High Incidence of Estrous Cycle Irregularities in Heterogeneous Stock (HS) Rats is Associated with Footshock-Resistant Cocaine Intake

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Sneddon, Supakorn Chonwattanagul, Kathleen Bai, Pranav H. Kurup, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8950642/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Mar, 2026 Read the published version in Psychopharmacology → Version 1 posted You are reading this latest preprint version Abstract Rationale: Hormonal fluctuations throughout the estrous cycle are hypothesized to influence drug-related behaviors. Preclinical models show that some cocaine-related behaviors are influenced by the estrous cycle. However, the extent to which the estrous cycle modulates cocaine self-administration in outbred heterogeneous stock (HS) rats is unknown. Objectives We aimed to examine the relationship between estrous phases and cocaine self-administration behavior in HS rats using an operant model of extended access to cocaine self-administration. Methods We assessed the escalation of intake, breaking point, and resistance to foot shock. Using vaginal swabbing and lavage techniques, we characterized the relationship between estrous phase and cocaine behaviors. We then comprehensively evaluated estrous cycling patterns in young adult and adult HS rats, comparing them with Wistar rats. Results Estrous phase showed no association with cocaine self-administration in HS rats. 82% of female HS rats exhibited irregular estrous cycling with variability to the phase length, even in the absence of drug exposure, a phenomenon not observed in the Wistar strain. Females with irregular cycling showed greater footshock-resistant cocaine intake. Conclusions This study provides the first evidence that most female HS rats exhibit irregular estrous cycling. In HS rats, the estrous phase per se has no major influence on cocaine self-administration, whereas cycling irregularity was associated with specific addiction-related behaviors, including footshock-resistant intake. As HS rats gain popularity in behavioral and genome-wide studies, understanding these cycle disruptions is crucial as they may reveal genetic links into cycling variability and individual differences to aspects of cocaine use. estrous cycle Heterogenous Stock rats females cocaine operant self-administration Wistar rats hormonal fluctuations Figures Figure 1 Figure 2 Figure 3 Introduction In the United States, 32.1 million women have substance use or mental health disorders (Bustamante 2020 ). Over the past decade, the rate of cocaine use has increased steadily for women, who more rapidly progress from initial use to dependence than men (Kerver and Becker 2017 ). Women report stronger pleasurable effects (Becker and Hu 2008 ) and craving during abstinence (Elman et al. 2001 ) compared to men. However, the mechanisms for these differences are unclear. Hormonal fluctuations across the menstrual cycle (~ 28 days) (Mihm et al. 2011 ) may influence drug-related behaviors. While some studies report no differences of smoked cocaine use between the follicular (high estrogen) and luteal phases (Evans et al. 2002 ), others report women in the follicular phase rate cocaine as more pleasurable compared to those in the luteal phase (Evans et al. 2002 ). Cravings from cocaine- or stress-related cues are also stronger during the follicular phase (Sinha et al. 2007 ; Moran-Santa Maria et al. 2014 ; Reed and Carr 2018). Intranasal cocaine results in higher plasma cocaine levels during the follicular phase (Lukas et al. 1996 ), though this is not observed for intravenous cocaine (Mendelson et al. 1999 ). As such, hormonal fluctuations may play a critical role in cocaine use disorder in women. Like humans, rodents have a similar pattern of fluctuating hormone levels in their estrous cycle (4–5 days), which consists of proestrus, estrus, metestrus, and diestrus (Ajayi and Akhigbe 2020 ). Self-administration varies during the estrous cycle, where rats show greater motivation and increased cocaine-seeking during the estrus phase (Roberts et al. 1989 ; Lynch et al. 2000 ; Carroll et al. 2002 ; Feltenstein and See 2007 ; Kohtz et al. 2022 ) and during estrus females show greater responding for cocaine paired with cues (Johnson et al. 2019 ). However, not all studies support this; one found no effect of estrous phase on preference for cocaine versus food (Kerstetter et al. 2012 ). Additionally, disruptions to the normal estrous cycle have been documented following cocaine self-administration in rodents (Roberts et al. 1989 ; Grimm 1997 ; Fuchs et al. 2005 ; Truckenbrod et al. 2023 ). Despite these associations, the relationship between estrous phase contributions remains poorly characterized in genetically diverse rodent models, which are commonly used for behavioral and genomic studies. Heterogeneous stock (HS) rats are valuable for investigating the genetic variation underlying drug-related behaviors. We and others have characterized a range of addiction-related behaviors for both drug (e.g., cocaine, oxycodone, and alcohol) and non-drug (e.g., food) rewards (King et al. 2016 , 2021 , 2024 ; Woods and Mott 2017 ; de Guglielmo et al. 2019 , 2024 ; Hughson et al. 2019 ; Kallupi et al. 2020 , 2022 , 2026 ; Carrette et al. 2021 , 2022 ; Sedighim et al. 2021 ; Allen et al. 2021 ; Gunturkun et al. 2022 ; Cannella et al. 2024 ; Kuhn et al. 2025a , b ; Doyle et al. 2025 ; Lara et al. 2025 ; Delorme et al. 2025 ; Ramborger et al. 2026 ). Sex differences in self-administration for both cocaine (de Guglielmo et al. 2024 ) and oxycodone (Kallupi et al. 2026 ) have been identified in HS rats. Despite the strength of this model, it has yet to be validated if the estrous cycle is consistent with other strains and if specific phases are associated with cocaine-related behaviors. We aimed to characterize the estrous cycle in HS rats and assess its association with cocaine-related behaviors. Vaginal samples or lavages were collected at multiple time points across experiments. In Experiment 1, rats underwent cocaine self-administration, with the estrus cycle measured before and during drug exposure. Experiment 2 further examined estrous cycling in young adult and adult HS rats at various timepoints over five consecutive days. Because we observed irregular cycles, we then sought to validate our methods. Experiment 3 assessed estrous cycling in adult Wistar rats with a similar sampling protocol. We hypothesized that HS rats would show increased cocaine use during high-estrogen phases (estrus + proestrus). This study aimed to clarify how hormonal fluctuations influence cocaine-related behaviors in this translational model. Here, we show that female HS rats with irregular estrous cycling may influence footshock-resistant responding, even in the absence of direct phase associations on single swabbing days. Methods Subjects 403 female HS rats were obtained from Wake Forest University (WFU; NMcwiWFsm #13673907, RRID:RGD_13673907; n = 248) and UC San Diego (McwiWfsmAap:HS # 155269102, RID:RGD_155269102; n = 155). Ten female Wistar rats were obtained from Charles River for control experiments. HS rats shipped from WFU arrived at UC San Diego at 3–4 weeks of age. HS rats shipped from UC San Diego were transferred from one room in a vivarium to another in the same vivarium. Wistar rats arrived at 6 weeks of age. Upon arrival from WFU, rats underwent a 2-week quarantine, then were housed in pairs under a 12-hour light/dark cycle (lights off at 8 AM) at controlled temperature (20–22°C) and humidity (45–55%). Rats had ad libitum access to tap water and food (PJ Noyes Company, Lancaster, NH, USA) and were handled for at least five days before experiments. All procedures followed NIH guidelines and were approved by the UC San Diego IACUC committee. Estrous cycle monitoring For Experiment 1, HS rats (n = 298) were vaginally swabbed using a sterile cotton swab dipped in Milli-Q® water one hour before drug exposure, either on the final short access (ShA 10) or the first progressive ratio (PR01) session, and the last long access (LgA 14). Following LgA 14, another PR session was conducted (PR02), followed by a test to measure resistance to footshock (Fig. 1 A). The vaginal cells were collected and placed on a glass microscope slide for visualization. Because the self-administration paradigm was conducted quarterly in separate cohorts (30–60 rats per cohort), different animals were sampled at different timepoints. As such, the sample sizes reported for each behavioral measure do not sum to the total N, as some rats were assessed once and others across multiple timepoints. In an independent, smaller cohort of 39 HS rats, 28 of which received cocaine while 11 remained cocaine-naive, vaginal samples were collected every 24 hours (1 hour before the dark cycle) before the drug self-administration paradigm began for four consecutive days. For Experiment 2, the estrous cycle was monitored in sexually mature (Sengupta 2013 ) female HS rats (n = 81) at 7–8 weeks of age. Samples were taken every 7–9 hours (1 hour before the dark cycle, 8 hours into the dark cycle, and 7 hours before the dark cycle) across 5 days (Fig. 2 A). Given the multiple time points of sample collection, vaginal lavage was used since this method is less invasive (Cora et al. 2015 ; Dalla et al. 2024 ), and has shown consistent findings in past work (Sneddon et al. 2023 ). An additional cohort of rats (n = 24) received vaginal lavage at 10–11 weeks of age to assess if the estrous cycle stabilized in adulthood. For Experiment 3, estrous cycle was monitored in female Wistar rats (n = 10) using vaginal lavage for 5 days every 12 hours (1 hour before the dark cycle and 1 hour before the light cycle) as a control (Fig. 3 A). This schedule of sampling and strain was used as Wistars have been validated as having consistent estrous cycling with up to 60–70% of rats showing regular estrous cycle (Marcondes et al. 2002 ). Unstained slides (n = 298) were visualized in Experiment 1. All other samples were stained 24 hours post-collection using a Hema 3 stat pack (Fisher Scientific, Pittsburgh, PA), with slides dipped in Fixative (30 sec), Solution I (30 sec), and Solution II (15 sec). Estrous phases were identified using a BZ-X800 Analyzer (Keyence, Itasca, IL) based on cell type distribution (Waynforth and Flecknell 1992 ; Ajayi and Akhigbe 2020 ; Sneddon et al. 2023 ; Doyle et al. 2023 ). Regular cycles followed established phase durations (Ajayi and Akhigbe 2020 ), while irregular cycles exceeded these durations or deviated from typical patterns (Marcondes et al. 2002 ) (see Data Analysis section for details on how irregularities were categorized). Apparatus & Behavioral Testing Cocaine self-administration was conducted in operant conditioning chambers (Med Associates, St. Albans, VT, USA) housed in soundproof, ventilated cubicles, as previously described (Kallupi et al. 2020 , 2026 ; Carrette et al. 2021 ; Sedighim et al. 2021 ; de Guglielmo et al. 2024 ). Each chamber contained two retractable levers, with a cue light above the active lever, and a floor made of metal rods. Foot shocks (0.3 mA, 0.5 seconds) were delivered through an aversive stimulator (ENV-414S, Med Associates). Rats underwent 10 short-access (ShA; 2-hour) sessions followed by 14 long-access (LgA; 6-hour) sessions, conducted on weekdays, within two hours at the start of the dark cycle, as previously described (de Guglielmo et al. 2024 ). Cocaine (0.5 mg/kg/infusion) was delivered intravenously on a fixed ratio schedule, with each infusion followed by a 20-second timeout. Inactive lever responses were recorded. Following self-administration, rats completed progressive ratio (PR) testing after ShA 10 (PR01) and LgA 14 (PR02), where the breakpoint was defined as the last completed ratio before a 60-minute period during which a ratio was not completed. A final one-hour foot shock session was conducted under the fixed ratio 1 conditions, with 30% of cocaine infusions paired with foot shocks. Additional details are available in the George lab protocol repository: https://www.protocols.io/workspaces/george-lab (Carrette et al. 2021 ). Drugs & Surgery Cocaine HCl (National Institute on Drug Abuse, Bethesda, MD) was dissolved in 0.9% sterile saline. Postoperative care included subcutaneous flunixin (2.5 mg/kg) for analgesia and intramuscular cefazolin (330 mg/kg) to prevent infection. Catheter patency was maintained with a daily flush of heparin sodium (10 U/mL) and cefazolin in bacteriostatic saline. Rats in Experiment 1 were implanted with jugular vein catheters under isoflurane anesthesia (1–5%) using aseptic techniques (Kallupi et al. 2020 , 2026 ; Carrette et al. 2021 ; Sedighim et al. 2021 ; de Guglielmo et al. 2024 ). Catheters were inserted into the right jugular vein, which was connected to a cannula secured with dental cement and mesh. The cannula port was externalized via a dorsal incision on the back of the rodent. Incisions were closed with Vetbond tissue adhesive (Santa Cruz Biotechnology Inc., Dalla, TX), and rats recovered for five days before behavioral testing. Data Analysis For Experiment 1, cocaine infusions were normalized to infusions per hour. Self-administration data were analyzed using repeated measures (RM) One-Way or Two-Way Analysis of Variance (ANOVA) (session or session × group as factors). If no interaction was detected, groups were collapsed for a One-Way ANOVA. In cases of missing values, a Mixed-Effects ANOVA was used. Post hoc Dunnett’s tests