<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.151166.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Effects of Acute Toluene Exposure on Oxidative Stress Parameters and Endothelial Markers in the Coronary Artery of Wistar Rats</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Setya Maryiantari</surname>
                        <given-names>Ellyza</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-4368-2844</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Keman</surname>
                        <given-names>Soedjajadi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Sudiana</surname>
                        <given-names>I Ketut</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Martini</surname>
                        <given-names>Santi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-2424-1776</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Faculty of Public Health, Universitas Airlangga, Surabaya, East Java, Indonesia</aff>
                <aff id="a2">
                    <label>2</label>Department of Anatomic Pathology, Faculty of Medicine, Universitas Airlangga, Surabaya, East Java, Indonesia</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:soedja_keman@fkm.unair.ac.id">soedja_keman@fkm.unair.ac.id</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>6</day>
                <month>2</month>
                <year>2025</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2025</year>
            </pub-date>
            <volume>14</volume>
            <elocation-id>168</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>5</day>
                    <month>11</month>
                    <year>2024</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Setya Maryiantari E et al.</copyright-statement>
                <copyright-year>2025</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/14-168/pdf"/>
            <abstract>
                <sec>
                    <title>Objective</title>
                    <p>Toluene is the most abundant lipophilic aromatic compound in our environment. Exposure to toluene through inhalation is toxic to the cardiovascular system due to the formation of reactive oxygen species (ROS) that trigger oxidative stress. This study aims to examine the response of coronary arteries to toluene inhalation exposure based on the expression of superoxide dismutase (SOD), catalase (CAT), malondialdehyde (MDA), vascular cell adhesion molecule-1 (VCAM-1) in coronary arteries, and levels of CYP2E1 with oxidized low-density lipoprotein (Ox-LDL) in the serum.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>This was a true experimental study on Wistar rats with a post-test control group design. In total, 36 Wistar rats were divided into five experimental (X1&#x2013;X5) and one control group. The experimental groups were exposed to 1.6, 3.2, 6.4, 12.8, and 25.6 mL of toluene, respectively. All groups, except control, received inhalation exposure for 14 d (6 h/d).</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>In Wistar rats, toluene exposure significantly reduced the expression of SOD and CAT enzymes while it increased the expression of MDA and VCAM-1 in the coronary artery. Serum levels of CYP2E1 and Ox-LDL were unaffected.</p>
                </sec>
                <sec>
                    <title>Conclusion</title>
                    <p>Acute inhalation exposure to toluene significantly decreased SOD and CAT expression with increased MDA and VCAM-1 expression in coronary arteries. Other findings suggest that decreased CAT expression leads to increased VCAM-1 expression in the coronary artery.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Coronary artery disease</kwd>
                <kwd>oxidative stress</kwd>
                <kwd>vascular cell adhesion molecule-1</kwd>
                <kwd>toluene</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1" xlink:href="http://dx.doi.org/10.13039/501100008463">
                    <funding-source>Universitas Airlangga</funding-source>
                </award-group>
                <funding-statement>The authors are grateful to the Universitas Airlangga for the support provided under Doctoral Dissertation Research number 947/UN3.15/PT/2022 on May 12, 2022.  </funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>1. Introduction</title>
            <p>Exposure to toluene in the blood and tissues triggers oxidative stress due to free radical production (
                <xref ref-type="bibr" rid="ref1">Abouee-Mehrizi et al., 2023</xref>; 
                <xref ref-type="bibr" rid="ref8">Demir et al., 2017</xref>). Here, oxidative stress is mediated by benzyl alcohol, which induces cytochrome P450 (CYP) 2E1 (
                <xref ref-type="bibr" rid="ref16">Hanioka et al., 2010</xref>; 
                <xref ref-type="bibr" rid="ref26">Kim et al., 2015</xref>) to produce unpaired electrons that are reactive toward glycoproteins and lipoproteins (
                <xref ref-type="bibr" rid="ref24">Jomova et al., 2023</xref>). This leads to the formation of oxidized lipids, such as low-density lipoprotein (Ox-LDL) (
                <xref ref-type="bibr" rid="ref13">Guan et al., 2019</xref>; 
                <xref ref-type="bibr" rid="ref42">Stajkovi&#x0107; et al., 2009</xref>). Ox-LDL triggers monocyte entry into the intima, which is mediated by adhesion molecules, including vascular cell adhesion molecule-1 (VCAM-1). After entering the intima, monocytes differentiate into macrophages and scavenge Ox-LDL (
                <xref ref-type="bibr" rid="ref43">Toma et al., 2016</xref>; 
                <xref ref-type="bibr" rid="ref48">Yurdagul et al., 2016</xref>).</p>
            <p>Oxidative stress from exposure to harmful chemicals, such as toluene, may lead to the development of CVD (
                <xref ref-type="bibr" rid="ref20">He et al., 2024</xref>; 
                <xref ref-type="bibr" rid="ref27">Kim et al., 2012</xref>; 
                <xref ref-type="bibr" rid="ref35">Miller, 2020</xref>). Endothelial dysfunction is an early phase of most CVDs, and therefore, can be used to predict CVDs (
                <xref ref-type="bibr" rid="ref19">Hayek et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref41">Smiljic, 2017</xref>). Endothelial oxidative stress is characterized by the formation of lipid peroxidation products, such as malondialdehyde (MDA), and a decrease in the activity of antioxidant enzymes, such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px) (
                <xref ref-type="bibr" rid="ref1">Abouee-Mehrizi et al., 2023</xref>; 
                <xref ref-type="bibr" rid="ref10">Gamez-Mendez et al., 2015</xref>; 
                <xref ref-type="bibr" rid="ref31">Mao et al., 2019</xref>). Moreover, endothelial dysfunction is characterized by a decreased bioavailability of nitric oxide (NO), which releases adhesion cells, including VCAM-1-capturing monocytes and T cells (
                <xref ref-type="bibr" rid="ref2">Ardiana et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref12">Gradinaru et al., 2015</xref>).</p>
            <p>VCAM-1 is an adhesion molecule on the endothelial surface. VCAM-1 expression is induced during the inflammatory process by mediators such as reactive oxygen species (ROS) (
                <xref ref-type="bibr" rid="ref5">Cook-Mills et al., 2011</xref>; 
                <xref ref-type="bibr" rid="ref38">Mu et al., 2015</xref>). An increase in VCAM-1 indicates endothelial damage due to inflammatory dysregulation and is the beginning of atherosclerosis, leading to CVD (
                <xref ref-type="bibr" rid="ref25">Kaur et al., 2022</xref>; 
                <xref ref-type="bibr" rid="ref41">Smiljic, 2017</xref>). This study uses a fixed dose and time to analyze the effect of acute toluene toxicity in the air, namely Serum CYP2E1 and Ox-LDL. On the other hand, SOD, CAT, MDA, and VCAM-1from the coronary artery, were used as biomarkers. We analyzed the combined effects of all bio-markers with toluene exposure on coronary arteries. Our findings provide a basis for research on the adverse effects of toluene toxicity.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>2. Methods</title>
            <sec id="sec7">
                <title>2.1 Study design</title>
                <p>This study was conducted at Universitas Airlangga from November 2022 to March 2023. The study used a true experimental approach, with a post-test control group design. Wistar rats were exposed to toluene inhalation for 14 d (6 h/d). According to 
                    <italic toggle="yes">Lemeshow&#x2019;s</italic> formula, which was &#x03b1; = 0.05 and &#x03b2; = 0.05, each group had six rats that were randomly and evenly distributed using a computerized number generator. This study analyzed five treatment groups at different exposure doses (12.5, 25, 50, 100, and 200 ppm) and one control group (
                    <xref ref-type="bibr" rid="ref6">Cosnier et al., 2013</xref>). The dose of toluene exposure is given in mL by converting the calculation from the part per million (ppm). Mathematical calculations for unit dose conversion of liquid toluene in an aquarium volume of 128 L obtained different toluene exposure doses of 1.6, 3.2, 6.4, 12.8, and 25.6 mL.</p>
                <p>Wistar rats were injected with a lethal dose of ketamine&#x2013;xylazine. The name of the anesthetic was Xylazine of Holland Brand
                    <sup>&#x00ae;</sup> with the manufacture name of 
                    <italic toggle="yes">Tekad Mandiri Citra Corporation.</italic> The ketamine used in this study was Ket-A-100
