Female rats are more vulnerable to binge drinking behavior in an operant self-administration paradigm: implication for transition to alcohol use disorders

Female rats are more vulnerable to binge drinking behavior in an operant self-administration paradigm: implication for transition to alcohol use disorders | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Female rats are more vulnerable to binge drinking behavior in an operant self-administration paradigm: implication for transition to alcohol use disorders Jérôme Jeanblanc, Amélie Soyer, Mickaël Naassila This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8561890/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Biology of Sex Differences → Version 1 posted 11 You are reading this latest preprint version Abstract While binge drinking can significantly impact health negatively, it has become increasingly important to understand how sex differences contribute to this hazardous behavior, which may also serve as a risk factor for alcohol use disorder. We employed the binge drinking experimental model we developed previously to specifically analyze sex differences. Forty male and 40 female Long Evans rats were tested in the alcohol self-administration procedure, operationalized as alcohol responding in short daily session. We tested other parameters, including motivation, seeking, responses during cue omission sessions, withdrawal scores, and relapse after abstinence. We also conducted experiments to assess perseverance despite satiety. For the analysis we used first an unsupervised clustering approach using drinking speed and frequency of alcohol responses and then we analyzed our data by taking sex as the differentiating factor. Unbiased clustering analysis revealed four distinct groups: Fast Bingers, Bingers, Extreme Bingers and Social drinkers. Higher alcohol consumption and faster consumption speed correlated with elevated withdrawal scores. Sex-related differences were observed, with females outnumbering males in Extreme bingers. Females also exhibited higher alcohol-seeking behavior, relapse rates, and withdrawal scores. In addition, females exhibit lower sensitivity to devaluation in the satiety test. Our results suggest that females display greater vulnerability to cue-mediated alcohol-seeking behaviors and a more inflexible behavior. This underscores the importance of considering sex as a biological variable in both preclinical and clinical research on binge drinking behaviors that is not only a hazardous behavior but may also be a critical factor in AUD vulnerability, particularly in females. Binge Drinking alcohol sex differences operant self-administration relapse withdrawal Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Plain English summary Binge drinking is a specific pattern of alcohol consumption based on consuming large amounts in a short period of time. Binge drinking is known to be a risk factor to the transition to latter alcohol addiction. A recent study has shown greater brain damage in women who binge drink than in men. Thus, in the present study we used the animal model we developed to mimic the binge drinking behaviour in rats. We used 40 male and 40 female adult rats to evaluate a series of behaviors associated to the consumption of alcohol such as motivation, seeking, relapse and transition to drug addiction. In a first analysis combining both sexes we found 4 distinct groups of drinkers, the bingers, the fast bingers, the extreme bingers and finally the social drinkers that do not drink much alcohol. The distribution of the sexes was not well balanced in the groups with the extreme bingers represented mostly by females. We then evaluated the differences between both sexes and we found that the females consumed more alcohol than the males, females were more sensitive to the contextual cues associated to each delivery of alcohol. We also found that females are more vulnerable to addiction after chronic binge drinking and that they will relapse at higher levels than males. Overall, we demonstrate the need to include the females in our preclinical studies because they do not display similar sensitivity to drug consumption than males. Highlights Cluster analysis based on quantity of alcohol consumed during a 15-min operant self-administration session and speed of consumption revealed 3 different groups of ‘bingers’ and a group of ‘social drinkers’. The ‘extreme bingers’ differ from the others by the quantity consumed and the ‘fast bingers’ differ from the ‘bingers’ by consuming the same amount of alcohol but twice faster. The ‘extreme bingers’ group is composed by more than 70% of female rats The sex-based analysis demonstrates a higher sensitivity to the cue associated to the delivery of alcohol in females Females are less sensitive to the devaluation of the reward than the males leading to perseverance of the operant behavior despite satiety and higher levels of relapse after abstinence. Introduction Binge drinking is a dangerous and harmful alcohol consumption behavior characterized, among other criteria, by large quantities ingested over a short period of time 1 . Unlike patients with alcohol use disorders (AUD), binge drinkers experience intermittent episodes of consumption interspersed with periods of non-consumption 2 . Binge drinking behavior is rather heterogeneous behavior. We recently proposed a mathematical model to better categorize binge drinking behavior in young adults, and we identified the existence of four groups based on the consumption profile: low-risk, hazardous, binge, and high-intensity binge drinking 3 . Furthermore, binge drinking is considered a factor involved in the development of AUD. A study in France has shown that frequent binge drinking between 18 and 25 years (4+/5 + drinks/occasion for females/males, more than twice a month) leads to an approximately threefold increased risk of developing AUD at adulthood (between 25 and 45 years) 4 . Another study in the United States showed that nearly 80% of those young adults who reported engaging in high-intensity drinking (10 + drinks in a row) at age 29/30 later reported AUD symptoms at age 35 5 . Therefore, it is conceivable that a chronic pattern of binge drinking is associated with the transition to addictive behavior, and it is possible, in particular, that the repetitive aspect of binge drinking behavior facilitates the establishment of habit learning or attentional biases, that may play an important role in AUD. While AUD is more commonly found in men, there is a notable and accelerating rise in the number of women affected by AUD, particularly among adolescents 6 . Women exhibit greater susceptibility to the medical consequences associated with alcohol consumption, such as alcohol-related liver disease. This trend is not solely attributed to sex-based differences in alcohol pharmacokinetics; women also demonstrate an expedited progression from initial alcohol use to the onset of AUD. The current knowledge on binge drinking behavior has not clearly demonstrated sex-related differences in vulnerability, not only to this behavior but also regarding its role in the development of AUD or some of its symptoms. However, some studies have shown sex-related differences in young binge drinkers. For example, one study that used clustering analysis, suggested that male and female binge drinkers should not be considered a unitary group, but rather a population of individuals that encompasses at least 2 distinct personality patterns with Cloninger's type I (high harm-avoidance) and II (high novelty-seeking) AUD typology 7 . Various animal models have been developed to study binge drinking behavior 8 . We demonstrated that daily access to an alcohol self-administration operant chamber for just 15 minutes over several months facilitates the emergence of a behavior resembling binge drinking in humans, with rapid consumption leading to significant blood ethanol levels and ataxia in rats 9 . In addition, we identified using the same model, that binge drinking behavior is dependent upon genetic factors since among three different outbred rat strains, the Long Evans one is more prone to binge drinking 10 . This model is also characterized by excellent predictive validity, as we have demonstrated that various treatments for AUD are effective 11 . By definition, binge drinking is characterized by the excessive consumption of alcohol within a very short period of time. Therefore, reducing the time required to access alcohol, as observed during happy hours in humans, acts as a facilitator of binge drinking behavior. In contrast to the study of Wheeler et al. 12 , which concluded that shortening the session duration does not promote binge drinking, our operant self-administration paradigm is based on a fundamentally different behavioral and motor framework. In their study, rats were trained on a “sipper” device in which a single operant response grants access to the drinking spout for a fixed period, and they then assessed the effect of reducing session duration (30 to 15 min) on appetitive and consummatory behaviors. This type of setup allows for prolonged drinking bouts per reinforcement, minimizes motor demands, and hardly engages automatization or habit formation (one response = long fluid access). By contrast, in our procedure, each reinforcement delivers a single 0.1 mL drop of ethanol (FR-3), which requires ~ 100 active responses per session instead of a few dozen, enforces a “sip-paced” drinking pattern, and deliberately challenges the motor/repetitive components involved in the automatization of alcohol seeking. Shortening the session to 15 min in this context produces precisely the kind of “binge-like” profile—rapid intake, elevated BECs, and behavioral alterations—that validates the face validity of the model. More broadly, several studies have shown that temporal compression increases “front-loading” and can even bring male rats closer to the rapid intake phenotype typically observed in females under FR schedules, directly contradicting Wheeler’s general statement when extrapolated to other operant contingencies 13 . In sum, comparing our results to those of Wheeler as if the two approaches were interchangeable neglects crucial mechanistic differences: (i) mode of delivery (continuous sipper access vs. unitary drops), (ii) response cost (FR-1/prolonged access vs. FR-3/0.1 mL), and (iii) motor load and propensity for stimulus–response automatization. Wheeler’s conclusion that “shortening the session does not matter” therefore cannot be generalized to protocols in which alcohol intake is discretized and response-costly—precisely those paradigms designed to model operant binge drinking and the development of automatisms. It is also important to emphasize that any direct comparison between paradigms requires isomorphic contingencies—namely equivalent session duration, response cost, delivery granularity, and mode of access (continuous sipper vs. unitary drops). In the absence of such equivalence, reducing session length in a sipper model primarily decreases the number of opportunities to respond and the total available volume, whereas in an FR-3 schedule, the same temporal compression intensifies early responding and promotes front-loading. This distinction is critical, as it is precisely this front-loading dynamic that operant binge models are designed to capture. Here, we sought to characterize sex differences in chronic voluntary binge drinking and especially in several operant self-administration criteria such as ingested alcohol, drinking speed, alcohol seeking in a drug omission session and motivation. Reward comprises learning (cue associations), hedonic (“liking”), and motivational (“wanting”) components 14 . Initially linked with a reward, conditioned stimuli have the potential to transform into independent motivational cues, prompting both appetitive approach and consummatory behaviors 14 . The transition from casual to compulsive alcohol use is believed to coincide with heightened motivation to get alcohol. In animals, this escalated exertion of effort can be quantified through progressive ratio (PR) schedules of reinforcement. We also measured other criteria more linked to addiction such as withdrawal symptoms after abstinence and perseverance of the operant self-administration despite the devaluation of the reward by a satiety test. Thus, and as we recently did in humans, we used first a clustering approach to better characterize different binge drinking patterns and since the results revealed sex-related differences we further determined criteria related to addictive behaviors in both sexes. Materials and Methods Animals Forty males and forty females Long Evans rats were purchased from Janvier Labs (Le Genest-Saint-Isle, France) at the age of 7 weeks. The time line of all experiments is presented on Fig. 1 A. The animals were housed individually without enrichment in a thermo-regulated animal facility (22 ± 1°C and 40 ± 10% humidity), with a 12/12hrs light/dark cycle (light on at 8:00 am). All animals were provided with water and food ad libitum . The behavioral tests were performed between 9:00 and 12:00 am. The experimental procedures were performed according to the principles set forth by the Council responsible for the protection of animals used for experimental purposes (EEC N° 86/609) and approved by the local ethical committee (CREMEAP, APAFIS#26615). Reagents Ethanol, (ETOH 96°) was purchased from VWR (Strasbourg, France) and was diluted in tap water at the concentration of 20% (v/v). Voluntary Operant Binge Drinking The procedure of voluntary operant binge drinking is identical to the one already described (9). Briefly, rats were first submitted to 4 weeks of a two-bottle choice intermittent access paradigm with water solution available every day and with 20% EtOH solution available every other day (Mondays, Wednesdays and Fridays) for 24 hrs starting at 2:00 pm. At the end of this procedure, rats underwent training sessions of operant self-administration for EtOH (20% v/v) in Med Associates operant cages (ENV-008, Med Associates, Albans, VT, USA). Two overnight sessions under a fixed ratio 1 schedule were followed by 5 sessions of each schedule and duration: 1 hr-FR1, 1hr-FR3, 30 min-FR3 and finally 15 min-FR3. Maintenance of binge drinking behavior was achieved over 2 months (5 sessions a week). Ethanol reward was a 0.1 mL drop of the 20% ethanol solution and its delivery was accompanied by contextual cues: a light (within the delivery compartment) and a tone stimulus both for 3 seconds. The cages are controlled and the behaviors recorded through the MEP IV software (Med Associates, Albans, VT, USA). Blood Ethanol Concentration Blood collection was performed at the end of the maintenance period of 1 month under the 15 min-FR3 sessions, once stable EtOH consumption was well established. Rats undergoing EtOH operant binge drinking were anesthetized under 5% IsoFlurane (IsoVet, Piramal HealthCare, Northumberland, UK) 5 min after the end of the self-administration session for 2 minutes. Blood (~ 300 µL) was collected from the sublingual vein in heparinized tubes before centrifugation to collect the plasma and stored at 4°C until analysis. We used the ANALOX system (Imlab SARL, Lille, France) in order to evaluate the blood ethanol concentrations (BECs). AUD-associated behaviors Motivation Hypermotivation to obtain the drug, reflected by an increased willingness to work for it, is a core hallmark of addictive behavior across substances. It captures the transition from controlled, recreational intake to compulsive drug seeking, and is therefore a critical dimension of addiction-like phenotypes. After ten sessions under a fixed-ratio 3 (FR3) 15-min reinforcement schedule, animals’ motivation to self-administer alcohol or saccharin was assessed using a progressive-ratio reinforcement protocol. In this procedure, the response requirement for each subsequent reward gradually increases (3, 4, 5, 7, 9, 12, 15, 17, 20, 22, 25, 28, 30, 33, and 35 responses) 15 . Eventually, animals cease pressing the active lever; this final ratio completed is termed the breaking point, and serves as an index of the animal’s motivational drive to obtain ethanol. Sessions lasted 30 minutes to ensure sufficient time for animals to complete the progressive schedule. 