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<article xml:lang="en" article-type="research-article" dtd-version="1.4"><processing-meta base-tagset="archiving" mathml-version="3.0" table-model="xhtml" tagset-family="jats"><restricted-by>pmc</restricted-by></processing-meta><front><journal-meta><journal-id journal-id-type="nlm-ta">Front Pharmacol</journal-id><journal-id journal-id-type="iso-abbrev">Front Pharmacol</journal-id><journal-id journal-id-type="pmc-domain-id">1524</journal-id><journal-id journal-id-type="pmc-domain">frontpharmacol</journal-id><journal-id journal-id-type="nlm-id">101548923</journal-id><journal-id journal-id-type="publisher-id">Front. Pharmacol.</journal-id><journal-title-group><journal-title>Frontiers in Pharmacology</journal-title></journal-title-group><issn pub-type="epub">1663-9812</issn><?publisher_abbrev frontiers?><publisher><publisher-name>Frontiers Media SA</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmcid">PMC11384591</article-id><article-id pub-id-type="pmcid-ver">PMC11384591.1</article-id><article-id pub-id-type="pmcaid">11384591</article-id><article-id pub-id-type="pmcaiid">11384591</article-id><article-id pub-id-type="pmid">39257392</article-id><article-id pub-id-type="doi">10.3389/fphar.2024.1448170</article-id><article-id pub-id-type="publisher-id">1448170</article-id><article-version article-version-type="pmc-version">1</article-version><article-categories><subj-group subj-group-type="heading"><subject>Pharmacology</subject><subj-group><subject>Original Research</subject></subj-group></subj-group></article-categories><title-group><article-title>Cannabidiol or ketamine for preventing the impact of adolescent early drug initiation on voluntary ethanol consumption in adulthood</article-title><alt-title alt-title-type="left-running-head">Colom-Rocha et al.</alt-title><alt-title alt-title-type="right-running-head">
<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://doi.org/10.3389/fphar.2024.1448170" ext-link-type="uri">10.3389/fphar.2024.1448170</ext-link>
</alt-title></title-group><contrib-group><contrib contrib-type="author"><name name-style="western"><surname>Colom-Rocha</surname><given-names initials="C">Carles</given-names></name><xref rid="aff1" ref-type="aff">
<sup>1</sup>
</xref><xref rid="aff2" ref-type="aff">
<sup>2</sup>
</xref><xref rid="aff3" ref-type="aff">
<sup>3</sup>
</xref><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/methodology/"/><role content-type="https://credit.niso.org/contributor-roles/investigation/"/><role content-type="https://credit.niso.org/contributor-roles/Writing - review &amp; editing/"/></contrib><contrib contrib-type="author"><name name-style="western"><surname>Bis-Humbert</surname><given-names initials="C">Cristian</given-names></name><xref rid="aff1" ref-type="aff">
<sup>1</sup>
</xref><xref rid="aff2" ref-type="aff">
<sup>2</sup>
</xref><xref rid="fn1" ref-type="author-notes">
<sup>†</sup>
</xref><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/investigation/"/><role content-type="https://credit.niso.org/contributor-roles/methodology/"/><role content-type="https://credit.niso.org/contributor-roles/Writing - review &amp; editing/"/></contrib><contrib contrib-type="author" corresp="yes"><name name-style="western"><surname>García-Fuster</surname><given-names initials="MJ">M. Julia</given-names></name><xref rid="aff1" ref-type="aff">
<sup>1</sup>
</xref><xref rid="aff2" ref-type="aff">
<sup>2</sup>
</xref><xref rid="aff3" ref-type="aff">
<sup>3</sup>
</xref><xref rid="c001" ref-type="corresp">*</xref><uri xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://loop.frontiersin.org/people/499361/overview"/><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/methodology/"/><role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/><role content-type="https://credit.niso.org/contributor-roles/supervision/"/><role content-type="https://credit.niso.org/contributor-roles/validation/"/><role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/></contrib></contrib-group><aff id="aff1">
<sup>1</sup>
<institution>University Research Institute of Health Sciences</institution>, <institution>University of the Balearic Islands</institution>, <addr-line>Palma</addr-line>, <country>Spain</country>
</aff><aff id="aff2">
<sup>2</sup>
<institution>Health Research Institute of the Balearic Islands (IdISBa)</institution>, <addr-line>Palma</addr-line>, <country>Spain</country>
</aff><aff id="aff3">
<sup>3</sup>
<institution>Department of Medicine</institution>, <institution>University of the Balearic Islands</institution>, <addr-line>Palma</addr-line>, <country>Spain</country>
</aff><author-notes><fn fn-type="edited-by"><p>
<bold>Edited by:</bold>
<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://loop.frontiersin.org/people/199820/overview" ext-link-type="uri">Subhash C. Pandey</ext-link>, University of Illinois Chicago, United States</p></fn><fn fn-type="edited-by"><p>
<bold>Reviewed by:</bold>
<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://loop.frontiersin.org/people/1161075/overview" ext-link-type="uri">Jesse Schank</ext-link>, University of Georgia, United States</p><p>
<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://loop.frontiersin.org/people/91988/overview" ext-link-type="uri">Jacqueline M. Barker</ext-link>, Drexel University, United States</p></fn><corresp id="c001">*Correspondence: M. Julia García-Fuster, <email>j.garcia@uib.es</email>
</corresp><fn fn-type="present-address" id="fn1"><label>
<sup>†</sup>
</label><p>
<bold>Present address:</bold> Cristian Bis-Humbert, Department of Experimental and Health Sciences, Neurobiology of Behavior Research Group (GReNeC-NeuroBio), Universitat Pompeu Fabra, Barcelona, Spain</p></fn></author-notes><pub-date pub-type="epub"><day>27</day><month>8</month><year>2024</year></pub-date><pub-date pub-type="collection"><year>2024</year></pub-date><volume>15</volume><issue-id pub-id-type="pmc-issue-id">454176</issue-id><elocation-id>1448170</elocation-id><history><date date-type="received"><day>12</day><month>6</month><year>2024</year></date><date date-type="accepted"><day>15</day><month>8</month><year>2024</year></date></history><pub-history><event event-type="pmc-release"><date><day>27</day><month>08</month><year>2024</year></date></event><event event-type="pmc-live"><date><day>10</day><month>09</month><year>2024</year></date></event><event event-type="pmc-last-change"><date iso-8601-date="2024-09-11 17:25:16.723"><day>11</day><month>09</month><year>2024</year></date></event></pub-history><permissions><copyright-statement>Copyright © 2024 Colom-Rocha, Bis-Humbert and García-Fuster.</copyright-statement><copyright-year>2024</copyright-year><copyright-holder>Colom-Rocha, Bis-Humbert and García-Fuster</copyright-holder><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/" specific-use="textmining" content-type="ccbylicense">https://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p></license></permissions><self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pmc-pdf" xlink:href="fphar-15-1448170.pdf"><?pdf-name fphar-15-1448170.pdf?><?pdf-size 2086771?><?pdf-md5 d67612e3dd4b61b339b12a56c5ecc780?><?pdf-image-server-status NEVER_LOAD?><?pdf-cloudpmc-urn urn:app:cf83/11384591/d67612e3dd4b/fphar-15-1448170.pdf?></self-uri><abstract><sec><title>Background</title><p>Few studies have previously evaluated the long-term impact of initiating the combined use of alcohol and cocaine early-in-life during adolescence. Our preclinical study characterized changes in affective-like behavior and/or voluntary ethanol consumption emerging later on in adulthood induced by a prior adolescent drug exposure, as well as tested therapeutical interventions (i.e., cannabidiol or ketamine) to prevent the observed effects.</p></sec><sec><title>Methods</title><p>We performed three independent studies with male and female Sprague-Dawley rats, treated in adolescence (postnatal days, PND 29–38) with non-contingent paradigms of ethanol, cocaine, their combination or vehicle. Later on, adult rats were (1) scored for their affective-like state (forced-swim, elevated-plus maze, novelty-suppressed feeding, sucrose preference), (2) allowed to freely drink ethanol for 6 weeks (two-bottle choice), or (3) treated with cannabidiol or ketamine before given access to ethanol in adulthood.</p></sec><sec><title>Results</title><p>No signs of increased negative affect were observed in adulthood following the adolescent treatments. However, adolescent ethanol exposure was a risk-factor for later developing an increased voluntary ethanol consumption in adulthood, both for male and female rats. This risk was similar when ethanol was combined with adolescent cocaine exposure, since cocaine alone showed no effects on later ethanol intake. Finally, rats exposed to adolescent ethanol and pretreated in adulthood with cannabidiol (and/or ketamine, but just for females) reduced their ethanol voluntary consumption.