                    <sup>&#x00ae;</sup> which was distributed by Aggrovet Market as a supplier. Blood was collected without anticoagulants using a 5 mL syringe with the heart puncture technique. The heart and other organs were placed in a tube containing 10% neutral buffered formalin (NBF-10%). Blood samples were taken to the Integrated Laboratory of Airlangga University Hospital (Tropical Disease Center), to measure serum levels of CYP2E1 and Ox-LDL. Coronary artery tissue was examined immunohistochemically for SOD, CAT, MDA, and VCAM-1 at the Airlangga University Research Center. The results were analyzed statistically using the generalized linear model (GLM) method. Finally, the remaining animal parts were placed in wooden boxes and cremated to avoid infected by bacteria.</p>
            </sec>
            <sec id="sec8">
                <title>2.2 Experimental animals</title>
                <p>Sixteen-week-old male Wistar rats weighing 200&#x2013;290 g were used in this study. The rats purchased were from PT. AIRC Indonesia and researched with certificate number 10822/HEW/PTRAI/2022, on August 22, 2022. The rats were maintained under controlled environmental conditions, with 26&#x00b0;C&#x2013;30&#x00b0;C (
                    <xref ref-type="bibr" rid="ref11">Garber, 2011</xref>) temperature, 40%&#x2013;90% relative humidity, and lighting adjusted according to the room. The rats were given a standard diet and water 
                    <italic toggle="yes">ad libitum</italic>.</p>
            </sec>
            <sec id="sec9">
                <title>2.3 Exposure to toluene</title>
                <p>Toluene was 99.9% pure (catalog number 1.08325.2500, Merck). According to experimental animal guidelines, the required aquarium area for one mouse weighing 200&#x2013;500 g is 387 cm
                    <sup>2</sup>, with cage height =18 cm (
                    <xref ref-type="bibr" rid="ref11">Garber, 2011</xref>). The aquarium size used in this study was 80 &#x00d7; 40&#x00d7;40 cm
                    <sup>3</sup>. The top side of the aquarium, namely 10 cm from the top edge of the aquarium, had a gutter measuring 80 &#x00d7;10 cm for spraying liquid toluene. Toluene vapor was prepared by spraying 1.6, 3.2, 6.4, 12.8, and 25.6 mL of pure toluene through an injection syringe in a glass gutter at the top of the aquarium. This was accompanied by flowing air through the bubbler into the aquarium and assisted by a small fan placed at the top of the aquarium.</p>
                <p>The hole for air flowing out of the aquarium is located at the top of the aquarium because the specific gravity of toluene vapor is greater than that of air. The concentration is obtained by adjusting the amount of airflow through the bubbler and the amount of air leaving the aquarium (
                    <xref ref-type="bibr" rid="ref6">Cosnier et al., 2013</xref>). The aquarium was maintained at 27&#x00b0;C&#x2013;30.5&#x00b0;C and 40%&#x2013;90% humidity to keep the animals comfortable and to facilitate toluene dispersion.</p>
                <p>
                    <xref ref-type="fig" rid="f1">Figure 1</xref> has been permitted to be used by Airlangga University Faculty of Public Health because this figure added with the photo (
                    <xref ref-type="fig" rid="f2">Figure 2</xref>) taken by the laboratory employee was intended to be used for doctoral degree students. For further information or verification of rights, please contact the administrator via E-mail at 
                    <email xlink:href="mailto:info@fkm.unair.ac.id">info@fkm.unair.ac.id</email> or by telephone at +62 315920948.</p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>
Figure 1. </label>
                    <caption>
                        <title>Illustration of rats exposed to toluene.</title>
                        <p>Source: Photo taken by authors&#x2019; camera on laboratory by the rights of Faculty of Public Health of Airlangga University</p>
                    </caption>
                    <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/165791/bfa93941-4ae3-4a3d-b524-bbd0ffb77d5a_figure1.gif"/>
                </fig>
                <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                    <label>
Figure 2. </label>
                    <caption>
                        <title>Experimental design of toluene exposure in air.</title>
                        <p>Source: Photo taken by authors.</p>
                        <p>Note: 1. Ventilation 2. Wind fan (for air circulation and to evaporate toluene immediately) 3. Gutter channel (to insert toluene liquid) 4. Aerometer (tool for circulating air) 5. Digital thermohygrometer.</p>
                    </caption>
                    <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/165791/bfa93941-4ae3-4a3d-b524-bbd0ffb77d5a_figure2.gif"/>
                </fig>
                <p>The figure shows that airflow is depicted with an arrow. Initially, air enters the chamber through a hole at the level of the mouse&#x2019;s nose (4 cm from the base). Liquid toluene is sprayed into the chamber (in ppm). Liquid toluene is allowed to evaporate and measurements are taken. Toluene vapor is at the bottom of the chamber because the specific gravity of toluene vapor &gt; the particular gravity of air. Airflow (and toluene) from the chamber is placed at the top.</p>
                <p>

                    <bold>Toluene steam generation technique</bold>

                    <list list-type="order">
                        <list-item>
                            <label>1.</label>
                            <p>The rat cage (glass chamber) measures 80 cm long, 40 cm wide and 40 cm high, so the cage volume is 128,000 cm
                                <sup>3</sup> = 128 liters, ordered at the Aneka Aquarium Surabaya shop.</p>
                        </list-item>
                        <list-item>
                            <label>2.</label>
                            <p>Each glass chamber contains 6 rats.</p>
                        </list-item>
                        <list-item>
                            <label>3.</label>
                            <p>Exposure uses pure toluene for analysis 99.9% from Merck catalog number 1.08325.2500.</p>
                        </list-item>
                        <list-item>
                            <label>4.</label>
                            <p>To obtain toluene vapor, pure toluene is pumped through a syringe into a glass tube at the top of the chamber, respectively (1.6; 3.2; 6.4; 12.8 and 25.6 mL) accompanied by flowing air through a bubbler. into the chamber and assisted by a small fan placed above the chamber.</p>
                        </list-item>
                        <list-item>
                            <label>5.</label>
                            <p>Air circulation through a hole (bubbler image) located under one of the chamber walls. Ventilation holes are made at the level of the rat's nose (&#x00b1; 4 cm from the base).</p>
                        </list-item>
                        <list-item>
                            <label>6.</label>
                            <p>This concentration is achieved by regulating the amount of air that passes through the bubbler, which is adjusted to the amount of air that comes out of the chamber, which is obtained through measurements and calculations. The hole for air flow out of the chamber is located at the top because the specific gravity of the toluene vapor is greater than the specific gravity of the air so the toluene vapor will be at the bottom of the chamber.</p>
                        </list-item>
                        <list-item>
                            <label>7.</label>
                            <p>This liquid toluene will be allowed to evaporate until it runs out and as soon as it runs out the toluene vapor will be measured using the Toluene-C7H8 Gas Analyzer PI967SII. In this experiment, toluene vapor will be at the bottom of the cage relative to the air, because the density of toluene vapor is 3.18 times the density of air.</p>
                        </list-item>
                        <list-item>
                            <label>8.</label>
                            <p>Air flow and toluene vapor come out of the chamber which is placed on the upper side of one of the chamber walls.</p>
                        </list-item>
                        <list-item>
                            <label>9.</label>
                            <p>The environmental conditions of the chamber are maintained to maintain the physical condition of the test animals and encourage the spread of toluene. A digital thermohygrometer is a tool for measuring environmental temperature and humidity. The lighting corresponds to the lighting in the experimental animal laboratory room.</p>
                        </list-item>
                    </list>
                </p>
                <p>

                    <bold>Toluene dose conversion calculations</bold>
                </p>
                <table-wrap id="T1" orientation="portrait" position="anchor">
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Toluene level (ppm)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Conversion calculation</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Toluene dosage (Ml)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.5/1000000 &#x00d7; 128 liters</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">25</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25/1000000 &#x00d7; 128 liters</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.2</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">50</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50/1000000 &#x00d7; 128 liters</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6.4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">100</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">100/1000000 &#x00d7; 128 liters</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.8</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">200</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">200/1000000 &#x00d7; 128 liters</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25.6</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec10">
