Background

Numerous populations – nearly 3% of people aged 25-64 years – experience focal hyperhidrosis, an idiopathic abnormality characterized by hyper-sweating concentrated in certain regions of the body, e.g., palms, soles, face, and armpits (Haider et al., 2005). It interferes with daily activities; therefore, this condition poses substantial emotional, psychological, social, and professional burden (Strutton et al., 2004) and even leads to social anxiety disorders (Solish et al., 2007). During the development of drugs or medications for the treatment of focal hyperhidrosis, rational assays for evaluating sweating are necessary to evaluate excessive perspiration symptoms. Several tests used in clinical practice and research studies are not sensitive enough to detect subtle perspiration changes resulting from medications (Provitera et al., 2010). The thermoregulatory sweat test stimulates entire body sweating, including central and peripheral components, but does not localize the sweating lesion site (Fealey et al., 1989). Simple colorimetric procedures, such as the Neuropad test, evaluate sweating abnormalities but do not provide detailed analysis (Quattrini et al., 2008). In addition, abundant in vivo preclinical data are necessary for the verification of anti-perspiration efficacy before clinical trials; however, studies, particularly using mouse models, are rare.

The iodine-starch test is a well-known chemical reaction between starch and iodine, which instantly produces an intense blue-black color. The test was first described in 1814 (Colin et al., 1814) and first applied in 1928 as a medical test for visualizing sudomotor function (perspiration or sweating) (Minor, 1928). Polyiodides complexed with the amylose helix in starch form infinite polyiodide homopolymers and produce the blue-black color, whereas non-ionized iodine dissolved in nonpolar solvents and individual iodide (I⁻) do not react with starch (Madhu et al., 2016). The triiodide (I₃⁻) ion is the simplest polyiodide, which is yellow-to-brown in aqueous conditions with no starch. In addition, the blue-black color of the triiodide-starch complex is so deep, which can also be detected visually when the concentration of iodine is as low as 2 × 10⁻⁵ M at 20°C. Consequently, the iodine-starch test has been used as a well-established diagnostic tool to evaluate underactive (hypohidrosis) and overactive (hyperhidrosis) sweating (Chia et al., 2013).

Even in the mouse sweat assays, various errors may occur owing to arbitrary judgment because the number of sweating spots, attributed to the iodine-starch reaction, is manually counted to quantitate the sweating score (Nejsum et al., 2002; Liu et al., 2017). For the data analysis, image-processing using ImageJ, a free software provided by the National Institutes of Health (NIH), can be utilized to eliminate possible arbitrary judgment and errors. In this protocol, we generated a mouse sweat-assay model and used ImageJ for image analysis (Ban et al., 2020). The sweating area on the skin of hind footpads of anesthetized mice was stained blue-black using an iodine-starch test. The blue-black pixels were extracted from the footpad images obtained, adjusted using the Auto Local Threshold function in ImageJ, and measured to the area fraction (sweating area %). Using the present protocol, a clear difference between the control and the antiperspirant-administered mice was observed with respect to the sweating area % with no error. Moreover, whether expected antiperspirants exploit either circulatory-systematic or focal anti-perspiration efficacy can also be assessed using this protocol.