15 . Seeking (Drug Omission test) Drug seeking in the absence of the drug is commonly used as an operational measure of drug craving and diminished behavioral control in animal models. In our protocol, loss of control and/or craving for alcohol was assessed during a dedicated session in which no alcohol solution was delivered despite active lever presses, while all conditioned cues previously associated with alcohol remained present. The persistence of active lever pressing under these omission conditions is interpreted as an increased motivational drive for alcohol and reflects a higher level of craving-like behavior and of loss of control. Cue Omission test One of the behavioral criteria of addiction is the excessive sensitivity to environmental cues associated with drug consumption, which can by themselves trigger or intensify drug-seeking behavior. The Cue Omission test is useful for assessing this cue reactivity, namely the disproportionate motivational value acquired by stimuli predicting reward delivery. Although this test does not directly measure attentional capacities or attentional biases in the strict cognitive sense, it provides insight into the salience of drug-associated cues and the degree of behavioral automatization: a strong cue-controlled response is typically observed in addictive-like behaviors. In our operant model of binge drinking, the cues associated with solution delivery gradually acquire secondary reinforcing value. It is well established that such contextual cues can elicit consumption-related behaviors. Therefore, to evaluate the vulnerability to these cues in our model, we conducted a Cue Omission session. Sensitivity to the cue associated with delivery was assessed in a session in which the drug was still delivered after three active lever presses, but without presentation of the cues normally paired with its delivery. In our paradigm the drug is still delivered after 3 active lever presses but no cues were associated with it. Relapse after chronic binge drinking After 11 weeks of operant binge-drinking sessions, rats underwent an ethanol deprivation period during which they were not exposed to the operant self-administration chambers for 10 consecutive days. Following this abstinence interval, animals were reintroduced into the operant chambers for a standard binge-drinking session in which alcohol-associated cues were presented and ethanol was again available. To facilitate the initiation of relapse, a priming free drop of ethanol was delivered at the onset of the session. This procedure enables the assessment of relapse-like drinking behavior following chronic intermittent alcohol exposure. Withdrawal Score Withdrawal syndrome refers to the emergence of physical signs following drug cessation and is a hallmark of dependence (signs of physical dependence in AUD). To quantify withdrawal severity, we adapted the scoring system previously developed by Gilpin and colleagues (14). After five days of abstinence, rats were observed for several minutes in their home cage, and their behavior was evaluated according to the following criteria: (i) aggression and/or vocalizations; (ii) posture (immobility or slowing); (iii) tail rigidity; (iv) hyperlocomotion (e.g., convulsions or escape attempts); and (v) tremors, stereotypies, or rotational behavior. Each criterion was rated on a 0–2 scale based on symptom intensity, and individual scores were summed to generate a global withdrawal score. The scoring scale and detailed criteria are shown in Fig. 1 B. Resistance to devaluation (satiety test) Resistance to outcome devaluation, i.e. the persistence of consummatory behavior despite a reduced reward value, is a key marker of the transition from controlled to compulsive drug use. In addiction models, animals that remain goal-directed typically decrease their responding when the drug is devalued, whereas animals that have shifted toward habitual or addiction-like behavior show little or no reduction. To assess whether our animals displayed such a transition, we implemented a satiety-induced devaluation procedure. After several days of stable operant self-administration, rats received 1 hour of free access to ethanol in their home cage (two-bottle choice: water vs. ethanol) to reduce the reward value of the drug. Immediately after this devaluation session, animals were placed back into the operant chambers for a standard 15-min FR3 session with alcohol and associated cues available. The number of active lever presses during this session served as the index of sensitivity, or resistance, to reward devaluation. Statistical analysis Clustering BD phenotype analysis is performed to obtain different clusters. The analysis is performed using the JASP software (Version 0.14.1) using k-means partitioning. This method belongs to the unsupervised classification algorithms which means that the groups do not exist before being created so the number of clusters is determined during the analysis. Two parameters are chosen for the classification method: the ethanol consumption (in g/kg) and the speed of consumption calculated as the time to obtain 50% of the total rewards. From the different groups obtained thanks to these criteria, the severity of the addictive behavior (motivation, seeking, relapse) is analyzed for each group. All data are presented as means ± standard error (SEM). Data were analyzed (Sigma Plot) using a one-way or two-way ANOVA test (with or without repeated measures) followed by a Tukey multiple comparison test when a significant effect was observed. For single comparison, we used a Student’s t test (two-tailed), and for correlation, the Pearson correlation test is used. Significance is established at p < 0.05. Results Clustering analysis First, a clustering analysis is performed using the k-means method on the data from the 80 rats exposed to EtOH. It allows us to group similar data in the same cluster. Then a screen plot is performed which compiles the ratio between the total within cluster sum of squares and the total sum of square. This allows us to locate the "elbow", which corresponds to the ideal number of clusters (in our case, 4 groups), see Additional Fig.1 and Additional Table 1. The selected model is the one that minimizes the Bayesian information criterion (BIC), derived from the Akaike information criterion (AIC). The best model has the lowest BIC and AIC values. Our selected model has the highest silhouette coefficient, corresponding to the clustering quality. Moreover, the elevated r 2 (0.752) suggests a good fit of the model. Four groups are obtained from this model (Fig. 2 and Table 1): - Group 1, consisting of 18 ♂ and 18 ♀, considered ‘fast Bingers’ with EtOH consumption at 0.94 g/kg and time to 50% reward at 3.14 min - Group 2, consisting of 9 ♂ and 4 ♀, considered ‘Bingers’ with EtOH consumption at 0.95 g/kg and time to obtain 50% of rewards at 6.59 min - Group 3, consisting of 5 ♂ and 14 ♀, considered ‘extreme Bingers’ with EtOH consumption at 1.60 g/kg and the time to obtain 50% of the rewards at 4.20 min - Group 4, consisting of 8 ♂ and 4 ♀, considered the ‘social drinkers’ with EtOH consumption at 0.33 g/kg and time to obtain 50% of the rewards at 1.21min. AUD-associated behaviors The statistical analysis of the different AUD-associated behaviors is listed in Table 2. The consumption averaged over the 3 last sessions of drinking in the 2BCIA procedure indicates that the 3 groups categorized as ‘bingers’ (Group 1, 2 and 3) do not differ between them but are all significantly higher drinker than the group 4 (Table 1). Table 1: AUD-associated behaviors in the 4 identified groups of the whole population (males and females). AUD-associated behaviors ANOVA G1 Fast bingers n = 18F + 18M G2 Bingers n = 4F + 9M G3 Extreme bingers n = 14F + 5M G4 Social drinkers n = 4F + 8M Post hoc pairwise comparison 2BC consumption (g/kg/24hr) F (3,76) = 6.23 pG4 SA – Active lever presses F (3,76) = 24.496 pG2=G1>G4 SA – EtOH consumed (g/kg/15 min) F (3,76) = 74.886 p G2=G1>G4 Speed of consumption (time to achieve 50% of total consumption - min) F (3,76) = 50.68 p G1>G3>G2 Motivation (active lever presses) F (3,76) = 4,249 pG1=G2>G4 Seeking (active lever presses) F (3,76) = 6,469 pG4 Cue Omission (active lever presses) F (3,76) = 9,619 pG4 Relapse (g/kg/15 min) F (3,76) = 9.99 pG4 Withdrawal Score (arbitrary unit) F (3,75) = 1.61 p=0.195 1.60 ± 0.18 2.00 ± 0.28 2.21 ± 0.27 1.50 ± 0.40 G1=G2=G3=G4 After prolonged training to self-administer alcohol, the group ‘extreme bingers’ significantly drink more pure ethanol than all other groups (Fig. 2A). ‘Fast bingers’ (Group 1) consume the 50% of their total amount faster than the ‘bingers’ (Group 2) but not than the ‘extreme bingers’ (Group 3) and ‘social drinkers’ (Group 4) (Fig. 2B). Profiles of operant responding, meaning the number of active lever presses, are similar to the quantity of ethanol consumed (Fig. 2C). Motivation (Fig. 2D), seeking (Fig. 2E), response during a cue omission test (Fig. 2F) and relapse after abstinence (Fig. 2G) are similar between the 3 bingers groups and all 3 groups are significantly higher than the ‘social drinkers’. During the period of abstinence, withdrawal score was measured and we found a trend to have higher score for the ‘extreme bingers’ as compare to ‘fast bingers’ and ‘social drinkers’ (Fig. 2H). Within each of the clusters, the sex distribution is very different with 50% of males in the ‘fast bingers’ group, more than 60% of males in the ‘bingers’ group and more than 70% of females in the ‘extreme bingers’ group. We finally found a majority of males in the ‘social drinkers’ (Fig. 2I). In order to evaluate if rats did their transition from controlled to uncontrolled behavior, we performed, as already mentioned, a satiety test (Fig. 3A). During the free hour of access to alcohol in the homecage, we only found one statistical difference between the ‘extreme bingers’ and the ‘social drinkers’ that drink less (Fig. 3B). After devaluation, during a regular FR3-15 min session of self-administration we observed a higher consumption in the ‘extreme bingers’ as compared to the ‘bingers’ and ‘social drinkers’ (Fig. 3C). Sex differences We identified that there was some discrepancy in the sex balance in some of the groups an especially in the group “Extreme Bingers”, thus we analyzed the data based on the sex. The results are depicted in Fig. 4 and the statistical analysis of these data in Table 2. Table 2: AUD-associated behaviors in males and females. AUD-associated behaviors Student’s t-test Males Females % of change vs. Males 2BC consumption (g/kg/24hr) p = 0.046 6.41 ± 0.38 7.60 ± 0.45 * 18% F > M SA – Active lever presses p = 0.055 60.95 ± 4.58 50.10 ± 3.19 M > F (ns) SA – EtOH consumed (g/kg/15 min) p = 0.003 0.86 ± 0.07 1.16 ± 0.07 ** 35% F > M Speed of consumption (time to achieve 50% of total consumption - min) p = 0.043 4.28 ± 0.31 3.45 ± 0.27 * -20% F > M Motivation (active lever presses) p = 0.744 82.30 ± 6.03 79.58 ± 5.73 M = F (ns) Seeking – Drug Omission (active lever presses) p = 0.004 47.60 ± 3.90 64.95 ± 4.30 ** 36% F > M Cue Omission (active lever presses) p = 0.139 56.43 ± 4.78 47.83 ± 3.20 M > F (ns) Relapse (g/kg/15 min) p = 0.0003 1.10 ± 0.08 1.54 ± 0.08 40% F > M Withdrawal Score (arbitrary unit) p = 0.009 1.46 ± 0.17 2.13 ± 0.18 ** 46% F > M Satiety 1 hr free EtOH consumed (g/kg/1 hr) p = 0.0017 2.11 ± 0.10 2.57 ± 0.10 ** 22% F > M Satiety EtOH consumed post devaluation (g/kg/15 min) p M First during the 2BCIA procedure, the average of alcohol consumed over the 3 last drinking sessions, females consumed significantly more ethanol than males (7.60 ± 0.45 vs 6.41 ± 0.38 g/kg/24 hrs, p < 0.05, Table 2). After weeks of stabilization of the operant behaviour, female rats consumed more ethanol than males (Fig. 4A) and do it faster (Fig. 4B) without exhibiting higher number of active lever presses (Fig. 4C). Despite this higher consumption, motivation measured as the breaking point during a progressive Ration test is not different between males and females (Fig. 4D). We thus evaluated the sensitivity to the presence or absence of the drug and of the associated cues. During the seeking session, in which no alcohol is provided despite the active lever presses and the presence of the cues, the females significantly pressed more than the males (Fig. 4E). On the opposite, when drug was delivered but no cues were associated to the delivery, no difference between both sexes (Fig. 4F). During these 2 sessions, some rats showed an increase in active lever presses as compared to baseline responding (3 consecutive self-administration sessions). Interestingly, for the “seeking” as well as for the “cue omission” sessions higher proportion of females exhibited this increase (67.5% vs 30% for the “seeking sessions” and 37.5% vs. 22.5% for the “cue omission” session). Thirty