</p></sec><sec><title>Conclusion</title><p>Our data provided two therapeutical options capable of preventing the impact of an early drug initiation during adolescence by decreasing voluntary ethanol consumption in adult rats</p></sec></abstract><kwd-group><kwd>addiction risk factors</kwd><kwd>adolescence</kwd><kwd>alcohol use disorder</kwd><kwd>sex differences</kwd><kwd>therapeutical options</kwd><kwd>rodent models</kwd></kwd-group><funding-group><funding-statement>The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Research was funded by Delegación del Gobierno para el Plan Nacional sobre Drogas (grant 2020/001, Ministerio de Sanidad, Spain) to MG-F. CC-R’s salary was initially funded by the beforementioned grant, and is now supported by a pre-doctoral scholarship (FPU 2022-012-A; Conselleria de Fons Europeus, Universitat i Cultura del Govern de les Illes Balears). The program “TECH” from project “TALENT PLUS Construint Salut, Generant Valor” (IdISBa, GOIB) supported CB-H’s salary while at the University of the Balearic Islands. Open-access fees were covered by LIBERI PROGRAM 2024 (IdISBa).</funding-statement></funding-group><custom-meta-group><custom-meta><meta-name>pmc-status-qastatus</meta-name><meta-value>0</meta-value></custom-meta><custom-meta><meta-name>pmc-status-live</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-status-embargo</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-status-released</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-open-access</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-olf</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-manuscript</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-legally-suppressed</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-has-pdf</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-has-supplement</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-pdf-only</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-suppress-copyright</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-is-real-version</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-is-scanned-article</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-preprint</meta-name><meta-value>no</meta-value></custom-meta><custom-meta><meta-name>pmc-prop-in-epmc</meta-name><meta-value>yes</meta-value></custom-meta><custom-meta><meta-name>pmc-license-ref</meta-name><meta-value>CC BY</meta-value></custom-meta><custom-meta><meta-name>section-at-acceptance</meta-name><meta-value>Neuropharmacology</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="s1"><title>Highlights</title><p>
<list list-type="simple"><list-item><p>Adolescent ethanol exposure is a risk-factor for later voluntary ethanol consumption.</p></list-item><list-item><p>This increased vulnerability is observed both for male and female rats.</p></list-item><list-item><p>Adding cocaine exposure in adolescence does not increase the observed risk.</p></list-item><list-item><p>Cannabidiol (and/or ketamine, but just for females) reduced the observed risk.</p></list-item></list>
</p></sec><sec id="s2"><title>Background</title><p>Besides our individual biological genetic predisposition, several other factors might be responsible for a higher risk of developing substance use disorder later in life, especially early drug initiation during adolescence (<xref rid="B52" ref-type="bibr">Morales et al., 2020</xref>; <xref rid="B53" ref-type="bibr">Nawi et al., 2021</xref>). Interestingly, adolescence is a period of critical brain development that appears to be highly conserved across species in terms of its neurobehavioral and physiological features. Similar to the stages observed in humans, early (10–13 years), middle (14–17 years), and late adolescence/young adulthood [18–21 years (<xref rid="B12" ref-type="bibr">Christie and Viner, 2005</xref>; <xref rid="B2" ref-type="bibr">Backes and Bonnie, 2019</xref>)], in rodents, adolescence could be divided into early (postnatal day, PND 21–34), mid (PND 34-46) and late adolescence [PND 46-59 (<xref rid="B64" ref-type="bibr">Spear, 2004</xref>)]. Therefore, the use of rodents provides a great preclinical model (<xref rid="B27" ref-type="bibr">García-Fuster, 2021</xref>; <xref rid="B54" ref-type="bibr">Nieto et al., 2021</xref>) with face and construct validity (<xref rid="B64" ref-type="bibr">Spear, 2004</xref>) in which to study particular windows of adolescent vulnerability to psychopathology and therapeutic strategies (<xref rid="B1" ref-type="bibr">Adriani and Laviola, 2004</xref>).</p><p>In this context, our research group, among others [reviewed by <xref rid="B67" ref-type="bibr">Steinfeld and Torregrossa (2023)</xref>], aimed at characterizing adolescent windows of vulnerability during which the use of illicit drugs could be more harmful, both behaviorally and neurochemically (<xref rid="B26" ref-type="bibr">García-Cabrerizo et al., 2015</xref>; <xref rid="B24" ref-type="bibr">García-Cabrerizo and García-Fuster, 2016</xref>; <xref rid="B25" ref-type="bibr">García-Cabrerizo and García-Fuster, 2019</xref>; <xref rid="B30" ref-type="bibr">García-Fuster et al., 2017</xref>; <xref rid="B56" ref-type="bibr">Parsegian et al., 2022</xref>). In particular, a regimen of adolescent cocaine exposure known to induce psychomotor sensitization was more harmful during PND 33-39 than other earlier (PND 26-32) or later (PND 40-46) windows of adolescence (<xref rid="B26" ref-type="bibr">García-Cabrerizo et al., 2015</xref>), showing signs of increased negative affect (<xref rid="B25" ref-type="bibr">García-Cabrerizo and García-Fuster, 2019</xref>) and addictive-like behaviors (<xref rid="B30" ref-type="bibr">García-Fuster et al., 2017</xref>; <xref rid="B56" ref-type="bibr">Parsegian et al., 2022</xref>) when rats were re-exposed to cocaine in adulthood, as well as changes in neurochemical markers of neurotoxicity (<xref rid="B26" ref-type="bibr">García-Cabrerizo et al., 2015</xref>; <xref rid="B24" ref-type="bibr">García-Cabrerizo and García-Fuster, 2016</xref>; <xref rid="B30" ref-type="bibr">García-Fuster et al., 2017</xref>; <xref rid="B56" ref-type="bibr">Parsegian et al., 2022</xref>). Although all of these studies were done in male rats, we also recently reported that adolescent cocaine induced persistent negative affect in adult female rats (<xref rid="B8" ref-type="bibr">Bis-Humbert and García-Fuster, 2021</xref>). Therefore, this window and pattern of cocaine exposure during mid-adolescence is of high vulnerability to the long-term effects emerging in adulthood and caused by an early drug initiation.</p><p>Interestingly, cocaine is rarely consumed alone, since it is frequently combined with alcohol; out of the individuals who reported heavy alcohol use in the past month, 5% also consumed cocaine (<xref rid="B34" ref-type="bibr">Graziani et al., 2014</xref>). Both the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) as well as the National Center for Drug Abuse Statistics (NCDAS) in US, yearly report that alcohol is by far the most commonly consumed substance among teens and young adults. This data proves an earlier initiation and a higher use for alcohol, as compared to cocaine, and therefore suggests that alcohol initiation will be generally sooner, and that the combined use of both drugs would parallel the time at which cocaine’s use is started. The many prior studies evaluating the effects of adolescent alcohol consumption suggested that the behavioral irregularities (i.e., elevations in anxiety, disinhibition, impulsivity and risk-taking, decreased cognitive flexibility) and neural consequences of adolescent alcohol use may persist into adulthood [reviewed by <xref rid="B65" ref-type="bibr">Spear (2016)</xref>; <xref rid="B66" ref-type="bibr">Spear (2018)</xref>; <xref rid="B45" ref-type="bibr">Lees et al. (2020)</xref>], including an increased ethanol drinking in adulthood (<xref rid="B69" ref-type="bibr">Strong et al., 2010</xref>; <xref rid="B61" ref-type="bibr">Sherrill et al., 2011</xref>). However, studies evaluating the combined impact of alcohol and cocaine have been centered mainly in the cardiotoxic effects mediated by cocaethylene (the active metabolite produced by both drugs), so there is a need for novel data on the long-term impact of initiating alcohol alone and/or combined with cocaine during adolescence on later alcohol use disorder rates in adulthood.