<?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.173387.1</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>Serum Neurogranin as a Diagnostic Biomarker for Acute Ischemic Stroke: Performance Comparison Between Thrombotic and Embolic subtypes</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="yes">
                    <name>
                        <surname>Saleh</surname>
                        <given-names>Tiba H.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0009-0008-1566-0841</uri>
                    <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>Haddad</surname>
                        <given-names>Namir I. A.</given-names>
                    </name>
                    <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/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Chemistry, College of Science, University of Baghdad, Baghdad, Iraq</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:tiba.saleh2305@sc.uobaghdad.edu.iq">tiba.saleh2305@sc.uobaghdad.edu.iq</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>18</day>
                <month>12</month>
                <year>2025</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2025</year>
            </pub-date>
            <volume>14</volume>
            <elocation-id>1412</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>12</day>
                    <month>12</month>
                    <year>2025</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Saleh TH and Haddad NIA</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/14-1412/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>Ischemic stroke (IS) is a severe neurological disorder that can lead to disability and mortality in adults. The management of acute ischemic stroke (AIS) requires the ability to predict functional outcomes. Blood biomarkers are valuable prognostic tools because of their rapid assessment, cost-effectiveness, and clinical accessibility. Given that Neurogranin (Ng) is a small postsynaptic neural protein, and when the blood-brain barrier (BBB) is damaged, Ng levels are altered in the bloodstream.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>This study aimed to assess the concentration of Ng in patients with acute ischemic stroke. We investigated forty-six thrombotic patients, forty-five embolic patients, and forty-five healthy individuals. Serum concentrations of Ng, D-dimer, random blood sugar (RBS), lipid profile, renal function tests, liver function tests, complete blood count (CBC), and electrolyte tests were performed for all participants.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>The results revealed that the embolic group had the highest serum level of Ng compared to the thrombotic and control groups (0.600&#x00b1;0.339 ng/ml, 0.464&#x00b1;0.121 ng/ml, and 0.304&#x00b1;0.065 ng/ml, respectively). Moreover, correlation analysis revealed that serum Ng was positively correlated with some biomarker parameters, specifically platelets, total cholesterol (TC), and low-density lipoprotein (LDL), in the embolic group. Meanwhile, Receiver Operating Characteristic (ROC) Curve analysis yielded area under the curve (AUC) values of 0.879 vs. 0.897 for the thrombotic and embolic groups, respectively.</p>
                </sec>
                <sec>
                    <title>Conclusion</title>
                    <p>These results led us to conclude that the assessment of serum Ng levels suggests that it can be used as a successful diagnostic parameter for ischemic stroke patients during the early stages of the disease.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Neurogranin</kwd>
                <kwd>Ischemic Stroke</kwd>
                <kwd>Thrombotic</kwd>
                <kwd>Embolic</kwd>
                <kwd>Cardioembolism.</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>1. Introduction</title>
            <p>Ischemic stroke (IS) is a cerebrovascular disease (CVD) and the most common subtype of stroke, accounting for approximately 70% of cases associated with substantial disability and mortality in adults worldwide. It occurs when a blood clot blocks or narrows an artery, depriving the brain of oxygen and glucose.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>,
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> The IS classification is based on the mechanism and includes two main groups: thrombotic stroke, which mechanism occurs when blood vessels are obstructed by an in-situ thrombosis, leading to a brain infarction in the area supplied by those ischemic strokes. An embolic stroke occurs when a blood clot forms in another part of the body, travels through the bloodstream to the brain, causing acute blockage of blood flow, resulting in infarction in the affected brain territory.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>,
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
            </p>
            <p>Thrombotic events can precipitate strokes through multiple pathways. When blood clots obstruct major cerebral vessels, they result in either large-artery occlusion or small-artery occlusion (lacunar stroke). Thrombotic processes may also affect the cerebral veins and venous sinuses, thereby complicating clinical presentation. Conversely, embolic stroke occurs when cerebral arteries become occluded by thromboemboli originating from cardiac sources, and is termed cardioembolism. Moreover, approximately 50% of ischemic stroke cases are linked to cardiac embolism, 25% to large vascular occlusion, and 10% to small vascular occlusion.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
            </p>
            <p>There is a critical need to novel and reliable biomarkers that can be utilized in stroke prognostic and severity assessments.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>,
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> When measured in blood samples, elevated levels of these biomarkers serve as indicators of cerebral damage.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>,
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> These biomarkers are proteins associated with the Central Nervous System (CNS). During stroke events, disorders of the Blood-Brain Barrier (BBB) lead to elevation of these biomarkers in the peripheral circulation.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>,
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> Neurogranin (Ng) is a calmodulin-binding protein predominantly found in the brain, especially in dendritic spines. It is a significant postsynaptic protein that is part of the signaling pathway for protein kinase C (PKC), regulating the availability of calmodulin by binding to it when calcium is absent.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> This protein demonstrates extensive distribution through multiple of the brain regions, showing up localization in cortical layers II-IV and notably appearing in the neocortex, amygdala, caudate nucleus, putamen, and hippocampus. Furthermore, its calcium-dependent interaction with calmodulin, this protein regulates numerous essential cellular processes, including cellular growth, transcriptional activity, cell movement, protein modification through phosphorylation and dephosphorylation cascades, ionic transport mechanisms, and modulation of neurotransmitter and hormonal signaling pathways. Consequently, the broad anatomical distribution and diverse functional involvement highlight the fundamental importance of this protein.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
            </p>
            <p>This study aimed to assess the ability of Ng to be used as a potential biomarker for ischemic stroke patients and to determine the serum concentration of Ng in Iraqi individuals who have been diagnosed with ischemic stroke across various groups. Furthermore, it was designed to determine the correlation between Ng and the additional anthropometric and biochemical parameters.</p>
        </sec>
        <sec id="sec6">
            <title>2. Materials and methods</title>
            <sec id="sec7">
                <title>2.1 Research subjects</title>
                <p>The present research collects ninety-one patients with acute ischemic stroke (AIS) who were admitted to three hospitals in Iraq: Dr. Saad AL-Witry Neuroscience Hospital (Baghdad), Neurosurgery Hospital (Baghdad), and AL-Hakeem Teaching Hospital (Maysan) between March 31 and September 1, 2025. All patients were initially evaluated in the emergency department (ED) and subsequently transferred to the neurology department for further management. Based on stroke etiology determined by neuroimaging, patients were classified into two groups: thrombotic stroke group (n = 46): 25 men and 21 women, age range&#x2013;40-85 years, and embolic stroke group (n = 45): 26 men and 19 women, age range&#x2013;45-88 years. Additionally, a control group (n = 45) of age- and sex-matched healthy volunteers (26 men and 19 women, age range&#x2013;40-75 years) was included. All AIS diagnoses were confirmed by neurologists based on neuroimaging results, including computed tomography (CT) and magnetic resonance imaging (MRI) and clinical presentation.
                    <sup>
                        <xref ref-type="bibr" rid="ref16">16</xref>
                    </sup> Electrocardiography (ECG) was performed to identify the potential cardiac sources of embolism.</p>
            </sec>
            <sec id="sec8">
                <title>2.2 Exclusion criteria</title>
                <p>The study excluded patients with a cancer history, acute inflammation, and chronic conditions diseases such as liver diseases, renal failure, hemorrhagic stroke, and transient ischemic stroke attacks (TIAs).</p>
            </sec>
            <sec id="sec9">
                <title>2.3 Ethical approval and consent</title>
                <p>This study was conducted in accordance with the principles of the Declaration of Helsinki and approved by the Research Ethics Committee of the College of Science, University of Baghdad, Baghdad, Iraq (Approval Number: Ref. CSEC/0325/0053 on March 27, 2025) (
                    <italic toggle="yes">as in Extended data</italic>).
                    <sup>
                        <xref ref-type="bibr" rid="ref17">17</xref>
                    </sup> Appropriate permits were obtained from relevant hospital authorities. Written informed consent was obtained from all participants or their legally authorized representatives prior to enrollment (
                    <italic toggle="yes">as in Extended data</italic>).
                    <sup>
                        <xref ref-type="bibr" rid="ref17">17</xref>
                    </sup> For patients unable to provide consent due to their medical condition, consent was obtained from their next of kin in accordance with local regulations. All patient data were de-identified and coded to protect participant confidentiality. Demographic and medical history data were collected using a standardized questionnaire (
                    <italic toggle="yes">as in Extended data</italic>).
                    <sup>
                        <xref ref-type="bibr" rid="ref17">17</xref>
                    </sup>
                </p>
            </sec>
            <sec id="sec10">
                <title>2.4 Neurobiochemical and other biochemical parameters analysis</title>
                <p>