percent of female rats increased their pressing levels in both sessions (seeking and cue omission) whereas only 12.5% of males did (Fig. 4G, Chi 2 p < 0.001). After a prolonged abstinence, females rats showed higher level of relapse than males ((Fig. 4H). During this abstinence period, female rats exhibited also higher withdrawal score than males (Fig. 4I). In regard to the perseverance of instrumental responding despite reward devaluation, we performed, as previously described, a satiety test to assess whether animals would reduce their lever pressing when the value of the ethanol reward was diminished (Fig. 5A). During the free access period to alcohol in the homecage, female rats consumed significantly more alcohol than males (+22%, Fig. 5B). Interestingly, this higher intake persisted in the subsequent operant self-administration session, during which female rats consumed drastically more alcohol than males (+183%, Fig. 5C). Discussion Binge drinking is a heterogeneous pattern of alcohol consumption characterized by multiple dimensions, including the speed, quantity, and frequency of intake, as well as associated consequences such as blackout episodes and the severity of hangovers. Building on our previous results on binge drinking behavior in students showing the existence of four subgroups 3 , we applied a similar type of clustering analysis to our animal model of operant binge drinking, which we have developed and begun to characterize 11 , 16 ,although without initially considering sex differences. Our cohort of 80 rats (40 females and 40 males) was trained to self-administer an ethanol solution during short, binge-like access periods, providing a robust and sex-balanced model of excessive alcohol intake. After a minimum of eight weeks of training, this longitudinal design allowed us to establish stable baseline consumption levels and to systematically evaluate a comprehensive set of parameters associated with AUD. Our first unsupervised clustering analysis based on criteria of alcohol quantity and consumption speed identified, similar to our clinical study 3 , four distinct groups. Among the four groups, there is group 1 of ‘Fast Bingers’ characterized by rapid consumption of large amount of alcohol, group 2 of ‘Bingers’ who drink similar large amount of alcohol but a little bit slower, group 3 of ‘Extreme bingers’ characterized by heavy alcohol consumption, and group 4 of ‘Social drinkers’ characterized by lower motivation, seeking, and relapse. Social drinkers only had to perform 11 presses and thus to consume 3 rewards to achieve the 50% of their total amount whereas the extreme bingers had to perform 40 active lever presses to achieve their 50% of total amount. That certainly explain the speed of consumption for the ‘social drinkers’ group. The markedly higher alcohol consumption in Group 3 (‘Extreme bingers’) was accompanied by a trend toward higher withdrawal scores relative to the other groups. Binge drinking and AUD may be associated with habit learning development, and it is conceivable that habit learning among binge drinkers could play a role in the transition from binge drinking behavior to AUD. Previous studies have suggested that binge drinking is a repetitive behavior which can lead to the formation of habits and have also shown that student alcohol consumption is ‘automatically activated by relevant contextual cues’ 17 . Habitual binge drinking can be assessed with the Self-Report Habit Index that is composed of some items such as ‘I do frequently’, ‘I do automatically’, ‘I do without having to consciously remember’ and ‘I do without thinking’ 17 . High automaticity score has been associated with an increased risk of harmful alcohol use 18 . In animals, when operant behavior is unaffected by a loss of subjective value of alcohol (devaluation), the behavior is considered habitual. Interestingly, our results indicate that group 3 of ‘Extreme bingers’, predominantly females, tends to consume the most alcohol in a devaluation session and exhibit behavior of perseverance of alcohol consumption despite satiety. This initial analysis also revealed sex-related proportion differences among the groups, with an equal distribution of males and females in group 1, more males in groups 2 and 4, and more females in group 3 of ‘Extreme bingers’. This prompted us to conduct a more in-depth analysis of the results across the entire cohort, focusing on sex differences. Sex-specific analyses show that females consume more alcohol (35% increase) with a slightly higher consumption speed (20% decrease of the latency to achieve 50% of their total intake). While there is no difference in motivation to consume, females exhibit higher alcohol-seeking behavior (36% increase) associated with higher relapse (+ 40%) and withdrawal scores (46% increase). It is also observed that the proportion of females significantly increases their alcohol-seeking behavior when the drug is omitted and that the number of active lever presses tends to be decreased when the cue associated with the drug is omitted. This aligns with previous rodent studies reporting that females consume more alcohol relative to their body weight and display higher levels of cue-mediated alcohol-seeking behaviors than male 13 , 19 – 22 . The lack of sex-related difference observed here is also in line with previous study that measured breakpoints in Long Evans rats, but in this study, lower breakpoint values were achieved (around 10) compared to the ones we obtained (around 20) 21 probably due to the duration of the session 30 minutes vs. 15 minutes), but also to the difference in the schedule of increment used in both studies and the type of alcohol solution (20% v/v for our study and 15% ethanol + 2% sucrose in Randall’s one). The interplay between gonadal hormones and dopamine offers valuable insights into the molecular mechanisms that underlie sex differences in the rewarding properties of alcohol 23 . Our results also demonstrate that females, as expected, consume more alcohol when alcohol is available ad libitum in their home cage for devaluation in the satiety test. We did not investigate the effect of the estrous cycle on alcohol-related behaviors in our rats because it has been repeatedly demonstrated that estrous cycle does not substantially impact alcohol intake in naturally cycling rats 24 – 26 . While the rewarding effects of alcohol contribute substantially to its addictive potential, there is a growing acknowledgment that the aversive properties of alcohol also wield a crucial influence on the inclination to consume it. Following recurrent episodes of binge drinking, individuals may develop a negative affective state upon voluntarily or involuntarily withdrawal from alcohol. This encompasses dysregulated stress hormone levels, dysphoria, anxiety, depression, and irritability, an array of symptoms believed to stem, at least in part, from adaptations in stress-related neural pathways 27 . We showed that females displayed more severe withdrawal score and this result suggests that increased sensitivity to the aversive properties of alcohol withdrawal may contribute to higher levels of binge drinking in order to alleviate withdrawal symptoms. These results are in line with clinical observations suggesting that women are more likely to drink alcohol to alleviate unpleasant emotions and relapse in response to negative affect 28 , 29 . To pursue on this line, our data reveal that females exhibit higher consumption than males during relapse after abstinence. Although we observed a higher level of ethanol relapse in females compared to males after 10 days of abstinence, another study conducted on Long Evans rats demonstrated the opposite trend, with no relapse behavior observed in females and a clear relapse in males after a 3-week period of abstinence 21 . However, in this later study, rats had access to alcohol during 30 minutes sessions and with sucrose added to the ethanol solution. We already demonstrated that, even with a similar level of alcohol self-administration, the speed of consumption is crucial to alter alcohol-associated behaviors 9 . After prolonged abstinence, alcohol-associated cues can acquire strong incentive salience, thereby intensifying cravings and precipitating relapse 14 . In humans, men generally report higher levels of alcohol craving than women 30 , and similarly, male rodents are often described as more susceptible to relapse than females 31 . However, our findings point in the opposite direction since in our paradigm, females displayed more pronounced seeking behavior when alcohol was omitted, as well as higher drinking levels during relapse following abstinence. Finally, in our study, females showed a tendency to reduce their level of active responses during cue omission, yet increased their operant responding during the seeking session (in which no alcohol was available). Compared with males, this pattern suggests that females may be particularly sensitive to the presence or absence of alcohol-associated cues and may rely more strongly on cue-reward associations. Consequently, females seem to interpret the presence of cues as signaling that the drug should be available, which promote the persistence of responding even when ethanol is absent. Our findings therefore suggest that cue-drug associations are stronger in females than in males within this paradigm. Supporting this interpretation, a greater proportion of females increased their lever pressing in these two cue-sensitive tests compared with males. Other studies using food as the reward, have suggested that females not only engage more, and may acquire more in stimulus-directed Pavlovian approach behaviors (i.e; sign-tracking) but also acquire these behaviors more rapidly than males 32 , 33 . Sign-tracking refers to the attraction toward cues that predict a reward, reflecting incentive motivational processes directed both toward the reward itself and toward its associated cues. This behavior has been linked to excessive and inflexible reward-seeking tendencies. Under outcome devaluation conditions, animals that continue to engage with cues associated with a now-devalued reward are often considered to display compulsive or overly habitual responding. However, another study in Long Evans rats reported that females and males acquire sign-tracking at similar rates and show comparable levels of sign-tracking following outcome devaluation 34 . In contrast, our findings show that females increased their active lever responses during the seeking session (when alcohol was unavailable), and persisted in consummatory-like responding despite reward devaluation. This pattern suggests that at least some females may have developed habit-based responding and may no longer rely on goal-directed control. In addition, our study revealed that females exhibit a reduced sensitivity to outcome devaluation, which can be interpreted as a form of behavioral inflexibility. In contrast, males almost completely ceased alcohol consumption following devaluation. Previous work has shown that female alcohol-preferring rats display a tendency toward habitual behavior, reflected for example by an Increased latency to initiate alcohol responding after devaluation, a recognized indicator of habit formation 35 . Together, these sex-related differences are particularly intriguing, as they suggest that females may be more prone to developing automatic, habit-based behaviors that could contribute to a greater susceptibility to AUD. However, this interpretation will need confirmation from clinical studies. Supporting this hypothesis, a recent study reported that female Wistar rats displayed higher levels of compulsive alcohol self-administration, both foot-shock-resistant and quinine-resistant behaviors that are commonly interpreted as reflecting a transition from goal-directed to habitual responding 36 . Similarly, another systematically devaluating alcohol by delaying its delivery found that females persistently engaged in habitual responding despite delay-induced reinforcer devaluation 24 . Overall, our results, in combination with findings from these previous studies, suggest that females may be more vulnerable to the development of habit learning and compulsive alcohol use, which aligns with clinical observations indicating that women may be particularly at risk for the rapid emergence of AUD. Perspective and significance Preclinical models are essential for dissecting the behavioral and neurobiological mechanisms that underlie binge drinking. Recognizing sex as a critical biological variable is fundamental to identifying vulnerability factors contributing to the initiation and escalation of binge drinking behaviors. Our dataset provides a comprehensive characterization of how sex differences shape alcohol drinking patterns, offering valuable insights that can guide the development of improved prevention and treatment strategies. Moreover, as recently demonstrated by our group 37 , pharmacological treatments for AUD may differ in efficacy between males and females, highlighting the necessity of systematically incorporating both sexes in preclinical and translational research on AUD. Conclusions In conclusion, our study used unsupervised clustering analyses to identify distinct groups of binge drinking profiles, mirroring the heterogeneity observed in clinical populations. We identified four primary groups on multiple drinking dimensions. Our findings highlight the importance of resistance to reward devaluation as key feature of binge drinking behavior and a potential marker of vulnerability to AUD. We also observed clear sex-related differences across these groups, females exhibited stronger alcohol-seeking responses, higher withdrawal scores, and increased consumption during relapse compared with males. Furthermore, our data suggest that females may be more prone to developing cue-driven automatic behaviors, consistent with habit learning, which could contribute to their heightened susceptibility to AUD. Altogether, these findings provide important insights into the complex interplay between sex, drinking trajectories, and the development of compulsive alcohol use, and they underscore the need for continued investigation in clinical populations. Declarations Ethics approval and consent to participate Experimental procedures were conducted in accordance with the European Union Directive 2010/63/EU, and the protocol was approved by the Ethics Committee for Animal Care and Use at University of Picardie Jules Verne (CREMEAP). Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study can be made available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding Open access funding provided by University of Picardie Jules Verne. This study was supported by the IReSP in the framework of the 2021 call for the research against the uses and addictions to psychoactive substances (SPAV1-22-019) and by the INSERM. Author contributions JJ, AS drafted the manuscript and analyzed and interpreted the data. JJ, AS conducted experiments, collected, and processed the data. MN processed the data. JJ and MN designed/supervised experiments and revised the manuscript. All authors have read and approved the manuscript. Acknowledgements Not applicable. Author details INSERM UMR1247 - Groupe de Recherche sur l’alcool et les pharmacodépendances GRAP. Université de Picardie Jules Verne, Centre universitaire de recherche en santé CURS, Chemin du Thil, 80025, Amiens, France. References Rolland B, Naassila M. Binge Drinking: Current Diagnostic and Therapeutic Issues. 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Supplementary Files Additionalmaterial1.docx Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Biology of Sex Differences → Version 1 posted Editorial decision: Revision requested 14 Feb, 2026 Reviews received at journal 13 Feb, 2026 Reviews received at journal 08 Feb, 2026 Reviews received at journal 27 Jan, 2026 Reviewers agreed at journal 12 Jan, 2026 Reviewers agreed at journal 12 Jan, 2026 Reviewers agreed at journal 12 Jan, 2026 Reviewers invited by journal 12 Jan, 2026 Editor assigned by journal 12 Jan, 2026 Submission checks completed at journal 12 Jan, 2026 First submitted to journal 09 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":480063,"visible":true,"origin":"","legend":"\u003cp\u003eA. Timeline of the experiment and analysis. The 80 rats underwent our operant binge drinking (OBD) protocol and were subsequently tested for various parameters relevant to the study of Alcohol Use Disorder (AUD). A clustering analysis was performed focusing on the quantity of alcohol consumed in one session of OBD and the speed of consumption (time to reach 50% of the total number of active lever presses). All the different parameters studied were analysed based on the four clusters identified. Subsequently, a sex-based analysis was conducted on the same parameters. B. Withdrawal score scale. To assess the withdrawal score, we followed a scale divided into 5 items with scores. The first three items are based on simple observation without manipulation. Open the cage and observe the rat for 3 minutes. At the opening, if the rat moves normally, count 0; if it freezes, count 1 if it is less than 5 seconds and 2 if more than 5 seconds. Observe the tail and its orientation (1 if horizontal during the walk, 2 if vertical to the top). Then, observe if the rat exhibits tremors or stereotypies. The most frequent stereotypies are first burying its head in the bedding and then grooming. Depending on the frequency of the stereotypies, score 0 for none, 1 if 1-2 per minute, and 2 if 3 or more per minute. If the rat vocalizes at the opening of the cage, score 2; if it only vocalizes during manipulation, score 1; if it does not vocalize at any time, score 0. Finally, we evaluated escape behaviour by placing the rat on our arm and assessing the way the rat returns to its cage. If the descent is smooth, score 0; if the rat jumps, score 1; if the rat jumps repetitively as soon as its paws touch your arm, score 2.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8561890/v1/44b436cbfe86c7f97a70590b.jpeg"},{"id":100267413,"identity":"331fb156-9347-4ed0-bc81-54fd3b2046ca","added_by":"auto","created_at":"2026-01-14 18:46:22","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":381340,"visible":true,"origin":"","legend":"\u003cp\u003eClustering analysis. Based on the quantity of alcohol consumed (A) and the speed of consuming it (B), the clustering analysis provided 4 distinct groups of consumers. The operant responding (C) during a typical session of OBD was analysed depending of these clusters, as well as the motivation (D) through a progressive ratio session, the seeking (E) for alcohol (a session in which alcohol is absent but the cues associated are present), the perseverance of operant responding during a session in which alcohol is delivered but the cue-associated are absent (F, cue omission) and finally the relapse (G) after 14 days of abstinence. The withdrawal score (H) was measured the day before the relapse session meaning 13 days after the last session of OBD. Finally, the distribution of both sexes within each cluster is depicted in panel (I). Cluster 1 n = 36, Cluster 2, n = 13, Cluster 3 n = 19, Cluster 4 n = 12. One-way ANOVA followed by Tukey test: * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8561890/v1/10ead05abe2d9ecc2d4882a1.jpeg"},{"id":100372498,"identity":"5049034b-e626-42b9-9314-5734d773e4b1","added_by":"auto","created_at":"2026-01-16 08:12:30","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":151196,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePerseverance despite devaluation. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eThe devaluation test is divided in 2 phases: the first one consists in providing free alcohol for one hour in the home cage of the rats. The second phase is the phase of test in which rats are submitted to a regular OBD session with access to alcohol upon 3 consecutive active lever presses. In Panel (\u003cstrong\u003eB\u003c/strong\u003e) are depicted the amount of alcohol consumed (expressed in g/kg/1 hr) during the hour of free access to alcohol. The result of the devaluation is depicted in panel (\u003cstrong\u003eC\u003c/strong\u003e) with the amount of alcohol consumed (g/kg/15 min) during the OBD session. Cluster 1 n = 36, Cluster 2, n = 13, Cluster 3 n = 19, Cluster 4 n = 12. 1-way ANOVA followed by Tukey test: * p \u0026lt; 0.05, *** p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8561890/v1/ff83a2890fe5e188a43d7b0e.jpeg"},{"id":100267414,"identity":"a92bc75e-4235-4e8c-a56d-6358d9f98f39","added_by":"auto","created_at":"2026-01-14 18:46:22","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":303829,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSex-based analysis.\u003c/strong\u003e Based on the sex, quantity of alcohol consumed (\u003cstrong\u003eA\u003c/strong\u003e), speed of consuming it (\u003cstrong\u003eB\u003c/strong\u003e), operant responding (\u003cstrong\u003eC\u003c/strong\u003e) during a typical session of OBD the motivation (\u003cstrong\u003eD\u003c/strong\u003e) through a progressive ratio session, the seeking (\u003cstrong\u003eE\u003c/strong\u003e) for alcohol (a session in which alcohol is absent but the cues associated are present), the perseverance of operant responding during a session in which alcohol is delivered but the cue-associated are absent (\u003cstrong\u003eF\u003c/strong\u003e, cue omission). We analysed the proportion of individuals that increase their operant responding during the Seeking and the Cue Omission sessions as compared to the typical OBD session (\u003cstrong\u003eG\u003c/strong\u003e). Relapse (\u003cstrong\u003eH\u003c/strong\u003e) after 14 days of abstinence was also analysed. The withdrawal score (\u003cstrong\u003eI\u003c/strong\u003e) was measured the day before the relapse session meaning 13 days after the last session of OBD. Finally, the distribution of both sexes within each cluster is depicted in panel \u003cstrong\u003eI\u003c/strong\u003e. Bilateral unpaired Student’s t-test for A, B, C, D, E, F, H and I: * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001. Chi-square for G.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8561890/v1/2e461b6584f52d6ef8164d8e.jpeg"},{"id":100371852,"identity":"63c4c1b8-38ae-41f5-8589-2de3147bcbf6","added_by":"auto","created_at":"2026-01-16 08:11:07","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":157410,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFemales persevere more despite devaluation. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eThe devaluation test is divided in 2 phases: the first one consists in providing free alcohol for one hour in the homecage of the rats. The second phase is the phase of test in which rats are submitted to a regular OBD session with access to alcohol upon 3 consecutive active lever presses. In Panel (\u003cstrong\u003eB\u003c/strong\u003e) are depicted the amount of alcohol consumed (expressed in g/kg/1 hr) during the hour of free access to alcohol. The result of the devaluation is depicted in panel (\u003cstrong\u003eC\u003c/strong\u003e) with the amount of alcohol consumed (g/kg/15 min) during the OBD session. A schematic view of the devaluation (\u003cstrong\u003eD\u003c/strong\u003e) expressed as alcohol consumed during a typical OBD session (Before) and during the devaluation test (After). Bilateral unpaired Student’s t-test for A, B, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8561890/v1/6c02e5f788eeef29eb5c70c1.jpeg"},{"id":108438042,"identity":"57dcf408-8abe-4814-a4b2-de0ed460de81","added_by":"auto","created_at":"2026-05-04 16:05:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1902291,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8561890/v1/8f52f674-59c1-4424-93e3-6331af660c28.pdf"},{"id":100267417,"identity":"317a6a25-0b55-457b-9179-7425ce13d8ef","added_by":"auto","created_at":"2026-01-14 18:46:22","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":206055,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalmaterial1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8561890/v1/a481c38521a19976bab1ca57.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Female rats are more vulnerable to binge drinking behavior in an operant self-administration paradigm: implication for transition to alcohol use disorders","fulltext":[{"header":"Plain English summary","content":"\u003cp\u003eBinge drinking is a specific pattern of alcohol consumption based on consuming large amounts in a short period of time. Binge drinking is known to be a risk factor to the transition to latter alcohol addiction. A recent study has shown greater brain damage in women who binge drink than in men. Thus, in the present study we used the animal model we developed to mimic the binge drinking behaviour in rats. We used 40 male and 40 female adult rats to evaluate a series of behaviors associated to the consumption of alcohol such as motivation, seeking, relapse and transition to drug addiction. In a first analysis combining both sexes we found 4 distinct groups of drinkers, the bingers, the fast bingers, the extreme bingers and finally the social drinkers that do not drink much alcohol. The distribution of the sexes was not well balanced in the groups with the extreme bingers represented mostly by females. We then evaluated the differences between both sexes and we found that the females consumed more alcohol than the males, females were more sensitive to the contextual cues associated to each delivery of alcohol. We also found that females are more vulnerable to addiction after chronic binge drinking and that they will relapse at higher levels than males. Overall, we demonstrate the need to include the females in our preclinical studies because they do not display similar sensitivity to drug consumption than males.\u003c/p\u003e"},{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eCluster analysis based on quantity of alcohol consumed during a 15-min operant self-administration session and speed of consumption revealed 3 different groups of \u0026lsquo;bingers\u0026rsquo; and a group of \u0026lsquo;social drinkers\u0026rsquo;.\u003c/li\u003e\n \u003cli\u003eThe \u0026lsquo;extreme bingers\u0026rsquo; differ from the others by the quantity consumed and the \u0026lsquo;fast bingers\u0026rsquo; differ from the \u0026lsquo;bingers\u0026rsquo; by consuming the same amount of alcohol but twice faster.\u003c/li\u003e\n \u003cli\u003eThe \u0026lsquo;extreme bingers\u0026rsquo; group is composed by more than 70% of female rats\u003c/li\u003e\n \u003cli\u003eThe sex-based analysis demonstrates a higher sensitivity to the cue associated to the delivery of alcohol in females\u003c/li\u003e\n \u003cli\u003eFemales are less sensitive to the devaluation of the reward than the males leading to perseverance of the operant behavior despite satiety and higher levels of relapse after abstinence.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eBinge drinking is a dangerous and harmful alcohol consumption behavior characterized, among other criteria, by large quantities ingested over a short period of time \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Unlike patients with alcohol use disorders (AUD), binge drinkers experience intermittent episodes of consumption interspersed with periods of non-consumption \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Binge drinking behavior is rather heterogeneous behavior. We recently proposed a mathematical model to better categorize binge drinking behavior in young adults, and we identified the existence of four groups based on the consumption profile: low-risk, hazardous, binge, and high-intensity binge drinking \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Furthermore, binge drinking is considered a factor involved in the development of AUD. A study in France has shown that frequent binge drinking between 18 and 25 years (4+/5\u0026thinsp;+\u0026thinsp;drinks/occasion for females/males, more than twice a month) leads to an approximately threefold increased risk of developing AUD at adulthood (between 25 and 45 years) \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Another study in the United States showed that nearly 80% of those young adults who reported engaging in high-intensity drinking (10\u0026thinsp;+\u0026thinsp;drinks in a row) at age 29/30 later reported AUD symptoms at age 35 \u003csup\u003e5\u003c/sup\u003e. Therefore, it is conceivable that a chronic pattern of binge drinking is associated with the transition to addictive behavior, and it is possible, in particular, that the repetitive aspect of binge drinking behavior facilitates the establishment of habit learning or attentional biases, that may play an important role in AUD.