                <title>2.4 Examination of serum CYP2E1 and Ox-LDL levels</title>
                <p>Serum CYP2 E1 was examined with sandwich ELISA, following the protocol of Rat CYP2E1 ELISA Kit (
                    <ext-link ext-link-type="uri" xlink:href="http://MyBioSource.com">MyBioSource.com</ext-link>, USA) with Cat No. (MBS165228). Rat oxidized low-density lipoprotein (Ox-LDL) ELISA Kit (
                    <ext-link ext-link-type="uri" xlink:href="http://MyBioSource.com">MyBioSource.com</ext-link> USA) with Cat No. (MBS262297) was used to detect rat Ox-LDL.</p>
            </sec>
            <sec id="sec11">
                <title>2.5 Immuno-histochemical staining</title>
                <p>Cardiac coronary tissue was dehydrated in alcohol for 30 min, cleared with 3:1 xylol for 60 min, and treated with paraffin to block infiltration. Paraffinized tissue was sliced into&#x2013;4 &#x03bc;m sections with a microtome, mounted on a slide coated with poly L-lysine, de-paraffinized in xylol for 3&#x2013;5 min three times, soaked in absolute ethanol for 1&#x2013;3 min three times, treated with 70% ethanol for 1&#x2013;3 minimum in two times, washed three times with aqua bidets, incubated with 3% H
                    <sub>2</sub>O
                    <sub>2</sub> at room temperature for 10 min, washed three times with PBS, incubated with 0.025% trypsin at 37&#x00b0;C for 6 min, washed three times with PBS, and incubated with Ultra V Block at room temperature for 5 min.</p>
                <p>For staining, tissues were incubated with monoclonal antibodies (1:100) for 25&#x2013;30 min at room temperature, according to the manufacturer&#x2019;s protocol. Superoxide Dismutase 1 (4C1) Monoclonal Antibody (bsm52817R), Catalase (9C9) Monoclonal Antibody (bsm52906R), and VCAM1 (24D1) Monoclonal Antibody (bsm-52248R) were from BIOSS, USA; and MDA Antibody (orb396658) was from BIORBYT Ltd., UK. Biotinylated and HRP polymers were added after the monoclonal antibodies. Finally, the tissues were incubated with the DAB chromogen in the dark for 5&#x2013;15 min.</p>
            </sec>
            <sec id="sec12">
                <title>2.6 Assessment of SOD, CAT, MDA, and VCAM-1 expression</title>
                <p>Immunohistochemical analysis of SOD, CAT, MDA, and VCAM-1 expression in the coronary arteries of Wistar rats was performed using a binocular light microscope, with 400&#x00d7; magnification. The average number of endothelial cells expressing SOD, CAT, MDA, and VCAM-1 was counted sequentially on each slide in ten fields first left to right, then up, and finally toward the center. The readings were recorded on an examination sheet. Endothelial cells expressing the proteins appeared dark brown due to the usage of the DAB chromogen.</p>
            </sec>
            <sec id="sec13">
                <title>2.7 Statistical analysis</title>
                <p>Data were analyzed using IBM SPSS Statistics 26 (SPSS Inc., Chicago, IL, USA). The tables express Data as mean and standard deviation (SD). The Kolmogorov&#x2013;Smirnov test was used to test the distribution of data. For data sets with normal distribution, the 
                    <italic toggle="yes">T</italic>-test or ANOVA was used. The Mann&#x2013;Whitney U test or Kruskal Wallis H test was used for data sets with non-normal distribution. This study used GLM to analyze the effects of toluene exposure and combined biomarkers. All analyses were considered statistically significant at 
                    <italic toggle="yes">P</italic>&lt;0.05.</p>
            </sec>
        </sec>
        <sec id="sec14" sec-type="results">
            <title>3. Results</title>
            <sec id="sec15">
                <title>3.1 Effects of exposure to toluene in air on serum CYP2E1 and Ox-LDL levels and SOD, CAT, MDA, and VCAM-1 expression in the coronary artery</title>
                <p>CYP2E1 is a major source of cellular and mitochondrial reactive ROS/nitrogen species, causing tissue damage in various diseases. Elevated levels of CYP2E1 can occur under various conditions, including fasting, nutritional intake, and pathological states. Our results showed that the increase in serum CYP2E1 was different between the control group and X4 (
                    <xref ref-type="table" rid="T2">
Table 1</xref>). Repeated toluene exposure induced significant CYP2E1 expression on day 5, which then decreased and remained stable for up to 14 d. In addition, exposure to 100 ppm toluene resulted in CYP1A1 over-expression (
                    <xref ref-type="bibr" rid="ref34">M&#x00e9;ausoone et al., 2021</xref>).</p>
                <table-wrap id="T2" orientation="portrait" position="float">
                    <label>
Table 1. </label>
                    <caption>
                        <title>Measurement of serum CYP2E1 and Ox-LDL levels with SOD, CAT, MDA, and VCAM-1 expression in the coronary artery.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="2" rowspan="1" valign="top">Variable</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Control</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">X1</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">X2</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">X3</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">X4</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">X5</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
p</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="8" rowspan="1" valign="middle">Levels in serum (ng/mL)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="2" rowspan="1" valign="middle">CYP2E1</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Mean &#x00b1; SD</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.92 &#x00b1; 0.23</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.98 &#x00b1; 0.32</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.09 &#x00b1; 0.70</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.18 &#x00b1; 0.37</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.29 &#x00b1; 0.31
                                    <sup>a</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.29 &#x00b1; 0.51</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.585</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Median</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.01</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.96</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.17</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.19</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.36</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.18</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Min - Max</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.53&#x2013;3.10</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.61&#x2013;3.46</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.22&#x2013;3.81</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.65&#x2013;3.65</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.84&#x2013;3.62</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.73&#x2013;4.22</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">95% CI</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.68&#x2013;3.16</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.64&#x2013;3.32</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.36&#x2013;3.83</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.80&#x2013;3.56</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.97&#x2013;3.61</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.75&#x2013;3.82</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="2" rowspan="1" valign="middle">Ox-LDL
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Mean &#x00b1; SD</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.22 &#x00b1; 0.14</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.3 &#x00b1; 0.20</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.37 &#x00b1; 0.19</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.28 &#x00b1; 0.08</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.25 &#x00b1; 0.12</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.38&#x00b1;0.14</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.415</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Median</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.20</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.29</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.36</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.30</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.29</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.40</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Min-Max
</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.03&#x2013;0.44</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.03&#x2013;0.58</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.14&#x2013;0.63</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.15&#x2013;0.37</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.10&#x2013;0.43</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.14&#x2013;0.56</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">95% CI</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.08&#x2013;0.36</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.08&#x2013;0.51</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.16&#x2013;0.57</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.19&#x2013;0.36</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.13&#x2013;0.38</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.23&#x2013;0.52</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="8" rowspan="1" valign="middle">Expression in coronary artery tissue of the heart (in Cells/Field of View)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="2" rowspan="1" valign="middle">SOD</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Mean &#x00b1; SD</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">12.41 &#x00b1; 7.72</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">22.42 &#x00b1; 7.36</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">17.92 &#x00b1; 7.80</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">13.78 &#x00b1; 6.02</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5.79 &#x00b1; 3.81