</p><p>Against this background, we characterized the changes induced by an even earlier start of adolescent ethanol exposure at PND 28, as compared to the one previously depicted for cocaine initiation (vulnerability window starting on PND 33), as well as their combined impact on the effects emerging in adulthood, and while including both sexes in the study (<xref rid="B70" ref-type="bibr">Towers et al., 2023</xref>; <xref rid="B3" ref-type="bibr">Becker and Koob, 2016</xref>), since most of the data summarized above was done in male rodents. Particularly, we assessed affective- (i.e., behavioral despair and/or stress-coping mechanisms, anxiety-related behaviors, anhedonic-like response) and/or addictive-like behaviors [i.e., voluntary consumption: 20% ethanol two-bottle choice paradigm (<xref rid="B13" ref-type="bibr">Colom-Rocha et al., 2023</xref>)]. Then, we selected the worst outcome induced by prior adolescent drug exposure, to test whether two therapeutical interventions (cannabidiol or ketamine) would prevent the increased ethanol consumption emerging in adulthood (<xref rid="B76" ref-type="bibr">Yardley and Ray, 2017</xref>). These options were chosen based on previous preclinical and/or clinical data suggesting an amelioration of ethanol-motivated behaviors both by cannabidiol (<xref rid="B73" ref-type="bibr">Viudez-Martínez et al., 2018</xref>; <xref rid="B72" ref-type="bibr">Viudez-Martínez et al., 2020</xref>; <xref rid="B55" ref-type="bibr">Nona et al., 2019</xref>; <xref rid="B47" ref-type="bibr">Maccioni et al., 2022</xref>; <xref rid="B71" ref-type="bibr">Tringali et al., 2023</xref>; <xref rid="B31" ref-type="bibr">Gasparyan et al., 2023</xref>) or ketamine [reviews by <xref rid="B75" ref-type="bibr">Worrell and Gould (2021)</xref>; <xref rid="B32" ref-type="bibr">Goldfine et al. (2023)</xref>; <xref rid="B39" ref-type="bibr">Kelson et al. (2023)</xref>; <xref rid="B41" ref-type="bibr">Krystal et al. (2024)</xref>], although most of these studies were tested in either pups from pregnant rodents exposed to drugs during gestation, and/or in rodents that received drugs in adolescence and/or adulthood, but were tested at the same age-window of study, and therefore, data evaluating the possible preventive effects of these options following an early adolescent drug experience are missing. A pre-print version of this manuscript has been uploaded to Research Square (<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://doi.org/10.21203/rs.3.rs-3943360/v1" ext-link-type="uri">https://doi.org/10.21203/rs.3.rs-3943360/v1</ext-link>).</p></sec><sec sec-type="methods" id="s3"><title>Methods</title><sec id="s3-1"><title>Animals</title><p>A total of 196 Sprague-Dawley rats (102 males, 94 females) were bred in the animal facility at the University of the Balearic Islands. After weaning (PND 21), groups of allocated rats were used in three independent studies (<xref rid="F1" ref-type="fig">Figure 1</xref>). Unless otherwise specified, rats were housed (groups of 2–4) in standard cages following a 12 h light/dark schedule (lights on at 8:00 AM) in a climate-controlled room (22°C, 70% humidity) and with limitless access to a standard diet and water. Procedures were performed during the light-period and complied with ARRIVE Guidelines (<xref rid="B59" ref-type="bibr">Percie du Sert et al., 2020</xref>), EU Directive 2010/63/EU, and Spanish Royal Decree 53/2013, requiring prior approval by the Local Bioethical Committee (CEEA 148-09-20) and Regional Government (2021/01/AEXP). All efforts were made to minimize the number of rats used, the number of procedures and their suffering. To avoid unnecessary stress in females, the specific stages of the estrous cycle were not monitored, since cyclicity of females was not part of our research question (<xref rid="B5" ref-type="bibr">Beltz et al., 2019</xref>) and females seem as variable as males due to hormonal periodicity (<xref rid="B4" ref-type="bibr">Becker et al., 2016</xref>; <xref rid="B38" ref-type="bibr">Kaluve et al., 2022</xref>) (reinforced by the observed individual variability for males and females in this study).</p><fig position="float" id="F1" orientation="portrait"><label>FIGURE 1</label><caption><p>Experimental timeline. <bold>(A)</bold> Affective-like state during adulthood following adolescent drug exposure. <bold>(B)</bold> Evaluating voluntary ethanol consumption in adulthood following adolescent drug exposure. <bold>(C)</bold> Pharmacological intervention during adulthood before voluntary ethanol access. <bold>(A–C)</bold> Adolescent drug treatments were done at the indicated times: vehicle (V: 0.9% NaCl, 1 mL/kg/day, i. p.), ethanol (E: 2 g/kg, i. p.), cocaine (C: 15 mg/kg/day, i. p.), and/or their combination (EC: ethanol + cocaine as described). EPM, elevated plus maze; FST, forced swim test; NSF, novelty-suppressed feeding test; PND, post-natal day; SP, sucrose preference.</p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" position="float" orientation="portrait" xlink:href="fphar-15-1448170-g001.jpg"><?image-name fphar-15-1448170-g001.jpg?><?image-size 104758?><?image-md5 c37dac413d8e38938fbe4e74c4335e61?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 691?><?image-original-width 1772?><?image-scaled-height 276?><?image-scaled-width 708?><?image-cloudpmc-urn urn:cdn:blobs/cf83/11384591/c37dac413d8e/fphar-15-1448170-g001.jpg?><?thumb-name fphar-15-1448170-g001.gif?><?thumb-size 14315?><?thumb-md5 be25c9d9211c006d330113e3a7dcd956?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 78?><?thumb-scaled-width 200?><?thumb-cloudpmc-urn urn:cdn:blobs/cf83/11384591/be25c9d9211c/fphar-15-1448170-g001.gif?></graphic></fig></sec><sec id="s3-2"><title>Pharmacological treatments during adolescence</title><p>The exposure paradigm followed was based on the combination of two well-known prior paradigms for each drug separately. On one end, a psychomotor sensitizing regimen of cocaine exposure has been extensively characterized in adolescence by our research group, even the impact of the drugs at different windows during this developmental time-period (i.e., early, middle vs late adolescence) (<xref rid="B26" ref-type="bibr">García-Cabrerizo et al., 2015</xref>; <xref rid="B24" ref-type="bibr">García-Cabrerizo and García-Fuster, 2016</xref>; <xref rid="B25" ref-type="bibr">García-Cabrerizo and García-Fuster, 2019</xref>; <xref rid="B30" ref-type="bibr">García-Fuster et al., 2017</xref>; <xref rid="B56" ref-type="bibr">Parsegian et al., 2022</xref>). We selected the window starting at PND 33 that we have characterized in more detail in terms of inducing long-term changes in affective- and addictive-like behaviors (<xref rid="B26" ref-type="bibr">García-Cabrerizo et al., 2015</xref>; <xref rid="B24" ref-type="bibr">García-Cabrerizo and García-Fuster, 2016</xref>; <xref rid="B25" ref-type="bibr">García-Cabrerizo and García-Fuster, 2019</xref>; <xref rid="B30" ref-type="bibr">García-Fuster et al., 2017</xref>; <xref rid="B56" ref-type="bibr">Parsegian et al., 2022</xref>), which therefore defined the timing and cocaine regimen followed in the present experiment. On the other end, since ethanol exposure needed to start sooner than cocaine, to mimic the pattern of consumption in adolescents, ethanol was initiated on PND 29 and was administered in an intermittent fashion following a binge design. In particular, allocated adolescent male and female rats were treated with ethanol (2 g/kg, i. p; 3 rounds of 2 days at 48-h intervals; PND 29-30, PND 33-34 and PND 37–38 [<xref rid="B57" ref-type="bibr">Pascual et al., 2007</xref>; <xref rid="B58" ref-type="bibr">Pascual et al., 2017</xref>; <xref rid="B16" ref-type="bibr">Crabbe et al., 2011</xref>)], cocaine [15 mg/kg/day, i. p., 6 days from PND 33-38, as previously characterized (<xref rid="B26" ref-type="bibr">García-Cabrerizo et al., 2015</xref>; <xref rid="B24" ref-type="bibr">García-Cabrerizo and García-Fuster, 2016</xref>; <xref rid="B25" ref-type="bibr">García-Cabrerizo and García-Fuster, 2019</xref>; <xref rid="B30" ref-type="bibr">García-Fuster et al., 2017</xref>; <xref rid="B56" ref-type="bibr">Parsegian et al., 2022</xref>)], or their combination (ethanol + cocaine as described above). Also, ethanol was administered via i. p. Injections as opposed to oral gavage so it could be combined and given concomitantly with cocaine as detailed in <xref rid="F1" ref-type="fig">Figure 1</xref>. Vehicle (0.9% NaCl) was administered at the indicated days in the control group, but also at the days no ethanol or cocaine was programmed in comparison to the ethanol + cocaine group (<xref rid="F1" ref-type="fig">Figure 1</xref>). The same experimenter was involved in all pharmacological administrations and/or procedures. We relied on a non-contingent regime of drug exposure in adolescence, so we could account for the same dosing in each experimental group as opposed to the individual values we would have obtained for each rat if a contingent regime was followed.</p></sec><sec id="s3-3"><title>Affective-like state in adulthood following adolescent drug exposure</title><p>Rats from Study I were left undisturbed until adulthood (PND 64), when they were scored across time through a battery of tests following standard protocols (<xref rid="B10" ref-type="bibr">Bodnoff et al., 1988</xref>; <xref rid="B63" ref-type="bibr">Slattery et al., 2007</xref>; <xref rid="B62" ref-type="bibr">Slattery and Cryan, 2012</xref>) that measure different affective-like dimensions: forced-swim (FST: PND 64-65), elevated plus maze (EPM: PND 69), novelty-suppressed feeding (NSF: PND 73), and sucrose preference through the two-bottle choice test (SP: PND 77-78) (<xref rid="F1" ref-type="fig">Figure 1A</xref>).