assessed escalation vs. session 1. For all experiments, all raw data from the animals was evaluated, and any subject who did not complete the paradigm due to catheters failing, deaths, those identified as outliers, or those who exhibited anomalous behavior (de-escalation or unstable responding) inconsistent with prior work (de Guglielmo et al. 2024 ) were excluded. Exclusion of rats for these reasons was done without knowledge of their estrus cycles. To confirm the exclusion did not impact our results, we compared session 1 and 14 between the two separate cohorts, larger (n = 298) and smaller cohort (n = 22) using an unpaired t-test with Welch’s correction. Greenhouse–Geisser correction was applied when sphericity was violated (ε 0.05). Given the lack of differences, phases were collapsed into high (proestrus + estrus) vs. low (metestrus + diestrus) estrogen groups and reassessed using an unpaired t-test with Welch’s correction. An addiction index was calculated using the variables of escalation, motivation, and compulsive-like behavior, represented as the averaged Z-scores of three dependent variables that together explained ~ 50% of the variance (de Guglielmo et al. 2024 ). Z-scores were determined as follows: the escalation index was the Z-score of an animal’s average intake over the last three days of LgA; the motivation index was the Z-score of breaking point during the PR session following LgA; and the compulsivity index was the Z-score of the number of infusions obtained during the session with contingent foot shock. The addiction index was then computed by averaging these three behavioral indexes. This addiction index resulted in four quartile groups categorized as resilient, mild, moderate, or severe. To assess estrous phase X addiction index associations on cocaine infusions, a Two-Way ANOVA was performed. If subjects did not have values or data for any of the variables needed to conduct the addiction index, they were excluded from this analysis (ShA10, n = 10; LgA14, n = 13; PR01, n = 11). To assess the relationship between estrous cycling and cocaine self-administration, an irregularity index was assigned (0–3) based on skipped phases, prolonged durations, or atypical phase sequences (Marcondes et al. 2002 ). A score of 0 indicated a regular 4–5 day cycle with normal progression through each phase. A score of 1 reflected a single irregularity (e.g., one skipped or prolonged phase), 2 indicated two distinct irregularities across the monitoring period, and 3 indicated three irregularities or persistent atypical phase transitions. Spearman’s correlation was used to test associations between cycling irregularities and cocaine infusions during early ShA (first four sessions) and late LgA (last four sessions). The distribution of regular vs. irregular cycling across addiction index groups was determined, followed by a One-Way ANOVA to assess the influence of the addiction index. Estrous phase duration was analyzed using Two-Way ANOVA (estrous phase × timepoint). A subject was considered in a phase if present for at least one timepoint, with cumulative time estimated based on consecutive observations. Phase durations were summarized as mean ± SEM. Percentages of regular vs. irregular cycling subjects were also calculated. Comparisons between rat strains were analyzed using a Chi Square Test (95% confidence interval). Parametric tests were applied only to continuous behavioral variables previously demonstrated to meet assumptions of normality and homoscedasticity, whereas ordinal measures (e.g., irregularity index) were analyzed using nonparametric statistics. Behavioral data were collected using MED-PC IV software. Imaging data with insufficient samples or contamination (e.g., urine) were excluded. For Experiment 3, data for timepoint 3 were unavailable due to unforeseen circumstances. Two independent researchers verified estrous phase classification. Data analysis and visualization were conducted using GraphPad Prism 10.2.2, RStudio, Microsoft Excel, and BioRender. All values are reported as mean ± SEM unless otherwise stated, with statistical significance set at p < 0.05. Effect sizes (η², 95% CI, and r²) are reported where applicable. Results Experiment 1: Estrous phase is not associated with cocaine-related behaviors in HS rats A repeated measures One-Way ANOVA revealed a main effect of session during ShA (F (4.616, 1366.4) = 63.890, p < 0.0001, r 2 = 0.178). A post hoc Dunnett’s test revealed that sessions 2–10 were increased compared to session 1 (all p < 0.05). For LgA sessions, a Mixed Effects ANOVA found a main effect of session (F (6.190, 1831.9) = 47.283, p < 0.0001, r 2 = 0.394). A post hoc Dunnett’s test showed that sessions 4–14 were higher compared to session 1 (Fig. 1 B). An unpaired Welch’s t-test found no significant differences between number of infusions as a function of estrous phase on the last cocaine ShA session (t (109.79) = 0.629, p = 0.531, r 2 = 0.004) (Fig. 1 C) or the last cocaine LgA session (t (137.916) = 0.942, p = 0.316, r 2 = 0.006) (Fig. 1 D). When assessing cocaine infusions between the last ShA and LgA session, a Two-Way ANOVA found a significant main effect of session (F (1,407) = 75.223, p < 0.0001, h 2 = 0.149) (Fig. 1 E ) . An unpaired Welch’s t-test found no significant differences between phases on the first PR session (t (46.838) = 1.144, p = 0.258, r 2 = 0.027) (Fig. 1 F). A Two-Way ANOVA found a significant main effect of addiction index on the last cocaine ShA session (F (3, 158) = 3.861, p = 0.011), the last cocaine LgA session (F (3, 216) = 55.378, p < 0.0001), and the first PR session (F(3, 131) = 7.706, p < 0.001) but no effects of estrous phase ( Suppl. Figure 1A-C ). In a subset of rats (n = 39), when assessing daily cycling before exposure to cocaine, we found that 82.05% of the subjects had cycling irregularities and 17.95% exhibited regular cycling (Fig. 1 G-I). For self-administration sessions, the rats exposed to cocaine were assessed (n = 28), but six of these were excluded due to catheter patency failure, deaths, or anomalous behavior (de-escalation) (as in previous work, (de Guglielmo et al. 2024 )). To ensure this exclusion did not influence our results, we compared sessions 1 and 14 between the larger (n = 298) and smaller (n = 22) cohorts. An unpaired Welch’s t-test showed no differences between the cohorts for LgA1 (t (26.879) = 0.162, p = 0.872, r 2 = 0.0009) or LgA14 (t (24.584) = 1.786, p = 0.09, r 2 = 0.115). The larger cohort infused 11.20 ± 0.54 of 0.5 mg/kg/hour on LgA1 and 16.62 ± 0.46 of 0.5 mg/kg per hour on LgA14. The smaller cohort infused 11.45 ± 1.47 of 0.5 mg/kg/hour on LgA1 and 13.65 ± 1.60 of 0.5 mg/kg per hour on LgA14. A RM Two-Way ANOVA found a main effect of session for ShA (F (2.772, 47.130) = 1.101, p = 0.001, h 2 = 0.166) and LgA (F (3.928, 66.777) = 0.429, p = 0.022, h 2 = 0.051). As no interaction was found, the data were collapsed across groups. A One-Way ANOVA for ShA found a main effect of session (F (3.258, 58.650) = 8.835, p < 0.0001, r 2 = 0.130) and a main effect of session for LgA (F (3.463, 58.875) = 3.209, p = 0.024, r 2 = 0.698) (Fig. 1 J). No correlation between irregularity index and cocaine infusions during the first four ShA sessions (r (22) = 0.176, p = 0.432, CI: -0.277 to 0.566) (Fig. 1 K) or the last four LgA sessions was observed (r (22) = -0.147, p = 0.515, CI: -0.545 to 0.305) (Fig. 1 L). A One-Way ANOVA found no significant differences in cocaine infusions at ShA10, LgA11-14, PR01, or PR02 (all p > 0.05) (Fig. 1 M-Q). A One-Way ANOVA revealed a main effect of irregularity index on cocaine infusions during the shock session (F (3,18) = 3.693, p = 0.031, r 2 = 0.381). A post hoc Dunnett’s test showed that there was a significant difference between number of infusions for those with 0 vs 3 cycling irregularities (p = 0.034) (Fig. 1 P) For rats with regular cycling, 16.67% (n = 1) were characterized as resilient, 33.33% (n = 2) as mild, and 50% (n = 3) as moderate for the addiction index. For the rats with irregular cycling, 25% (n = 4) were characterized as resilient, 18.75% (n = 3) as mild, 18.75% (n = 3) as moderate, and 37.5% (n = 6) as for the severe addiction index ( Suppl. Figure 2A ). When assessing if the addiction index varied by irregularity index, a One-Way ANOVA discovered a main effect of addiction index (F (3,18) = 4.114, p = 0.022, r 2 = 0.407) ( Suppl. Figure 2B ). Experiment 2: Estrous cycle irregularities are observed in young adult and adult female HS rats We found that 96.15% of the young adult rats (n = 78) had cycling irregularities and 3.85% (n = 3) had a regular cycle (Fig. 2 B-E). A significant main effect of estrous phase was observed when assessing the percentage of subjects in each phase across time point (F (3, 42) = 79.29, p < 0.0001, h 2 = 84.99) (Fig. 2 C). When assessing the duration of each estrous phase in young adult female rats, the time spent in each phase (in hours) are shown in Table 1 . When evaluating the percentage of rats that experienced each estrous phase at least once, we observed that 100% of the rats experienced proestrus and estrus, 82.72% experienced metestrus, and 53.09% experienced diestrus. We found that 100% of the adult female HS rats (n = 24) had cycling irregularities (Fig. 2 F-H). A significant main effect of estrous phase was observed when assessing the percentage of subjects in each phase across time point (F (3, 42) = 11.05, p < 0.0001, h 2 = 40.48) (Fig. 2 G). When assessing the duration of each estrous phase in adult female rats, the time spent in each phase (in hours) are shown in Table 1 . When evaluating the percentage of rats that experienced each estrous phase at least once, we observed that 100% of the rats experienced proestrus and estrus, while 95.83% experienced metestrus, and 54.17% experienced diestrus. Experiment 3: Wistar rats show regular estrous cycling Sixty percent of the female Wistar rats (n = 10) had regular cycling while the other forty percent did not (Fig. 3 B – D ). The distribution of regular versus irregular cycles varied strongly by strain, χ²(2, N = 115) = 88.14, p < 0.0001. Nearly all HS rats displayed irregular cycles, whereas a majority of Wistars cycled regularly. When comparing the length of the proestrus phase between Wistar, young adult, and adult HS rats, a One-Way ANOVA identified a significant main effect (F (1, 112) = 9.19, p = 0.0002, r 2 = 0.14). A post hoc Holm Sidak’s test revealed that the adult HS rats had a longer proestrus phase compared to the young adult HS rats (p = 0.001) and adult Wistars (p = 0.0008). When assessing the length of the estrus phase between groups, a One-Way ANOVA discovered a significant main effect (F (1, 112) = 5.92, p = 0.0036, r 2 = 0.10). A post hoc Holm Sidak’s test found that the adult HS rats had a shorter estrus compared to the young adult HS rats (p = 0.004) and adult Wistars (p = 0.026). When comparing the length of the metestrus phase between groups, a One-Way ANOVA discovered a significant main effect (F (1, 112) = 11.91, p = 0.004, r 2 = 0.18). A post hoc Holm Sidak’s test identified that young adult (p < 0.0001) and adult (p < 0.0001) HS rats had a shorter metestrus phase compared to adult Wistars. When assessing the length of the diestrus phase between groups, a One-Way ANOVA revealed a significant main effect (F (1, 112) = 5.14, p = 0.007, r 2 = 0.08). A post hoc Holm Sidak’s test identified that young adult (p = 0.017) and adult (p = 0.005) HS rats had a shorter diestrus phase compared to adult Wistar rats (Table 1 ). Table 1 Length of Estrous Phases in Young Adult and Adult HS Rats and Adult Wistar Rats (in hours) Estrous phase Statistical Test Cycle Length (hours) Young Adult HS (7–8 weeks) Adult HS (10–11 weeks) Adult Wistars (10–11 weeks) Proestrus Mean ± SEM 18.33 ± 1.19 # 27.25 ± 2.59 12 ± 0 Median 17 24 12 Range 7–57 15–56 12–12 Estrus Mean ± SEM 19.68 ± 1.40 # 10.38 ± 0.78 22 ± 6.51 Median 16 9 12 Range 7–63 7–17 12–48 Metestrus Mean ± SEM 9.09 ± 0.36 7.87 ± 0.35 16 ± 4 Median 8 7 12 Range 7–24 7–15 12–36 Diestrus Mean ± SEM 8.71 ± 0.48 7.57 ± 0.20 12 ± 0 Median 7 7 12 Range 7–31 7–9 12–12 Table 1 . Length of Estrous Phases in Young Adult and Adult HS Rats and Adults Wistar Rats (in hours). Average and range of rats were in each phase of the estrous cycle. Data are expressed as mean ± SEM, the median, or ranges. Young adults (n = 81), adult (n = 24), and Wistar (n = 10) rats. ( # p < 0.05 Young Adult vs. Adult HS rats; Holm Sidak’s) Discussion We found that baseline irregular estrous cycling in female HS rats does not influence overall cocaine intake or escalation, but severe cycling irregularities were associated with increased levels of footshock-resistant cocaine intake. Given the lack of data on estrous cycling in drug-naive HS rats, we conducted additional experiments. HS females lack the regular estrous cycling observed in other outbred lines, such as Wistar rats. These findings conflict with the existing literature and suggest that the HS rats may be a powerful model to investigate estrous cycle irregularities. We did not find any direct associations between estrous phase and cocaine self-administration during the acquisition (ShA10), escalation (LgA14), or progressive ratio (PR01) phases when estrous samples were collected at these timepoints. These null findings should be interpreted with caution, as a subset of HS rats revealed that less than 20% of the subjects exhibited baseline regular cycling patterns before cocaine exposure. We characterized an irregularity index (criteria determined from (Marcondes et al. 2002 )) to assess whether the baseline irregularities before self-administration correlated with future cocaine-related behaviors. Estrous cycling irregularities before drug exposure were not correlated with early short access or long-access self-administration. In addition, cycling irregularities were not associated with difference in cocaine infusions during acquisition (ShA7-10), escalation (LgA11-14), or progressive ratio (PR01 or PR02). We did see that females with severe cycling irregularities responded more for cocaine despite a footshock. This finding agrees with one other study where female Sprague-Dawley rats who had greater preference for larger, risker rewards and showed more cycling irregularities (Truckenbrod et al. 2023 ). These results suggest that estrous cycle irregularities may lead to cocaine under stressful conditions resulting in an increase of aversion-resistant cocaine use. However, because no significant effects were observed for escalation of intake or motivation under progressive ratio conditions, for future studies it will be important to further evaluate the relationship between estrous cycle irregularities and aversion-resistant drug seeking. Additional paradigms assessing aversion resistance, such as varying shock probability and intensity, higher progressive ratio schedules, varying aversive stimuli (e.g., shock vs. quinine), and drug–alternative procedures will be critical for determining the generalizability and significance of these effects. It remains unclear whether cocaine exposure further disrupted the cycle in this study, as for logistical reasons we couldn’t perform a week-long estrous cycle analysis after escalation of cocaine intake. As most rats showed irregularities before drug exposure, it is unclear how to assess if cocaine further disrupted the cycle. While some studies link high estradiol to increased cocaine use (Lynch et al. 2000 ; Feltenstein and See 2007 ; Feltenstein et al. 2009 ), others report no association or cue-dependent effects (Lacy et al. 2016 ; Doncheck et al. 2020 ). Proestrus and estrus consistently correlate with greater motivation in progressive ratio and reinstatement tests (Roberts et al. 1989 ; Feltenstein and See 2007 ; Lynch 2008 ; Lacy et al. 2016 ; Nicolas et al. 2019 ; Doncheck et al. 2020 ; Corbett et al. 2021 ). However, we saw no association with the progressive ratio session, which deviates from these findings. As mentioned above, one study has seen that females with greater cocaine intake also showed greater preference for larger, risker rewards and showed more cycling irregularities (Truckenbrod et al. 2023 ). This study saw that there were prolonged estrus and/or proestrus phases (Truckenbrod et al. 2023 ) while another linked stressed-related cocaine seeking with the diestrus and proestrus phases (Doncheck et al. 2020 ). As such, further investigation is warranted to determine which phases are associated with footshock-resistant cocaine intake and if cycling irregularities are a driving factor of this behavior. Since the HS rats are ideal for assessing individual differences (Solberg Woods and Palmer 2019 ), we examined whether estrous cycle irregularities prior to cocaine exposure correlate with addiction-related behaviors using an addiction index (Carrette et al. 2021 ; de Guglielmo et al. 2024 ). Rats exhibiting irregular estrous cycling were disproportionately represented at both the resilient and severe ends of the Addiction Index categories, corresponding to the lowest and highest addiction-related phenotypes. This bimodal pattern suggests that pre-existing cycle irregularities may be associated with divergent vulnerability trajectories rather than a uniform effect on cocaine intake. Although the sample size limits definitive conclusions, these findings indicate that irregular cycling may contribute to either reduced or heightened addiction-like behavior. Previous studies have shown that cocaine exposure can disrupt estrous cycling (Raap et al. 2000 ; Truckenbrod et al. 2023 ). However, our data provide initial evidence that pre-existing irregularities may also influence subsequent drug-taking behavior. Because most studies exclude subjects with irregular cycling (Dalla et al., 2024 ), our approach offers a unique opportunity to examine cycle irregularity as a factor that may shape individual vulnerability to cocaine use. Originally, our goal was to investigate whether cocaine disrupts the estrous cycling in HS rats. We hypothesized that we would observe regular phase progression with disruptions following cocaine exposure, as previously reported (Raap et al. 2000 ; Truckenbrod et al. 2023 ). However, we found that 96.15% of young adults and 100% of adults exhibited irregular cycling with no apparent pattern in drug-naïve subjects. The timescale in each phase did not match previous reports of the estrous cycle in other strains of rats, such as Lewis, Wistar, and Sprague-Dawley (Ajayi and Akhigbe 2020 ). In HS rats, we observed that the proestrus and metestrus were extended while estrus and diestrus were blunted in both young adult and adult rats. Proestrus was the most prominent phase, while diestrus was the least, contradicting the literature for other strains (Marcondes et al. 2002 ; Goldman et al. 2007 ; Cora et al. 2015 ; Ajayi and Akhigbe 2020 ). Similar proestrus extension has been observed in the Goto-Kakizaki rat strain, potentially due to hypothalamic-pituitary-gonadal axis dysregulation (Pinto-Souza et al. 2016 ), which could explain our findings. Our results were surprising as we are unaware of any other rodent model that shows irregularities to this extent and requires further exploration. Our control experiment with Wistar rats showed 60% regular cycling, consistent with prior reports (Marcondes et al. 2002 ; Elsayed et al. 2022 ). Although Wistar rats were sampled every 12 hours and HS rats every 7–9 hours, this difference in timing is unlikely to explain the large strain differences we observed. Irregular cycling occurred in 96–100% of HS rats compared to only 40% of Wistars, a highly significant contrast (p < 0.0001). Importantly, irregularity in HS rats was apparent both when assessed at a single timepoint and when monitored across multiple timepoints, indicating that the higher sampling resolution did not inflate irregularity detection. Given similar irregularity patterns observed in other strains (Karim et al. 2003 ; Mourlon et al. 2011 ; Schuh et al. 2024 ) with rates between 9–40% (Marcondes et al. 2002 ; Karim et al. 2003 ; Mourlon et al. 2011 ), methodological error is unlikely. Vaginal swabbing, lavages, and staining have been used in our studies in Wistar rats (Doyle et al. 2023 ) and C57BL/6J mice (Sneddon et al. 2023 ) without any methodological issues. Although estrous variability is common (Robert et al. 2021 ), HS rats show unprecedented irregularities. Cycle length can vary from 3–38 days in rats (Long and Evans 1922 ; Westwood 2008 ), though most studies phase across 4–5 days (Marcondes et al. 2002 ; Cora et al. 2015 ; Ajayi and Akhigbe 2020 ). Cycle and phase length may be different in these rats, but that does not account for cellular variability. Sexual maturation can range from 30 to 38 days in female rats (Spear 2000 ; Lewis et al. 2002 ; Lenschow et al. 2017 ). We initially attributed the irregularities at 7–8 weeks to sexual immaturity or stress from rehousing, but the respective irregularities persisted at 10–11 weeks, suggesting permanence. While excluding rats with irregular cycling is recommended (Dalla et al. 2024 ; Holalagoudar et al. 2024 ) to simplify data collection, this approach does not reflect the human population where 14% − 25% of women experience cycling irregularities (Nobles et al. 2022 ; Flickr). Women with menstrual cycle irregularities show 40% higher rates of mental disorders, including substance use disorder (Poyastro Pinheiro et al. 2007 ; Barron et al. 2008 ; Nillni et al. 2011 , 2018 ; Algars et al. 2014 ; Toffol et al. 2014 ; Gleeson et al. 2016 ; Yu et al. 2017 ; Reilly et al. 2020 ; Ajari 2021 ; Milano et al. 2022 ; Green and Graham 2022 ). As cycling irregularities are associated with mental health outcomes, understanding the factors driving cycling regularity in humans and rodents is crucial. HS rats may be valuable for exploring the genetic factors influencing cycle irregularities and mental health, as we observed that irregular cycling is linked to more severe cocaine addiction-related behaviors. Additionally, HS rats display increased fear, anxiety, and depressive-like behaviors associated with heightened prolactin levels (Lopez-Aumatell et al. 2008 ; López-Aumatell et al. 2011 ; Díaz-Morán et al. 2013 ), though no estrous cycle associations were measured. A meta-analysis found that increased anxiety-like behaviors are tied to lower estrogen levels (Pestana and Graham 2024 ). The shortened or skipped metestrus and diestrus phases in female HS rats may lead to increased exposure to estrogen due to the more frequent occurrence of estrus and proestrus phases, potentially affecting their anxiety profile. One limitation of this study is that estrous cycling was assessed in separate cohorts of young adult and adult rats rather than longitudinally within the same subjects. Although such an approach could provide additional insight into whether specific irregular patterns are stable within individuals subjects, the extremely high prevalence of irregular cycling in both age groups (96–100%) indicates that irregularity is a robust feature of this strain. Therefore, a longitudinal design would be unlikely to alter the primary conclusion that estrous cycling is broadly irregular across development. These results are based on vaginal cytology, not direct hormonal measurement. While this does limit our conclusions, vaginal cytology remains the most reliable method to assess estrous fluctuations in rodents (Dalla et al. 2024 ). Serum hormone measurement was considered, but due to irregular cycling in HS rats, determining an appropriate non-invasive blood collection schedule was not feasible for accurately characterizing the cycle. Additionally, ELISA measurement of estradiol in rodents can vary (Chan et al. 2013 ), supporting the continued assessment of vaginal smears. As such, vaginal smears were the most accurate assessment of the estrous cycle at our disposal. This study is the first to demonstrate that female HS rats exhibit irregular estrous cycling in the absence of drug exposure. While these irregularities were not associated with uniform changes in addiction-like behavior, rats with severe cycling disruptions showed greater footshock-resistant cocaine responding compared to animals with no irregularities. Together, these findings suggest that estrous cycle irregularity may differentially influence specific aspects of addiction-related behavior rather than producing a single, consistent phenotype. Given the increasing use of HS rats in behavioral and genome-wide studies, characterizing these endogenous cycle disruptions is important, as they may provide insight into genetic and hormonal mechanisms underlying cycling irregularities observed in women. Declarations Competing interests: The authors declare no competing interests. Author Contribution Conceptualization: EAS and OG. Methodology: EAS and OG. Formal analysis: ES, SC, SS, and SZ. Investigation: EAS, SC, KB, PK, SLP, MRD, BCS, DNO, and MB. Writing – Original Draft: EAS, SC, and KB. Writing – Review and Editing: EAS, SC, KB, SLP, MRD, SZ, SS, GdG, MK, LLGC, AAP, and OG. Visualization: ES and SZ. Supervision: EAS and OG. Resources: AAP. Project Administration: EAS, MB, GdG, MK, LLGC, and OG. Funding acquisition: EAS, LLGC, and OG. Acknowledgement The authors would like to thank the Preclinical Addiction Research Consortium at UCSD. This work was supported by the National Institute on Drug Abuse (U01DA04379 and U01DA044451 to OG, P50DA037844 and P30DA060810 to AAP, and K00DA057923 to EAS) and the Burroughs Wellcome Fund (to EAS). Data Availability All images and data for this project are available from the corresponding author upon request. References Ajari EE (2021) Connecting the dots between mental and menstrual health: An exploratory review. J Health Rep Technol 8. https://doi.org/10.5812/jhrt.114869 Ajayi AF, Akhigbe RE (2020) Staging of the estrous cycle and induction of estrus in experimental rodents: an update. 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(A) At ShA10 (n = 167), (B) LGA14 (n = 213), (C) and PR01 (n = 139), estrous phase and addiction index did not influence cocaine infusions. SupplementalFigure2.tiff Supplemental Figure 2. Irregular cycling and Addiction Index Associations. (A) Percentage of rats with regular (left) or irregular (right) cycling based on their addiction index. Regular: resilient (n =1), mild (n = 2), and moderate (n = 3). Irregular: resilient (n = 4), mild (n = 3), moderate (n = 3), severe (n =6). (B) Distribution of rats by the irregularity and addiction indices (*p < 0.05, One-Way ANOVA). 