                    <bold>2.4.1 Sample collection</bold>
                </p>
                <p>Five-milliliter blood samples were drowning from each participant and aseptically transferred to tightly sealed gel and EDTA tubes. An EDTA tube containing 2 ml of whole blood was used to assess the Complete Blood Count (CBC), while a gel tube containing 3 ml of blood was subsequently centrifuged at 1000 x g for 20 min until serum was separated. All samples were stored at -20 &#x00b0;C until biochemical analysis was conducted.</p>
                <p>

                    <bold>2.4.2 Neurobiochemical analysis</bold>
                </p>
                <p>Serum levels of Ng protein were estimated using Enzme-linked immunosorbent assay (ELISA), with commercially available kits from MyBioSource (Catalog No: MBS8806622), USA, which are designed in accordance with established protocols for this biomarker.</p>
                <p>

                    <bold>2.4.3 Biochemical parameters analysis</bold>
                </p>
                <p>Blood samples were analyzed using various automated device. Renal function tests, lipid profile, Random blood sugar (RBS), and calcium levels were measured using a spectrophotometer (APEL, Japan). The electrolyte levels (potassium, sodium, and chloride) were determined using an Electrolyte Analyzer EL-120 (Erma, Japan). Liver enzyme activities (ALT and AST) levels were analyzed using the analyzer cobas c 111 (Roche, Switzerland), and D-dimer concentrations were assessed by immunofluorescence assay using the i-CHROMA-II system. A Mindray BC-10 hematology analyzer (Mindray, Germany) was used to perform complete blood counts.</p>
            </sec>
            <sec id="sec11">
                <title>2.5 Statistical analysis</title>
                <p>IBM SPSS software version 27.0 and GraphPad prism version 10 were used for statistical analysis. The numerical data were expressed as mean and standard deviation (&#x00b1;SD), while the categorical data were displayed as numbers and percentages. Group comparisons were performed using one-way ANOVA followed by Tukey&#x2019;s post hoc test. Pearson correlation analysis was employed to examine relationships between serum Ng levels and other measured biochemical parameters. Statistical significance was set at 
                    <italic toggle="yes">p</italic>&lt;0.05, with 
                    <italic toggle="yes">p</italic>

