TailTimer: A device for automating data collection in the rodent tail immersion assay

Abstract

The tail immersion assay is a widely used method for measuring acute thermal pain in a way which is quantifiable and reproducible. It is non-invasive and measures response to a stimulus that may be encountered by an animal in its natural environment. However, quantification of tail withdrawal latency relies on manual timing of tail flick using a stopwatch, and precise temperatures of the water at the time of measurement are most often not recorded. These two factors greatly reduce the reproducibility of tail immersion assay data and likely contribute to some of the discrepancies present among relevant literature. We designed a device, TailTimer, which uses a Raspberry Pi single-board computer, a digital temperature sensor, and two electrical wires, to automatically record tail withdrawal latency and water temperature. We programmed TailTimer to continuously display and record water temperature and to only permit the assay to be conducted when the water is within ± 0.25°C of the target temperature. Our software also records the identification of the animals using a radio frequency identification (RFID) system. We further adapted the RFID system to recognize several specific keys as user interface commands, allowing TailTimer to be operated via RFID fobs for increased usability. Data recorded using the TailTimer device showed a negative linear relationship between tail withdrawal latency and water temperature when tested between 47–50°C. We also observed a previously unreported, yet profound, effect of water mixing speed on latency. In one experiment using TailTimer, we observed significantly longer latencies following administration of oral oxycodone versus a distilled water control when measured after 15 mins or 1 h, but not after 4 h. TailTimer also detected significant strain differences in baseline latency. These findings valorize TailTimer in its sensitivity and reliability for measuring thermal pain thresholds.

The Wistar Kyoto Rat: A Model of Depression Traits

“…Another characteristic of human depression is altered tolerance or sensitivity to pain [ 39 ]. Compared to SD controls, both WMI and WLI rats exhibit significantly lower thermal pain thresholds when tested in the tail immersion assay [ 182 ]. These findings are consistent with human MDD patients, who demonstrate reduced thresholds for pain relative to non-depressed controls [ 183 ].…”

“…These findings are consistent with human MDD patients, who demonstrate reduced thresholds for pain relative to non-depressed controls [ 183 ]. The study by Udell et al [ 182 ] further elucidated significant differences in pain sensitivity within the WKY substrains, such that latencies to elicit a pain response were significantly shorter among WMIs compared to their depression-resistant WLI counterparts. The increased pain sensitivity observed in WLI versus SD rats is likely related to their anxious phenotype, as the severity of anxiety symptoms predicts self-reported pain perception ratings in humans [ 184 ].…”

Spontaneous remyelination following dimethyl sulfoxide-induced demyelination is accompanied by behavioral and neurological alteration in mice

“…Pain perception was evaluated by inducing heat painful stimuli after putting the mouse tail into a reservoir with hot water (constant temperature 50.0±1.0°С). Tail flick latency response was registered (Udell et al 2021).…”

Diabetic neuropathy protective action of polyherbal preparation

“…Diabetic sensorimotor polyneuropathy is a type of neuropathy that often leads to pathophysiological complications like foot ulceration (Perkins & Bril, 2003) [9] As a consequence of the adverse effects associated with the use of insulin and oral hypoglycemic drugs, patients are demanding more natural anti-diabetic remedies. There are a variety of traditional medicinal plants with hypoglycemic properties, such as Azadirachta indica (Dholi et al, 2011) [1] , Cinnamomum zeylanicum (Udell et al, 2021;Verspohl et al, 2005) [12,13] , Terminalia bellirica (Gupta et al, 2020;Kadian et al, 2014) [5,6] and Withania somnifera (Sarangi et al, 2013) [10] .…”