Validation of severity assessment and refinement in neuroscience rat models of subarachnoid hemorrhage and cerebrovascular research

• Applicant: Professorin Dr. Ute Lindauer
• Subject Area: Molecular and Cellular Neurology and Neuropathology ; Sensory and Behavioural Biology ; Experimental Models for the Understanding of Nervous System Diseases ; Clinical Neurology; Neurosurgery and Neuroradiology
• Term: since 2017
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 321137804

Animal models of acute brain injury pose a special challenge regarding severity assessment. The brain lesion itself may cause behavioural alterations like sensory and motor deficits, cognitive deficits, or impulse deficiency, which all may influence the outcome of tests for well-being, which are generally applied for severity assessment. In addition, invasive surgery procedures are needed for lesion initiation, which adds to the burden induced by the pathophysiological processes. Within the first two funding periods we have used two models of subarachnoid hemorrhage (SAH) in rats (filament perforation; cisterna magna blood injection) to identify most useful measures of reduced well-being, distress or burden, applicable in rat acute brain injury models and models for cerebrovascular research in general. Due to the comparably high death rate in the SAH models best reflecting the pathophysiology in humans, we additionally focused on identification of animals at risk for rapidly reaching humane endpoint or premature death. Supported by data science approaches, we have identified core outcome parameters that can be implemented in the everyday care of the animals (body weight and voluntary wheel running, supplementing the classical clinical score). Activity in open field and burrowing figured out as further useful parameters, with their assessment being more time-consuming and showing more heterogenous results between animals. In the third funding period, based on this dataset, we will perform cross-model analysis of the two assessed SAH models in the acute and sub-acute phase aiming at grading of severity of the resultant SAH as well as of the respective surgical approach in sham animals. In a cross-laboratory and cross-model analysis within all neuroscience groups, these core parameters will be validated for their informative value, robustness and generalisability within the time scales of the studies. We will also specifically address the exposure of sham operated control groups in an inter-laboratory approach. In addition to further elaborate data science approaches, the algorithm-based multidimensional scheme of RELative Severity Assessment (RELSA) for continuous quantitative monitoring of distress during the course of the experiment, as well as the developed bioinformatics work flow of composite measure schemes for comparative severity assessment between the different models within the research unit will be applied. Based on data of behavioural and vital parameters (activity, temperature, heart rate) achieved from homecage monitoring and implanted telemetric devices, severity grading and refinement of early humane endpoint detection will be performed by support vector machine classification with unsupervised k-means clustering. Finally, for evidence-based analgesia refinement, the multimodal approach of carprofen in combination with long-lasting local anaesthesia will be assessed as an alternative, non-opioid based strategy to buprenorphine.

• DFG Programme: Research Units
• Subproject of: FOR 2591: Severity assessment in animal-based research