                    <inline-formula>

                        <mml:math display="inline">
                            <mml:mo>&#x2264;</mml:mo>
                        </mml:math>
</inline-formula>0.01 considered highly significant. Receiver operating characteristic (ROC) curve analysis was applied to distinguish ischemic stroke patients from healthy controls and to determine the diagnostic accuracy of neurogranin as a biomarker.</p>
            </sec>
        </sec>
        <sec id="sec12" sec-type="results">
            <title>3. Result</title>
            <p>The results of the present study included one hundred and thirty-six participants who were divided into three groups: n=46 in the thrombotic group, n=45 in the embolic group, and n=45 in the control group. 
                <xref ref-type="table" rid="T1">
Table 1</xref> summarizes the baseline demographic characteristics, including age ranges, numbers and percentages for sex, previous stroke, and relevant risk factors.</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>
Table 1. </label>
                <caption>
                    <title>The baseline clinical characteristics of the patients with ischemic stroke and healthy group.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Characters</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Thrombotic
                                <break/>n=46</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Embolic *Cardio embolism
                                <break/>n=45</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Control
                                <break/>n=45</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age (Range)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">40-85 years</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">45-88 years</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">40-75 years</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Gender</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Male, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">25(54.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">26(57.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">26(57.8%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Female, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21(45.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19(42.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19(42.2%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Pervious IS</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12(26.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18(40.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0(0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">No, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">34(73.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">27(60.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">45(100%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Risk factors</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HTN, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">42(91.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">37(82.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19(42.2%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DM, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">30(65.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23(51.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19(42.2%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Smoking, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16(34.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8(17.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18(40.0%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Alcohol, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1(2.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2(4.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">AF, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">36(80.0%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Others, n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8(17.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11(24.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>The results are expressed as range (minimum-maximum) or number (percentage). DM stands for Diabetes Mellitus, AF for Atrial Fibrillation, IS for ischemic stroke, HTN for hypertension.</p>
                </table-wrap-foot>
            </table-wrap>
            <p>The general clinical data and biochemical parameters for all studied groups are shown in 
                <xref ref-type="table" rid="T2">
Table 2</xref>. The Statistical ANOVA and post hoc test showed that there was a highly significant difference in systolic blood pressure (SBP) between the thrombotic group and control (156.50 vs 138.37 mmHg, 
                <italic toggle="yes">p</italic>&lt;0.01), but no discernible difference existed between the embolic and healthy groups or between the patient groups. However, the WBCs showed a highly significant difference between the thrombotic group and embolic group compared to control group (8.17 and 8.47 vs 6.61 
                <inline-formula>

                    <mml:math display="inline">
                        <mml:mo>&#x00d7;</mml:mo>
                    </mml:math>
</inline-formula> 10
                <sup>3</sup>/&#x03bc;L, 
                <italic toggle="yes">p</italic>&lt;0.01). In contrast, RBCs, Hb, and platelets showed that were not any significant differences between the three groups. In comparison to the embolic and healthy groups, the embolic group&#x2019;s the mean of serum random blood sugar (RBS) was noticeably higher (11.00 vs 8.4 and 7.67 mmol/l, 
                <italic toggle="yes">p</italic>&lt;0.01). Moreover, the mean of serum total cholesterol showed a highly significant difference between the thrombotic group and control group (198.50 vs 150.60 mg/l, 
                <italic toggle="yes">p</italic>&lt;0.01) and a significant difference between the embolic group and control (177.27 vs 150.60 mg/l, 
                <italic toggle="yes">p</italic>&lt;0.05). The mean of serum TG level showed a highly significant difference in the thrombotic group and embolic group compared to control group (226.93 and 208.24 vs 163.60 mg/l, 
                <italic toggle="yes">p</italic>&lt;0.01).</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>
Table 2. </label>
                <caption>
                    <title>Clinical and biochemical characteristics of the study groups.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Parameters</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Thrombotic
                                <break/>n=46</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Embolic *Cardio embolism
                                <break/>n=45</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Control
                                <break/>n=45</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">

                                <italic toggle="yes">p-value
</italic>
</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BMI (Kg/m
                                <sup>2</sup>)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">30.85&#x00b1;7.55
                                <xref ref-type="table-fn" rid="tfn2"/>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">31.38&#x00b1;7.20</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">28.97&#x00b1;3.57</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.175</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">SBP mmHg</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">156.50&#x00b1;24.64
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">145.62&#x00b1;22.91</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">138.37&#x00b1;20.44</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DBP mmHg</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">90.63&#x00b1;17.66</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">88.00&#x00b1;15.86</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">88.11&#x00b1;15.31</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.685</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">WBCs 
                                <inline-formula>

                                    <mml:math display="inline">
                                        <mml:mo mathvariant="bold">&#x00d7;</mml:mo>
                                    </mml:math>
</inline-formula> 10
                                <sup>3</sup>/&#x03bc;L</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.17&#x00b1;2.42
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.47&#x00b1;2.68
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>b</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.61&#x00b1;1.65</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">RBCs 
                                <inline-formula>

                                    <mml:math display="inline">
                                        <mml:mo mathvariant="bold">&#x00d7;</mml:mo>
                                    </mml:math>
</inline-formula> 10
                                <sup>6</sup>/&#x03bc;L</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.50&#x00b1;0.66</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.70&#x00b1;0.79</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.79&#x00b1;0.51</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.112</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Hb g/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12.83&#x00b1;1.76</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12.88&#x00b1;2.16</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">13.55&#x00b1;1.46</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.114</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Platelets 
                                <inline-formula>

