫，神经发育和神经精神疾病，表明，由此产生的多维计划的严重程度评估到一个新的水平的敏感性，允许比较评估与精确分级的痛苦水平。多变量方法也已成功地应用于验证潜在的细化措施（例如，优化的多模式镇痛;遥测与栓系记录），用于神经科学研究中的常见干预和技术。实验研究和系统评价的结果可作为选择最有希望的参数进行深入实验室内和总体实验室间分析的基础，提供有关其信息价值、灵敏度、可重复性、稳健性和可推广性的进一步信息。沿着这些路线，设计多维复合测量方案的生物信息学工作流程将应用于来自不同合作伙伴的数据集，以确认其对不同动物模型的有效性并确定必要的调整。此外，我们将对我们的数据集应用CIMSA，以确认该多维评分系统用于持续严重程度监测的有效性，并将支持特定研究设计的变体开发。在基于证据的细化方面，对实验室内和实验室间数据的分析以及多模式围手术期镇痛方案的常规使用将告知此类方案的普遍性。通过使用发射器植入物和遗传小鼠模型的多中心研究期间记录的数据集，我们将有助于验证新的智能家居笼系统。根据我们的研究结果和与利益相关者的讨论，我们将为基于证据的严重程度评估和基于证据的改进措施的多变量方案的设计和应用提供建议。

During funding phase 1 and 2, a comprehensive set of behavioural, biochemical, and telemetrically-analysed physiological parameters has been assessed in various induced and genetic mouse and rat models of neuropediatric and neurological disorders. A cross-age, -model, -species and -sex validation provided valuable information about generalisability of selected parameter candidates. Respective information was considered for the design and validation of a test battery allowing assessment of cumulative severity across the developmental trajectory of young genetically-modified mice. Moreover, we have further developed, and optimised a bioinformatic workflow for parameter selection and design of multidimensional composite measure schemes. Case studies, focussed on models of epilepsy, neurodevelopmental and neuropsychiatric disorders, demonstrated that the resulting multidimensional schemes take severity assessment to a new level of sensitivity allowing comparative assessment with precise grading of distress levels. Multivariate approaches have also been successfully applied to validate potential refinement measures (e.g., optimised multimodal analgesia; telemetric vs. tethered recordings) for common interventions and techniques in neuroscientific research. Findings from experimental studies and systematic reviews serve as a basis for selecting the most promising parameters for an in-depth intra-laboratory and an overarching inter-laboratory analysis, providing further information about their informative value, sensitivity, replicability, robustness, and generalisability. Along these lines, the bioinformatic workflow for the design of multidimensional composite measure schemes will be applied to datasets from different collaboration partners to confirm its validity for different animal models and identify necessary adaptations. In addition, we will apply RELSA to our data sets to confirm the validity of this multidimensional scoring system for continuous severity monitoring and will support the development of variants for specific study designs. In terms of evidence-based refinement, analysis of intra- and inter-laboratory data and routine use of multimodal perioperative analgesic regimens will inform about the generalisability of such regimens. With data sets recorded during a multicentre study with transmitter implants and from a genetic mouse model, we will contribute to the validation of a new smart home cage system. Based on our findings and discussions with stakeholders, we will provide recommendations for the design and application of multivariate schemes for evidence-based severity assessment and for evidence-based refinement measures.