scTELL: A Single-Cell ATAC-seq Tool for Locus-Specific Transposable Element Identification in Chromatin Accessibility

scTELL: A Single-Cell ATAC-seq Tool for Locus-Specific Transposable Element Identification in Chromatin Accessibility | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Method Article scTELL: A Single-Cell ATAC-seq Tool for Locus-Specific Transposable Element Identification in Chromatin Accessibility Kyeonghun Jeong, Hongseok Ha, Jinchuan Xing, Jinwook Choi, Kwangsoo Kim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6574738/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Transposable elements (TEs) are essential genomic entities that play the roles of eukaryotic genome regulators and are involved in controlling gene expression patterns, cell-type specialization, and diseases. Recent improvements of single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) have enhanced the chromatin accessibility investigation with cell type specificity. However, existing techniques do not address the locus-specific activity of TEs. Here, we present scTELL (single-cell Transposable Element Locus-Level analysis), a bioinformatics tool for the analysis of TE accessibility at the single-cell level. Based on the distribution of scATAC-seq peaks, scTELL enablesusers with the ability to analyze the locus-specific TE activity in relation to cellular heterogeneity as well as changes in regulatory dynamics occurring across different samples. Through scTELL, we mapped TEs in both quiescent healthy peripheral blood mononuclear cells (PBMC) and in cancer cells: clear cell renal cell carcinoma (ccRCC) and breast cancer (BRCA), defining cell type-specific and tumor-specific TE groups. L1PA2 expression in ccRCC consistently exhibited the locus-specific pattern and predicted cancer progression and patient survival. Likewise, in BRCA, scTELL identified prognostic TE loci whose accessibility profiles are associated with patient survival. These results reveal that TEs can alter tumor heterogeneity and point to TEs as a prognostic factor. The scTELL framework provides a new way of determining the regulatory roles of TEs in various biological settings and improving the knowledge of the role of TEs in both normal and pathological cellular conditions. Figures Figure 1 Figure 2 Figure 3 Figure 4 Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.xlsx Jeongetal.SupplementaryFigS1.pdf Supplementary Figure S1. Cell type-specific activity scores of known marker genes in PBMCs. UMAP visualization of activity scores (log 2 -transformed normalized counts) for known marker genes used in cell type annotation of PBMC samples: MS4A1 (B cells), MAL (naive CD4⁺ T cells), CD8A (CD8⁺ T cells), FLT3 (dendritic cells), and NCR1 (NK cells). Each panel highlights expression enrichment in distinct clusters corresponding to specific immune cell types, serving as validation of the manual cell type annotations performed in this study. Jeongetal.SupplementaryFigS2.pdf Supplementary Figure S2. Cell-type-specific activity of LTR2B loci across PBMC populations. UMAP projections showing the normalized activity of selected LTR2B loci that exhibit distinct enrichment patterns across specific immune cell types. aIn B cells, loci such as chr1:247639458-247639957(-), chr12:9865526-9865858(-), and chr19:42022622-42023127(-) display strong activity. b In CD8⁺ T cells, activity is concentrated at chr6:130581267-130581755(+). cMonocyte-enriched loci include chr7:134856015-134856493(+), chr17:27220612-27221082(+), and chr19:55470072-55470495(-). These visualizations expand upon the representative examples provided in Fig. 2e and offer a broader view of the locus-specific activity landscape of LTR2B elements within the PBMC dataset, underscoring their differential regulation across immune lineages. Jeongetal.SupplementaryFigS3.pdf Supplementary Figure S3. Prognostic value of a tumor-specific SVA-F locus in ccRCC. Kaplan-Meier survival analysis using TCGA-KIRC ATAC-seq data indicates that lower accessibility at the SVA-F locus chr8:9153426-9154908(-) is significantly associated with poorer PFI in clear cell renal cell carcinoma (Log-rank p-value = 0.017). This suggests a potential functional or regulatory role of the locus in ccRCC tumor heterogeneity and prognosis. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6574738","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Method Article","associatedPublications":[],"authors":[{"id":452701351,"identity":"9e1793ae-cbe1-4ff2-aa53-9b7f68fe956f","order_by":0,"name":"Kyeonghun Jeong","email":"","orcid":"","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Kyeonghun","middleName":"","lastName":"Jeong","suffix":""},{"id":452701352,"identity":"3095b47e-ca78-4270-8ee7-47758b6cc6e3","order_by":1,"name":"Hongseok Ha","email":"","orcid":"","institution":"Seoul National University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hongseok","middleName":"","lastName":"Ha","suffix":""},{"id":452701353,"identity":"5f6de014-3adb-454f-bc80-953a447155b6","order_by":2,"name":"Jinchuan