                                    <mml:math display="inline">
                                        <mml:mo mathvariant="bold">&#x00d7;</mml:mo>
                                    </mml:math>
</inline-formula> 10
                                <sup>3</sup>/&#x03bc;L</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">233.19&#x00b1;84.46</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">223.80&#x00b1;94.46</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">229.88&#x00b1;59.19</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.854</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">RBS mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.00&#x00b1;4.29
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a,c</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.41&#x00b1;3.27
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>c</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.67&#x00b1;2.89</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">TC mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">198.50&#x00b1;48.06
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">177.27&#x00b1;53.76
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                                <sup>b</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">150.60&#x00b1;32.03</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">TG mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">226.93&#x00b1;63.84
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">208.24&#x00b1;93.18
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>b</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">163.13&#x00b1;30.70</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HDL mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">35.78&#x00b1;11.72
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a,</sup>
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                                <sup>c</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">29.03&#x00b1;10.87
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>b,</sup>
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                                <sup>c</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">53.55&#x00b1;12.87</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">vLDL mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">45.38&#x00b1;12.76
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">41.64&#x00b1;18.63
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>b</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">32.62&#x00b1;6.14</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">LDL mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">117.33&#x00b1;43.81
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">106.58&#x00b1;45.60
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>b</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">63.58&#x00b1;29.95</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Ca mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.15&#x00b1;0.16</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.15&#x00b1;0.25</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.15&#x00b1;0.11</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.989</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Na
                                <sup>+</sup> mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">135.53&#x00b1;6.80
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">136.22&#x00b1;5.05
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>b</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">141.06&#x00b1;2.47</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cl
                                <sup>-</sup> mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">103.77&#x00b1;4.01</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">104.06&#x00b1;4.17</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">103.97&#x00b1;2.61</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.927</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">K
                                <sup>+</sup> mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.94&#x00b1;0.50</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.92&#x00b1;0.44
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                                <sup>b</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.16&#x00b1;0.44</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.02</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">ALT u/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">15.97&#x00b1;5.67</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.08&#x00b1;6.63</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14.18&#x00b1;5.33</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.233</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">AST u/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19.46&#x00b1;8.17</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23.02&#x00b1;15.79</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18.17&#x00b1;4.57</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.083</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Urea mmol
                                <italic toggle="yes">/</italic>l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.95&#x00b1;2.40</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.88&#x00b1;2.54</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.06&#x00b1;0.94</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.098</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Creatinine &#x03bc;mol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">70.23&#x00b1;21.50</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">75.88&#x00b1;26.10</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">68.60&#x00b1;12.90</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.226</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">D.dimer ng/ml</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3905.45&#x00b1;1745.84
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a,c</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6036.30&#x00b1;2941.49
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>b,c</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">285.36&#x00b1;133.40</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Ng ng/ml</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.464&#x00b1;0.121
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>a,c</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.600&#x00b1;0.339
                                <xref ref-type="table-fn" rid="tfn2">**</xref>
                                <sup>b,c</sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.304&#x00b1;0.065</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>ANOVA test was used to compare between the three groups, and the results are presented as the mean&#x00b1;SD.</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn1">
                            <label>*</label>
                            <p>Statistically significant differences at p&lt; 0.05.</p>
                        </fn>
                        <fn id="tfn2">
                            <label>**</label>
                            <p>Statistically highly significant differences at p&#x2264;0.01, 
                                <sup>a</sup> denotes to significant differences between thrombotic group &amp; control. 
                                <sup>b</sup> denotes significant differences between the embolic and control groups. 
                                <sup>c</sup> denotes significant differences between thrombotic and embolic groups. BMI = body mass index; SBP = Systolic Blood Pressure; DBP = Diastolic Blood Pressure; WBC = white blood cell; RBC = red blood cell; Hb = hemoglobin; RBS = Random blood sugar; TC = total cholesterol; TG = triglyceride; HDL = high-density lipoprotein; vLDL = very low-density lipoprotein; LDL = low-density lipoprotein; Ca = calcium; Na
                                <sup>+</sup> = sodium; Cl
                                <sup>--</sup> = chloride; K
                                <sup>+</sup> = potassium; AST = aspartate aminotransferase; ALT = alanine aminotransferase; Ng = neurogranin.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>In addition, the mean of serum HDL level showed a highly significant difference in the thrombotic group and embolic group compared to the control group (35.78 and 29.03 vs 53.55 mg/ml, 
                <italic toggle="yes">p</italic>&lt;0.01), and a significant difference between the thrombotic and embolic groups (35.78 vs 29.03, 
                <italic toggle="yes">p</italic>&lt;0.05). Similarly, by comparing the means of very low-density lipoprotein (vLDL) and low-density lipoprotein (LDL), there were a significantly increased in thrombotic and embolic stroke patients compared to healthy individuals (
                <italic toggle="yes">p</italic>&lt;0.01).</p>
            <p>Therefore, the Sodium (Na
                <sup>+</sup>) was significantly higher in the control group compared to the patients groups (
                <italic toggle="yes">p</italic>&lt;0.01). In addition, potassium (K
                <sup>+</sup>) showed a significant difference increased in the control group compared to that in the embolic group (4.16 vs 3.92 mmol/l, 
                <italic toggle="yes">p</italic>= 0.02). Furthermore, the mean of serum D-dimer level was showed a high significantly different between the thrombotic group and embolic group compared to that in the control group (3905.45 and 6036.30 vs 285.36 ng/ml, 
                <italic toggle="yes">p</italic>&lt;0.01). As well, 
                <xref ref-type="fig" rid="f1">
Figure 1</xref> used to show that the serum Ng level in the embolic group was higher than that in the thrombotic and healthy groups.</p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>
Figure 1. </label>
                <caption>
                    <title>Serum Ng levels ng/ml across study groups.</title>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/191198/c13dba03-1400-42a0-8750-05c1222d27f4_figure1.gif"/>
            </fig>
            <p>
                <xref ref-type="table" rid="T3">
Table 3</xref> shows the Pearson correlation coefficients of serum Ng with other biochemical parameters in the thrombotic and embolic groups. Based on these results, the serum Ng level in the embolic group (cardioembolism) had a positive correlation with platelets (
                <italic toggle="yes">p</italic>=0.041), total cholesterol (TC) (
                <italic toggle="yes">p</italic>=0.021), and LDL (
                <italic toggle="yes">p</italic>=0.030). Similarly, as illustrated in 
                <xref ref-type="fig" rid="f2">
Figure 2</xref>.</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>
Table 3. </label>
                <caption>
                    <title>Pearson correlation between serum level of Ng and biochemical parameters in ischemic stroke patients groups.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="3" valign="top">Parameters</th>
                            <th align="left" colspan="4" rowspan="1" valign="top">Circulating Levels of Ng Protein ng/ml</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="2" rowspan="1" valign="top">Thrombotic
                                <break/>n=46</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">Embolic*cardio embolism
                                <break/>n=45</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">r</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">