</p><p>The FST, which is regularly performed in our group (<xref rid="B29" ref-type="bibr">García-Fuster et al., 2012</xref>; <xref rid="B28" ref-type="bibr">García-Fuster and García-Sevilla, 2016</xref>; <xref rid="B7" ref-type="bibr">Bis-Humbert et al., 2021</xref>; <xref rid="B43" ref-type="bibr">Ledesma-Corvi et al., 2022</xref>), consisted of a pre-test session, when rats were placed in individual tanks (41 cm high × 32 cm diameter, 25 cm depth) filled with water (25°C ± 1°C) during 15 min (D1: PND 64) to learn there is no escape, followed by a 5-min test session (D2: PND 65), when the behavioral response was videotaped (<xref rid="F1" ref-type="fig">Figure 1A</xref>). Clean water tanks were used for each rat. Videos were blindly analyzed by two independent experimenters (Behavioral Tracker, CA, United States): increased immobility rates as a measure of behavioral despair vs swimming or climbing a measure of escaping behaviors. The number of feces were quantified at the end of the test session as a measurement of distress (correlated with a higher number of feces).</p><p>The EPM was later performed in a black Plexiglas maze with four elevated arms (50 cm from ground × 50 cm long × 10 cm wide), two open and two closed arms with 40 cm high walls. Each rat (PND 69) was placed for 5-min in the central square (10 cm × 10 cm) facing a closed arm (<xref rid="B29" ref-type="bibr">García-Fuster et al., 2012</xref>) and allowed to freely explore under red-lighting. The maze was cleaned with 70% ethanol between animals. Individual sessions were recorded with a Logitech HD webcam c270 and were analyzed through a computerized tracking system (SMART, v.3.0.06; Panlab Harvard Apparatus<sup>®</sup>, Barcelona, Spain) that provided several measurements: latency to open arm (s), number of open vs closed arms entries, time spent in open vs closed arms (s). Besides latency to open arms (s), results were expressed as percent open arm entries (%) and percent open arm time (%). Percent open time was calculated by dividing open time by open + closed time, thus discounting the time spent in the center compartment of the apparatus.</p><p>Then, and in an attempt to acquire the food motivation required for the NSF test, rats were food-deprived for 48 h from PND 71-73 (see <xref rid="F1" ref-type="fig">Figure 1A</xref>), following similar prior procedures (<xref rid="B7" ref-type="bibr">Bis-Humbert et al., 2021</xref>; <xref rid="B43" ref-type="bibr">Ledesma-Corvi et al., 2022</xref>). On test day (PND 73), each rat was placed at one of the corners facing the wall of the square open-field arena (60 cm × 60 cm, 40 cm high walls), and was allowed to freely explore the arena for 5 min under housing illumination conditions with three food pellets in the center (<xref rid="B7" ref-type="bibr">Bis-Humbert et al., 2021</xref>; <xref rid="B43" ref-type="bibr">Ledesma-Corvi et al., 2022</xref>). Sessions were videotaped to then analyze feeding time (s), total distance traveled (cm) and latency to food (s). The arena was cleaned in between animals with 70% ethanol to avoid potential behavioral interferences caused by individual odors.</p><p>Finally, rats were exposed to the SP test. To do so and prior to testing, rats were single-housed (PND 73) to obtain individual drinking values. Rats were trained to drink from two water bottles placed on each side of the housing cage for 24 h (PND 76), then, for the next 2 days, they were given access to one bottle containing 1% sucrose and the other one containing water (PND 77-78; <xref rid="F1" ref-type="fig">Figure 1A</xref>) (<xref rid="B25" ref-type="bibr">García-Cabrerizo and García-Fuster, 2019</xref>; <xref rid="B37" ref-type="bibr">Jiménez-Romero et al., 2020</xref>; <xref rid="B6" ref-type="bibr">Bis-Humbert et al., 2020</xref>; <xref rid="B7" ref-type="bibr">Bis-Humbert et al., 2021</xref>; <xref rid="B43" ref-type="bibr">Ledesma-Corvi et al., 2022</xref>). Bottles were placed in alternate cage positions to prevent specific-side preferences. On PND 79, rats were presented with two water bottles for 24 h, to control for bias for either bottle and/or side of the cage. Bottles were daily weighted to calculate sucrose preference (%) and intake (g/kg).</p></sec><sec id="s3-4"><title>Voluntary ethanol consumption in adulthood following adolescent drug exposure</title><p>Rats from Studies II and III were allowed to voluntarily drink ethanol (20%) for a total of 6 weeks by a two-bottle choice test, starting on PND 80 (<xref rid="F1" ref-type="fig">Figures 1B, C</xref>), and thus were exposed to the same experimental conditions. This provided four experimental groups/sex that only differed in adolescent drug exposure. The difference in sample sizes is related to the need of splitting the study in two independent waves while including enough controls in both of them. The design followed an intermittent access to 20% ethanol described to exert a steady consumption sustained over time, with higher overall doses for females (<xref rid="B13" ref-type="bibr">Colom-Rocha et al., 2023</xref>). In particular, this procedure allowed, on a weekly basis and for a total of 6 weeks, unlimited voluntary access to ethanol (20% ethanol vs. water) for 72 consecutive hours (3 days from Tuesdays to Thursdays, D3-D5, <xref rid="F1" ref-type="fig">Figure 1</xref>) followed by a 4-day period with no ethanol access (access to two water-bottles: D6-D7, D1-D2) every week (i.e., a total of 18 ethanol sessions of 24 h). Ethanol bottles were located in alternate positions (right of left side) to account for potential side preferences. Bottles were weighed every morning during the 3 days of weekly ethanol access. Results are expressed (average consumption during all sessions) in terms of ethanol preference (%), water or ethanol volume consumed (ml/24 h), and ethanol dose (g/kg/24 h). Ethanol preference was calculated as the amount of ethanol consumed (mL) divided by total fluid intake (sum of both bottles in ml) and multiplied by 100 (% values).</p></sec><sec id="s3-5"><title>Pharmacological intervention before drug re-exposure in adulthood</title><p>Given that adolescent ethanol exposure increased voluntary drug consumption in adulthood (as described in Study II), in an attempt to reduce the number of animals used (3Rs), all rats from Study III were exposed to ethanol in adolescence. No vehicle group was included in adolescence since that comparison was already evaluated in Study II. Plus, our goal was to ascertain whether the pharmacological intervention would decrease the increased voluntary ethanol consumption observed in adulthood driven by the prior adolescent experience. The idea was to pharmacologically treat rats in adulthood right before drug re-exposure (i.e., allowing voluntary ethanol access), with either cannabidiol [30 mg/kg, i. p (<xref rid="B6" ref-type="bibr">Bis-Humbert et al., 2020</xref>; <xref rid="B22" ref-type="bibr">Gálvez-Melero et al., 2023</xref>)], ketamine [5 mg/kg, i. p (<xref rid="B44" ref-type="bibr">Ledesma-Corvi et al., 2023</xref>)], or vehicle for seven consecutive days (PND 72-78; <xref rid="F1" ref-type="fig">Figure 1C</xref>), to ascertain their prevention on the impact of adolescent ethanol on voluntary consumption. Also, drugs were scored for their potential antidepressant-like responses in the FST (pre-test: PND 71; 5-min test: PND 79) (<xref rid="B6" ref-type="bibr">Bis-Humbert et al., 2020</xref>; <xref rid="B22" ref-type="bibr">Gálvez-Melero et al., 2023</xref>; <xref rid="B44" ref-type="bibr">Ledesma-Corvi et al., 2023</xref>). Since the FST affected all groups in a similar fashion, any decreases observed in ethanol preference and/or consumption would prove a therapeutical option for the tested drugs (cannabidiol or ketamine vs vehicle-treated rats in adulthood).</p></sec><sec id="s3-6"><title>Data analyses and statistics</title><p>All data analyses and graph plotting were done with GraphPad Prism, Version 10 (GraphPad Software, United States) following guidelines in experimental pharmacology for displaying data and statistical methods (<xref rid="B50" ref-type="bibr">Michel et al., 2020</xref>). Results are reported as mean values ±standard error of the mean (SEM); individual symbols are shown for each rat within bar-graphs. Assumptions for normality of data distribution and homogeneity of variance were met. <xref rid="s13" ref-type="sec">Supplementary Table S1</xref> includes two-way ANOVAs (independent variables: Sex, Treatment) of all data evaluated. Sex effects are also reported in graphs (<xref rid="B18" ref-type="bibr">Dalla et al., 2024</xref>). Since expected sex-differences were initially hypothesized in affective-like responses (<xref rid="B37" ref-type="bibr">Jiménez-Romero et al., 2020</xref>; <xref rid="B44" ref-type="bibr">Ledesma-Corvi et al., 2023</xref>) and ethanol consumption (<xref rid="B13" ref-type="bibr">Colom-Rocha et al., 2023</xref>), but also in the potential therapeutical response induced by cannabidiol (<xref rid="B22" ref-type="bibr">Gálvez-Melero et al., 2023</xref>) or ketamine (<xref rid="B44" ref-type="bibr">Ledesma-Corvi et al., 2023</xref>) (see main effects of Sex when performing two-way ANOVAs in <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>), male and female rats were analyzed separately through one-way ANOVAs. Multiple comparisons tests were performed for <italic toggle="yes">post hoc</italic> comparisons when appropriate (Dunnett’s). Level of significance: <italic toggle="yes">p</italic> ≤ 0.05. Data supporting the present findings will be available upon reasonable request to the corresponding author.