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Palmer","email":"","orcid":"","institution":"University of California, San Diego","correspondingAuthor":false,"prefix":"","firstName":"Abraham","middleName":"A.","lastName":"Palmer","suffix":""},{"id":595970121,"identity":"31d6679d-3cb5-42ef-9048-0c47074fb917","order_by":12,"name":"Marsida Kallupi","email":"","orcid":"","institution":"University of California, San Diego","correspondingAuthor":false,"prefix":"","firstName":"Marsida","middleName":"","lastName":"Kallupi","suffix":""},{"id":595970124,"identity":"817b11b5-574d-4e73-bfa8-3a23c9cb381d","order_by":13,"name":"Lieselot L.G. Carrette","email":"","orcid":"","institution":"University of California, San Diego","correspondingAuthor":false,"prefix":"","firstName":"Lieselot","middleName":"L.G.","lastName":"Carrette","suffix":""},{"id":595970125,"identity":"7a477aab-03ac-4e2b-94d5-9522633bfd82","order_by":14,"name":"Giordano Guglielmo","email":"","orcid":"","institution":"University of California, San Diego","correspondingAuthor":false,"prefix":"","firstName":"Giordano","middleName":"","lastName":"Guglielmo","suffix":""},{"id":595970131,"identity":"8493b65c-e99f-4663-b224-2ac5d5fe989c","order_by":15,"name":"Olivier George","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYDACdijNLwEkHjAcAHOAbGbcWmBSkjOAREICKVoMbhCrhZ+Z/eKDj3tq5YxvNx/8kPjjDoPB8eMPbzBUWCc24NAi2cxTbDjj2XFjszvHkiUSEp4xGJzJMbZgOJOOU4vBYZ40aZ4DxxK33cgxAGo5DHQhD5sEY9thfFrSfwO11G+ekf/5B0QL+zMJxn/4tLAfY+Y5UJNgIJHDBrWFwUyCsQG3FqBfmCVnHDhgOONGmplFQtphHkmQXxKOpRvj0sLP3v7ww4cDdfL8M5If3/hgc1iODxRiH2qsZXFpYWDgMQAShxFcMJmAUzkIsD8AEnV4lYyCUTAKRsEIBwDXt2AJU9GGpgAAAABJRU5ErkJggg==","orcid":"","institution":"University of California, San Diego","correspondingAuthor":true,"prefix":"","firstName":"Olivier","middleName":"","lastName":"George","suffix":""}],"badges":[],"createdAt":"2026-02-23 20:54:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8950642/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8950642/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00213-026-07041-8","type":"published","date":"2026-03-24T16:11:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":103507566,"identity":"d0974c94-fda0-489d-8e4a-a3735e7899d5","added_by":"auto","created_at":"2026-02-26 13:42:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":276548,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIrregular estrous cycling may influence cocaine vulnerability. (A) \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eTimeline of Experiment 1. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(B) \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eCocaine infusions across short access (ShA) and long access (LgA) sessions (n = 298). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(C)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Number of infusions by estrouscycle phase during ShA10 (n = 178).\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e (D)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Number of infusions by estrous cycle phase distribution during long access LgA 14 (n = 238). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(E)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Regardless of the collapsed estrous phase, subjects earned more cocaine infusions during LgA vs. ShA sessions. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(F)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e The collapsed estrous phases are not associated with cocaine infusions during progressive ratio 1 (PR01, n = 151). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(G)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Visual representation of cytology in each phase of the estrous cycle: diestrus, proestrus, estrus, and metestrus. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(H) \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eVisualization of 24-h cycling in a subset of HS rats (n = 39). Regular cycling is outlined by a bolded line. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(I) \u003c/strong\u003e\u003c/em\u003e\u003cem\u003ePercentage of rats with regular vs. irregular cycling. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(J)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Self-administration of rats showing regular (n = 7) and irregular (n = 14) cycling patterns across ShA and LgA sessions. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(K)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Correlation between irregularity index and average infusions on ShA sessions 1-4 (p = 0.057). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(L)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e No correlation between the irregularity index and cocaine infusions during the last four sessions of LgA. Cycling irregularities were not associated with cocaine infusions during \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(M) \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eShA7-10, \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(N)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e LgA11-14, \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(O)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e PR01, or \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(P)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e, PR02. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(Q)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Rats with severe cycling irregularities infused more cocaine during the shock session. (* p \u0026lt; 0.05, ** p \u0026lt; 0.001, or **** p \u0026lt; 0.001, main effect One- or Two-Way ANOVA. # p\u0026lt; 0.05, ## p \u0026lt; 0.001, or ### p \u0026lt; 0.001, session compared to session 1, Dunnett’s).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"OnlineFig1revised.png","url":"https://assets-eu.researchsquare.com/files/rs-8950642/v1/cbd5909c044c513eaa04bfb3.png"},{"id":103507722,"identity":"5882b77b-1a29-41dd-aa3d-3c4bbd90309e","added_by":"auto","created_at":"2026-02-26 13:43:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":178115,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eYoung adult and adult female HS rats show irregular estrous cycling without drug exposure. (A)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Timeline of Experiments 2, sampling of young adult (7 – 8 weeks, n = 81) and adult (10 – 11 weeks, n = 24). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(B)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Percentage of rats with regular vs. irregular cycling in young adults. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(C)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Percentage of young adults in each phase across hours. Representative line graphs showing \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(D)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003eirregular and \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(E)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e regular cycling in young adult HS rats across phase: proestrus (P), estrus (E), metestrus (M), and diestrus (D). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(F)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Percentage of rats with irregular cycling in adults. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(G)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003ePercentage of adults in each phase across hours. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(H)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Representative line graphs showing irregular cycle in adults.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"OnlineFig2revised.png","url":"https://assets-eu.researchsquare.com/files/rs-8950642/v1/0ade481d99a4b43d032b1e8c.png"},{"id":103431160,"identity":"72b60b8c-1fb8-485f-a780-31d26525e3f2","added_by":"auto","created_at":"2026-02-25 15:28:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":88269,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eWistar rats show regular estrous cycling. (A) \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eTimeline sample collection. \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(B)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Line graph visualization of regular cycling in Wistar rats across phase: proestrus (P), estrus (E), metestrus (M), and diestrus (D). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(C)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Percentage of rats with regular vs. irregular cycling.\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e (D)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003eLine graph visualization of irregular estrous cycling in Wistar rats. (Tan indicates the transition from one phase to another).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"OnlineFig3revised.png","url":"https://assets-eu.researchsquare.com/files/rs-8950642/v1/19fcadc9906c5719e8fdc6c0.png"},{"id":105755969,"identity":"5d3699f8-52d1-4ee5-99d8-aaff86bb5706","added_by":"auto","created_at":"2026-03-30 16:33:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1808828,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8950642/v1/98f16cf5-96ef-4854-9e43-9611781b71bb.pdf"},{"id":103507229,"identity":"6905e6b7-02f3-4242-81ef-0549fc4ee78a","added_by":"auto","created_at":"2026-02-26 13:40:45","extension":"tiff","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":353442,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSupplemental Figure 1.\u003c/strong\u003e\u003c/em\u003e\u003cbr\u003e\n \u003cem\u003e\u003cstrong\u003eEstrous phase is not associated with Addiction Index at various timepoints. (A) \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eAt ShA10 (n = 167),\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e (B)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e LGA14 (n = 213), \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(C) \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eand\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003ePR01 (n = 139), estrous phase and addiction index did not influence cocaine infusions.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"SupplementalFigure1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-8950642/v1/3bd4d6dc4e10211f369e8f5e.tiff"},{"id":103431157,"identity":"4c61d1aa-51f0-4b9a-989e-00d00538657d","added_by":"auto","created_at":"2026-02-25 15:28:03","extension":"tiff","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":65519,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSupplemental Figure 2. Irregular cycling and Addiction Index Associations.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(A)\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e Percentage of rats with regular (left) or irregular (right) cycling based on their addiction index. Regular: resilient (n =1), mild (n = 2), and moderate (n = 3). Irregular: resilient (n = 4), mild (n = 3), moderate (n = 3), severe (n =6). \u003c/em\u003e\u003cem\u003e\u003cstrong\u003e(B) \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eDistribution of rats by the irregularity and addiction indices (*p \u0026lt; 0.05, One-Way ANOVA).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"SupplementalFigure2.tiff","url":"https://assets-eu.researchsquare.com/files/rs-8950642/v1/561e1570a578cebaa26fb4ff.tiff"},{"id":103431163,"identity":"96c8fd42-8b25-4ade-9a28-a1bf5c5a78e0","added_by":"auto","created_at":"2026-02-25 15:28:03","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":527398,"visible":true,"origin":"","legend":"","description":"","filename":"SneddonetalSupplementalPsychopharm22326.docx","url":"https://assets-eu.researchsquare.com/files/rs-8950642/v1/1de5099a07d3936027e659d0.docx"},{"id":103507379,"identity":"bde4da8e-8531-48ab-ad1a-82ae27ab9c49","added_by":"auto","created_at":"2026-02-26 13:41:12","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":59854,"visible":true,"origin":"","legend":"","description":"","filename":"SneddonetalTablesPsychopharm22326.docx","url":"https://assets-eu.researchsquare.com/files/rs-8950642/v1/086266322294ea2d4e6c6990.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"High Incidence of Estrous Cycle Irregularities in Heterogeneous Stock (HS) Rats is Associated with Footshock-Resistant Cocaine Intake","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn the United States, 32.1\u0026nbsp;million women have substance use or mental health disorders (Bustamante \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Over the past decade, the rate of cocaine use has increased steadily for women, who more rapidly progress from initial use to dependence than men (Kerver and Becker \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Women report stronger pleasurable effects (Becker and Hu \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and craving during abstinence (Elman et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) compared to men. However, the mechanisms for these differences are unclear.\u003c/p\u003e \u003cp\u003eHormonal fluctuations across the menstrual cycle (~\u0026thinsp;28 days) (Mihm et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) may influence drug-related behaviors. While some studies report no differences of smoked cocaine use between the follicular (high estrogen) and luteal phases (Evans et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), others report women in the follicular phase rate cocaine as more pleasurable compared to those in the luteal phase (Evans et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Cravings from cocaine- or stress-related cues are also stronger during the follicular phase (Sinha et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Moran-Santa Maria et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Reed and Carr 2018). Intranasal cocaine results in higher plasma cocaine levels during the follicular phase (Lukas et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), though this is not observed for intravenous cocaine (Mendelson et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). As such, hormonal fluctuations may play a critical role in cocaine use disorder in women.