                                <italic toggle="yes">p-value
</italic>
</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">r</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">

                                <italic toggle="yes">p-value
</italic>
</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="5" rowspan="1" valign="top">Demographic Data</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age (year)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.147</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.329</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.055</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.720</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BMI (kg/m
                                <sup>2</sup>)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.107</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.478</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.033</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.827</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">SBP mmHg</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.080</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.597</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.166</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.276</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">DBP mmHg</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.026</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.864</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.148</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.332</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="5" rowspan="1" valign="top">Hematological Parameters</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">WBCs 
                                <inline-formula>

                                    <mml:math display="inline">
                                        <mml:mo mathvariant="bold-italic">&#x00d7;</mml:mo>
                                    </mml:math>
</inline-formula>10
                                <sup>3</sup>/&#x03bc;l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.027</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.861</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.221</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.146</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">RBCs 
                                <inline-formula>

                                    <mml:math display="inline">
                                        <mml:mo mathvariant="bold-italic">&#x00d7;</mml:mo>
                                    </mml:math>
</inline-formula>10
                                <sup>6</sup>/&#x03bc;l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.118</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.435</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.102</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.506</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Hb g/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.038</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.803</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.106</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.487</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Platelets 
                                <inline-formula>

                                    <mml:math display="inline">
                                        <mml:mo mathvariant="bold-italic">&#x00d7;</mml:mo>
                                    </mml:math>
</inline-formula> 10
                                <sup>3</sup>/&#x03bc;l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.050</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.743</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.306</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.041
                                <xref ref-type="table-fn" rid="tfn3">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="5" rowspan="1" valign="top">Biochemical Parameters</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">RBS mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.225</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.133</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.226</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.135</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">TC mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.074</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.626</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.344</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.021
                                <xref ref-type="table-fn" rid="tfn3">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">TG mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.019</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.901</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.256</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.09</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HDL mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.036</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.815</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.097</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.527</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">vLDL mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.019</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.901</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.256</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.09</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">LDL mg/dl</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.066</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.663</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.324</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.030
                                <xref ref-type="table-fn" rid="tfn3">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Ca mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.010</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.948</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.097</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.527</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Na
                                <sup>+</sup> mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.184</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.220</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.020</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.897</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cl
                                <sup>-</sup> mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.108</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.476</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.078</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.609</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">K
                                <sup>+</sup> mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.243</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.103</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.003</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.983</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">D.dimer ng/ml</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.062</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.681</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.024</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.899</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">ALT u/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.133</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.380</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.168</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.271</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">AST u/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.233</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.119</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.114</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.456</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Urea mmol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.076</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.616</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.056</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.713</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Creatinine &#x03bc;mol/l</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.059</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.696</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.029</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.849</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>r = Pearson coefficient, P &gt; 0.05 = Statistically non-significant correlation.</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn3">