                                    <sup>b</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">4.76 &#x00b1; 3.40</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.001
                                    <sup>d</sup>
                                </td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Median</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">8.39</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">20.07</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">16.25</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">14.39</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5.15</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">4.39</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Min-Max
</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5.88&#x2013;23.91</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">16.00&#x2013;34.48</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">9.52&#x2013;27.91</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5.56&#x2013;22.41</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.04&#x2013;13.04</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00&#x2013;9.52</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">95% CI</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">4.31&#x2013;20.50</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">14.70&#x2013;30.14</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">9.73&#x2013;26.10</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">7.46&#x2013;20.10</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.79&#x2013;9.79</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.19&#x2013;8.34</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="2" rowspan="1" valign="middle">CAT</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Mean &#x00b1; SD</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">16.29 &#x00b1; 7.67</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">9.48 &#x00b1; 1.79</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">13.53 &#x00b1; 10.56</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">6.85 &#x00b1; 4.77
                                    <sup>b</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.59 &#x00b1; 0.72
                                    <sup>b</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.20 &#x00b1; 2.80
                                    <sup>b</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.001
                                    <sup>d</sup>
                                </td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Median</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">18.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">9.45</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">12.18</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">6.55</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.46</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.85</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Min-Max
</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5.71&#x2013;26.09</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">7.41&#x2013;11.76</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">4.00&#x2013;27.91</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00&#x2013;14.71</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.70&#x2013;4.88</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00&#x2013;7.32</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">95% CI</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">8.24&#x2013;24.34</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">7.60&#x2013;11.35</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.45&#x2013;24.62</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.84&#x2013;11.86</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.83&#x2013;4.35</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.26&#x2013;6.14</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="2" rowspan="1" valign="middle">MDA</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Mean &#x00b1; SD</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.81 &#x00b1; 2.29</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.98 &#x00b1; 2.40</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.85 &#x00b1; 2.85</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">4.49 &#x00b1; 2.79</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">13.03 &#x00b1; 4.88
                                    <sup>b</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">22.83 &#x00b1; 2.19
                                    <sup>b</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.000
                                    <sup>d</sup>
                                </td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Median</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.19</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.65</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5.37</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">13.66</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">22.97</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Min-Max
</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00&#x2013;5.71</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00&#x2013;5.88</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00&#x2013;7.55</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00&#x2013;7.32</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">4.76&#x2013;18.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">19.35&#x2013;26.00</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">95% CI</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-0.60&#x2013;4.22</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-1.54&#x2013;3.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-0.14&#x2013;5.84</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.57&#x2013;7.41</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">7.91&#x2013;18.15</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">20.53&#x2013;25.13</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="2" rowspan="1" valign="middle">VCAM-1</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Mean &#x00b1; SD</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.78 &#x00b1; 1.23</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">9.38 &#x00b1; 6.99
                                    <sup>a</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">13.59 &#x00b1; 5.48
                                    <sup>a</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">17.26 &#x00b1; 8.30
                                    <sup>a</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">31.82 &#x00b1; 3.51
                                    <sup>a</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">27.13 &#x00b1; 3.50
                                    <sup>a</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.000
                                    <sup>c</sup>
                                </td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Median</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">8.38</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">14.52</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">21.87</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">31.65</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">27.02</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Min-Max
</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.00&#x2013;2.70</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.22&#x2013;20.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">6.25&#x2013;21.62</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.70&#x2013;22.86</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">28.21&#x2013;38.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">22.92&#x2013;31.71</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">95% CI</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">-0.51&#x2013;2.06</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.04&#x2013;16.72</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">7.84&#x2013;19.34</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">8.55&#x2013;25.96</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">28.14&#x2013;35.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23.46&#x2013;30.80</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Note: n = 36, n = 6; SD: Standard deviation; 95% CI: 95% confidence interval; Cytochrome P450 2E1(CYP2E1), superoxide dismutase (SOD), catalase (CAT), malondialdehyde (MDA), oxidation LDL (Ox-LDL), and vascular cell adhesion molecule-1 (VCAM-1); significant at 
                            <italic toggle="yes">P</italic>&lt;0.05 (independent 
                            <italic toggle="yes">t</italic>-test), significant at 
                            <italic toggle="yes">P</italic>&lt;0.05 (Mann&#x2013;Whitney U
                            <italic toggle="yes">-</italic>test) significant at 
                            <italic toggle="yes">P</italic>&lt;0.05 (ANOVA), significant at 
                            <italic toggle="yes">P</italic>&lt;0.05 (Kruskal Wallis).</p>
                    </table-wrap-foot>
