Comparative Severity Assessment of Genetic, Stress-Based, and Pharmacological Mouse Models of Depression

et al. 2023

Sci Rep

Self Cite

The fundament of an evidence-based severity assessment in laboratory animal science is reliable distress parameters. Many readouts are used to evaluate and determine animal distress and the severity of experimental procedures. Therefore, we analyzed four distinct parameters like the body weight, burrowing behavior, nesting, and distress score in the four gastrointestinal animal models (pancreatic ductal adenocarcinoma (PDA), pancreatitis, CCl4 intoxication, and bile duct ligation (BDL)). Further, we determined the parameters’ robustness in various experimental subgroups due to slight variations like drug treatment or telemeter implantations. We used non-parametric bootstrapping to get robust estimates and 95% confidence intervals for the experimental groups. It was found that the performance of the readout parameters is model-dependent and that the distress score is prone to experimental variation. On the other hand, we also found that burrowing and nesting can be more robust than, e.g., the body weight when evaluating PDA. However, the body weight still was highly robust in BDL, pancreatitis, and CCl4 intoxication. To address the complex nature of the multi-dimensional severity space, we used the Relative Severity Assessment (RELSA) procedure to combine multiple distress parameters into a score and mapped the subgroups and models against a defined reference set obtained by telemeter implantation. This approach allowed us to compare the severity of individual animals in the experimental subgroups using the maximum achieved severity (RELSAmax). With this, the following order of severity was found for the animal models: CCl4 < PDA ≈ Pancreatitis < BDL. Furthermore, the robustness of the RELSA procedure and outcome was externally validated with a reference set from another laboratory also obtained from telemeter implantation. Since the RELSA procedure reflects the multi-dimensional severity information and is highly robust in estimating the quantitative severity within and between models, it can be deemed a valuable tool for laboratory animal severity assessment.

Section: Discussionmentioning

confidence: 89%

Section: Discussionmentioning

confidence: 99%

Robustness of a multivariate composite score when evaluating distress of animal models for gastrointestinal diseases

Talbot

Kumstel

et al. 2023

Sci Rep

Self Cite

“…Possibly, methods measure distress in an animal-model specific manner. This outcome was also marked by Mallien et al when genetic, stress-based, and pharmacological mouse models of depression were compared [64]. These differences between animal models highlight the need to perform multi-parametric severity assessment when comparing different animal models [45,55].…”

Section: Discussionmentioning

confidence: 99%

Robustness of a multivariate composite score when evaluating distress of animal models for gastrointestinal diseases

Talbot

Kumstel

et al. 2022

Preprint

Self Cite

The fundament of an evidence-based severity assessment in laboratory animal science is reliable distress parameters. Many readouts are used to evaluate and determine animal distress and the severity of experimental procedures. Therefore, we analyzed four distinct parameters like the body weight, burrowing behavior, nesting, and distress score in the four gastrointestinal animal models (pancreatic ductal adenocarcinoma (PDA), pancreatitis, CCl4intoxication, and bile duct ligation (BDL)). Further, we determined the parameters‘ robustness in various experimental subgroups due to slight variations like drug treatment or telemeter implantations. We used non-parametric bootstrapping to get robust estimates and 95 % confidence intervals for the experimental groups. It was found that the performance of the readout parameters is model-dependent and that the distress score is prone to experimental variation. On the other hand, we also found that burrowing and nesting can be more robust than, e.g., the body weight when evaluating PDA. However, the body weight still was highly robust in BDL, pancreatitis, and CCl4intoxication. To address the complex nature of the multi-dimensional severity space, we used the Relative Severity Assessment (RELSA) procedure to combine multiple distress parameters into a score and mapped the subgroups and models against a defined reference set obtained by telemeter implantation. This approach allowed us to compare the severity of individual animals in the experimental subgroups using the maximum achieved severity (RELSAmax). With this, the following order of severity was found for the animal models: CCl4< PDA ≈ Pancreatitis < BDL. Furthermore, the robustness of the RELSA procedure and outcome was externally validated with a reference set from another laboratory also obtained from telemeter implantation. Since the RELSA procedure reflects the multi-dimensional severity information and is highly robust in estimating the quantitative severitywithinandbetweenmodels, it can be deemed a valuable tool for laboratory animal severity assessment.

“…For example, one can perform such an analysis using z-scores [ 53 ], k-means clustering [ 54 ], principal component analysis [ 55 , 56 ] binary logistic regression [ 36 , 37 ] or support vector machine classification [ 26 ]. Another recently developed tool for a multivariate analysis of animal wellbeing is the Relative Severity Score (RELSA), which was developed by Talbot et al [ 25 ], and is currently tested by various research groups [ 57 ]. In this study, we gave an overview on the ability of several methods to differentiate between healthy and diseased animals.…”

Section: Discussionmentioning

confidence: 99%

Generalizability, Robustness and Replicability When Evaluating Wellbeing of Laboratory Mice with Various Methods

Zechner

Tang

et al. 2022

Animals

Self Cite

An essential basis for objectively improving the status of animals during in vivo research is the ability to measure the wellbeing of animals in a reliable and scientific manner. Several non-invasive methods such as assessing body weight, burrowing activity, nesting behavior, a distress score and fecal corticosterone metabolites were evaluated in healthy mice and after three surgical interventions or during the progression of four gastrointestinal diseases. The performance of each method in differentiating between healthy and diseased animals was assessed using receiver operating characteristic curves. The ability to differentiate between these two states differed between distinct surgical interventions and distinct gastrointestinal diseases. Thus, the generalizability of these methods for assessing animal wellbeing was low. However, the robustness of these methods when assessing wellbeing in one gastrointestinal disease was high since the same methods were often capable of differentiating between healthy and diseased animals independent of applied drugs. Moreover, the replicability when assessing two distinct cohorts with an identical surgical intervention was also high. These data suggest that scientists can reach valid conclusions about animal wellbeing when using these methods within one specific animal model. This might be important when optimizing methodological aspects for improving animal wellbeing. The lack of generalizability, however, suggests that comparing animal models by using single methods might lead to incorrect conclusions. Thus, these data support the concept of using a combination of several methods when assessing animal welfare.