                            <label>*</label>
                            <p>Statistically significant correlation at P &lt; 0.05.</p>
                        </fn>
                        <fn id="tfn4">
                            <label>**</label>
                            <p>Statistically highly significant correlation at P &#x2264; 0.01.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                <label>
Figure 2. </label>
                <caption>
                    <title>Correlation analysis of serum Ng concentrations with biochemical parameters in the embolic group: (A) platelets, (B) TC = total cholesterol, (C) LDL = low-density lipoprotein.</title>
                </caption>
                <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/191198/c13dba03-1400-42a0-8750-05c1222d27f4_figure2.gif"/>
            </fig>
            <p>The Receiver Operating Characteristic (ROC) Curve of serum Ng level analysis was used to identify ischemic stroke groups (thrombotic and embolic) and to distinguish ischemic stroke patients from healthy controls. 
                <xref ref-type="table" rid="T4">
Table 4</xref> shows the comparison between the thrombotic and embolic groups. For the thrombotic group, the AUC value for Ng was 0.879, with a cut-off of 0.39991 ng/ml (
                <italic toggle="yes">p</italic>&lt;0.001) and sensitivity and specificity of 80.4% and 88.9%, respectively, with a positive predictive value (PPV) was 88.1%, a negative predictive value (NPV) was 81.6%, and an accuracy was 84.61%. For the embolic group, the AUC value for Ng was 0.897, with a cut-off of 0.34443 ng/ml (
                <italic toggle="yes">p</italic>&lt;0.001) and sensitivity and specificity of 75.6% and 100%, respectively. PPV, NPV, and accuracy were 100%, 80.4%, and 87.7%, respectively. Furthermore, 
                <xref ref-type="fig" rid="f3">
Figure 3</xref> illustrates the differences in ROC curves between both patient groups and demonstrates the overall diagnostic performance accuracy of serum Ng levels in distinguishing the thrombotic and embolic groups.</p>
            <table-wrap id="T4" orientation="portrait" position="float">
                <label>
Table 4. </label>
                <caption>
                    <title>The comparisons show between the thrombotic and embolic groups using the following parameters of AUC, SE, CI, PPV, NPV and accuracy.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Items</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Thrombotic
                                <break/>(n=46)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Embolic*cardioembolism
                                <break/>(n=45)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">AUC</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.879</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.897</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">SE</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.037</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.036</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">P-value
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">95% CI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.806-0.952</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.826-0.967</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cutoff ng/ml</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.3991</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.4443</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Sensitivity</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">80.4%</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">75.6%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Specificity</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">88.9%</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">100%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">PPV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">88.1%</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">100%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">NPN</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">81.6%</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">80.4%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Accuracy</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">84.61%</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">87.7%</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>AUC = area under the ROC curve, SE = standard error, CI = confidence interval, PPV = positive predictive value, NPV = negative predictive value.</p>
                </table-wrap-foot>
            </table-wrap>
            <fig fig-type="figure" id="f3" orientation="portrait" position="float">
                <label>
Figure 3. </label>
                <caption>
                    <title>ROC curve analysis comparing thrombotic (A) and embolic (B) stroke groups with healthy controls.</title>
                    <p>Overall model quality (C, D) illustrates model performance for serum Ng concentrations (ng/ml) in thrombotic and embolic groups, respectively, demonstrating that optimal diagnostic parameters consistently achieve AUC values above 0.5.</p>
                </caption>
                <graphic id="gr3" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/191198/c13dba03-1400-42a0-8750-05c1222d27f4_figure3.gif"/>
            </fig>
        </sec>
        <sec id="sec13" sec-type="discussion">
            <title>4. Discussion</title>
            <p>By comparing the results of this study, it was demonstrated that serum Ng concentrations were significantly elevated in patients with ischemic stroke of embolic etiology compared to those with thrombotic stroke and healthy control subjects, as shown in 
                <xref ref-type="fig" rid="f1">
Figure 1</xref>. These findings provide evidence that increased Ng concentrations in serum positively correlate with the degree of acute cerebral infarction volume. Ku&#x015f;do&#x011f;an 
                <italic toggle="yes">et al</italic>. and De Vos 
                <italic toggle="yes">et al</italic>.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>,
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> Additionally, L. Li 
                <italic toggle="yes">et al</italic>. observed elevated protein levels in the lesion area as early as 24 hours post-middle cerebral artery occlusion, which peaked at day 7, and subsequently declined progressively.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> Pohlan 
                <italic toggle="yes">et al.</italic> established a positive correlation between Ng concentration and infarct volume, which confirmed its diagnostic value in distinguishing ischemic from hemorrhagic stroke. The authors also reported that Ng phosphorylation through the PKC pathway decreased its calmodulin-binding affinity.
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> Subsequently, Gerendasy 
                <italic toggle="yes">et al</italic>. explained that unphosphorylated Ng maintains a high binding capacity to CaM, thereby decreasing intracellular calcium availability.
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> These results agree with the findings of the current study, which demonstrated that elevated levels of unphosphorylated Ng corresponded to reduced intracellular calcium concentrations. To further characterize the relationship between Ng and other clinical parameters, we performed comprehensive biochemical analysis. The statistical tests showed that concentrations of Ng, urea, creatinine, ALT, AST, Hb, and platelets (
                <xref ref-type="table" rid="T2">
Table 2</xref>) have a highly significant difference in the patient groups compared to healthy individuals. These findings were consistent with Ozensoy 
                <italic toggle="yes">et al</italic>.
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup> Additionally
                <bold>,
</bold> Canturk 
                <italic toggle="yes">et al.</italic>
 reported that serum Ng, WBC, and sodium levels showed highly significant differences in patient groups compared to controls.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> In the current study, however, while Ng and WBCs (
                <xref ref-type="table" rid="T2">
Table 2</xref>) findings were consistent with those of Canturk 