\u003c/p\u003e \u003cp\u003eWhile AUD is more commonly found in men, there is a notable and accelerating rise in the number of women affected by AUD, particularly among adolescents \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Women exhibit greater susceptibility to the medical consequences associated with alcohol consumption, such as alcohol-related liver disease. This trend is not solely attributed to sex-based differences in alcohol pharmacokinetics; women also demonstrate an expedited progression from initial alcohol use to the onset of AUD. The current knowledge on binge drinking behavior has not clearly demonstrated sex-related differences in vulnerability, not only to this behavior but also regarding its role in the development of AUD or some of its symptoms. However, some studies have shown sex-related differences in young binge drinkers. For example, one study that used clustering analysis, suggested that male and female binge drinkers should not be considered a unitary group, but rather a population of individuals that encompasses at least 2 distinct personality patterns with Cloninger's type I (high harm-avoidance) and II (high novelty-seeking) AUD typology \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eVarious animal models have been developed to study binge drinking behavior \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. We demonstrated that daily access to an alcohol self-administration operant chamber for just 15 minutes over several months facilitates the emergence of a behavior resembling binge drinking in humans, with rapid consumption leading to significant blood ethanol levels and ataxia in rats \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In addition, we identified using the same model, that binge drinking behavior is dependent upon genetic factors since among three different outbred rat strains, the Long Evans one is more prone to binge drinking \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. This model is also characterized by excellent predictive validity, as we have demonstrated that various treatments for AUD are effective \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBy definition, binge drinking is characterized by the excessive consumption of alcohol within a very short period of time. Therefore, reducing the time required to access alcohol, as observed during happy hours in humans, acts as a facilitator of binge drinking behavior.\u003c/p\u003e \u003cp\u003eIn contrast to the study of Wheeler et al. \u003csup\u003e12\u003c/sup\u003e, which concluded that shortening the session duration does not promote binge drinking, our operant self-administration paradigm is based on a fundamentally different behavioral and motor framework. In their study, rats were trained on a \u0026ldquo;sipper\u0026rdquo; device in which a single operant response grants access to the drinking spout for a fixed period, and they then assessed the effect of reducing session duration (30 to 15 min) on appetitive and consummatory behaviors. This type of setup allows for prolonged drinking bouts per reinforcement, minimizes motor demands, and hardly engages automatization or habit formation (one response\u0026thinsp;=\u0026thinsp;long fluid access). By contrast, in our procedure, each reinforcement delivers a single 0.1 mL drop of ethanol (FR-3), which requires\u0026thinsp;~\u0026thinsp;100 active responses per session instead of a few dozen, enforces a \u0026ldquo;sip-paced\u0026rdquo; drinking pattern, and deliberately challenges the motor/repetitive components involved in the automatization of alcohol seeking. Shortening the session to 15 min in this context produces precisely the kind of \u0026ldquo;binge-like\u0026rdquo; profile\u0026mdash;rapid intake, elevated BECs, and behavioral alterations\u0026mdash;that validates the face validity of the model. More broadly, several studies have shown that temporal compression increases \u0026ldquo;front-loading\u0026rdquo; and can even bring male rats closer to the rapid intake phenotype typically observed in females under FR schedules, directly contradicting Wheeler\u0026rsquo;s general statement when extrapolated to other operant contingencies \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. In sum, comparing our results to those of Wheeler as if the two approaches were interchangeable neglects crucial mechanistic differences: (i) mode of delivery (continuous sipper access \u003cem\u003evs.\u003c/em\u003e unitary drops), (ii) response cost (FR-1/prolonged access \u003cem\u003evs.\u003c/em\u003e FR-3/0.1 mL), and (iii) motor load and propensity for stimulus\u0026ndash;response automatization. Wheeler\u0026rsquo;s conclusion that \u0026ldquo;shortening the session does not matter\u0026rdquo; therefore cannot be generalized to protocols in which alcohol intake is discretized and response-costly\u0026mdash;precisely those paradigms designed to model operant binge drinking and the development of automatisms.\u003c/p\u003e \u003cp\u003eIt is also important to emphasize that any direct comparison between paradigms requires isomorphic contingencies\u0026mdash;namely equivalent session duration, response cost, delivery granularity, and mode of access (continuous sipper vs. unitary drops). In the absence of such equivalence, reducing session length in a sipper model primarily decreases the number of opportunities to respond and the total available volume, whereas in an FR-3 schedule, the same temporal compression intensifies early responding and promotes front-loading. This distinction is critical, as it is precisely this front-loading dynamic that operant binge models are designed to capture.\u003c/p\u003e \u003cp\u003eHere, we sought to characterize sex differences in chronic voluntary binge drinking and especially in several operant self-administration criteria such as ingested alcohol, drinking speed, alcohol seeking in a drug omission session and motivation. Reward comprises learning (cue associations), hedonic (\u0026ldquo;liking\u0026rdquo;), and motivational (\u0026ldquo;wanting\u0026rdquo;) components \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Initially linked with a reward, conditioned stimuli have the potential to transform into independent motivational cues, prompting both appetitive approach and consummatory behaviors \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The transition from casual to compulsive alcohol use is believed to coincide with heightened motivation to get alcohol. In animals, this escalated exertion of effort can be quantified through progressive ratio (PR) schedules of reinforcement. We also measured other criteria more linked to addiction such as withdrawal symptoms after abstinence and perseverance of the operant self-administration despite the devaluation of the reward by a satiety test. Thus, and as we recently did in humans, we used first a clustering approach to better characterize different binge drinking patterns and since the results revealed sex-related differences we further determined criteria related to addictive behaviors in both sexes.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003eForty males and forty females Long Evans rats were purchased from Janvier Labs (Le Genest-Saint-Isle, France) at the age of 7 weeks. The time line of all experiments is presented on Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA. The animals were housed individually without enrichment in a thermo-regulated animal facility (22\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C and 40\u0026thinsp;\u0026plusmn;\u0026thinsp;10% humidity), with a 12/12hrs light/dark cycle (light on at 8:00 am). All animals were provided with water and food \u003cem\u003ead libitum\u003c/em\u003e. The behavioral tests were performed between 9:00 and 12:00 am. The experimental procedures were performed according to the principles set forth by the Council responsible for the protection of animals used for experimental purposes (EEC N\u0026deg; 86/609) and approved by the local ethical committee (CREMEAP, APAFIS#26615).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eReagents\u003c/h3\u003e\n\u003cp\u003eEthanol, (ETOH 96\u0026deg;) was purchased from VWR (Strasbourg, France) and was diluted in tap water at the concentration of 20% (v/v).\u003c/p\u003e\n\u003ch3\u003eVoluntary Operant Binge Drinking\u003c/h3\u003e\n\u003cp\u003eThe procedure of voluntary operant binge drinking is identical to the one already described (9). Briefly, rats were first submitted to 4 weeks of a two-bottle choice intermittent access paradigm with water solution available every day and with 20% EtOH solution available every other day (Mondays, Wednesdays and Fridays) for 24 hrs starting at 2:00 pm. At the end of this procedure, rats underwent training sessions of operant self-administration for EtOH (20% v/v) in Med Associates operant cages (ENV-008, Med Associates, Albans, VT, USA). Two overnight sessions under a fixed ratio 1 schedule were followed by 5 sessions of each schedule and duration: 1 hr-FR1, 1hr-FR3, 30 min-FR3 and finally 15 min-FR3. Maintenance of binge drinking behavior was achieved over 2 months (5 sessions a week). Ethanol reward was a 0.1 mL drop of the 20% ethanol solution and its delivery was accompanied by contextual cues: a light (within the delivery compartment) and a tone stimulus both for 3 seconds. The cages are controlled and the behaviors recorded through the MEP IV software (Med Associates, Albans, VT, USA).\u003c/p\u003e\n\u003ch3\u003eBlood Ethanol Concentration\u003c/h3\u003e\n\u003cp\u003eBlood collection was performed at the end of the maintenance period of 1 month under the 15 min-FR3 sessions, once stable EtOH consumption was well established. Rats undergoing EtOH operant binge drinking were anesthetized under 5% IsoFlurane (IsoVet, Piramal HealthCare, Northumberland, UK) 5 min after the end of the self-administration session for 2 minutes. Blood (~\u0026thinsp;300 \u0026micro;L) was collected from the sublingual vein in heparinized tubes before centrifugation to collect the plasma and stored at 4\u0026deg;C until analysis. We used the ANALOX system (Imlab SARL, Lille, France) in order to evaluate the blood ethanol concentrations (BECs).\u003c/p\u003e\n\u003ch3\u003eAUD-associated behaviors\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMotivation\u003c/h2\u003e \u003cp\u003eHypermotivation to obtain the drug, reflected by an increased willingness to work for it, is a core hallmark of addictive behavior across substances. It captures the transition from controlled, recreational intake to compulsive drug seeking, and is therefore a critical dimension of addiction-like phenotypes. After ten sessions under a fixed-ratio 3 (FR3) 15-min reinforcement schedule, animals\u0026rsquo; motivation to self-administer alcohol or saccharin was assessed using a progressive-ratio reinforcement protocol. In this procedure, the response requirement for each subsequent reward gradually increases (3, 4, 5, 7, 9, 12, 15, 17, 20, 22, 25, 28, 30, 33, and 35 responses) \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Eventually, animals cease pressing the active lever; this final ratio completed is termed the breaking point, and serves as an index of the animal\u0026rsquo;s motivational drive to obtain ethanol. Sessions lasted 30 minutes to ensure sufficient time for animals to complete the progressive schedule.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSeeking (Drug Omission test)\u003c/h3\u003e\n\u003cp\u003eDrug seeking in the absence of the drug is commonly used as an operational measure of drug craving and diminished behavioral control in animal models. In our protocol, loss of control and/or craving for alcohol was assessed during a dedicated session in which no alcohol solution was delivered despite active lever presses, while all conditioned cues previously associated with alcohol remained present. The persistence of active lever pressing under these omission conditions is interpreted as an increased motivational drive for alcohol and reflects a higher level of craving-like behavior and of loss of control.\u003c/p\u003e\n\u003ch3\u003eCue Omission test\u003c/h3\u003e\n\u003cp\u003eOne of the behavioral criteria of addiction is the excessive sensitivity to environmental cues associated with drug consumption, which can by themselves trigger or intensify drug-seeking behavior. The Cue Omission test is useful for assessing this cue reactivity, namely the disproportionate motivational value acquired by stimuli predicting reward delivery. Although this test does not directly measure attentional capacities or attentional biases in the strict cognitive sense, it provides insight into the salience of drug-associated cues and the degree of behavioral automatization: a strong cue-controlled response is typically observed in addictive-like behaviors. In our operant model of binge drinking, the cues associated with solution delivery gradually acquire secondary reinforcing value. It is well established that such contextual cues can elicit consumption-related behaviors. Therefore, to evaluate the vulnerability to these cues in our model, we conducted a Cue Omission session. Sensitivity to the cue associated with delivery was assessed in a session in which the drug was still delivered after three active lever presses, but without presentation of the cues normally paired with its delivery. In our paradigm the drug is still delivered after 3 active lever presses but no cues were associated with it.