\u003c/p\u003e \u003cp\u003eLike humans, rodents have a similar pattern of fluctuating hormone levels in their estrous cycle (4\u0026ndash;5 days), which consists of proestrus, estrus, metestrus, and diestrus (Ajayi and Akhigbe \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Self-administration varies during the estrous cycle, where rats show greater motivation and increased cocaine-seeking during the estrus phase (Roberts et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Lynch et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Carroll et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Feltenstein and See \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Kohtz et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and during estrus females show greater responding for cocaine paired with cues (Johnson et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, not all studies support this; one found no effect of estrous phase on preference for cocaine versus food (Kerstetter et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Additionally, disruptions to the normal estrous cycle have been documented following cocaine self-administration in rodents (Roberts et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Grimm \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Fuchs et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Truckenbrod et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite these associations, the relationship between estrous phase contributions remains poorly characterized in genetically diverse rodent models, which are commonly used for behavioral and genomic studies.\u003c/p\u003e \u003cp\u003eHeterogeneous stock (HS) rats are valuable for investigating the genetic variation underlying drug-related behaviors. We and others have characterized a range of addiction-related behaviors for both drug (e.g., cocaine, oxycodone, and alcohol) and non-drug (e.g., food) rewards (King et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Woods and Mott \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; de Guglielmo et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Hughson et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kallupi et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2026\u003c/span\u003e; Carrette et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sedighim et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Allen et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Gunturkun et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Cannella et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kuhn et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003eb\u003c/span\u003e; Doyle et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Lara et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Delorme et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Ramborger et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). Sex differences in self-administration for both cocaine (de Guglielmo et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and oxycodone (Kallupi et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2026\u003c/span\u003e) have been identified in HS rats. Despite the strength of this model, it has yet to be validated if the estrous cycle is consistent with other strains and if specific phases are associated with cocaine-related behaviors.\u003c/p\u003e \u003cp\u003eWe aimed to characterize the estrous cycle in HS rats and assess its association with cocaine-related behaviors. Vaginal samples or lavages were collected at multiple time points across experiments. In Experiment 1, rats underwent cocaine self-administration, with the estrus cycle measured before and during drug exposure. Experiment 2 further examined estrous cycling in young adult and adult HS rats at various timepoints over five consecutive days. Because we observed irregular cycles, we then sought to validate our methods. Experiment 3 assessed estrous cycling in adult Wistar rats with a similar sampling protocol. We hypothesized that HS rats would show increased cocaine use during high-estrogen phases (estrus\u0026thinsp;+\u0026thinsp;proestrus). This study aimed to clarify how hormonal fluctuations influence cocaine-related behaviors in this translational model. Here, we show that female HS rats with irregular estrous cycling may influence footshock-resistant responding, even in the absence of direct phase associations on single swabbing days.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003e403 female HS rats were obtained from Wake Forest University (WFU; NMcwiWFsm #13673907, RRID:RGD_13673907; n\u0026thinsp;=\u0026thinsp;248) and UC San Diego (McwiWfsmAap:HS \u003cb\u003e#\u003c/b\u003e155269102, RID:RGD_155269102; n\u0026thinsp;=\u0026thinsp;155). Ten female Wistar rats were obtained from Charles River for control experiments. HS rats shipped from WFU arrived at UC San Diego at 3\u0026ndash;4 weeks of age. HS rats shipped from UC San Diego were transferred from one room in a vivarium to another in the same vivarium. Wistar rats arrived at 6 weeks of age. Upon arrival from WFU, rats underwent a 2-week quarantine, then were housed in pairs under a 12-hour light/dark cycle (lights off at 8 AM) at controlled temperature (20\u0026ndash;22\u0026deg;C) and humidity (45\u0026ndash;55%). Rats had \u003cem\u003ead libitum\u003c/em\u003e access to tap water and food (PJ Noyes Company, Lancaster, NH, USA) and were handled for at least five days before experiments. All procedures followed NIH guidelines and were approved by the UC San Diego IACUC committee.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEstrous cycle monitoring\u003c/h3\u003e\n\u003cp\u003eFor Experiment 1, HS rats (n\u0026thinsp;=\u0026thinsp;298) were vaginally swabbed using a sterile cotton swab dipped in Milli-Q\u0026reg; water one hour before drug exposure, either on the final short access (ShA 10) or the first progressive ratio (PR01) session, and the last long access (LgA 14). Following LgA 14, another PR session was conducted (PR02), followed by a test to measure resistance to footshock (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The vaginal cells were collected and placed on a glass microscope slide for visualization. Because the self-administration paradigm was conducted quarterly in separate cohorts (30\u0026ndash;60 rats per cohort), different animals were sampled at different timepoints. As such, the sample sizes reported for each behavioral measure do not sum to the total N, as some rats were assessed once and others across multiple timepoints. In an independent, smaller cohort of 39 HS rats, 28 of which received cocaine while 11 remained cocaine-naive, vaginal samples were collected every 24 hours (1 hour before the dark cycle) before the drug self-administration paradigm began for four consecutive days.\u003c/p\u003e \u003cp\u003eFor Experiment 2, the estrous cycle was monitored in sexually mature (Sengupta \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) female HS rats (n\u0026thinsp;=\u0026thinsp;81) at 7\u0026ndash;8 weeks of age. Samples were taken every 7\u0026ndash;9 hours (1 hour before the dark cycle, 8 hours into the dark cycle, and 7 hours before the dark cycle) across 5 days (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Given the multiple time points of sample collection, vaginal lavage was used since this method is less invasive (Cora et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Dalla et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and has shown consistent findings in past work (Sneddon et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). An additional cohort of rats (n\u0026thinsp;=\u0026thinsp;24) received vaginal lavage at 10\u0026ndash;11 weeks of age to assess if the estrous cycle stabilized in adulthood.\u003c/p\u003e \u003cp\u003eFor Experiment 3, estrous cycle was monitored in female Wistar rats (n\u0026thinsp;=\u0026thinsp;10) using vaginal lavage for 5 days every 12 hours (1 hour before the dark cycle and 1 hour before the light cycle) as a control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). This schedule of sampling and strain was used as Wistars have been validated as having consistent estrous cycling with up to 60\u0026ndash;70% of rats showing regular estrous cycle (Marcondes et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUnstained slides (n\u0026thinsp;=\u0026thinsp;298) were visualized in Experiment 1. All other samples were stained 24 hours post-collection using a Hema 3 stat pack (Fisher Scientific, Pittsburgh, PA), with slides dipped in Fixative (30 sec), Solution I (30 sec), and Solution II (15 sec). Estrous phases were identified using a BZ-X800 Analyzer (Keyence, Itasca, IL) based on cell type distribution (Waynforth and Flecknell \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Ajayi and Akhigbe \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sneddon et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Doyle et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Regular cycles followed established phase durations (Ajayi and Akhigbe \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), while irregular cycles exceeded these durations or deviated from typical patterns (Marcondes et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) (see Data Analysis section for details on how irregularities were categorized).\u003c/p\u003e\n\u003ch3\u003eApparatus \u0026 Behavioral Testing\u003c/h3\u003e\n\u003cp\u003eCocaine self-administration was conducted in operant conditioning chambers (Med Associates, St. Albans, VT, USA) housed in soundproof, ventilated cubicles, as previously described (Kallupi et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2026\u003c/span\u003e; Carrette et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sedighim et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; de Guglielmo et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Each chamber contained two retractable levers, with a cue light above the active lever, and a floor made of metal rods. Foot shocks (0.3 mA, 0.5 seconds) were delivered through an aversive stimulator (ENV-414S, Med Associates).\u003c/p\u003e \u003cp\u003eRats underwent 10 short-access (ShA; 2-hour) sessions followed by 14 long-access (LgA; 6-hour) sessions, conducted on weekdays, within two hours at the start of the dark cycle, as previously described (de Guglielmo et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Cocaine (0.5 mg/kg/infusion) was delivered intravenously on a fixed ratio schedule, with each infusion followed by a 20-second timeout. Inactive lever responses were recorded. Following self-administration, rats completed progressive ratio (PR) testing after ShA 10 (PR01) and LgA 14 (PR02), where the breakpoint was defined as the last completed ratio before a 60-minute period during which a ratio was not completed. A final one-hour foot shock session was conducted under the fixed ratio 1 conditions, with 30% of cocaine infusions paired with foot shocks. Additional details are available in the George lab protocol repository: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.protocols.io/workspaces/george-lab\u003c/span\u003e\u003cspan address=\"https://www.protocols.io/workspaces/george-lab\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Carrette et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eDrugs \u0026 Surgery\u003c/h3\u003e\n\u003cp\u003eCocaine HCl (National Institute on Drug Abuse, Bethesda, MD) was dissolved in 0.9% sterile saline. Postoperative care included subcutaneous flunixin (2.5 mg/kg) for analgesia and intramuscular cefazolin (330 mg/kg) to prevent infection. Catheter patency was maintained with a daily flush of heparin sodium (10 U/mL) and cefazolin in bacteriostatic saline.\u003c/p\u003e \u003cp\u003eRats in Experiment 1 were implanted with jugular vein catheters under isoflurane anesthesia (1\u0026ndash;5%) using aseptic techniques (Kallupi et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2026\u003c/span\u003e; Carrette et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sedighim et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; de Guglielmo et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Catheters were inserted into the right jugular vein, which was connected to a cannula secured with dental cement and mesh. The cannula port was externalized via a dorsal incision on the back of the rodent. Incisions were closed with Vetbond tissue adhesive (Santa Cruz Biotechnology Inc., Dalla, TX), and rats recovered for five days before behavioral testing.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eFor Experiment 1, cocaine infusions were normalized to infusions per hour. Self-administration data were analyzed using repeated measures (RM) One-Way or Two-Way Analysis of Variance (ANOVA) (session or session \u0026times; group as factors). If no interaction was detected, groups were collapsed for a One-Way ANOVA. In cases of missing values, a Mixed-Effects ANOVA was used. \u003cem\u003ePost hoc\u003c/em\u003e Dunnett\u0026rsquo;s tests assessed escalation vs. session 1. For all experiments, all raw data from the animals was evaluated, and any subject who did not complete the paradigm due to catheters failing, deaths, those identified as outliers, or those who exhibited anomalous behavior (de-escalation or unstable responding) inconsistent with prior work (de Guglielmo et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) were excluded. Exclusion of rats for these reasons was done without knowledge of their estrus cycles. To confirm the exclusion did not impact our results, we compared session 1 and 14 between the two separate cohorts, larger (n\u0026thinsp;=\u0026thinsp;298) and smaller cohort (n\u0026thinsp;=\u0026thinsp;22) using an unpaired t-test with Welch\u0026rsquo;s correction. Greenhouse\u0026ndash;Geisser correction was applied when sphericity was violated (ε\u0026thinsp;\u0026lt;\u0026thinsp;0.75).