                <italic toggle="yes">et al</italic>., serum sodium levels were paradoxically increased in control subjects compared to patient groups. Moreover, the Pearson correlation coefficient of serum Ng with other biochemicals showed a positive correlation with platelets, TC, and LDL in the embolic group (
                <xref ref-type="table" rid="T3">
Table 3</xref>), as shown in 
                <xref ref-type="fig" rid="f2">
Figure 2</xref>. Consequently, this study provides the first evidence of a correlation between Ng and these biomarkers in patients with ischemic stroke, thereby addressing a previously unexplored gap in stroke biomarker research and establishing a foundation for future investigations. However, in ROC curve analysis, Faraggi 
                <italic toggle="yes">et al</italic>. found that the AUC of any biomarker parameter can be classified as follows: 0.90-1.00, excellent; 0.80-0.90, good; 0.70-0.80, fair; 0.60-0.70, poor and 0.50-0.60 failing,
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup> in the current study, the AUC of serum Ng in the thrombotic and embolic groups was AUC (0.879 and 0.897, respectively). This means that Ng is an excellent biomarker parameter to be used for diagnosis and to distinguish patients with ischemic stroke, as illustrated in 
                <xref ref-type="fig" rid="f3">
Figure 3</xref>. Additionally, the cut-off values in the thrombotic and embolic groups were (0.3991 and 0.4443 ng/ml, respectively) with a sensitivity and specificity of (80.4% and 88.9%, respectively) in the thrombotic group, while in the embolic (cardioembolism) group they were (75.6% and 100%, respectively), as illustrated in 
                <xref ref-type="table" rid="T4">
Table 4</xref>. These findings were consistent with those reported by Ku&#x015f;do&#x011f;an 
                <italic toggle="yes">et al</italic>.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
            </p>
            <p>Overall, the results obtained from the conducted questionnaire showed that cardiac conditions, such as myocardial infarction, heart failure, and atrial fibrillation were among the most significant contributors to embolic ischemic stroke in our cohort (
                <xref ref-type="table" rid="T1">
Table 1</xref>). These results are consistent with established literature demonstrating a strong association between cardiac comorbidities and cerebrovascular events.
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup> In contrast, thrombotic stroke is primarily associated with metabolic syndrome and atherosclerotic vascular diseases. Metabolic syndrome, characterized by high blood pressure (HBP), insulin resistance, obesity, and dyslipidemia, contributes to cerebrovascular pathology through distinct inflammatory and vascular mechanisms. This syndrome promotes a chronic pro-inflammatory state characterized by elevated levels of tumor necrosis factor-alpha (TNF-&#x03b1;), which weakens endothelial function and increases BBB permeability. HBP and dyslipidemia accelerate atherosclerotic changes in the cerebral vasculature, compromising neuronal and glial perfusion. Progressive atherosclerosis induces chronic cerebral hypoxia, whereas TNF-&#x03b1;-mediated glutamate dysregulation triggers excitotoxic neuronal injury. The resulting energy deficit leads to mitochondrial dysfunction, oxidative stress, lipid peroxidation, and ultimately neuronal apoptosis.
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup> These damaged neurons lead to the release of intracellular proteins, including Ng, into the bloodstream, thereby providing a biomarker of neuronal injury. Moreover, our analysis revealed that modifiable risk factors, such as hypertension, diabetes mellitus, smoking, alcohol consumption, obesity, and lifestyle (physical inactivity)&#x2014;represent critical targets for preventive interventions. In contrast, Non-modifiable factors, such as age, sex, and previous stroke, were significant predictors of increased stroke risk. As these factors cannot be modified, their presence in patients emphasizes the critical importance of early identification and effective management of controllable risk factors to reduce stroke risk and optimize prevention strategies. These findings are consistent with those reported by Murphy 
                <italic toggle="yes">et al.</italic> and Nindrea 
                <italic toggle="yes">et al.</italic>
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>,
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup>
            </p>
        </sec>
        <sec id="sec14" sec-type="conclusion">
            <title>5. Conclusion</title>
            <p>Our findings indicate that serum Ng levels suggest that it can be used as a successful diagnostic tool for AIS patients during the early stages of the disease. The performance was better in the embolic group, which may be due to the larger infarct size. Moreover, Ng levels demonstrated positive correlations with several biomarker parameters that may improve the diagnostic efficiency of Ng, specifically platelets, TC, and LDL, in the embolic group. Furthermore, having had a previous stroke is a factor that can help to identify individuals at the highest risk of recurrent ischemic stroke.</p>
        </sec>
    </body>
    <back>
        <sec id="sec17" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec18">
                <title>Underlying data</title>
                <p>Figshare Repository: Serum Neurogranin as a Diagnostic Biomarker for Acute Ischemic Stroke: Performance Comparison Between Thrombotic and Embolic subtypes, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.30664889.v1">https://doi.org/10.6084/m9.figshare.30664889.v1</ext-link>.
                    <sup>
                        <xref ref-type="bibr" rid="ref17">17</xref>
                    </sup>
                </p>
                <p>This dataset contains the following underlying data:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Data excel sheet F1000Research.exsl</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>The values use for build graphs F1000Research.docx</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>The values use for description data F1000Research.docx</p>
                        </list-item>
                    </list>
                </p>
            </sec>
            <sec id="sec19">
                <title>Extended data</title>
                <p>Figshare Repository: Serum Neurogranin as a Diagnostic Biomarker for Acute Ischemic Stroke: Performance Comparison Between Thrombotic and Embolic subtypes, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.30664889.v1">https://doi.org/10.6084/m9.figshare.30664889.v1</ext-link>.
                    <sup>
                        <xref ref-type="bibr" rid="ref17">17</xref>
                    </sup>
                </p>
                <p>This dataset contains the following underlying data:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Esthetics committee biochemical.pdf</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Informed consent form.pdf</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Questionnaire stroke.pdf</p>
                        </list-item>
                    </list>
                </p>
            </sec>
            <sec id="sec20">
                <title>Reporting guidelines</title>
                <p>Figshare Repository: Serum Neurogranin as a Diagnostic Biomarker for Acute Ischemic Stroke: Performance Comparison Between Thrombotic and Embolic subtypes, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.30664889.v1">https://doi.org/10.6084/m9.figshare.30664889.v1</ext-link>.
                    <sup>
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                </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>
        </sec>
        <ack>
            <title>Acknowledgement</title>
            <p>For their invaluable help in patient recruitment clinical assessment and sample collection, the authors would like to thank the neurology departments at all participating centers, physicians, nurses, and laboratory staff for their invaluable assistance in patient recruitment. Finally, we would like to sincerely thank all of the patients who voluntarily participated in this study.</p>
        </ack>
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                    <year>2018</year>;<volume>11</volume>(<issue>4</issue>):<fpage>369</fpage>&#x2013;<lpage>374</lpage>.</mixed-citation>
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                    <article-title>Namir IA Haddad, and Essam Nori, Correlation between Albuminuria Levels and Chitinase 3 like 1 Protein in Iraqi Patients with Type 2 Diabetes Mellitus.</article-title>
                    <source>