                </table-wrap>
                <p>The results showed that the average expression of SOD in the coronary artery of Wistar rats increased at small doses of toluene exposure (1.6, 3.2, and 6.4 mL) compared with the control group. Expression was lower in the higher dose group, suggesting that although toluene exposure slightly increased ROS levels in the early stages, accumulated ROS was removed by the combined action of antioxidants and detoxifying enzymes. Thus, exposure to toluene in the air could significantly induce a decrease in SOD expression in the coronary artery of Wistar rats a 
                    <italic toggle="yes">P</italic>-value of 0.001 (
                    <xref ref-type="table" rid="T2">
Table 1</xref>).</p>
                <p>The CAT expression decreased in all experimental groups. ROS generation leads to the accumulation of H
                    <sub>2</sub>O
                    <sub>2</sub>. As ROS concentration increases, more H
                    <sub>2</sub>O
                    <sub>2</sub> is formed, which poisons CAT, resulting in a significant decrease in CAT activity a 
                    <italic toggle="yes">P</italic>-value of 0.001. The low levels of SOD and CAT expression caused membrane (seen from the expression of MDA metabolites) in the coronary artery of Wistar rats to a 
                    <italic toggle="yes">P</italic>-value of 0.000 (
                    <xref ref-type="table" rid="T2">
Table 1</xref>).</p>
                <p>The toluene exposure correlated with an increase in VCAM-1 expression in the coronary artery of Wistar rats a 
                    <italic toggle="yes">P</italic>-value of 0.000 (
                    <xref ref-type="table" rid="T2">
Table 1</xref>). Thus, exposure to toluene in the air can significantly induce an increase in VCAM-1 expression.</p>
            </sec>
            <sec id="sec16">
                <title>3.2 Analysis of the interaction effect of toluene exposure levels and serum levels (CYP2E1, Ox-LDL) and expression (SOD, CAT, MDA, VCAM-1) of coronary arteries</title>
                <p>We used GLM to analyze the effect of toluene exposure and levels of serum CY2E1 and Ox-LDL, as well as expression of SOD, CAT, MDA, andVCAM-1in the coronary artery, on endothelial dysfunction. GLM is used to predict linear relationships between dependent variables and independent variables (factors and covariates). In addition, GLM allows for the abnormal distribution of variables.</p>
                <p>For GLM, VCAM-1 expression was the dependent variable. The independent variable was in the form of factors (categorical data), namely six exposure levels of toluene. The independent variables in covariate form included serum enzyme levels (CYP2E1, Ox-LDL) and expression (SOD, CAT, MDA) in the coronary artery.</p>
                <p>
                    <xref ref-type="table" rid="T2">
Table 1</xref> is a description of the toluene exposure group variables with categorical data types. There are six categories: control and five experimental groups X1&#x2013;X5, each exposure group with six replicates. Therefore, 36 datasets were analyzed for the exposure group. Results of the test of model effects on the value of significance from the Wald chi-square test is presented in 
                    <xref ref-type="table" rid="T3">
Table 2</xref>.</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>
Table 2. </label>
                    <caption>
                        <title>Test of model effects.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="2" valign="top">Source</th>
                                <th align="left" colspan="3" rowspan="1" valign="top">Type III</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Wald chi-square
</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">df</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Sig.</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Exposure * CYP2E1* SOD* CAT* MDA* Ox-LDL</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18.641</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.005</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="4" rowspan="1" valign="top">Dependent Variable: VCAM-1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="4" rowspan="1" valign="top">Model: Exposure * CYP2E1 * SOD * CAT * MDA * Ox-LDL</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>The significance value (
                    <italic toggle="yes">P</italic>-value) from the Wald chi-square test is 0.005. The result shown in 
                    <xref ref-type="table" rid="T3">
Table 2</xref> was statistically significant because the 
                    <italic toggle="yes">P</italic>-value &lt; 0.05. Therefore, the combined effect of independent variables on the dependent variable is significant. Exposure to toluene, combined with the effect of serum CYP2E1 and Ox-LDL levels, as well as coronary SOD, CAT, and MDA expression, are significantly related to VCAM-1.</p>
            </sec>
            <sec id="sec17">
                <title>3.3 Estimation parameter test of combined interaction in each group</title>
                <p>The effects of the combined interaction between serum enzyme levels and coronary artery expression in each group are shown in 
                    <xref ref-type="table" rid="T4">
Table 3</xref>. Values from the Wald chi-square and probability 
                    <italic toggle="yes">P</italic>-values showed the combined effect of each group. 
                    <italic toggle="yes">P</italic>-value &lt;0.05 was considered statistically significant.</p>
                <table-wrap id="T4" orientation="portrait" position="float">
                    <label>
Table 3. </label>
                    <caption>
                        <title>Estimation of parameters from combined interactions in each group (exposure level).</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Combined interaction parameters in each group</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">B</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Wald 
chi-square
</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">

                                    <italic toggle="yes">P</italic>-value</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Conclusion</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">[Exposure = 1]*CYP2E1*SOD*CAT*MDA*Ox-LDL
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.003</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.012</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.913</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Not significant</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">[Exposure = 2]*CYP2E1*SOD*CAT*MDA*Ox-LDL
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.012</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.342</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.559</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Not significant</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">[Exposure = 3]*CYP2E1*SOD*CAT*MDA*Ox-LDL
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.003</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.927</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.336</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Not significant</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">[Exposure = 4]*CYP2E1*SOD*CAT*MDA*Ox-LDL
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.022</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.337</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.068</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Significantly enough</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">[Exposure = 5]*CYP2E1*SOD*CAT*MDA*Ox-LDL
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.051</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.774</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.003</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Significant</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">[Exposure = 6]*CYP2E1*SOD*CAT*MDA*Ox-LDL
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.016</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.249</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.022</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Significant</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>[Exposure = 1] * CYP2E1 * SOD * CAT * MDA * Ox-LDL is the control group. 
                    <italic toggle="yes">P</italic>-value=0.913 indicates no significant effect on VCAM-1.</p>
                <p>[Exposure = 2] * CYP2E1 * SOD * CAT * MDA * Ox-LDL is toluene exposure group X1. 
                    <italic toggle="yes">P</italic>-value = 0.559 indicates no significant effect on VCAM-1.</p>
                <p>[Exposure = 3] * CYP2E1 * SOD * CAT * MDA * Ox-LDL is toluene exposure group X2. 
                    <italic toggle="yes">P</italic>-value = 0.336 indicates no significant effect on VCAM-1.</p>
                <p>[Exposure = 4] * CYP2E1 * SOD * CAT * MDA * Ox-LDL is toluene exposure group X3. 
                    <italic toggle="yes">P</italic>-value = 0.068 indicates a significant effect on VCAM-1. Thus, the variable in X3 has a significant effect on VCAM-1, where the effect value (B) of this exposure dose was 0.022 times the impact on increasing VCAM-1 expression.</p>
                <p>[Exposure = 5] * CYP2E1 * SOD * CAT * MDA * Ox-LDL is toluene exposure group X4. 
                    <italic toggle="yes">P</italic>-value =0.003 indicates a significant effect on VCAM-1. Thus, X4 has a significant effect on VCAM-1 expression, where the effect value (B) of this exposure dose is 0.051 times the impact on increasing VCAM-1 expression</p>
                <p>[Exposure = 6] * CYP2E1 * SOD * CAT * MDA * Ox-LDL is toluene exposure group X5. 