</p></sec></sec><sec sec-type="results" id="s4"><title>Results</title><sec id="s4-1"><title>No changes in the affective-like state of adult rats following adolescent drug exposure</title><p>An earlier adolescent drug treatment (ethanol, cocaine or their combination) did not induce changes in the affective-like state of male or female rats during adulthood, and as measured in FST (<xref rid="F2" ref-type="fig">Figures 2A–C</xref>), EPM (<xref rid="F2" ref-type="fig">Figures 2D–F</xref>), NSF (<xref rid="F2" ref-type="fig">Figures 2G–I</xref>) and SP (<xref rid="F2" ref-type="fig">Figures 2J, K</xref>; <xref rid="s13" ref-type="sec">Supplementary Table S1</xref> for further statistical details). Moreover, additional analyses were performed to estimate individual behavioral phenotypes for each rat (Z-score: affective-like state for all tests combined). This was done following prior literature suggesting that combining normalized values from many different behavioral measurements of different, but complementary, behavioral tests could be more precise than just analyzing individual items, to characterize a “depressive-like syndrome” in rodents (<xref rid="B74" ref-type="bibr">von Mücke-Heim et al., 2023</xref>). However, no significant changes in affective-like Z-scores were observed among treatment groups (<xref rid="s13" ref-type="sec">Supplementary Figure S1</xref>).</p><fig position="float" id="F2" orientation="portrait"><label>FIGURE 2</label><caption><p>Affective-like state during adulthood following adolescent drug exposure. <bold>(A)</bold> Time spent immobile (s) or <bold>(B)</bold> climbing (s), and <bold>(C)</bold> number of feces in the forced swim test (FST) on PND 65. <bold>(D)</bold> Latency to open arms (OA) (s), <bold>(E)</bold> OA entries, and <bold>(F)</bold> time spent in OA (s) in the elevated plus maze test (EPM) on PND 69. <bold>(G)</bold> Latency to food (s), <bold>(H)</bold> feeding time (s), and <bold>(I)</bold> distance travelled (cm) in the novelty-suppressed feeding test (NSF) on PND 73. <bold>(J)</bold> Sucrose preference (%) and <bold>(K)</bold> sucrose intake (g/kg) in the sucrose preference test (SP) on PND 77–78. <bold>(A–K)</bold> Each set of data represents the mean ± SEM of the corresponding measurement at the indicated PND of study. Individual values are shown for each rat (symbols). Groups of treatment: vehicle-male (n = 9); ethanol-male (n = 9); cocaine-male (n = 9); ethanol + cocaine-male (n = 7); vehicle-female (n = 6); ethanol-female (n = 9); cocaine-female (n = 9); ethanol + cocaine-female (n = 8). One-way ANOVAs (independent variable: Treatment) were performed for each sex separately, and are detailed in <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>. The table also includes two-way ANOVAs analyses with Sex and Treatment as independent variables (Effect of Sex: <sup>###</sup>
<italic toggle="yes">p</italic> &lt; 0.001 when comparing female vs male rats). V: vehicle; E: ethanol; C: cocaine; EC: combination.</p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" position="float" orientation="portrait" xlink:href="fphar-15-1448170-g002.jpg"><?image-name fphar-15-1448170-g002.jpg?><?image-size 168298?><?image-md5 115510b3e4b8b15443b730f5eab3a26a?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 1713?><?image-original-width 1772?><?image-scaled-height 684?><?image-scaled-width 708?><?image-cloudpmc-urn urn:cdn:blobs/cf83/11384591/115510b3e4b8/fphar-15-1448170-g002.jpg?><?thumb-name fphar-15-1448170-g002.gif?><?thumb-size 16720?><?thumb-md5 9f3a8cc60f233e15d46ffa02630f920e?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 97?><?thumb-scaled-width 100?><?thumb-cloudpmc-urn urn:cdn:blobs/cf83/11384591/9f3a8cc60f23/fphar-15-1448170-g002.gif?></graphic></fig><p>As expected, and previously hypothesized, some sex differences were observed in the tests performed. For example, in the NSF, female rats spent considerably longer times feeding (mean of 36 s vs. 7 s for males, ###<italic toggle="yes">p</italic> &lt; 0.001; <xref rid="F2" ref-type="fig">Figure 2H</xref>), while also travelled longer distances (mean of 1,654 cm vs. 1,259 cm for males, ###<italic toggle="yes">p</italic> &lt; 0.001; <xref rid="F2" ref-type="fig">Figure 2I</xref>). Moreover, females showed higher sucrose intake (+2.5 ± 0.6%, g/kg vs. males, ###<italic toggle="yes">p</italic> &lt; 0.001; <xref rid="F2" ref-type="fig">Figure 2K</xref>). These sex-differences suggested decreased anxiogenic- and improved hedonic-like responses in females, as compared to males, independently of the adolescent treatment.</p></sec><sec id="s4-2"><title>Increased voluntary ethanol consumption in adult rats following adolescent ethanol exposure: lack of cocaine effects</title><p>A prior adolescent drug treatment induced long-term changes in voluntary ethanol consumption for male and female adult rats (<xref rid="F3" ref-type="fig">Figure 3</xref>), as observed by significant ANOVAs (<xref rid="s13" ref-type="sec">Supplementary Table S1</xref>) for ethanol preference, ethanol intake (ml/24 h), and ethanol dose (g/kg/24 h). <italic toggle="yes">Post-hoc</italic> analysis revealed that adult male rats treated with ethanol in adolescence showed increased preference (+14.4 ± 3.8%, **<italic toggle="yes">p</italic> = 0.017; <xref rid="F3" ref-type="fig">Figure 3A</xref>), a higher volume of ethanol consumed (+12.1 ± 2.7 mL/24 h, ***<italic toggle="yes">p</italic> &lt; 0.001; <xref rid="F3" ref-type="fig">Figure 3C</xref>), and a higher overall dose (+6.5 ± 1.9 g/kg/24 h, **<italic toggle="yes">p</italic> = 0.005; <xref rid="F3" ref-type="fig">Figure 3D</xref>) than adolescent vehicle-treated rats, without changing the amount of water consumed (<xref rid="F3" ref-type="fig">Figure 3C</xref>). Interestingly, adolescent cocaine had no effect on ethanol voluntary consumption in adulthood, as was also the case when combining ethanol with cocaine (<xref rid="F3" ref-type="fig">Figures 3A–D</xref>).</p><fig position="float" id="F3" orientation="portrait"><label>FIGURE 3</label><caption><p>Voluntary ethanol consumption in adulthood following adolescent drug exposure. <bold>(A)</bold> ethanol preference (%), <bold>(B)</bold> water intake (ml/24 h), <bold>(C)</bold> ethanol intake (ml/24 h), and <bold>(D)</bold> ethanol dose (g/kg/24 h). <bold>(A–D)</bold> Columns represent mean ± SEM of the preference for ethanol (expressed as a % value), water or ethanol intake (ml/24 h) and ethanol dose consumed (g/kg/24 h) in the two-bottle choice test (20% ethanol vs water choice). Individual values are shown for each rat (symbols). Groups of treatment: vehicle-male (n = 15); ethanol-male (n = 9); cocaine-male (n = 8); ethanol + cocaine-male (n = 9); vehicle-female (n = 14); ethanol-female (n = 5); cocaine-female (n = 7); ethanol + cocaine-female (n = 8). One-way ANOVAs (independent variable: Treatment) were performed for each sex separately, and are detailed in <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>. Dunnett’s <italic toggle="yes">post hoc</italic> analyses: *<italic toggle="yes">p</italic> &lt; 0.05, **<italic toggle="yes">p</italic> &lt; 0.01, and ***<italic toggle="yes">p</italic> &lt; 0.001 vs same-sex vehicle-treated rats. The table also includes two-way ANOVAs analyses with Sex and Treatment as independent variables (Effect of Sex: <sup>###</sup>
