Track-by-Day: A standardized approach to estrous cycle monitoring in biobehavioral research.

Despite known sex differences in brain function, female subjects are underrepresented in preclinical neuroscience research. This is driven in part by concerns about variability arising from estrous cycle-related hormone fluctuations, especially in fear- and anxiety-related research where there are conflicting reports as to whether and how the cycle influences behavior. The inconsistency may arise from a lack of common standards for tracking and reporting the cycle as opposed to inherent unpredictability in the cycle itself. The rat estrous cycle is conventionally tracked by assigning vaginal cytology smears to one of four qualitatively-defined stages. Although the cytology stages are of unequal length, the stage names are often, but not always, used to refer to the four cycle days. Subjective staging criteria and inconsistent use of terminology are not necessarily a problem in research on the cycle itself, but can lead to irreproducibility in neuroscience studies that treat the stages as independent grouping factors. We propose the explicit use of cycle days as independent variables, which we term Track-by-Day to differentiate it from traditional stage-based tracking, and that days be indexed to the only cytology feature that is a direct and rapid consequence of a hormonal event: a cornified cell layer formed in response to the pre-ovulatory 17β-estradiol peak. Here we demonstrate that cycle length is robustly regular with this method, and that the method outperforms traditional staging in detecting estrous cycle effects on Pavlovian fear conditioning and on a separate proxy for hormonal changes, uterine histology. Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.

Citation

Gianna M Raimondi, Ashley K Eng, Murphy P Kenny, Madison A Britting, Linnaea E Ostroff. Track-by-Day: A standardized approach to estrous cycle monitoring in biobehavioral research. Behavioural brain research. 2024 Mar 12;461:114860

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PMID: 38216058

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