Refined Protocol for Newly Onset Identification in Non-obese Diabetic Mice: An Animal-friendly, Cost-Effective, and Efficient Alternative

Hsiang-Hsuan Sung, Chia-Chi Liao, Chia-Chun Hsieh, Min-Yuan Chou, Chuan-Chuan Huang, Jhih-Hong Lin, Shu-Hsien Lee
2023 · doi:10.21203/rs.3.rs-2816213/v1
preprint OA: closed CC-BY-4.0
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Abstract

Abstract Determining the onset of diabetes based on blood glucose (BG) levels can be challenging in mouse models, as thresholds can vary from 200 to 400 mg/dl in one or two consecutive tests. Urine glucose (UG) levels can be detected non-invasively as another criterion of diabetic condition, but it is considered a lagging indicator due to physiological downstream from BG. In this study, we demonstrate that the lagging period is practically unnoticeable in spontaneously model of non-obese diabetic (NOD) mice which develop autoimmune diabetes randomly from 12 to 32 weeks of age. After comprehensive measurements across entire onset window in 60 female NOD mice, we concluded that BG measurements before UG reaches 250 mg/l contribute nearly nothing to diabetic identification. Refined protocol encompasses UG survey twice-weekly to select positive candidates for further intensive BG measurements is recommended and tested in another batch of 60 mice. This protocol precisely identified every newly onset individual with average BG of 350 mg/dl which is lower than conventional once-weekly BG survey alone around 400 mg/dl. Moreover, intensive measurements near onset indicate two BG+ within four days can serve as a refined onset criterion, allowing for dynamic arrangement of sampling time to make the process even more efficient in practice. From 3R perspectives, this protocol potentially saves dozens of bleeding procedures in one individual mouse and hundreds of lancets, BG strips, labors, and unnecessary animal suffering during batch screening that serve as a convenient alternative for newly onset identification of diabetes.

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License: CC-BY-4.0