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRelapse after chronic binge drinking\u003c/h2\u003e \u003cp\u003eAfter 11 weeks of operant binge-drinking sessions, rats underwent an ethanol deprivation period during which they were not exposed to the operant self-administration chambers for 10 consecutive days. Following this abstinence interval, animals were reintroduced into the operant chambers for a standard binge-drinking session in which alcohol-associated cues were presented and ethanol was again available. To facilitate the initiation of relapse, a priming free drop of ethanol was delivered at the onset of the session. This procedure enables the assessment of relapse-like drinking behavior following chronic intermittent alcohol exposure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eWithdrawal Score\u003c/h2\u003e \u003cp\u003eWithdrawal syndrome refers to the emergence of physical signs following drug cessation and is a hallmark of dependence (signs of physical dependence in AUD). To quantify withdrawal severity, we adapted the scoring system previously developed by Gilpin and colleagues (14). After five days of abstinence, rats were observed for several minutes in their home cage, and their behavior was evaluated according to the following criteria: (i) aggression and/or vocalizations; (ii) posture (immobility or slowing); (iii) tail rigidity; (iv) hyperlocomotion (e.g., convulsions or escape attempts); and (v) tremors, stereotypies, or rotational behavior. Each criterion was rated on a 0\u0026ndash;2 scale based on symptom intensity, and individual scores were summed to generate a global withdrawal score. The scoring scale and detailed criteria are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eResistance to devaluation (satiety test)\u003c/h2\u003e \u003cp\u003eResistance to outcome devaluation, i.e. the persistence of consummatory behavior despite a reduced reward value, is a key marker of the transition from controlled to compulsive drug use. In addiction models, animals that remain goal-directed typically decrease their responding when the drug is devalued, whereas animals that have shifted toward habitual or addiction-like behavior show little or no reduction. To assess whether our animals displayed such a transition, we implemented a satiety-induced devaluation procedure. After several days of stable operant self-administration, rats received 1 hour of free access to ethanol in their home cage (two-bottle choice: water vs. ethanol) to reduce the reward value of the drug. Immediately after this devaluation session, animals were placed back into the operant chambers for a standard 15-min FR3 session with alcohol and associated cues available. The number of active lever presses during this session served as the index of sensitivity, or resistance, to reward devaluation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003eClustering\u003c/h2\u003e \u003cp\u003eBD phenotype analysis is performed to obtain different clusters. The analysis is performed using the JASP software (Version 0.14.1) using k-means partitioning. This method belongs to the unsupervised classification algorithms which means that the groups do not exist before being created so the number of clusters is determined during the analysis. Two parameters are chosen for the classification method: the ethanol consumption (in g/kg) and the speed of consumption calculated as the time to obtain 50% of the total rewards. From the different groups obtained thanks to these criteria, the severity of the addictive behavior (motivation, seeking, relapse) is analyzed for each group.\u003c/p\u003e \u003cp\u003eAll data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SEM). Data were analyzed (Sigma Plot) using a one-way or two-way ANOVA test (with or without repeated measures) followed by a Tukey multiple comparison test when a significant effect was observed. For single comparison, we used a Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test (two-tailed), and for correlation, the Pearson correlation test is used. Significance is established at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003eClustering analysis\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, a clustering analysis is performed using the k-means method on the data from the 80 rats exposed to EtOH. It allows us to group similar data in the same cluster. Then a screen plot is performed which compiles the ratio between the total within cluster sum of squares and the total sum of square. This allows us to locate the \u0026quot;elbow\u0026quot;, which corresponds to the ideal number of clusters (in our case, 4 groups), see Additional Fig.1 and Additional Table 1. The selected model is the one that minimizes the Bayesian information criterion (BIC), derived from the Akaike information criterion (AIC). The best model has the lowest BIC and AIC values. Our selected model has the highest silhouette coefficient, corresponding to the clustering quality. Moreover, the elevated r\u003csup\u003e2\u003c/sup\u003e (0.752) suggests a good fit of the model.\u003c/p\u003e\n\u003cp\u003eFour groups are obtained from this model (Fig. 2 and Table 1):\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e- Group 1, consisting of 18\u0026nbsp;♂\u0026nbsp;and 18\u0026nbsp;♀, considered \u0026lsquo;fast Bingers\u0026rsquo; with EtOH consumption at 0.94 g/kg and time to 50% reward at 3.14 min\u003c/p\u003e\n\u003cp\u003e- Group 2, consisting of 9\u0026nbsp;♂\u0026nbsp;and 4\u0026nbsp;♀, considered \u0026lsquo;Bingers\u0026rsquo; with EtOH consumption at 0.95 g/kg and time to obtain 50% of rewards at 6.59 min\u003c/p\u003e\n\u003cp\u003e- Group 3, consisting of 5\u0026nbsp;♂\u0026nbsp;and 14\u0026nbsp;♀, considered \u0026lsquo;extreme Bingers\u0026rsquo; with EtOH consumption at 1.60 g/kg and the time to obtain 50% of the rewards at 4.20 min\u003c/p\u003e\n\u003cp\u003e- Group 4, consisting of 8\u0026nbsp;♂\u0026nbsp;and 4\u0026nbsp;♀, considered the \u0026lsquo;social drinkers\u0026rsquo; with EtOH consumption at 0.33 g/kg and time to obtain 50% of the rewards at 1.21min.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAUD-associated behaviors\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe statistical analysis of the different AUD-associated behaviors is listed in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe consumption averaged over the 3 last sessions of drinking in the 2BCIA procedure indicates that the 3 groups categorized as \u0026lsquo;bingers\u0026rsquo; (Group 1, 2 and 3) do not differ between them but are all significantly higher drinker than the group 4 (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1: AUD-associated behaviors in the 4 identified groups of the whole population (males and females).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUD-associated behaviors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANOVA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFast bingers\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 18F + 18M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBingers\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 4F + 9M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eExtreme bingers\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 14F + 5M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSocial drinkers\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 4F + 8M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ePost hoc\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;pairwise comparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2BC consumption\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g/kg/24hr)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003e(3,76)\u003c/sub\u003e = 6.23 p\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.39 \u0026plusmn; 0.5 **\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.09 \u0026plusmn; 0.82\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.33 \u0026plusmn; 0.62 ***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.73 \u0026plusmn; 0.73\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(G3=G1=G2)\u0026gt;G4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSA \u0026ndash; Active lever presses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003e(3,76)\u003c/sub\u003e = 24.496 p\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e53.69 \u0026plusmn; 2.72\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e55.00 \u0026plusmn; 5.67\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e80.32 \u0026plusmn; 5.00\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22.33 \u0026plusmn; 5.14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG3\u0026gt;G2=G1\u0026gt;G4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSA \u0026ndash; EtOH consumed (g/kg/15 min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003e(3,76)\u003c/sub\u003e = 74.886\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.94 \u0026plusmn; 0.03\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.94 \u0026plusmn; 0.08 ***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.60 \u0026plusmn; 0.06 ***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.33 \u0026plusmn; 0.08\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG3\u0026gt;G2=G1\u0026gt;G4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpeed of consumption (time to achieve 50% of total consumption - min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003e(3,76)\u003c/sub\u003e = 50.68\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.14 \u0026plusmn; 0.16 ***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.59 \u0026plusmn; 0.40 ***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.20 \u0026plusmn; 0.28 ***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.21 \u0026plusmn; 0.35\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG4\u0026gt;G1\u0026gt;G3\u0026gt;G2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMotivation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(active lever presses)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003e(3,76)\u003c/sub\u003e = 4,249 p\u0026lt;0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e85.51 \u0026plusmn; 4.78\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e81.38 \u0026plusmn; 8.43\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e96.84 \u0026plusmn; 8,97\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40.67 \u0026plusmn; 11.38\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eG3\u0026gt;G1=G2\u0026gt;G4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeeking\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(active lever presses)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003e(3,76)\u003c/sub\u003e = 6,469 p\u0026lt;0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e60.69 \u0026plusmn; 3.33\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e59.62 \u0026plusmn; 8.31\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e63.84 \u0026plusmn; 7.04\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.42 \u0026plusmn; 6.70\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(G3=G1=G2)\u0026gt;G4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCue Omission\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(active lever presses)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003e(3,76)\u003c/sub\u003e = 9,619 p\u0026lt;0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e55.61 \u0026plusmn; 4.04\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e57.38 \u0026plusmn; 7.85\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e61.89 \u0026plusmn; 4.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20.50 \u0026plusmn; 4.87\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(G3=G2=G1)\u0026gt;G4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRelapse\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g/kg/15 min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003e(3,76)\u003c/sub\u003e = 9.99\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.38 \u0026plusmn; 0.07\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.34 \u0026plusmn; 0.15\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.62 \u0026plusmn; 0.11\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.67 \u0026plusmn; 0.15\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(G3=G2=G1)\u0026gt;G4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithdrawal Score (arbitrary unit)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eF\u003csub\u003e(3,75)\u003c/sub\u003e = 1.61\u003c/p\u003e\n \u003cp\u003ep=0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.60 \u0026plusmn; 0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2.00 \u0026plusmn; 0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e2.21 \u0026plusmn; 0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1.50 \u0026plusmn; 0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eG1=G2=G3=G4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAfter prolonged training to self-administer alcohol, the group \u0026lsquo;extreme bingers\u0026rsquo; significantly drink more pure ethanol than all other groups (Fig. 2A). \u0026lsquo;Fast bingers\u0026rsquo; (Group 1) consume the 50% of their total amount faster than the \u0026lsquo;bingers\u0026rsquo; (Group 2) but not than the \u0026lsquo;extreme bingers\u0026rsquo; (Group 3) and \u0026lsquo;social drinkers\u0026rsquo; (Group 4) (Fig. 2B). Profiles of operant responding, meaning the number of active lever presses, are similar to the quantity of ethanol consumed (Fig. 2C). Motivation (Fig. 2D), seeking (Fig. 2E), response during a cue omission test (Fig. 2F) and relapse after abstinence (Fig. 2G) are similar between the 3 bingers groups and all 3 groups are significantly higher than the \u0026lsquo;social drinkers\u0026rsquo;. During the period of abstinence, withdrawal score was measured and we found a trend to have higher score for the \u0026lsquo;extreme bingers\u0026rsquo; as compare to \u0026lsquo;fast bingers\u0026rsquo; and \u0026lsquo;social drinkers\u0026rsquo; (Fig. 2H). Within each of the clusters, the sex distribution is very different with 50% of males in the \u0026lsquo;fast bingers\u0026rsquo; group, more than 60% of males in the \u0026lsquo;bingers\u0026rsquo; group and more than 70% of females in the \u0026lsquo;extreme bingers\u0026rsquo; group. We finally found a majority of males in the \u0026lsquo;social drinkers\u0026rsquo; (Fig. 2I).\u003c/p\u003e\n\u003cp\u003eIn order to evaluate if rats did their transition from controlled to uncontrolled behavior, we performed, as already mentioned, a satiety test (Fig. 3A). During the free hour of access to alcohol in the homecage, we only found one statistical difference between the \u0026lsquo;extreme bingers\u0026rsquo; and the \u0026lsquo;social drinkers\u0026rsquo; that drink less (Fig. 3B). After devaluation, during a regular FR3-15 min session of self-administration we observed a higher consumption in the \u0026lsquo;extreme bingers\u0026rsquo; as compared to the \u0026lsquo;bingers\u0026rsquo; and \u0026lsquo;social drinkers\u0026rsquo; (Fig. 3C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cu\u003eSex differences\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe identified that there was some discrepancy in the sex balance in some of the groups an especially in the group \u0026ldquo;Extreme Bingers\u0026rdquo;, thus we analyzed the data based on the sex. The results are depicted in Fig. 4 and the statistical analysis of these data in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: AUD-associated behaviors in males and females.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUD-associated behaviors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudent\u0026rsquo;s t-test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% of change vs. Males\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2BC consumption (g/kg/24hr)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep = 0.046\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.41 \u0026plusmn; 0.