                    <italic toggle="yes">P</italic>-value =0.022 indicates a significant effect on VCAM-1. Thus, the variable in X5 has a significant effect on VCAM-1, where the effect value (B) of this exposure dose was 0.016 times the impact on increasing VCAM-1 expression.</p>
            </sec>
        </sec>
        <sec id="sec18" sec-type="discussion">
            <title>4. Discussion</title>
            <p>Toluene is one of the most produced and used industrial solvents worldwide. It is the most widely abused volatile substance that is toxic to several organs (
                <xref ref-type="bibr" rid="ref4">Camara-Lemarroy et al., 2015</xref>; 
                <xref ref-type="bibr" rid="ref9">Djurendic-Brenesel et al., 2016</xref>; 
                <xref ref-type="bibr" rid="ref46">Yasar et al., 2016</xref>). Toluene is extensively metabolized by CYP2E1, leading to the formation of toluene epoxides, which can generate free radicals (
                <xref ref-type="bibr" rid="ref22">Ji et al., 2017</xref>; 
                <xref ref-type="bibr" rid="ref34">M&#x00e9;ausoone et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref37">Moro et al., 2012</xref>). At low levels of free radicals, intracellular antioxidants, such as SOD, CAT, and GSH-Px, can reduce oxidative stress-mediated cell damage (
                <xref ref-type="bibr" rid="ref15">Hamid et al., 2022</xref>; 
                <xref ref-type="bibr" rid="ref23">Jim&#x00e9;nez-Garza et al., 2015</xref>). Oxidative stress due to toluene exposure is mediated by benzyl alcohol, which activates CYP2E1 to produce ROS in the form of free radicals, such as O
                <sub>2</sub>*, H
                <sub>2</sub>O
                <sub>2</sub>, and *OH that damage proteins, lipids, and DNA (
                <xref ref-type="bibr" rid="ref23">Jim&#x00e9;nez-Garza et al., 2015</xref>; 
                <xref ref-type="bibr" rid="ref27">Kim et al., 2012</xref>; 
                <xref ref-type="bibr" rid="ref28">Kodavanti et al., 2015</xref>).</p>
            <p>Increased ROS production due to toluene exposure can trigger oxidative stress, which is characterized by accumulation of non-enzymatic oxidative damage of cell function. Oxidative stress can be identified by increasing lipid peroxides, especially polyunsaturated fatty acids in biological membranes, which will form MDA (
                <xref ref-type="bibr" rid="ref29">Konuk et al., 2012</xref>; 
                <xref ref-type="bibr" rid="ref48">Yurdagul et al., 2016</xref>). Increased lipid peroxidase (MDA) can interfere with the cofactor endothelial NO synthase (eNOS), causing a decrease in eNOS production and decreased bioavailability of nitric oxide (NO). In the presence of oxygen (through the formation of NO
                <sub>2</sub> and N
                <sub>2</sub>O
                <sub>3</sub>) or superoxide (through the formation of peroxynitrite), NO can cause oxidation of lipid components, resulting in the formation of Ox-LDL (
                <xref ref-type="bibr" rid="ref2">Ardiana et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref40">Shiroto et al., 2014</xref>; 
                <xref ref-type="bibr" rid="ref42">Stajkovi&#x0107; et al., 2009</xref>). The chemotactic activity of Ox-LDL stimulates the binding of monocytes to endothelial cells, thereby enhancing the adhesive properties of the endothelium, including over-expression of VCAM-1, representing a key step in endothelial dysfunction (
                <xref ref-type="bibr" rid="ref12">Gradinaru et al., 2015</xref>; 
                <xref ref-type="bibr" rid="ref15">Hamid et al., 2022</xref>; 
                <xref ref-type="bibr" rid="ref21">Ivanova et al., 2017</xref>).</p>
            <p>Serum CYP2E1 concentration in the experimental groups was higher than in the control group, although this difference was not statistically significant. CYP2E1 is a key enzyme involved in toluene toxicity (
                <xref ref-type="bibr" rid="ref17">Harjum&#x00e4;ki et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref18">Hartman et al., 2017</xref>), because toluene regulates its metabolism by inducing CYP2E1 activity. This was because of altering protein stability, causing toxicity or cell damage through the production of toxic metabolites. In addition, free radicals can cause oxidative stress. According to 
                <xref ref-type="bibr" rid="ref13">Guan et al., (2019)</xref> and 
                <xref ref-type="bibr" rid="ref30">Lu et al., (2012)</xref>, CYP2E1 bioactivation could trigger apoptosis, which induces tissue and cell damage. During toluene biotransformation, SOD activity decreases, resulting in the accumulation of metabolic intermediates and byproducts of oxygen-derived free radicals: O
                <sub>2</sub>*and OH*or their derivatives, such as H
                <sub>2</sub>O
                <sub>2</sub> (
                <xref ref-type="bibr" rid="ref22">Ji et al., 2017</xref>; 
                <xref ref-type="bibr" rid="ref27">Kim et al., 2012</xref>; 
                <xref ref-type="bibr" rid="ref42">Stajkovi&#x0107; et al., 2009</xref>). When toluene concentration is higher, more H
                <sub>2</sub>O
                <sub>2</sub> is produced, which cannot be rapidly degraded, and eventually, inactivates SOD.</p>
            <p>Excessive free radicals inactivate antioxidant enzymes CAT, GSH-Px, etc., because accumulated H
                <sub>2</sub>O
                <sub>2</sub> poisons CAT, resulting in a significant decrease in CAT expression (
                <xref ref-type="bibr" rid="ref15">Hamid et al., 2022</xref>; 
                <xref ref-type="bibr" rid="ref42">Stajkovi&#x0107; et al., 2009</xref>). Consistently, in this study, significantly lower CAT expression in the experimental group (compared with the control group) correlated with decreased SOD. A decrease in CAT activity is associated with an increase in VCAM-1 expression because high doses of toluene lead to increased H
                <sub>2</sub>O
                <sub>2</sub> formation (
                <xref ref-type="bibr" rid="ref25">Kaur et al., 2022</xref>). This stimulates an increase in O
                <sub>2</sub>* to induce oxidative stress and endothelial dysfunction (
                <xref ref-type="bibr" rid="ref7">Coyle &amp; Kader, 2007</xref>; 
                <xref ref-type="bibr" rid="ref14">Habas &amp; Shang, 2018</xref>).</p>
            <p>Malondialdehyde (MDA), one of the byproducts of lipid peroxidation, is used as a marker of oxidative stress. In this study, the positive correlation between the expression of MDA metabolites and toluene levels may be due to an increase in lipid peroxidase resulting from increased toluene levels (
                <xref ref-type="bibr" rid="ref29">Konuk et al., 2012</xref>). Under conditions of high oxidative stress, the expression of MDA metabolites increases, which induces an increase in vascular endothelial growth factor and stimulates caveolin-1. This inhibits eNOS, decreases eNOS production, and reduces the bioavailability of NOS (
                <xref ref-type="bibr" rid="ref36">Moraes et al., 2014</xref>; 
                <xref ref-type="bibr" rid="ref40">Shiroto et al., 2014</xref>; 
                <xref ref-type="bibr" rid="ref47">Ye et al., 2016</xref>). Imbalance in NOS production results in a proinflammatory response, characterized by increased VCAM-1.</p>
            <p>Several studies have found that toluene exposure can interfere with lipid function, such as increased plasma LDL (
                <xref ref-type="bibr" rid="ref29">Konuk et al., 2012</xref>; 
                <xref ref-type="bibr" rid="ref42">Stajkovi&#x0107; et al., 2009</xref>) and triglycerides (
                <xref ref-type="bibr" rid="ref27">Kim et al., 2012</xref>; 
                <xref ref-type="bibr" rid="ref45">Won et al., 2011</xref>). High triglyceride levels, reflecting increased concentrations of lipoproteins, including LDL, can exacerbate endothelial inflammation and promote monocyte infiltration into the arterial wall (