<italic toggle="yes">p</italic> &lt; 0.001 when comparing female vs male rats). V: vehicle; E: ethanol; C: cocaine; EC: combination.</p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" position="float" orientation="portrait" xlink:href="fphar-15-1448170-g003.jpg"><?image-name fphar-15-1448170-g003.jpg?><?image-size 56758?><?image-md5 847ca219f8c170b7dfffef1cec108e0f?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 314?><?image-original-width 1772?><?image-scaled-height 125?><?image-scaled-width 708?><?image-cloudpmc-urn urn:cdn:blobs/cf83/11384591/847ca219f8c1/fphar-15-1448170-g003.jpg?><?thumb-name fphar-15-1448170-g003.gif?><?thumb-size 9380?><?thumb-md5 c052313bc4044db8b14f399515d66ddf?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 35?><?thumb-scaled-width 200?><?thumb-cloudpmc-urn urn:cdn:blobs/cf83/11384591/c052313bc404/fphar-15-1448170-g003.gif?></graphic></fig><p>On the other hand, adult female rats treated with adolescent ethanol also showed a higher volume of ethanol consumed (+11.2 ± 3.1 mL/24 h, **<italic toggle="yes">p</italic> = 0.003; <xref rid="F3" ref-type="fig">Figure 3C</xref>), and a higher overall dose (+13.1 ± 2.8 g/kg/24 h, ***<italic toggle="yes">p</italic> &lt; 0.001; <xref rid="F3" ref-type="fig">Figure 3D</xref>) than vehicle-treated female rats (<xref rid="F3" ref-type="fig">Figure 3C</xref>). While adolescent cocaine lacked significant effects over ethanol voluntary consumption, the combined exposure of ethanol and cocaine showed increased ethanol preference (+9.2 ± 2.8%, **<italic toggle="yes">p</italic> = 0.064; <xref rid="F3" ref-type="fig">Figure 3A</xref>) and consumption (+8.4 ± 2.6 mL/24 h, **<italic toggle="yes">p</italic> = 0.009; <xref rid="F3" ref-type="fig">Figure 3C</xref>) in adult female rats.</p><p>Again, and as previously described (Colom-Rocha et al., 2023), some sex differences were observed at the level of the dose of ethanol consumed, with female rats showing an overall higher dose (+8.5 ± 1.2 g/kg/24 h, ###<italic toggle="yes">p</italic> &lt; 0.001) than males (<xref rid="F3" ref-type="fig">Figure 3D</xref>; <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>). However, no sex differences were observed for ethanol preference, and/or ethanol or water volume consumed (<xref rid="F3" ref-type="fig">Figures 3A–C</xref>).</p></sec><sec id="s4-3"><title>Cannabidiol or ketamine diminished voluntary ethanol consumption in adult rats following adolescent ethanol exposure</title><p>Cannabidiol or ketamine induced antidepressant-like responses in the FST in male rats, as observed by a decreased immobility (−36.4 ± 15.4 s, *<italic toggle="yes">p</italic> = 0.040 and −45.5 ± 15.7 s, *<italic toggle="yes">p</italic> = 0.011 respectively; <xref rid="F4" ref-type="fig">Figure 4A</xref>; <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>) when compared to vehicle-treated rats. However, cannabidiol was not efficacious in female rats, and ketamine even induced an increase in immobility (+33.5 ± 11.9 s, *<italic toggle="yes">p</italic> = 0.017; <xref rid="F4" ref-type="fig">Figure 4A</xref>; <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>). These results paired with opposite changes in climbing behavior (<xref rid="F4" ref-type="fig">Figure 4B</xref>), while swimming (<xref rid="F4" ref-type="fig">Figure 4C</xref>) or the number of feces were not altered by any of the treatments tested (<xref rid="F4" ref-type="fig">Figure 4D</xref>; <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>).</p><fig position="float" id="F4" orientation="portrait"><label>FIGURE 4</label><caption><p>Pharmacological intervention before ethanol re-exposure in adulthood. <bold>(A)</bold> Time spent immobile (s), <bold>(B)</bold> climbing (s) or <bold>(C)</bold> swimming (s), and <bold>(D)</bold> number of feces in the forced swim test FST in adult rats following adolescent ethanol exposure. <bold>(E)</bold> ethanol preference (%), <bold>(F)</bold> water intake (ml/24 h), <bold>(G)</bold> ethanol intake (ml/24 h), and <bold>(H)</bold> ethanol dose (g/kg/24 h). <bold>(A–F)</bold> Columns represent mean ± SEM of the different scores for each test. Individual values are shown for each rat (symbols). Groups of treatment: vehicle-male (n = 8); cannabidiol-male (n = 10); ketamine-male (n = 9); vehicle-female (n = 9); cannabidiol-female (n = 10); ketamine-female (n = 9). One-way ANOVAs (independent variable: Treatment) were performed for each sex separately, and are detailed in <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>. Dunnett’s <italic toggle="yes">post hoc</italic> analyses: *<italic toggle="yes">p</italic> &lt; 0.05 and ***<italic toggle="yes">p</italic> &lt; 0.001 vs same-sex vehicle-treated rats. The table also includes two-way ANOVAs analyses with Sex and Treatment as independent variables (Effect of Sex: <sup>##</sup>
<italic toggle="yes">p</italic> &lt; 0.01 and <sup>###</sup>
<italic toggle="yes">p</italic> &lt; 0.001 when comparing female vs male rats). V: vehicle; CBD: cannabidiol; Ket: ketamine. Colom-Rocha, Bis-Humbert and García-Fuster.</p></caption><graphic xmlns:xlink="http://www.w3.org/1999/xlink" position="float" orientation="portrait" xlink:href="fphar-15-1448170-g004.jpg"><?image-name fphar-15-1448170-g004.jpg?><?image-size 91152?><?image-md5 01520e318dc18ed1020080d210ba5795?><?image-image-server-status LOAD_COMPLETED?><?image-original-height 695?><?image-original-width 1772?><?image-scaled-height 278?><?image-scaled-width 708?><?image-cloudpmc-urn urn:cdn:blobs/cf83/11384591/01520e318dc1/fphar-15-1448170-g004.jpg?><?thumb-name fphar-15-1448170-g004.gif?><?thumb-size 14397?><?thumb-md5 7ebcdb679892b14dc3bf3fb74ca1e117?><?thumb-image-server-status NEVER_LOAD?><?thumb-scaled-height 78?><?thumb-scaled-width 200?><?thumb-cloudpmc-urn urn:cdn:blobs/cf83/11384591/7ebcdb679892/fphar-15-1448170-g004.gif?></graphic></fig><p>As for the effects of the therapeutical intervention after adolescent ethanol exposure, but right before ethanol re-exposure in adulthood, adult male rats pretreated with cannabidiol showed a drop in preference (−12.6% ± 4.9%, *<italic toggle="yes">p</italic> = 0.033; <xref rid="F4" ref-type="fig">Figure 4E</xref>), a lower volume of ethanol consumed (−6.4 ± 1.3 mL/24 h, ***<italic toggle="yes">p</italic> &lt; 0.001; <xref rid="F4" ref-type="fig">Figure 4G</xref>), and a lower overall dose (−3.6 ± 0.9 g/kg/24 h, ***<italic toggle="yes">p</italic> &lt; 0.001; <xref rid="F4" ref-type="fig">Figure 4H</xref>) than rats pretreated with vehicle, and without changing the amount of water consumed (<xref rid="F4" ref-type="fig">Figure 4F</xref>; <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>).</p><p>Interestingly, in female rats, both cannabidiol and ketamine showed signs of efficacy on later improving ethanol consumption in adulthood. In particular, both pretreatments were capable of lowering the volume of ethanol (−5.4 ± 0.8 mL/24 h, ***<italic toggle="yes">p</italic> &lt; 0.001 and −3.7 ± 0.8 mL/24 h, ***<italic toggle="yes">p</italic> &lt; 0.001, respectively; <xref rid="F4" ref-type="fig">Figure 4G</xref>), as well as the overall dose consumed (−4.7 ± 0.6 g/kg/24 h, ***<italic toggle="yes">p</italic> &lt; 0.001 and −2.7 ± 0.6 g/kg/24 h, ***<italic toggle="yes">p</italic> &lt; 0.001, respectively; <xref rid="F4" ref-type="fig">Figure 4H</xref>), vs. rats pretreated with vehicle, and without changing water consumption (<xref rid="F4" ref-type="fig">Figure 4F</xref>; <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>).</p><p>In line with prior results (<xref rid="F3" ref-type="fig">Figure 3</xref>), some sex differences were reported, both at the level of ethanol consumption and overall dose (<xref rid="s13" ref-type="sec">Supplementary Table S1</xref>), with female rats showing overall higher rates (volume consumed: +1.8 ± 0.6 mL/24 h, ##<italic toggle="yes">p</italic> = 0.006; dose: +2.4 ± 0.4 g/kg/24 h, ###<italic toggle="yes">p &lt;</italic> 0.001) than males (<xref rid="F4" ref-type="fig">Figures 4G, H</xref>; <xref rid="s13" ref-type="sec">Supplementary Table S1</xref>). No sex differences were observed for ethanol preference or water volume consumed (<xref rid="F4" ref-type="fig">Figures 4E, F</xref>).</p></sec></sec><sec sec-type="discussion" id="s5"><title>Discussion</title><p>This study examined the long-term changes in affective-like responses and in ethanol voluntary consumption in adult male and female rats previously exposed to ethanol, cocaine or their combination during vulnerable windows of adolescence. The main results showed that exposing rats to these drugs in adolescence did not induce signs of increased negative affect during adulthood, although this conclusion is limited to the doses, regimens and methods of administration followed. However, when rats were also allowed to voluntarily consume ethanol in adulthood, some differences emerged depending on the drug they previously received in adolescence. In particular, adolescent ethanol exposure was a risk-factor for later developing an increased voluntary ethanol consumption in adulthood, both in male and female rats. This risk was similar when ethanol was combined with cocaine exposure in adolescence, since adolescent cocaine exposure alone did not affect ethanol intake in adulthood. Finally, rats exposed to ethanol in adolescence and pretreated in adulthood with either cannabidiol (and/or ketamine but just for females) reduced ethanol voluntary consumption. Overall, our data provided two therapeutical options capable of attenuating voluntary ethanol consumption rates in adulthood caused by a prior adolescent drug exposure.