\u003c/p\u003e \u003cp\u003eFor Experiment 1, estrous phase effects on ShA10, LgA14, or PR01 infusions were analyzed using One-Way ANOVA, with phase as a between-subjects factor (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Given the lack of differences, phases were collapsed into high (proestrus\u0026thinsp;+\u0026thinsp;estrus) vs. low (metestrus\u0026thinsp;+\u0026thinsp;diestrus) estrogen groups and reassessed using an unpaired t-test with Welch\u0026rsquo;s correction. An addiction index was calculated using the variables of escalation, motivation, and compulsive-like behavior, represented as the averaged Z-scores of three dependent variables that together explained\u0026thinsp;~\u0026thinsp;50% of the variance (de Guglielmo et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Z-scores were determined as follows: the escalation index was the Z-score of an animal\u0026rsquo;s average intake over the last three days of LgA; the motivation index was the Z-score of breaking point during the PR session following LgA; and the compulsivity index was the Z-score of the number of infusions obtained during the session with contingent foot shock. The addiction index was then computed by averaging these three behavioral indexes. This addiction index resulted in four quartile groups categorized as resilient, mild, moderate, or severe. To assess estrous phase X addiction index associations on cocaine infusions, a Two-Way ANOVA was performed. If subjects did not have values or data for any of the variables needed to conduct the addiction index, they were excluded from this analysis (ShA10, n\u0026thinsp;=\u0026thinsp;10; LgA14, n\u0026thinsp;=\u0026thinsp;13; PR01, n\u0026thinsp;=\u0026thinsp;11).\u003c/p\u003e \u003cp\u003eTo assess the relationship between estrous cycling and cocaine self-administration, an irregularity index was assigned (0\u0026ndash;3) based on skipped phases, prolonged durations, or atypical phase sequences (Marcondes et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). A score of 0 indicated a regular 4\u0026ndash;5 day cycle with normal progression through each phase. A score of 1 reflected a single irregularity (e.g., one skipped or prolonged phase), 2 indicated two distinct irregularities across the monitoring period, and 3 indicated three irregularities or persistent atypical phase transitions. Spearman\u0026rsquo;s correlation was used to test associations between cycling irregularities and cocaine infusions during early ShA (first four sessions) and late LgA (last four sessions). The distribution of regular vs. irregular cycling across addiction index groups was determined, followed by a One-Way ANOVA to assess the influence of the addiction index.\u003c/p\u003e \u003cp\u003eEstrous phase duration was analyzed using Two-Way ANOVA (estrous phase \u0026times; timepoint). A subject was considered in a phase if present for at least one timepoint, with cumulative time estimated based on consecutive observations. Phase durations were summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. Percentages of regular vs. irregular cycling subjects were also calculated. Comparisons between rat strains were analyzed using a Chi Square Test (95% confidence interval). Parametric tests were applied only to continuous behavioral variables previously demonstrated to meet assumptions of normality and homoscedasticity, whereas ordinal measures (e.g., irregularity index) were analyzed using nonparametric statistics.\u003c/p\u003e \u003cp\u003eBehavioral data were collected using MED-PC IV software. Imaging data with insufficient samples or contamination (e.g., urine) were excluded. For Experiment 3, data for timepoint 3 were unavailable due to unforeseen circumstances. Two independent researchers verified estrous phase classification. Data analysis and visualization were conducted using GraphPad Prism 10.2.2, RStudio, Microsoft Excel, and BioRender. All values are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM unless otherwise stated, with statistical significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Effect sizes (η\u0026sup2;, 95% CI, and r\u0026sup2;) are reported where applicable.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eExperiment 1: Estrous phase is not associated with cocaine-related behaviors in HS rats\u003c/h2\u003e \u003cp\u003eA repeated measures One-Way ANOVA revealed a main effect of session during ShA (F\u003csub\u003e(4.616, 1366.4)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;63.890, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.178). A \u003cem\u003epost hoc\u003c/em\u003e Dunnett\u0026rsquo;s test revealed that sessions 2\u0026ndash;10 were increased compared to session 1 (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For LgA sessions, a Mixed Effects ANOVA found a main effect of session (F\u003csub\u003e(6.190, 1831.9)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;47.283, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.394). A \u003cem\u003epost hoc\u003c/em\u003e Dunnett\u0026rsquo;s test showed that sessions 4\u0026ndash;14 were higher compared to session 1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). An unpaired Welch\u0026rsquo;s t-test found no significant differences between number of infusions as a function of estrous phase on the last cocaine ShA session (t\u003csub\u003e(109.79)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.629, p\u0026thinsp;=\u0026thinsp;0.531, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.004) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) or the last cocaine LgA session (t\u003csub\u003e(137.916)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.942, p\u0026thinsp;=\u0026thinsp;0.316, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.006) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). When assessing cocaine infusions between the last ShA and LgA session, a Two-Way ANOVA found a significant main effect of session (F\u003csub\u003e(1,407)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;75.223, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, h\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.149) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. An unpaired Welch\u0026rsquo;s t-test found no significant differences between phases on the first PR session (t\u003csub\u003e(46.838)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1.144, p\u0026thinsp;=\u0026thinsp;0.258, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.027) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). A Two-Way ANOVA found a significant main effect of addiction index on the last cocaine ShA session (F\u003csub\u003e(3, 158)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;3.861, p\u0026thinsp;=\u0026thinsp;0.011), the last cocaine LgA session (F\u003csub\u003e(3, 216)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;55.378, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and the first PR session (F(3, 131)\u0026thinsp;=\u0026thinsp;7.706, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but no effects of estrous phase (\u003cb\u003eSuppl. Figure\u0026nbsp;1A-C\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eIn a subset of rats (n\u0026thinsp;=\u0026thinsp;39), when assessing daily cycling before exposure to cocaine, we found that 82.05% of the subjects had cycling irregularities and 17.95% exhibited regular cycling (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG-I). For self-administration sessions, the rats exposed to cocaine were assessed (n\u0026thinsp;=\u0026thinsp;28), but six of these were excluded due to catheter patency failure, deaths, or anomalous behavior (de-escalation) (as in previous work, (de Guglielmo et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)). To ensure this exclusion did not influence our results, we compared sessions 1 and 14 between the larger (n\u0026thinsp;=\u0026thinsp;298) and smaller (n\u0026thinsp;=\u0026thinsp;22) cohorts. An unpaired Welch\u0026rsquo;s t-test showed no differences between the cohorts for LgA1 (t\u003csub\u003e(26.879)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.162, p\u0026thinsp;=\u0026thinsp;0.872, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0009) or LgA14 (t\u003csub\u003e(24.584)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1.786, p\u0026thinsp;=\u0026thinsp;0.09, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.115). The larger cohort infused 11.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54 of 0.5 mg/kg/hour on LgA1 and 16.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46 of 0.5 mg/kg per hour on LgA14. The smaller cohort infused 11.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47 of 0.5 mg/kg/hour on LgA1 and 13.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60 of 0.5 mg/kg per hour on LgA14. A RM Two-Way ANOVA found a main effect of session for ShA (F\u003csub\u003e(2.772, 47.130)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1.101, p\u0026thinsp;=\u0026thinsp;0.001, h\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.166) and LgA (F\u003csub\u003e(3.928, 66.777)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.429, p\u0026thinsp;=\u0026thinsp;0.022, h\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.051). As no interaction was found, the data were collapsed across groups. A One-Way ANOVA for ShA found a main effect of session (F\u003csub\u003e(3.258, 58.650)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;8.835, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.130) and a main effect of session for LgA (F\u003csub\u003e(3.463, 58.875)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;3.209, p\u0026thinsp;=\u0026thinsp;0.024, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.698) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ).\u003c/p\u003e \u003cp\u003eNo correlation between irregularity index and cocaine infusions during the first four ShA sessions (r\u003csub\u003e(22)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.176, p\u0026thinsp;=\u0026thinsp;0.432, CI: -0.277 to 0.566) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eK) or the last four LgA sessions was observed (r\u003csub\u003e(22)\u003c/sub\u003e = -0.147, p\u0026thinsp;=\u0026thinsp;0.515, CI: -0.545 to 0.305) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eL). A One-Way ANOVA found no significant differences in cocaine infusions at ShA10, LgA11-14, PR01, or PR02 (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eM-Q). A One-Way ANOVA revealed a main effect of irregularity index on cocaine infusions during the shock session (F\u003csub\u003e(3,18)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;3.693, p\u0026thinsp;=\u0026thinsp;0.031, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.381). A post hoc Dunnett\u0026rsquo;s test showed that there was a significant difference between number of infusions for those with 0 vs 3 cycling irregularities (p\u0026thinsp;=\u0026thinsp;0.034) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eP) For rats with regular cycling, 16.67% (n\u0026thinsp;=\u0026thinsp;1) were characterized as resilient, 33.33% (n\u0026thinsp;=\u0026thinsp;2) as mild, and 50% (n\u0026thinsp;=\u0026thinsp;3) as moderate for the addiction index. For the rats with irregular cycling, 25% (n\u0026thinsp;=\u0026thinsp;4) were characterized as resilient, 18.75% (n\u0026thinsp;=\u0026thinsp;3) as mild, 18.75% (n\u0026thinsp;=\u0026thinsp;3) as moderate, and 37.5% (n\u0026thinsp;=\u0026thinsp;6) as for the severe addiction index (\u003cb\u003eSuppl. Figure\u0026nbsp;2A\u003c/b\u003e). When assessing if the addiction index varied by irregularity index, a One-Way ANOVA discovered a main effect of addiction index (F\u003csub\u003e(3,18)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;4.114, p\u0026thinsp;=\u0026thinsp;0.022, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.407) (\u003cb\u003eSuppl. Figure\u0026nbsp;2B\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperiment 2: Estrous cycle irregularities are observed in young adult and adult female HS rats\u003c/h3\u003e\n\u003cp\u003eWe found that 96.15% of the young adult rats (n\u0026thinsp;=\u0026thinsp;78) had cycling irregularities and 3.85% (n\u0026thinsp;=\u0026thinsp;3) had a regular cycle (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-E). A significant main effect of estrous phase was observed when assessing the percentage of subjects in each phase across time point (F\u003csub\u003e(3, 42)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;79.29, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, h\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;84.99) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). When assessing the duration of each estrous phase in young adult female rats, the time spent in each phase (in hours) are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. When evaluating the percentage of rats that experienced each estrous phase at least once, we observed that 100% of the rats experienced proestrus and estrus, 82.72% experienced metestrus, and 53.09% experienced diestrus.