                <xref ref-type="bibr" rid="ref44">Wang et al., 2013</xref>). Our results show that mean serum Ox-LDL levels were higher in the experimental group, although this difference was not statistically significant. Given that not all LDL molecules are of the same size. Some, such as small-dense LDL, may be more susceptible to chemical modifications that increase their atherogenicity (
                <xref ref-type="bibr" rid="ref21">Ivanova et al., 2017</xref>).</p>
            <p>VCAM-1 is expressed in the endothelium, indicating endothelial damage (
                <xref ref-type="bibr" rid="ref2">Ardiana et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref25">Kaur et al., 2022</xref>). Our results showed that toluene exposure increased VCAM-1 expression starting from experimental group X1 (low dose). This increase in VCAM-1 expression is associated with a decrease in CAT activity (
                <xref ref-type="bibr" rid="ref7">Coyle &amp; Kader, 2007</xref>; 
                <xref ref-type="bibr" rid="ref14">Habas &amp; Shang, 2018</xref>) and increase in MDA metabolites (
                <xref ref-type="bibr" rid="ref36">Moraes et al., 2014</xref>; 
                <xref ref-type="bibr" rid="ref47">Ye et al., 2016</xref>). Toluene is lipophilic increasing and, therefore, can change the structure of cell membrane lipids, increasing oxygen free radicals and H
                <sub>2</sub>O
                <sub>2</sub> (
                <xref ref-type="bibr" rid="ref15">Hamid et al., 2022</xref>; 
                <xref ref-type="bibr" rid="ref29">Konuk et al., 2012</xref>). The host antioxidant system cannot neutralize increased production of ROS. Furthermore, H
                <sub>2</sub>O
                <sub>2</sub> reacts with Fe
                <sup>+2</sup> and Cu+2 to form hydroxyl free radicals through the Fenton and Haber&#x2013;Weiss reactions. OH* is a very reactive species and initiates a chain reaction with one hydrogen atom from the cell membrane forlipid peroxidation. Products of lipid peroxidation include MDA (
                <xref ref-type="bibr" rid="ref14">Habas &amp; Shang, 2018</xref>; 
                <xref ref-type="bibr" rid="ref42">Stajkovi&#x0107; et al., 2009</xref>).</p>
            <p>The overall aim of this study was to analyze the impact of toluene exposure on coronary artery response. We found that oxidative stress due to free radicals originating from toluene exposure in the air adversely affects the coronary artery.</p>
        </sec>
        <sec id="sec19" sec-type="conclusion">
            <title>5. Conclusion</title>
            <p>This study shows that exposure to airborne toluene adversely affects the coronary arteries. Moreover, it also may increase the risk of endothelial dysfunction. Toluene exposure has toxic effects on the cardiovascular system, closely related to increased oxidative stress in the coronary artery. Low SOD and CAT expression with high MDA and VCAM-1 expression after toluene exposure may increase the risk of developing endothelial dysfunction, which reflects the onset of atherosclerosis as a cause of CVD. This adds to the evidence that toluene exposure causes CVD through the effects of oxidative stress on coronary arteries.</p>
        </sec>
        <sec id="sec21">
            <title>Statement of ethical approval</title>
            <p>This study followed the principle of ethics proven with the ethical approval test. The ethical approval certificate number was 801/HRECC.FODM/X/2022. The experimental protocol was approved by The Health Research Ethical Clearance Committee (HRECC), Faculty of Dentistry, Airlangga, on October 26, 2022.</p>
            <p>Enago has also checked this paper as an institution that provided a proofreading service on September 27, 2023. The certificate of proofreading has been uploaded to the Zenodo repository. The link to the certificate can be accessed on 
                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.13727263">https://doi.org/10.5281/zenodo.13727263</ext-link>.</p>
            <p>Animal ethics:
                <list list-type="order">
                    <list-item>
                        <label>1.</label>
                        <p>ANIMAL TREATMENT Blood Collection
</p>
                    </list-item>
                </list>

                <table-wrap id="T5" orientation="portrait" position="anchor">
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Anesthesia used</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Location</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Volume</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Frequency</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Ketamine 10% and Xyla</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Blood collection of rats through cardiac puncture</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3-5 Ml</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">At the end of the experiment</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>

                <list list-type="order">
                    <list-item>
                        <label>2.</label>
                        <p>Surgery</p>
                        <p>Surgery will be performed in the study. The surgeries performed are: Major surgery (by opening the chest/abdominal cavity). The surgery ends with termination</p>
                    </list-item>
                </list>

                <table-wrap id="T6" orientation="portrait" position="anchor">
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Drugs and materials used other than anesthesia</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Dose (mg/kg BW)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Route</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">23 G needle</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.1 Ml</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Intramuscular</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>

                <list list-type="order">
                    <list-item>
                        <label>3.</label>
                        <p>Euthanation</p>
                    </list-item>
                </list>
            </p>
            <table-wrap id="T7" orientation="portrait" position="anchor">
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Euthanation method</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Dose (mg/kg BW)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Route</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Intramuscular injection</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.,1-1.0 Ml</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Intramuscular</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>After euthanasia, rats will be collected in special plastic bags and wooden boxes, to then be burned in waste disposal at the Faculty of Veterinary Medicine, Universitas Airlangga.</p>
            <p>The animal ethics certificate includes a link to the dataset accessible below: 
                <ext-link ext-link-type="uri" xlink:href="https://zenodo.org/records/11438933">https://zenodo.org/records/11438933</ext-link>
            </p>
            <p>The Animal Care and Use Committee (ACUC) of the Faculty of Dentistry, Universitas Airlangga approved the protocol of all procedures described in this study on October 26, 2022. All experimental procedures were performed in accordance with the ARRIVE guidelines (
                <xref ref-type="bibr" rid="ref32">Maryiantari, 2022</xref>). Tissue dissection and collection were performed by experienced laboratory technicians from the Department of Biochemistry, Faculty of Medicine, Universitas Airlangga. The rats were fasted for 3 h and weighed using a precision electronic balance. Additionally, they were anesthetized by intramuscular injection of 100 mg/kg body weight of ketamine (Ket-A-100
                <sup>&#x00ae;</sup>, AgroVet, Peru) and 20 mg/kg body weight of xylazine (Interchemie werken &#x201c;De Adelaar&#x201d; B.V. The Netherlands. The protocol has been previously used and described by (
                <xref ref-type="bibr" rid="ref3">Bhatia et al., 2022</xref>; 
                <xref ref-type="bibr" rid="ref39">Olson et al., 2013</xref>).</p>