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.60 \u0026plusmn; 0.45 *\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026gt; M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSA \u0026ndash; Active lever presses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003ep = 0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e60.95 \u0026plusmn; 4.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e50.10 \u0026plusmn; 3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eM \u0026gt; F (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSA \u0026ndash; EtOH consumed (g/kg/15 min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep = 0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.86 \u0026plusmn; 0.07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.16 \u0026plusmn; 0.07 **\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026gt; M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpeed of consumption (time to achieve 50% of total consumption - min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep = 0.043\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.28 \u0026plusmn; 0.31\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.45 \u0026plusmn; 0.27 *\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-20%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026gt; M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMotivation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(active lever presses)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003ep = 0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e82.30 \u0026plusmn; 6.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e79.58 \u0026plusmn; 5.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eM = F (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeeking \u0026ndash; Drug Omission\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(active lever presses)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep = 0.004\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e47.60 \u0026plusmn; 3.90\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e64.95 \u0026plusmn; 4.30 **\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e36%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026gt; M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCue Omission\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(active lever presses)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003ep = 0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e56.43 \u0026plusmn; 4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e47.83 \u0026plusmn; 3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eM \u0026gt; F (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRelapse (g/kg/15 min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003ep = 0.0003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.10 \u0026plusmn; 0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.54\u0026nbsp;\u003c/strong\u003e\u0026plusmn;\u003cstrong\u003e\u0026nbsp;0.08\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026gt; M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithdrawal Score (arbitrary unit)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep = 0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.46 \u0026plusmn; 0.17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.13 \u0026plusmn; 0.18 **\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e46%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026gt; M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSatiety\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e1 hr free EtOH consumed\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g/kg/1 hr)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep = 0.0017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.11 \u0026plusmn; 0.10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.57 \u0026plusmn; 0.10 **\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026gt; M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSatiety\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eEtOH consumed post devaluation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(g/kg/15 min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.12 \u0026plusmn; 0.02\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.34\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;0.04 ***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e183%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF \u0026gt; M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFirst during the 2BCIA procedure, the average of alcohol consumed over the 3 last drinking sessions, females consumed significantly more ethanol than males (7.60\u0026nbsp;\u0026plusmn;\u0026nbsp;0.45 vs 6.41\u0026nbsp;\u0026plusmn;\u0026nbsp;0.38 g/kg/24 hrs, p \u0026lt; 0.05, Table 2). After weeks of stabilization of the operant behaviour, female rats consumed more ethanol than males (Fig. 4A) and do it faster (Fig. 4B) without exhibiting higher number of active lever presses (Fig. 4C). Despite this higher consumption, motivation measured as the breaking point during a progressive Ration test is not different between males and females (Fig. 4D). We thus evaluated the sensitivity to the presence or absence of the drug and of the associated cues. During the seeking session, in which no alcohol is provided despite the active lever presses and the presence of the cues, the females significantly pressed more than the males (Fig. 4E). On the opposite, when drug was delivered but no cues were associated to the delivery, no difference between both sexes (Fig. 4F). During these 2 sessions, some rats showed an increase in active lever presses as compared to baseline responding (3 consecutive self-administration sessions). Interestingly, for the \u0026ldquo;seeking\u0026rdquo; as well as for the \u0026ldquo;cue omission\u0026rdquo; sessions higher proportion of females exhibited this increase (67.5% vs 30% for the \u0026ldquo;seeking sessions\u0026rdquo; and 37.5% vs. 22.5% for the \u0026ldquo;cue omission\u0026rdquo; session). Thirty percent of female rats increased their pressing levels in both sessions (seeking and cue omission) whereas only 12.5% of males did (Fig. 4G, Chi\u003csup\u003e2\u003c/sup\u003e p \u0026lt; 0.001). After a prolonged abstinence, females rats showed higher level of relapse than males ((Fig. 4H). During this abstinence period, female rats exhibited also higher withdrawal score than males (Fig. 4I).\u003c/p\u003e\n\u003cp\u003eIn regard to the perseverance of instrumental responding despite reward devaluation, we performed, as previously described, a satiety test to assess whether animals would reduce their lever pressing when the value of the ethanol reward was diminished (Fig. 5A). During the free access period to alcohol in the homecage, female rats consumed significantly more alcohol than males (+22%, Fig. 5B). Interestingly, this higher intake persisted in the subsequent operant self-administration session, during which female rats consumed drastically more alcohol than males (+183%, Fig. 5C).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBinge drinking is a heterogeneous pattern of alcohol consumption characterized by multiple dimensions, including the speed, quantity, and frequency of intake, as well as associated consequences such as blackout episodes and the severity of hangovers. Building on our previous results on binge drinking behavior in students showing the existence of four subgroups \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, we applied a similar type of clustering analysis to our animal model of operant binge drinking, which we have developed and begun to characterize \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e,although without initially considering sex differences.\u003c/p\u003e \u003cp\u003eOur cohort of 80 rats (40 females and 40 males) was trained to self-administer an ethanol solution during short, binge-like access periods, providing a robust and sex-balanced model of excessive alcohol intake. After a minimum of eight weeks of training, this longitudinal design allowed us to establish stable baseline consumption levels and to systematically evaluate a comprehensive set of parameters associated with AUD. Our first unsupervised clustering analysis based on criteria of alcohol quantity and consumption speed identified, similar to our clinical study\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, four distinct groups. Among the four groups, there is group 1 of \u0026lsquo;Fast Bingers\u0026rsquo; characterized by rapid consumption of large amount of alcohol, group 2 of \u0026lsquo;Bingers\u0026rsquo; who drink similar large amount of alcohol but a little bit slower, group 3 of \u0026lsquo;Extreme bingers\u0026rsquo; characterized by heavy alcohol consumption, and group 4 of \u0026lsquo;Social drinkers\u0026rsquo; characterized by lower motivation, seeking, and relapse. Social drinkers only had to perform 11 presses and thus to consume 3 rewards to achieve the 50% of their total amount whereas the extreme bingers had to perform 40 active lever presses to achieve their 50% of total amount. That certainly explain the speed of consumption for the \u0026lsquo;social drinkers\u0026rsquo; group. The markedly higher alcohol consumption in Group 3 (\u0026lsquo;Extreme bingers\u0026rsquo;) was accompanied by a trend toward higher withdrawal scores relative to the other groups.\u003c/p\u003e \u003cp\u003eBinge drinking and AUD may be associated with habit learning development, and it is conceivable that habit learning among binge drinkers could play a role in the transition from binge drinking behavior to AUD. Previous studies have suggested that binge drinking is a repetitive behavior which can lead to the formation of habits and have also shown that student alcohol consumption is \u0026lsquo;automatically activated by relevant contextual cues\u0026rsquo; \u003csup\u003e17\u003c/sup\u003e. Habitual binge drinking can be assessed with the Self-Report Habit Index that is composed of some items such as \u0026lsquo;I do frequently\u0026rsquo;, \u0026lsquo;I do automatically\u0026rsquo;, \u0026lsquo;I do without having to consciously remember\u0026rsquo; and \u0026lsquo;I do without thinking\u0026rsquo; \u003csup\u003e17\u003c/sup\u003e. High automaticity score has been associated with an increased risk of harmful alcohol use \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In animals, when operant behavior is unaffected by a loss of subjective value of alcohol (devaluation), the behavior is considered habitual. Interestingly, our results indicate that group 3 of \u0026lsquo;Extreme bingers\u0026rsquo;, predominantly females, tends to consume the most alcohol in a devaluation session and exhibit behavior of perseverance of alcohol consumption despite satiety. This initial analysis also revealed sex-related proportion differences among the groups, with an equal distribution of males and females in group 1, more males in groups 2 and 4, and more females in group 3 of \u0026lsquo;Extreme bingers\u0026rsquo;. This prompted us to conduct a more in-depth analysis of the results across the entire cohort, focusing on sex differences.\u003c/p\u003e \u003cp\u003eSex-specific analyses show that females consume more alcohol (35% increase) with a slightly higher consumption speed (20% decrease of the latency to achieve 50% of their total intake). While there is no difference in motivation to consume, females exhibit higher alcohol-seeking behavior (36% increase) associated with higher relapse (+\u0026thinsp;40%) and withdrawal scores (46% increase). It is also observed that the proportion of females significantly increases their alcohol-seeking behavior when the drug is omitted and that the number of active lever presses tends to be decreased when the cue associated with the drug is omitted. This aligns with previous rodent studies reporting that females consume more alcohol relative to their body weight and display higher levels of cue-mediated alcohol-seeking behaviors than male \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The lack of sex-related difference observed here is also in line with previous study that measured breakpoints in Long Evans rats, but in this study, lower breakpoint values were achieved (around 10) compared to the ones we obtained (around 20) \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e probably due to the duration of the session 30 minutes vs. 15 minutes), but also to the difference in the schedule of increment used in both studies and the type of alcohol solution (20% v/v for our study and 15% ethanol\u0026thinsp;+\u0026thinsp;2% sucrose in Randall\u0026rsquo;s one). The interplay between gonadal hormones and dopamine offers valuable insights into the molecular mechanisms that underlie sex differences in the rewarding properties of alcohol \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Our results also demonstrate that females, as expected, consume more alcohol when alcohol is available \u003cem\u003ead libitum\u003c/em\u003e in their home cage for devaluation in the satiety test. We did not investigate the effect of the estrous cycle on alcohol-related behaviors in our rats because it has been repeatedly demonstrated that estrous cycle does not substantially impact alcohol intake in naturally cycling rats \u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile the rewarding effects of alcohol contribute substantially to its addictive potential, there is a growing acknowledgment that the aversive properties of alcohol also wield a crucial influence on the inclination to consume it. Following recurrent episodes of binge drinking, individuals may develop a negative affective state upon voluntarily or involuntarily withdrawal from alcohol. This encompasses dysregulated stress hormone levels, dysphoria, anxiety, depression, and irritability, an array of symptoms believed to stem, at least in part, from adaptations in stress-related neural pathways \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. We showed that females displayed more severe withdrawal score and this result suggests that increased sensitivity to the aversive properties of alcohol withdrawal may contribute to higher levels of binge drinking in order to alleviate withdrawal symptoms. These results are in line with clinical observations suggesting that women are more likely to drink alcohol to alleviate unpleasant emotions and relapse in response to negative affect \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. To pursue on this line, our data reveal that females exhibit higher consumption than males during relapse after abstinence. Although we observed a higher level of ethanol relapse in females compared to males after 10 days of abstinence, another study conducted on Long Evans rats demonstrated the opposite trend, with no relapse behavior observed in females and a clear relapse in males after a 3-week period of abstinence \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. However, in this later study, rats had access to alcohol during 30 minutes sessions and with sucrose added to the ethanol solution. We already demonstrated that, even with a similar level of alcohol self-administration, the speed of consumption is crucial to alter alcohol-associated behaviors \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. After prolonged abstinence, alcohol-associated cues can acquire strong incentive salience, thereby intensifying cravings and precipitating relapse \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In humans, men generally report higher levels of alcohol craving than women \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, and similarly, male rodents are often described as more susceptible to relapse than females \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. However, our findings point in the opposite direction since in our paradigm, females displayed more pronounced seeking behavior when alcohol was omitted, as well as higher drinking levels during relapse following abstinence.