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe found that 100% of the adult female HS rats (n\u0026thinsp;=\u0026thinsp;24) had cycling irregularities (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF-H). A significant main effect of estrous phase was observed when assessing the percentage of subjects in each phase across time point (F\u003csub\u003e(3, 42)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;11.05, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, h\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;40.48) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). When assessing the duration of each estrous phase in adult female rats, the time spent in each phase (in hours) are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. When evaluating the percentage of rats that experienced each estrous phase at least once, we observed that 100% of the rats experienced proestrus and estrus, while 95.83% experienced metestrus, and 54.17% experienced diestrus.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eExperiment 3: Wistar rats show regular estrous cycling\u003c/h2\u003e \u003cp\u003eSixty percent of the female Wistar rats (n\u0026thinsp;=\u0026thinsp;10) had regular cycling while the other forty percent did not (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB \u003cb\u003e\u0026ndash; D\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe distribution of regular versus irregular cycles varied strongly by strain, χ\u0026sup2;(2, N\u0026thinsp;=\u0026thinsp;115)\u0026thinsp;=\u0026thinsp;88.14, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001. Nearly all HS rats displayed irregular cycles, whereas a majority of Wistars cycled regularly. When comparing the length of the proestrus phase between Wistar, young adult, and adult HS rats, a One-Way ANOVA identified a significant main effect (F\u003csub\u003e(1, 112)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;9.19, p\u0026thinsp;=\u0026thinsp;0.0002, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.14). A \u003cem\u003epost hoc\u003c/em\u003e Holm Sidak\u0026rsquo;s test revealed that the adult HS rats had a longer proestrus phase compared to the young adult HS rats (p\u0026thinsp;=\u0026thinsp;0.001) and adult Wistars (p\u0026thinsp;=\u0026thinsp;0.0008). When assessing the length of the estrus phase between groups, a One-Way ANOVA discovered a significant main effect (F\u003csub\u003e(1, 112)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;5.92, p\u0026thinsp;=\u0026thinsp;0.0036, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.10). A \u003cem\u003epost hoc\u003c/em\u003e Holm Sidak\u0026rsquo;s test found that the adult HS rats had a shorter estrus compared to the young adult HS rats (p\u0026thinsp;=\u0026thinsp;0.004) and adult Wistars (p\u0026thinsp;=\u0026thinsp;0.026). When comparing the length of the metestrus phase between groups, a One-Way ANOVA discovered a significant main effect (F\u003csub\u003e(1, 112)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;11.91, p\u0026thinsp;=\u0026thinsp;0.004, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.18). A \u003cem\u003epost hoc\u003c/em\u003e Holm Sidak\u0026rsquo;s test identified that young adult (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and adult (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) HS rats had a shorter metestrus phase compared to adult Wistars. When assessing the length of the diestrus phase between groups, a One-Way ANOVA revealed a significant main effect (F\u003csub\u003e(1, 112)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;5.14, p\u0026thinsp;=\u0026thinsp;0.007, r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.08). A \u003cem\u003epost hoc\u003c/em\u003e Holm Sidak\u0026rsquo;s test identified that young adult (p\u0026thinsp;=\u0026thinsp;0.017) and adult (p\u0026thinsp;=\u0026thinsp;0.005) HS rats had a shorter diestrus phase compared to adult Wistar rats (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLength of Estrous Phases in Young Adult and Adult HS Rats and Adult Wistar Rats (in hours)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEstrous phase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStatistical Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eCycle Length (hours)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYoung Adult HS\u003c/p\u003e \u003cp\u003e(7\u0026ndash;8 weeks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdult HS\u003c/p\u003e \u003cp\u003e(10\u0026ndash;11 weeks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdult Wistars\u003c/p\u003e \u003cp\u003e(10\u0026ndash;11 weeks)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eProestrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMedian\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eRange\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u0026ndash;57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u0026ndash;56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEstrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;6.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMedian\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eRange\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u0026ndash;63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026ndash;48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMetestrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMedian\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eRange\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026ndash;36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDiestrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMedian\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eRange\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u0026ndash;31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u0026ndash;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003eLength of Estrous Phases in Young Adult and Adult HS Rats and Adults Wistar Rats (in hours).\u003c/b\u003e \u003cem\u003eAverage and range of rats were in each phase of the estrous cycle. Data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM, the median, or ranges. Young adults (n\u0026thinsp;=\u0026thinsp;81), adult (n\u0026thinsp;=\u0026thinsp;24), and Wistar (n\u0026thinsp;=\u0026thinsp;10) rats. (\u003c/em\u003e\u003csup\u003e\u003cem\u003e#\u003c/em\u003e\u003c/sup\u003e \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 Young Adult vs. Adult HS rats; Holm Sidak\u0026rsquo;s)\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe found that baseline irregular estrous cycling in female HS rats does not influence overall cocaine intake or escalation, but severe cycling irregularities were associated with increased levels of footshock-resistant cocaine intake. Given the lack of data on estrous cycling in drug-naive HS rats, we conducted additional experiments. HS females lack the regular estrous cycling observed in other outbred lines, such as Wistar rats. These findings conflict with the existing literature and suggest that the HS rats may be a powerful model to investigate estrous cycle irregularities.\u003c/p\u003e \u003cp\u003eWe did not find any direct associations between estrous phase and cocaine self-administration during the acquisition (ShA10), escalation (LgA14), or progressive ratio (PR01) phases when estrous samples were collected at these timepoints. These null findings should be interpreted with caution, as a subset of HS rats revealed that less than 20% of the subjects exhibited baseline regular cycling patterns before cocaine exposure. We characterized an irregularity index (criteria determined from (Marcondes et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2002\u003c/span\u003e)) to assess whether the baseline irregularities before self-administration correlated with future cocaine-related behaviors. Estrous cycling irregularities before drug exposure were not correlated with early short access or long-access self-administration. In addition, cycling irregularities were not associated with difference in cocaine infusions during acquisition (ShA7-10), escalation (LgA11-14), or progressive ratio (PR01 or PR02). We did see that females with severe cycling irregularities responded more for cocaine despite a footshock. This finding agrees with one other study where female Sprague-Dawley rats who had greater preference for larger, risker rewards and showed more cycling irregularities (Truckenbrod et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These results suggest that estrous cycle irregularities may lead to cocaine under stressful conditions resulting in an increase of aversion-resistant cocaine use. However, because no significant effects were observed for escalation of intake or motivation under progressive ratio conditions, for future studies it will be important to further evaluate the relationship between estrous cycle irregularities and aversion-resistant drug seeking. Additional paradigms assessing aversion resistance, such as varying shock probability and intensity, higher progressive ratio schedules, varying aversive stimuli (e.g., shock vs. quinine), and drug\u0026ndash;alternative procedures will be critical for determining the generalizability and significance of these effects.\u003c/p\u003e \u003cp\u003eIt remains unclear whether cocaine exposure further disrupted the cycle in this study, as for logistical reasons we couldn\u0026rsquo;t perform a week-long estrous cycle analysis after escalation of cocaine intake. As most rats showed irregularities before drug exposure, it is unclear how to assess if cocaine further disrupted the cycle. While some studies link high estradiol to increased cocaine use (Lynch et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Feltenstein and See \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Feltenstein et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), others report no association or cue-dependent effects (Lacy et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Doncheck et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Proestrus and estrus consistently correlate with greater motivation in progressive ratio and reinstatement tests (Roberts et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Feltenstein and See \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Lynch \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Lacy et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Nicolas et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Doncheck et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Corbett et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, we saw no association with the progressive ratio session, which deviates from these findings. As mentioned above, one study has seen that females with greater cocaine intake also showed greater preference for larger, risker rewards and showed more cycling irregularities (Truckenbrod et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This study saw that there were prolonged estrus and/or proestrus phases (Truckenbrod et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) while another linked stressed-related cocaine seeking with the diestrus and proestrus phases (Doncheck et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As such, further investigation is warranted to determine which phases are associated with footshock-resistant cocaine intake and if cycling irregularities are a driving factor of this behavior.\u003c/p\u003e \u003cp\u003eSince the HS rats are ideal for assessing individual differences (Solberg Woods and Palmer \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), we examined whether estrous cycle irregularities prior to cocaine exposure correlate with addiction-related behaviors using an addiction index (Carrette et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; de Guglielmo et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Rats exhibiting irregular estrous cycling were disproportionately represented at both the resilient and severe ends of the Addiction Index categories, corresponding to the lowest and highest addiction-related phenotypes. This bimodal pattern suggests that pre-existing cycle irregularities may be associated with divergent vulnerability trajectories rather than a uniform effect on cocaine intake. Although the sample size limits definitive conclusions, these findings indicate that irregular cycling may contribute to either reduced or heightened addiction-like behavior. Previous studies have shown that cocaine exposure can disrupt estrous cycling (Raap et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Truckenbrod et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, our data provide initial evidence that pre-existing irregularities may also influence subsequent drug-taking behavior. Because most studies exclude subjects with irregular cycling (Dalla et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), our approach offers a unique opportunity to examine cycle irregularity as a factor that may shape individual vulnerability to cocaine use.