            <p>After the reflex disappeared, the mice were placed in a supine position on the operating table, and blood was collected by cardiac puncture using a disposable terumo syringe with a 5 ml 23G needle, which was then placed in a tube without anticoagulant. After blood collection, the heart was cut, cleaned with isotonic sodium chloride solution, and placed in a tube containing 10% neutral buffered formalin (NBF-10%), then sent to the pathological anatomy laboratory of Universitas Airlangga. The blood in the tube was allowed to clot naturally (about 30 to 60 minutes) and then centrifuged at 3,500 rpm for 10 minutes to separate the serum. The blood was then poured into Eppendorf tubes and stored at -20&#x00b0;C until analysis of CYP2E1 enzyme levels and Ox-LDL serum was performed at the Tropical Blood Disease Research Center/TDRC Universitas Airlangga. Finally, the remains of the animals were collected in special plastic bags and wooden crates, then cremated at the landfill of the Faculty of Veterinary Medicine, Universitas Airlangga to avoid environmental pollution.</p>
        </sec>
    </body>
    <back>
        <sec id="sec24" sec-type="data-availability">
            <title>Data availability</title>
            <p>The DOI of dataset was Zenodo: Dataset for paper, 
                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.13896290">https://doi.org/10.5281/zenodo.13896290</ext-link> (
                <xref ref-type="bibr" rid="ref32">Maryiantari, E. S. 2022</xref>)</p>
            <p>This project contains the following data:
                <list list-type="bullet">
                    <list-item>
                        <label>-</label>
                        <p>00-Author Checklist - E10 only.docx (ARRIVE checklist)</p>
                    </list-item>
                    <list-item>
                        <label>-</label>
                        <p>CYP2E1 calculation result Conc ng per ml.pdf</p>
                    </list-item>
                    <list-item>
                        <label>-</label>
                        <p>ETHICAL CLEARANCE CERTIFICATE.pdf</p>
                    </list-item>
                    <list-item>
                        <label>-</label>
                        <p>mouse sample.jpg</p>
                    </list-item>
                    <list-item>
                        <label>-</label>
                        <p>Ox-LDL calculation result of Conc ng per ml.pdf</p>
                    </list-item>
                    <list-item>
                        <label>-</label>
                        <p>research funding contract.pdf</p>
                    </list-item>
                    <list-item>
                        <label>-</label>
                        <p>Result-IHC.xls</p>
                    </list-item>
                </list>
            </p>
            <p>Data are available under the terms of the 
                <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            <sec id="sec20">
                <title>Reporting guidelines</title>
                <p>This study followed the reporting guideline of ARRIVE version 2.0. This study used a checklist of ten minimum requirements for reporting animal research. The checklist of reporting guideline was sent along with this manuscript to the email of the editorial board of F1000 Research Journal for revision. The DOI number of the file was 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.13117744">https://doi.org/10.5281/zenodo.13117744</ext-link> (
                    <xref ref-type="bibr" rid="ref33">Maryiantari, E. S., 2024</xref>).</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgement</title>
            <p>The authors are also grateful to all staff at the Biomedical Laboratory and Tropical Disease Center of Universitas Airlangga No: 7379/UN3.1.10/PK/2022, on October 7, 2022. The authors were thankful for the Innovation Institute, Journal Development, Publishing, and Intellectual Property Rights of Airlangga University to provide the access on Enago as well as guiding the proper manuscript draft. The author also said thanks to Akhmad Kusuma Wardhana from Prince of Songkla University, Thailand, for collaboration in guiding to conduct data curation, data collection, and filling ARRIVE 2.0 reporting guidelines. We also obtained permission to upload the extended data, especially figures used in this study from the Faculty of Medicine Laboratory in Universitas Airlangga.</p>
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    <sub-article article-type="reviewer-report" id="report370303">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.165791.r370303</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Warnakulasuriya</surname>
                        <given-names>Tania</given-names>
                    </name>
                    <xref ref-type="aff" rid="r370303a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r370303a1">
                    <label>1</label>University of Kelaniya, Kelaniya, Western Province, Sri Lanka</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>12</day>
                <month>4</month>
                <year>2025</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Warnakulasuriya T</copyright-statement>
                <copyright-year>2025</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport370303" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.151166.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>This manuscript explores the effects of acute toluene exposure on markers of oxidative stress and endothelial function in Wistar rats. They have conducted an interesting experiment with a control group and 5 experimental groups with incremental toluene exposures. Their findings are important and provide insight into the pathophysiological mechanism of coronary arterial disease with toluene exposure. However, I would like to suggest a few amendments to improve the quality of the manuscript.&#x00a0;</p>
            <p> 1. Avoid repetition and make the manuscript succinct.&#x00a0;</p>
            <p> 2. Improve the results and statistical methods.&#x00a0;</p>
            <p> 3. Restructure the discussion.</p>
            <p> </p>
            <p> Specific comments are as below,</p>
            <p> </p>
            <p> Methods</p>
            <p> I recommend amending the sentence 'Wistar rats were injected with a lethal dose of ketamine&#x2013;xylazine.' to indicate that it was at the end of the exposure period.&#x00a0;</p>
            <p> </p>
            <p> I recommend removing the phrase 'to avoid infected by bacteria.'.</p>
            <p> </p>
            <p> Referring from repetition. I suggest the statements related to specific gravity except&#x00a0; 'In this experiment, toluene vapor will be at the bottom of the cage relative to the air, because the density of toluene vapor is 3.18 times the density of air.' to be removed.&#x00a0;</p>
            <p> </p>
            <p> Results</p>
            <p> Avoid discussion in the results section.&#x00a0;</p>
            <p> Remove 'CYP2E1 is a major source of cellular and mitochondrial reactive ROS/nitrogen species, causing tissue damage in various diseases. Elevated levels of CYP2E1 can occur under various conditions, including fasting, nutritional intake, and pathological states.'</p>
            <p> </p>
            <p> Table 1- footnote was not included. Add post hoc analysis.</p>
            <p> </p>
            <p> Use the p value in parenthesis. if the value is 0.000 it should be recorded as p&lt;0.001</p>
            <p> </p>
            <p> The subtopic 3.2 needs to be amended and parenthesis removed.&#x00a0;</p>
            <p> </p>
            <p> 3.3 - remove '
                <italic>P</italic>-value &lt;0.05 was considered statistically significant.' as it has been defined in methods.&#x00a0;</p>
            <p> </p>
            <p> Table 2- Report the unadjusted regression coefficients and significance of each variable used in the model.&#x00a0;</p>
            <p> </p>
            <p> Discussion</p>
            <p> Start the discussion with a summary of your key findings. Then explain the findings.&#x00a0;</p>
            <p> </p>
            <p> Conclusions</p>
            <p> Summarize the findings from the research and avoid repetition.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Physiology and exposure related health effects.</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
    </sub-article>
</article>