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                    <year>2022</year>;<volume>63</volume>(<issue>1</issue>):<fpage>21</fpage>&#x2013;<lpage>32</lpage>.
                    <pub-id pub-id-type="doi">10.24996/ijs.2022.63.1.3</pub-id>
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    </back>
    <sub-article article-type="reviewer-report" id="report474639">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.191198.r474639</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Al-Saeed</surname>
                        <given-names>Hassan H.</given-names>
                    </name>
                    <xref ref-type="aff" rid="r474639a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r474639a1">
                    <label>1</label>Collage of Medicine/Al-Nahrain University, Baghdad, Iraq</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>27</day>
                <month>4</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Al-Saeed HH</copyright-statement>
                <copyright-year>2026</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="relatedArticleReport474639" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.173387.1"/>
            <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>The manuscript addresses an important and clinically relevant topic: the identification of serum neurogranin (Ng) as a diagnostic biomarker in acute ischemic stroke (AIS), with subtype differentiation (thrombotic vs embolic). This is a worthwhile research direction, especially given the ongoing need for rapid, minimally invasive biomarkers in stroke triage.</p>
            <p> The focus on neurogranin, a postsynaptic protein linked to neuronal injury, is biologically plausible and aligns with BBB disruption mechanisms.</p>
            <p> The attempt to differentiate thrombotic vs embolic stroke adds translational value.</p>
            <p> The reported AUC values (0.88&#x2013;0.90) suggest potentially strong diagnostic performance.</p>
            <p> The study demonstrates promising preliminary findings, but there are some observations regarding the research. 
                <list list-type="order">
                    <list-item>
                        <p>The researchers did not specify the time duration for drawing blood samples from patients after an acute stroke.</p>
                    </list-item>
                    <list-item>
                        <p>Using a wide age range can confounders some of the results obtained, especially those related to lipid profile even for the same group, for example.</p>
                    </list-item>
                    <list-item>
                        <p>Figure 1 lack in detailed legends and clarity</p>
                    </list-item>
                    <list-item>
                        <p>Use of Pearson correlation without testing normality</p>
                    </list-item>
                    <list-item>
                        <p>multivariate regression analysis should be performed, because there were major stroke-related confounders are present, such as hypertension and diabetes, so Ng elevation may reflect confounding variables rather than independent diagnostic value</p>
                    </list-item>
                    <list-item>
                        <p>The authors conclude Ng is a successful diagnostic parameter. This is overstated because no comparison with established biomarkers for brain damage such as Neuron-Specific Enolase )NSE(, and S100B.</p>
                    </list-item>
                    <list-item>
                        <p>The researchers did not use a ROC curve to discriminate between ng levels in the thrombotic and embolic acute stoke to extract the cutoff value, nor did they use a d-dimer in the ROC curve for comparison with Ng.</p>
                    </list-item>
                </list>
            </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>Partly</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>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Biochemistry/ Clinical Biochemistry</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-type="response" id="comment16263-474639">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Saleh</surname>
                            <given-names>Tiba</given-names>
                        </name>
                        <aff>Chemistry, University of Baghdad, Baghdad, Iraq</aff>
                    </contrib>
                </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>21</day>
                    <month>5</month>
                    <year>2026</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <list list-type="order">
                        <list-item>
                            <p>Thank you for your comment. We have added the blood collection time (6&#x2013;12 hours from symptom onset) to section 2.1. Research subject of the revised manuscript.</p>
                        </list-item>
                        <list-item>
                            <p>We appreciate the reviewer's thoughtful comment. The wide age range (40-88 years) in our study reflects the clinical reality of acute ischemic stroke, which affects a broad age spectrum in our patient population. importantly, we ensured that all three groups (thrombotic, embolic, and control) were age-matched with no statistically significant differences in age distribution (Table 2). We used age as a matching variable, not as the outcome variable, with respect to considering it as one of the non-modifiable risk factors. Regarding lipid profiles, while age may influence lipid levels, our analysis focused on the relationship between Ng and stroke subtypes. The correlations we observed (Table 3) were specific to the embolic subtype. We agree that future studies with narrower age stratification could provide additional insights into age-specific biomarker performance.</p>
                        </list-item>
                        <list-item>
                            <p>Thank you for your comment. We have added more details to the legend of Figure 1, including group names, error bars (SD), and statistical significance indicators (** for p
                                <italic>&#x2264;</italic>0.01).</p>
                        </list-item>
                        <list-item>
                            <p>Thank you for your comment. We have added the Shapiro-Wilk test for normality to the Statistical analysis section.</p>
                        </list-item>
                        <list-item>
                            <p>We have performed multivariate binary logistic regression analysis to distinguish stroke patients from healthy controls after adjusting for hypertension and diabetes. Serum Ng remained significantly associated with stroke (p &lt; 0.01), confirming its independent diagnostic value beyond these confounders (see Table 5).</p>
                        </list-item>
                        <list-item>
                            <p>Thank you for your comment. We have modified our conclusion, changing "successful" to "promising", and we have added a limitation that we did not compare Ng with other established brain damage biomarkers. This has been added to the end discussion section.</p>
                        </list-item>
                        <list-item>
                            <p>We appreciate the reviewer's interest in exploring Ng's potential for subtype differentiation. We would like to respectfully, briefly clarify the methodological rationale for our analytical approach: 
                                <list list-type="order">
                                    <list-item>
                                        <p>
                                            <bold>Regarding ROC analysis methodologically,</bold> the ROC curve analysis is designed to assess diagnostic or prognostic performance by discriminating between diseased and non-diseased populations. The fundamental principle of ROC analysis requires a binary outcome (disease present vs. disease absent) to evaluate a biomarker's ability to correctly classify individuals into these distinct categories. Performing ROC analysis to discriminate between two disease subtypes (thrombotic vs. embolic stroke) would be mathematically inappropriate for the following reasons: 1) Both groups are diseased - there is no "reference negative" group against which sensitivity and specificity can be meaningfully calculated. 2) ROC curves measure diagnostic accuracy - separating patients from non-patients, not differentiating between disease mechanisms within a patient population.
                                            <bold> </bold>
                                        </p>
                                    </list-item>
                                    <list-item>
                                        <p>
                                            <bold>Regarding</bold> 
                                            <bold>D-dimer</bold> 
                                            <bold>comparison:</bold> While we appreciate this suggestion, D-dimer and Ng represent fundamentally different biological processes. D-dimer reflects systemic thrombosis and is non-specific (elevated in MI, PE, DVT, infection, surgery). Ng is neuron-specific and reflects acute synaptic injury. Direct ROC comparison would be methodologically inappropriate&#x2014;analogous to comparing troponin with D-dimer in myocardial infarction. Both are useful but measure different disease aspects. We agree that multi-biomarker panels combining neuronal injury markers (Ng) with thrombotic markers (D-dimer) represent a valuable future research direction.</p>
                                    </list-item>
                                </list> </p>
                        </list-item>
                    </list>
                </p>
            </body>
        </sub-article>
    </sub-article>
</article>