\u003c/p\u003e \u003cp\u003eOriginally, our goal was to investigate whether cocaine disrupts the estrous cycling in HS rats. We hypothesized that we would observe regular phase progression with disruptions following cocaine exposure, as previously reported (Raap et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Truckenbrod et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, we found that 96.15% of young adults and 100% of adults exhibited irregular cycling with no apparent pattern in drug-na\u0026iuml;ve subjects. The timescale in each phase did not match previous reports of the estrous cycle in other strains of rats, such as Lewis, Wistar, and Sprague-Dawley (Ajayi and Akhigbe \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In HS rats, we observed that the proestrus and metestrus were extended while estrus and diestrus were blunted in both young adult and adult rats. Proestrus was the most prominent phase, while diestrus was the least, contradicting the literature for other strains (Marcondes et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Goldman et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Cora et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ajayi and Akhigbe \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similar proestrus extension has been observed in the Goto-Kakizaki rat strain, potentially due to hypothalamic-pituitary-gonadal axis dysregulation (Pinto-Souza et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which could explain our findings. Our results were surprising as we are unaware of any other rodent model that shows irregularities to this extent and requires further exploration.\u003c/p\u003e \u003cp\u003eOur control experiment with Wistar rats showed 60% regular cycling, consistent with prior reports (Marcondes et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Elsayed et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although Wistar rats were sampled every 12 hours and HS rats every 7\u0026ndash;9 hours, this difference in timing is unlikely to explain the large strain differences we observed. Irregular cycling occurred in 96\u0026ndash;100% of HS rats compared to only 40% of Wistars, a highly significant contrast (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Importantly, irregularity in HS rats was apparent both when assessed at a single timepoint and when monitored across multiple timepoints, indicating that the higher sampling resolution did not inflate irregularity detection. Given similar irregularity patterns observed in other strains (Karim et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Mourlon et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Schuh et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) with rates between 9\u0026ndash;40% (Marcondes et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Karim et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Mourlon et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), methodological error is unlikely. Vaginal swabbing, lavages, and staining have been used in our studies in Wistar rats (Doyle et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and C57BL/6J mice (Sneddon et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) without any methodological issues.\u003c/p\u003e \u003cp\u003eAlthough estrous variability is common (Robert et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), HS rats show unprecedented irregularities. Cycle length can vary from 3\u0026ndash;38 days in rats (Long and Evans \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1922\u003c/span\u003e; Westwood \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), though most studies phase across 4\u0026ndash;5 days (Marcondes et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Cora et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ajayi and Akhigbe \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Cycle and phase length may be different in these rats, but that does not account for cellular variability. Sexual maturation can range from 30 to 38 days in female rats (Spear \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Lewis et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Lenschow et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). We initially attributed the irregularities at 7\u0026ndash;8 weeks to sexual immaturity or stress from rehousing, but the respective irregularities persisted at 10\u0026ndash;11 weeks, suggesting permanence.\u003c/p\u003e \u003cp\u003eWhile excluding rats with irregular cycling is recommended (Dalla et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Holalagoudar et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) to simplify data collection, this approach does not reflect the human population where 14% \u0026minus;\u0026thinsp;25% of women experience cycling irregularities (Nobles et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Flickr). Women with menstrual cycle irregularities show 40% higher rates of mental disorders, including substance use disorder (Poyastro Pinheiro et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Barron et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Nillni et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Algars et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Toffol et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Gleeson et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Yu et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Reilly et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ajari \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Milano et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Green and Graham \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As cycling irregularities are associated with mental health outcomes, understanding the factors driving cycling regularity in humans and rodents is crucial. HS rats may be valuable for exploring the genetic factors influencing cycle irregularities and mental health, as we observed that irregular cycling is linked to more severe cocaine addiction-related behaviors. Additionally, HS rats display increased fear, anxiety, and depressive-like behaviors associated with heightened prolactin levels (Lopez-Aumatell et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; L\u0026oacute;pez-Aumatell et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; D\u0026iacute;az-Mor\u0026aacute;n et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), though no estrous cycle associations were measured. A meta-analysis found that increased anxiety-like behaviors are tied to lower estrogen levels (Pestana and Graham \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The shortened or skipped metestrus and diestrus phases in female HS rats may lead to increased exposure to estrogen due to the more frequent occurrence of estrus and proestrus phases, potentially affecting their anxiety profile.\u003c/p\u003e \u003cp\u003eOne limitation of this study is that estrous cycling was assessed in separate cohorts of young adult and adult rats rather than longitudinally within the same subjects. Although such an approach could provide additional insight into whether specific irregular patterns are stable within individuals subjects, the extremely high prevalence of irregular cycling in both age groups (96\u0026ndash;100%) indicates that irregularity is a robust feature of this strain. Therefore, a longitudinal design would be unlikely to alter the primary conclusion that estrous cycling is broadly irregular across development. These results are based on vaginal cytology, not direct hormonal measurement. While this does limit our conclusions, vaginal cytology remains the most reliable method to assess estrous fluctuations in rodents (Dalla et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Serum hormone measurement was considered, but due to irregular cycling in HS rats, determining an appropriate non-invasive blood collection schedule was not feasible for accurately characterizing the cycle. Additionally, ELISA measurement of estradiol in rodents can vary (Chan et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), supporting the continued assessment of vaginal smears. As such, vaginal smears were the most accurate assessment of the estrous cycle at our disposal.\u003c/p\u003e \u003cp\u003eThis study is the first to demonstrate that female HS rats exhibit irregular estrous cycling in the absence of drug exposure. While these irregularities were not associated with uniform changes in addiction-like behavior, rats with severe cycling disruptions showed greater footshock-resistant cocaine responding compared to animals with no irregularities. Together, these findings suggest that estrous cycle irregularity may differentially influence specific aspects of addiction-related behavior rather than producing a single, consistent phenotype. Given the increasing use of HS rats in behavioral and genome-wide studies, characterizing these endogenous cycle disruptions is important, as they may provide insight into genetic and hormonal mechanisms underlying cycling irregularities observed in women.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: EAS and OG. Methodology: EAS and OG. Formal analysis: ES, SC, SS, and SZ. Investigation: EAS, SC, KB, PK, SLP, MRD, BCS, DNO, and MB. Writing \u0026ndash; Original Draft: EAS, SC, and KB. Writing \u0026ndash; Review and Editing: EAS, SC, KB, SLP, MRD, SZ, SS, GdG, MK, LLGC, AAP, and OG. Visualization: ES and SZ. Supervision: EAS and OG. Resources: AAP. Project Administration: EAS, MB, GdG, MK, LLGC, and OG. Funding acquisition: EAS, LLGC, and OG.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank the Preclinical Addiction Research Consortium at UCSD. This work was supported by the National Institute on Drug Abuse (U01DA04379 and U01DA044451 to OG, P50DA037844 and P30DA060810 to AAP, and K00DA057923 to EAS) and the Burroughs Wellcome Fund (to EAS).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll images and data for this project are available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAjari EE (2021) Connecting the dots between mental and menstrual health: An exploratory review. 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J Affect Disord 210:43\u0026ndash;48\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"estrous cycle, Heterogenous Stock rats, females, cocaine, operant self-administration, Wistar rats, hormonal fluctuations","lastPublishedDoi":"10.21203/rs.3.rs-8950642/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8950642/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eRationale:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eHormonal fluctuations throughout the estrous cycle are hypothesized to influence drug-related behaviors. Preclinical models show that some cocaine-related behaviors are influenced by the estrous cycle. However, the extent to which the estrous cycle modulates cocaine self-administration in outbred heterogeneous stock (HS) rats is unknown.\u003c/p\u003e\u003cp\u003e\u003cb\u003eObjectives\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe aimed to examine the relationship between estrous phases and cocaine self-administration behavior in HS rats using an operant model of extended access to cocaine self-administration.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe assessed the escalation of intake, breaking point, and resistance to foot shock. Using vaginal swabbing and lavage techniques, we characterized the relationship between estrous phase and cocaine behaviors. We then comprehensively evaluated estrous cycling patterns in young adult and adult HS rats, comparing them with Wistar rats.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eEstrous phase showed no association with cocaine self-administration in HS rats. 82% of female HS rats exhibited irregular estrous cycling with variability to the phase length, even in the absence of drug exposure, a phenomenon not observed in the Wistar strain. Females with irregular cycling showed greater footshock-resistant cocaine intake.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study provides the first evidence that most female HS rats exhibit irregular estrous cycling. In HS rats, the estrous phase \u003cem\u003eper se\u003c/em\u003e has no major influence on cocaine self-administration, whereas cycling irregularity was associated with specific addiction-related behaviors, including footshock-resistant intake. As HS rats gain popularity in behavioral and genome-wide studies, understanding these cycle disruptions is crucial as they may reveal genetic links into cycling variability and individual differences to aspects of cocaine use.\u003c/p\u003e","manuscriptTitle":"High Incidence of Estrous Cycle Irregularities in Heterogeneous Stock (HS) Rats is Associated with Footshock-Resistant Cocaine Intake","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-25 15:27:58","doi":"10.21203/rs.3.rs-8950642/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"74091288-fab4-4a70-b5fa-9e70ecf41cba","owner":[],"postedDate":"February 25th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:28:06+00:00","versionOfRecord":{"articleIdentity":"rs-8950642","link":"https://doi.org/10.1007/s00213-026-07041-8","journal":{"identity":"psychopharmacology","isVorOnly":false,"title":"Psychopharmacology"},"publishedOn":"2026-03-24 16:11:58","publishedOnDateReadable":"March 24th, 2026"},"versionCreatedAt":"2026-02-25 15:27:58","video":"","vorDoi":"10.1007/s00213-026-07041-8","vorDoiUrl":"https://doi.org/10.1007/s00213-026-07041-8","workflowStages":[]},"version":"v1","identity":"rs-8950642","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8950642","identity":"rs-8950642","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}