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Minimizing the variables of voiding spot assay for comparison between laboratories
Chuang Luo1, Juan Liu1, Jiali Yang1
1The School of Basic Medical Sciences, Southwest Medical University, Luzhou, China.
Peerj
|May 30, 2023
Summary
Standardizing the voiding spot assay (VSA) is crucial for reliable mouse urinary function studies. Minimizing variables like transportation time and housing acclimation improves data comparability across labs.
Area of Science:
- Urology
- Animal Models
- Physiology
Background:
- The voiding spot assay (VSA) is a common method for assessing mouse urinary function.
- VSA results are sensitive to housing and procedural variables, leading to data inconsistency across laboratories.
- Key variables include analytical software, housing, transportation, and time of day.
Purpose of the Study:
- To evaluate the comparability of VSA results across laboratories by minimizing key variables.
- To identify critical factors influencing VSA data consistency and reliability.
- To establish standardized protocols for inter-laboratory VSA data comparison.
Main Methods:
- Comparative analysis of VSA data using Fiji and MATLAB analytical software.
- Assessment of VSA outcomes with mice housed in different daily cages.
- Evaluation of VSA sensitivity to transportation and time of day (morning vs. afternoon).
- Performing VSA with identical parameters in two geographically distinct laboratories.
Main Results:
- Analytical tools Fiji and MATLAB show good agreement for VSA parameter quantification, particularly for primary voiding spot (PVS) parameters.
- Mice housed in different daily cages did not significantly alter voiding patterns in a standard VSA cage.
- Mice exhibited high sensitivity to transportation and time of day, impacting voiding patterns.
- Limited comparable VSA data, such as PVS volume, can be generated across laboratories under identical procedural parameters.
Conclusions:
- Standardization of VSA protocols, including acclimation periods after transportation, is essential for reliable and comparable data.
- Minimizing variables related to transportation and time of day is critical for consistent VSA results.
- Comparable VSA data can be achieved across laboratories by adhering to identical procedural parameters, particularly for metrics like PVS volume.