</p><p>This study initially hypothesized that the combined exposure of ethanol and cocaine in adolescence would show increased sings of negative affect in adult male and female rats. In this context, a recent review compared the behavioral phenotypes that emerge following different ethanol exposure models, and concluded that the complex outcomes from these studies highlighted the difficulties of assessing negative affective behaviors in rodent models designed for the study of alcohol use disorder (<xref rid="B9" ref-type="bibr">Bloch et al., 2022</xref>). In our case, the behavioral phenotyping was done through the sequential screening in different tests that try to capture different aspects of the symptomatology observed in humans, such as behavioral despair (<xref rid="B29" ref-type="bibr">García-Fuster et al., 2012</xref>) and/or stress-coping strategies (<xref rid="B51" ref-type="bibr">Molendijk and de Kloet, 2015</xref>; <xref rid="B15" ref-type="bibr">Commons et al., 2017</xref>) through FST, anxiety-like responses in EPM (<xref rid="B29" ref-type="bibr">García-Fuster et al., 2012</xref>) and NSF (<xref rid="B7" ref-type="bibr">Bis-Humbert et al., 2021</xref>; <xref rid="B43" ref-type="bibr">Ledesma-Corvi et al., 2022</xref>), and hedonic-like responses in SP (<xref rid="B37" ref-type="bibr">Jiménez-Romero et al., 2020</xref>). However, we found no evidence of a deteriorated affective-like state induced by any of the drugs administered in adolescence (ethanol, cocaine or their combination) in rats of both sexes. Note that adolescent drug exposure was administered by an experimenter in a non-contingent way so each experimental group received the same dose in terms of later being able to better understand the impact of a prior fixed drug exposure on ethanol voluntary intake in adulthood. Although this type of regimen did not inform about the motivation for the drug during adolescence, and might have impacted the lack of negative affect observed during drug abstinence, it is worth mentioning that this set of data aligned with our prior results suggesting that adolescent drug exposure alone may not be sufficient to induce negative affect in adulthood, since adult drug re-exposure was needed to observe a negative impact on behavior from an earlier adolescent exposure (<xref rid="B25" ref-type="bibr">García-Cabrerizo and García-Fuster, 2019</xref>; <xref rid="B8" ref-type="bibr">Bis-Humbert and García-Fuster, 2021</xref>; <xref rid="B7" ref-type="bibr">Bis-Humbert et al., 2021</xref>). Also, in this line of thought, adding stress could also be a possible factor that can reveal the phenotype, suggesting that adolescent early exposure to drugs increased susceptibility or vulnerability to later consumption. This idea reinforces the notion that one way to prevent substance use disorder later on relies on avoiding drug consumption early in life. Moreover, in line with the previously detected basal sex-differences for these particular tests of study (<xref rid="B35" ref-type="bibr">Hernández-Hernández et al., 2023</xref>; <xref rid="B44" ref-type="bibr">Ledesma-Corvi et al., 2023</xref>), the data reported a differential impact by sex in some tests, with a greater general exploratory-like behavior for females as observed in NSF, combined with a higher hedonic-like response in SP.</p><p>The next study evaluated the impact of the adolescent treatment on ethanol consumption later on in adulthood. Although no changes were observed when measuring affective-like responses, when exposing rats to a voluntary access to ethanol in adulthood [20% ethanol for three consecutive days per week, during 6 weeks; characterized in <xref rid="B13" ref-type="bibr">Colom-Rocha et al. (2023)</xref>], some differences in consumption emerged depending on the drug they previously received in adolescence. In particular, and in line with prior data (<xref rid="B69" ref-type="bibr">Strong et al., 2010</xref>; <xref rid="B61" ref-type="bibr">Sherrill et al., 2011</xref>) [reviewed by <xref rid="B65" ref-type="bibr">Spear (2016)</xref>; <xref rid="B66" ref-type="bibr">Spear (2018)</xref>; <xref rid="B45" ref-type="bibr">Lees et al. (2020)</xref>], adolescent ethanol exposure was a clear risk-factor for later developing an increased voluntary ethanol consumption in adulthood, both in male and female rats. In particular, previous adolescent ethanol exposure increased ethanol preference and voluntarily consumption in adulthood, being this effect of equal magnitude for both sexes. However, when correcting ethanol intake by weight to calculate the dose consumed per day (g/kg/24 h), female rats were exposed to higher doses than their male counterparts, in line with prior recent examples showing sex-specific drinking patterns in adult rodents (<xref rid="B13" ref-type="bibr">Colom-Rocha et al., 2023</xref>; <xref rid="B20" ref-type="bibr">Foo et al., 2023</xref>; <xref rid="B49" ref-type="bibr">McElroy et al., 2023</xref>). Moreover, the risk observed by ethanol combined with cocaine in adolescence was of a similar magnitude, or even a bit reduced, to the one induced just by ethanol, since adolescent cocaine exposure alone did not affect ethanol consumption in adulthood. Remarkably, the literature is full of data showing how adolescent ethanol exposure alters the rewarding effects of cocaine in adulthood (<xref rid="B36" ref-type="bibr">Hutchison and Riley, 2012</xref>; <xref rid="B48" ref-type="bibr">Mateos-García et al., 2015</xref>; <xref rid="B42" ref-type="bibr">Ledesma et al., 2017</xref>; <xref rid="B19" ref-type="bibr">Esteve-Arenys et al., 2017</xref>; <xref rid="B11" ref-type="bibr">Cantacorps et al., 2020</xref>), however, studies evaluating how adolescent cocaine impact later adult ethanol consumption are lacking. One example described the acute effects of cocaine stimulating ethanol intake in a two-bottle choice paradigm, but was done in adult male Sprague-Dawley rats (<xref rid="B14" ref-type="bibr">Colvin et al., 2022</xref>), Therefore, since adolescent cocaine exposure did not stimulate ethanol intake in adulthood, the effects observed by ethanol and cocaine combined in adolescence over the rate of voluntary ethanol consumption in adulthood might be driven exclusively by prior ethanol exposure in adolescence. These results reported that despite the fact that adolescent drug exposure did not induce any clear signs of negative affect, when adult rats were presented with a voluntary drug experience, the prior adolescent experience had clear consequences on the emerging addictive-like behaviors observed for both sexes. Although these negative effects were not observed for all drugs (lack of impact by adolescent cocaine), adolescent ethanol exposure increased the rates of ethanol consumption in adulthood. Interestingly, adolescent alcohol use was also proven a risk factor for adult alcohol and drug dependence in a clinical studies with twins (<xref rid="B33" ref-type="bibr">Grant et al., 2006</xref>). Therefore, since an early exposure to ethanol during adolescence induced long-term consequences for substance use disorders later on in adulthood, preventing an early-age initiation is postulated to be of vital importance to avoid future problems related to substance use disorders. However, for cases when adolescent drug exposure is already initiated, having access to therapeutical options that could prevent a later drug consumption when ethanol renders available in adulthood are of great relevance.</p><p>In this line of thought, our third study tested two therapeutical interventions (cannabidiol, ketamine) for preventing the increased ethanol consumption in adult rats following a prior adolescent ethanol exposure. Note that this experiment was done in the absence of ethanol-naive controls (i.e., all rats received ethanol in adolescence), since our prior experiment already characterized the long-term effects of ethanol vs vehicle exposure in adolescence, and the present goal was to ascertain whether the tested therapeutical options could reduce the voluntary drinking observed in adulthood and caused by a prior adolescent experience. In particular, the main results showed that rats exposed to ethanol in adolescence and pretreated in adulthood with cannabidiol (and/or ketamine but just for females) reduced ethanol voluntary consumption in adulthood. Interestingly, the rates of ethanol preference and/or consumption in adult male and female rats were similar to the ones observed in our prior study for the adolescent ethanol group, demonstrating that independent studies replicated and were therefore reliable. Moreover, both cannabidiol and ketamine showed antidepressant-like responses in FST in male rats exposed to ethanol in adolescence, in line with prior results in naïve rats (<xref rid="B6" ref-type="bibr">Bis-Humbert et al., 2020</xref>; <xref rid="B44" ref-type="bibr">Ledesma-Corvi et al., 2023</xref>), while rendered inefficacious or even deleterious for female rats (<xref rid="B43" ref-type="bibr">Ledesma-Corvi et al., 2022</xref>; <xref rid="B22" ref-type="bibr">Gálvez-Melero et al., 2023</xref>; <xref rid="B44" ref-type="bibr">Ledesma-Corvi et al., 2023</xref>). Prior data have already proven sex-differences in antidepressant-like responses, with clear drops in efficacy for female subjects (<xref rid="B40" ref-type="bibr">Kokras et al., 2011</xref>; <xref rid="B46" ref-type="bibr">LeGates et al., 2019</xref>). Clearly, the antidepressant-like response observed in FST in rats treated with adolescent ethanol did not parallel the response that these therapeutical options induced in terms of ethanol voluntary consumption rates (as detailed below), hence suggesting a broader therapeutical potential, other than their antidepressant-like action, both for cannabidiol and ketamine in adult rats of both sexes.