\u003c/p\u003e \u003cp\u003eFinally, in our study, females showed a tendency to reduce their level of active responses during cue omission, yet increased their operant responding during the seeking session (in which no alcohol was available). Compared with males, this pattern suggests that females may be particularly sensitive to the presence or absence of alcohol-associated cues and may rely more strongly on cue-reward associations. Consequently, females seem to interpret the presence of cues as signaling that the drug should be available, which promote the persistence of responding even when ethanol is absent. Our findings therefore suggest that cue-drug associations are stronger in females than in males within this paradigm. Supporting this interpretation, a greater proportion of females increased their lever pressing in these two cue-sensitive tests compared with males. Other studies using food as the reward, have suggested that females not only engage more, and may acquire more in stimulus-directed Pavlovian approach behaviors (i.e; sign-tracking) but also acquire these behaviors more rapidly than males \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Sign-tracking refers to the attraction toward cues that predict a reward, reflecting incentive motivational processes directed both toward the reward itself and toward its associated cues. This behavior has been linked to excessive and inflexible reward-seeking tendencies. Under outcome devaluation conditions, animals that continue to engage with cues associated with a now-devalued reward are often considered to display compulsive or overly habitual responding. However, another study in Long Evans rats reported that females and males acquire sign-tracking at similar rates and show comparable levels of sign-tracking following outcome devaluation \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. In contrast, our findings show that females increased their active lever responses during the seeking session (when alcohol was unavailable), and persisted in consummatory-like responding despite reward devaluation. This pattern suggests that at least some females may have developed habit-based responding and may no longer rely on goal-directed control.\u003c/p\u003e \u003cp\u003eIn addition, our study revealed that females exhibit a reduced sensitivity to outcome devaluation, which can be interpreted as a form of behavioral inflexibility. In contrast, males almost completely ceased alcohol consumption following devaluation. Previous work has shown that female alcohol-preferring rats display a tendency toward habitual behavior, reflected for example by an Increased latency to initiate alcohol responding after devaluation, a recognized indicator of habit formation \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Together, these sex-related differences are particularly intriguing, as they suggest that females may be more prone to developing automatic, habit-based behaviors that could contribute to a greater susceptibility to AUD. However, this interpretation will need confirmation from clinical studies. Supporting this hypothesis, a recent study reported that female Wistar rats displayed higher levels of compulsive alcohol self-administration, both foot-shock-resistant and quinine-resistant behaviors that are commonly interpreted as reflecting a transition from goal-directed to habitual responding \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Similarly, another systematically devaluating alcohol by delaying its delivery found that females persistently engaged in habitual responding despite delay-induced reinforcer devaluation \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Overall, our results, in combination with findings from these previous studies, suggest that females may be more vulnerable to the development of habit learning and compulsive alcohol use, which aligns with clinical observations indicating that women may be particularly at risk for the rapid emergence of AUD.\u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003ePerspective and significance\u003c/h2\u003e \u003cp\u003ePreclinical models are essential for dissecting the behavioral and neurobiological mechanisms that underlie binge drinking. Recognizing sex as a critical biological variable is fundamental to identifying vulnerability factors contributing to the initiation and escalation of binge drinking behaviors. Our dataset provides a comprehensive characterization of how sex differences shape alcohol drinking patterns, offering valuable insights that can guide the development of improved prevention and treatment strategies. Moreover, as recently demonstrated by our group \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, pharmacological treatments for AUD may differ in efficacy between males and females, highlighting the necessity of systematically incorporating both sexes in preclinical and translational research on AUD.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, our study used unsupervised clustering analyses to identify distinct groups of binge drinking profiles, mirroring the heterogeneity observed in clinical populations. We identified four primary groups on multiple drinking dimensions. Our findings highlight the importance of resistance to reward devaluation as key feature of binge drinking behavior and a potential marker of vulnerability to AUD. We also observed clear sex-related differences across these groups, females exhibited stronger alcohol-seeking responses, higher withdrawal scores, and increased consumption during relapse compared with males. Furthermore, our data suggest that females may be more prone to developing cue-driven automatic behaviors, consistent with habit learning, which could contribute to their heightened susceptibility to AUD. Altogether, these findings provide important insights into the complex interplay between sex, drinking trajectories, and the development of compulsive alcohol use, and they underscore the need for continued investigation in clinical populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExperimental procedures were conducted in accordance with the European Union Directive 2010/63/EU, and the protocol was approved by the Ethics Committee for Animal Care and Use at University of Picardie Jules Verne (CREMEAP).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study can be made available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOpen access funding provided by University of Picardie Jules Verne. This study was supported by the IReSP in the framework of the 2021 call for the research against the uses and addictions to psychoactive substances (SPAV1-22-019) and by the INSERM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJJ, AS drafted the manuscript and analyzed and interpreted the data. JJ, AS conducted experiments, collected, and processed the data. MN processed the data. JJ and MN designed/supervised experiments and revised the manuscript. All authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eINSERM UMR1247 - Groupe de Recherche sur l’alcool et les pharmacodépendances GRAP. Université de Picardie Jules Verne, Centre universitaire de recherche en santé CURS, Chemin du Thil, 80025, Amiens, France.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRolland B, Naassila M. Binge Drinking: Current Diagnostic and Therapeutic Issues. CNS Drugs. 2017;31:181\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaurage P, Lannoy S, Mange J, Grynberg D, Beaunieux H, Banovic I, et al. What We Talk About When We Talk About Binge Drinking: Towards an Integrated Conceptualization and Evaluation. Alcohol Alcohol. 2020;55:468\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndr\u0026eacute; J, Diouf M, Martinetti MP, Ortelli O, Gierski F, F\u0026uuml;rst F, et al. A new statistical model for binge drinking pattern classification in college-student populations. 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Front Pharmacol. 2023;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fphar.2023.1146848\u003c/span\u003e\u003cspan address=\"10.3389/fphar.2023.1146848\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"biology-of-sex-differences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bosd","sideBox":"Learn more about [Biology of Sex Differences](http://bsd.biomedcentral.com)","snPcode":"13293","submissionUrl":"https://submission.nature.com/new-submission/13293/3","title":"Biology of Sex Differences","twitterHandle":"@BiologySexDiff","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Binge Drinking, alcohol, sex differences, operant self-administration, relapse, withdrawal","lastPublishedDoi":"10.21203/rs.3.rs-8561890/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8561890/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWhile binge drinking can significantly impact health negatively, it has become increasingly important to understand how sex differences contribute to this hazardous behavior, which may also serve as a risk factor for alcohol use disorder. We employed the binge drinking experimental model we developed previously to specifically analyze sex differences.\u003c/p\u003e \u003cp\u003eForty male and 40 female Long Evans rats were tested in the alcohol self-administration procedure, operationalized as alcohol responding in short daily session. We tested other parameters, including motivation, seeking, responses during cue omission sessions, withdrawal scores, and relapse after abstinence. We also conducted experiments to assess perseverance despite satiety. For the analysis we used first an unsupervised clustering approach using drinking speed and frequency of alcohol responses and then we analyzed our data by taking sex as the differentiating factor.\u003c/p\u003e \u003cp\u003eUnbiased clustering analysis revealed four distinct groups: Fast Bingers, Bingers, Extreme Bingers and Social drinkers. Higher alcohol consumption and faster consumption speed correlated with elevated withdrawal scores. Sex-related differences were observed, with females outnumbering males in Extreme bingers. Females also exhibited higher alcohol-seeking behavior, relapse rates, and withdrawal scores. In addition, females exhibit lower sensitivity to devaluation in the satiety test.\u003c/p\u003e \u003cp\u003eOur results suggest that females display greater vulnerability to cue-mediated alcohol-seeking behaviors and a more inflexible behavior. This underscores the importance of considering sex as a biological variable in both preclinical and clinical research on binge drinking behaviors that is not only a hazardous behavior but may also be a critical factor in AUD vulnerability, particularly in females.\u003c/p\u003e","manuscriptTitle":"Female rats are more vulnerable to binge drinking behavior in an operant self-administration paradigm: implication for transition to alcohol use disorders","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-14 18:46:17","doi":"10.21203/rs.3.rs-8561890/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-14T14:55:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-14T04:03:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-08T20:04:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-27T21:54:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"106952742941693075608404023987167127052","date":"2026-01-13T00:32:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58329190132266512437336281625872819188","date":"2026-01-12T23:20:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66458636740403928088875272394727964551","date":"2026-01-12T21:05:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-12T19:00:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-12T05:57:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-12T05:55:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biology of Sex Differences","date":"2026-01-09T13:58:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biology-of-sex-differences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bosd","sideBox":"Learn more about [Biology of Sex Differences](http://bsd.biomedcentral.com)","snPcode":"13293","submissionUrl":"https://submission.nature.com/new-submission/13293/3","title":"Biology of Sex Differences","twitterHandle":"@BiologySexDiff","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"21f46340-01d8-4bad-a22c-d9fddb638cf3","owner":[],"postedDate":"January 14th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T16:05:42+00:00","versionOfRecord":{"articleIdentity":"rs-8561890","link":"https://doi.org/10.1186/s13293-026-00912-x","journal":{"identity":"biology-of-sex-differences","isVorOnly":false,"title":"Biology of Sex Differences"},"publishedOn":"2026-04-29 15:58:36","publishedOnDateReadable":"April 29th, 2026"},"versionCreatedAt":"2026-01-14 18:46:17","video":"","vorDoi":"10.1186/s13293-026-00912-x","vorDoiUrl":"https://doi.org/10.1186/s13293-026-00912-x","workflowStages":[]},"version":"v1","identity":"rs-8561890","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8561890","identity":"rs-8561890","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}