</p><p>In accordance with this, for example, both male and female rats pretreated with cannabidiol showed decreased ethanol intake in adulthood as observed by a drop in preference (although only significant in male rats), a lower volume of ethanol consumed, and a lower overall dose than rats pretreated with vehicle. These results aligned with previous preclinical data suggesting an improvement of ethanol-motivated behaviors by cannabidiol [reviewed by <xref rid="B55" ref-type="bibr">Nona et al. (2019)</xref>]; see also (<xref rid="B73" ref-type="bibr">Viudez-Martínez et al., 2018</xref>; <xref rid="B72" ref-type="bibr">Viudez-Martínez et al., 2020</xref>; <xref rid="B47" ref-type="bibr">Maccioni et al., 2022</xref>; <xref rid="B71" ref-type="bibr">Tringali et al., 2023</xref>; <xref rid="B31" ref-type="bibr">Gasparyan et al., 2023</xref>)], including the cognitive deficits and neuroinflammation induced by early ethanol exposure (<xref rid="B23" ref-type="bibr">García-Baos et al., 2021</xref>). Particularly, prior studies have proven cannabidiol efficacy in pups from pregnant rodents exposed to drugs during gestation, directly in adolescence (immediate effects), and/or in rodents that received drugs in adulthood. For example, cannabidiol (30 mg/kg/day, i. p., for up to 4–6 weeks) repaired the behavioral and brain disturbances in offspring exposed to an animal model of fetal alcohol spectrum disorder (<xref rid="B31" ref-type="bibr">Gasparyan et al., 2023</xref>). When administered during adolescence, cannabidiol (40 mg/kg) before each drinking session reduced ethanol consumption and preference in male rats that underwent the intermittent 20% ethanol two-bottle choice paradigm (<xref rid="B71" ref-type="bibr">Tringali et al., 2023</xref>). Moreover, during adulthood, the administration of cannabidiol in male mice reduced the reinforcing properties, motivation and relapse for ethanol (<xref rid="B73" ref-type="bibr">Viudez-Martínez et al., 2018</xref>). Later on, a follow-up study from the same group described sex differences in the effects of cannabidiol on ethanol binge drinking in adult mice, proving, similarly to the results obtained here, that although female mice exhibited higher ethanol intake during each drinking in the dark session, cannabidiol reduced ethanol consumption for both sexes; these effects were observed after an acute (90 mg/kg; highest dose tested) and/or chronic administration [although with different dose-dependent efficacy for males and females; males: 30, 60 and 90 mg/kg; females: only with 90 mg/kg (<xref rid="B72" ref-type="bibr">Viudez-Martínez et al., 2020</xref>)]. In another study in adult male rats, cannabidiol (≥12.5 mg/kg) markedly reduced lever responding for ethanol and amount of self-administered ethanol in selectively bred Sardinian ethanol-preferring male rats, a validated animal model of excessive ethanol consumption (<xref rid="B47" ref-type="bibr">Maccioni et al., 2022</xref>). Against this pool of published data, our study is quite original and novel in that it proposed a different approach, since it evaluated the beneficial effects of cannabidiol on preventing the impact of early drug initiation during adolescence on voluntary ethanol consumption in adult male and female rats. Taken together, these findings, in conjunction with the prior published data, suggested that cannabidiol may be a great candidate for preventing the development of alcohol-use disorders, independently of when drug exposure was initiated (i.e., during prenatal period, adolescence, and/or adulthood), and independently of sex, if previously adjusting the specific sex-related conditions required for efficacy (i.e., dose, length of treatment, animal species, etc.).</p><p>Finally, the other therapeutical option tested, at the conditions used, was only capable of showing signs of improvement in female rats. Mainly, ketamine showed signs of efficacy by decreasing ethanol consumption in adulthood, but only in female rats exposed to ethanol in adolescence. In particular, it lowered the volume as well as the overall dose of ethanol consumed, as compared to rats pretreated with vehicle. In line with our results, some prior studies also showed a greater sensitivity to the ketamine treatment in females, although ketamine significantly reduced both ethanol intake and preference in a time- and dose-dependent manner in ethanol preferring adult rats of both sexes, while it did so at higher doses [effective doses: 7.5 mg/kg, and 10 mg/kg (<xref rid="B60" ref-type="bibr">Rezvani et al., 2017</xref>)] than the ones used in the present study. Another experiment also reported a better therapeutical response for females by reporting that ketamine reduced binge-like drinking behavior exclusively in female rats exposed to a drinking in the dark model and when ketamine was given prior to ethanol exposure (<xref rid="B17" ref-type="bibr">Crowley et al., 2019</xref>). Contrarily, other studies found a greater sensitivity for ketamine in male rodents, for example, while ketamine decreased ethanol consumption in male rats that self-administered high levels of ethanol, it increased ethanol consumption in female rats that showed low levels of ethanol self-administration (<xref rid="B68" ref-type="bibr">Strong et al., 2019</xref>). Also, adolescent exposure to ketamine significantly decreased preference for ethanol consumption in males, with a smaller reduction of ethanol consumption in females (<xref rid="B21" ref-type="bibr">Franco et al., 2020</xref>). In general, prior results with ketamine at the preclinical and clinical level reported some beneficial effects on ameliorating ethanol-motivated behaviors for both sexes [see recent reviews by <xref rid="B75" ref-type="bibr">Worrell and Gould (2021)</xref>; <xref rid="B32" ref-type="bibr">Goldfine et al. (2023)</xref>; <xref rid="B39" ref-type="bibr">Kelson et al. (2023)</xref>; <xref rid="B41" ref-type="bibr">Krystal et al. (2024)</xref>], although with some differences in between sexes that should be further studied since they will likely play an important role in the future development of therapeutical options for alcohol use disorders. Overall, the use of ketamine for the treatment and/or prevention of alcohol use disorder is promising, with several ongoing clinical trials, but with still the need to further complete its efficacy validation and safety profile before recommending its broader clinical use [reviewed by <xref rid="B32" ref-type="bibr">Goldfine et al. (2023)</xref>].</p></sec><sec id="s6"><title>Perspectives and significance</title><p>These results provided two therapeutical options for preventing the effects of an early drug initiation during adolescence on ethanol voluntary consumption rates later on in adulthood. Thus, these results may be of relevance in view of possible future studies testing cannabidiol or ketamine in patients affected by alcohol use disorder, whose consumption started early in life during adolescence, and when sex-related differences might be affecting the treatment outcome.</p></sec></body><back><ack><p>MG-F and CC-R are members of “Red de Investigación en Atención Primaria de Adicciones” (RIAPAd: RD21/0009/0008; Instituto de Salud Carlos III, Plan de Recuperación, Transformación y Resilencia, NextGenerationEU).</p></ack><sec sec-type="data-availability" id="s7"><title>Data availability statement</title><p>The original contributions presented in the study are included in the article/<xref rid="s13" ref-type="sec">Supplementary Material</xref>, further inquiries can be directed to the corresponding author.</p></sec><sec id="s8"><title>Ethics statement</title><p>The animal study was approved by the studies involving animals were reviewed and approved by the Local Bioethical Committee “Comité de Ética de Experimentación Animal” (project number 148-09-20) and by the Regional Government (approved protocol number 2021/01/AEXP). The study was conducted in accordance with the local legislation and institutional requirements.</p></sec><sec id="s9"><title>Author contributions</title><p>CC-R: Data curation, Formal Analysis, Methodology, Investigation, Writing–review and editing. CB-H: Data curation, Investigation, Methodology, Writing–review and editing. MG-F: Data curation, Methodology, Conceptualization, Formal Analysis, Funding acquisition, Supervision, Validation, Writing–original draft.</p></sec><sec sec-type="COI-statement" id="s11"><title>Conflict of interest</title><p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p><p>The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.</p></sec><sec sec-type="disclaimer" id="s12"><title>Publisher’s note</title><p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec><sec id="s13"><title>Supplementary material</title><p>The Supplementary Material for this article can be found online at: <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://www.frontiersin.org/articles/10.3389/fphar.2024.1448170/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fphar.2024.1448170/full#supplementary-material</ext-link>
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