Xing","email":"","orcid":"","institution":"Rutgers, The State University of New Jersey","correspondingAuthor":false,"prefix":"","firstName":"Jinchuan","middleName":"","lastName":"Xing","suffix":""},{"id":452701354,"identity":"c17f13e4-4656-435f-81de-13f33dc5b0dc","order_by":3,"name":"Jinwook Choi","email":"","orcid":"","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Jinwook","middleName":"","lastName":"Choi","suffix":""},{"id":452701355,"identity":"4dea338a-edae-4ed2-b01a-597f5a56c13f","order_by":4,"name":"Kwangsoo Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACCTiDmYHxAZTNTLQWZgMStTAwsME4+LVIzkh+9vDLHxs5yXbutMqfOw4z8LcfYDauwKNFWiLN3Fi2Lc1Ympl3223eM4cZJM4kMCeewaNFTjrBTFqy4XDiPJAWxrbDDAw3GJgPNuDVkv5NWuIPREvhT6AWeUJapKVzzCQ/sB1OnA3UwsAL1GIA1JKIT4vk/Ddl0oxAv0g2826W5m1L5zE8k9hsiE+LxJnj2yR/AENM4vzZjR9/tlnLyR0/fFgSnxYQYOZB4gDZjIQ0AJX8IKhkFIyCUTAKRjQAACYFRiwgsIAFAAAAAElFTkSuQmCC","orcid":"","institution":"Seoul National University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Kwangsoo","middleName":"","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2025-05-02 01:23:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6574738/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6574738/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82311545,"identity":"03570ec6-2b2e-4d1c-9d91-bf7c2d6be5cc","added_by":"auto","created_at":"2025-05-09 01:56:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":46314,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverview of the scTELL framework for locus-specific TE activity analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e Schematic of the weighted accessibility scoring system used by scTELL to quantify chromatin accessibility at TE loci using single-cell ATAC-seq data. Scores are derived from reads within 5 kb upstream and downstream regions of the TE loci, with fragments closer to the locus receiving higher weights. \u003cstrong\u003eb\u003c/strong\u003e Diagram illustrating the weighted scoring model, where fragments closer to the TE locus receive higher weights, with the upstream region given the highest weight due to its potential regulatory role in TE activity via promoters. Fragments further from the locus receive reduced weights to concentrate the scoring on critical regions. \u003cstrong\u003ec\u003c/strong\u003eAggregated TE locus accessibility matrix summarizing TE activity across single-cell data for downstream analyses. \u003cstrong\u003ed \u003c/strong\u003eWorkflow for cluster-centric, cluster-free, and bulk ATAC-seq validation approaches used to analyze TE loci across single cells and confirm findings with bulk data.\u003c/p\u003e","description":"","filename":"Jeongetal.Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-6574738/v1/0540d6c430a33da418131674.png"},{"id":82311894,"identity":"5d7a7eff-0fbc-4f82-a7df-3caba9430d99","added_by":"auto","created_at":"2025-05-09 02:04:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":287165,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification and functional characterization of cell-type-specific LTR elements in PBMCs using scATAC-seq data.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e Proportion of selected LTR families from RepeatMasker data mapped to peaks from single-cell ATAC-seq datasets. \u003cstrong\u003eb\u003c/strong\u003e UMAP plot showing PBMC subtypes annotated by overlaying FACS-sorted bulk ATAC-seq data onto the single-cell data. \u003cstrong\u003ec\u003c/strong\u003e Heatmap displaying cell type-specific segregation of LTR families, highlighting differences across blood cell subtypes. \u003cstrong\u003ed \u003c/strong\u003eChromosomal ideogram showing the distribution of monocyte-specific ERVL-MaLR loci across chromosomes, with colors representing differential accessibility significance and genomic LTR element density. \u003cstrong\u003ee\u003c/strong\u003e UMAP plots showing B cell (or CD8\u003csup\u003e+\u003c/sup\u003e T cells or monocytes) specific activity of different LTR2B loci with. \u003cstrong\u003ef\u003c/strong\u003e Enrichment of transcription factor (TF) motifs for CD4\u003csup\u003e+\u003c/sup\u003e T cells, CD8\u003csup\u003e+\u003c/sup\u003e T cells, B cells, monocytes, and NK cells near cell-type-specific LTR loci. \u003cstrong\u003eg\u003c/strong\u003e Correlation between single-cell and bulk chromatin accessibility at LTR loci, validating the findings with FACS-sorted bulk ATAC-seq data.\u003c/p\u003e","description":"","filename":"Jeongetal.Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-6574738/v1/f584dc8fe0959e6a6d9a19be.png"},{"id":82311893,"identity":"7d77913e-a07c-486a-a991-54110dd485fd","added_by":"auto","created_at":"2025-05-09 02:04:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":320931,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTumor-specific TE loci in clear cell renal cell carcinoma (ccRCC).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea, b\u003c/strong\u003e UMAP plots of ccRCC samples in Discovery and Validation datasets, showing distinct cell clusters. \u003cstrong\u003ec\u003c/strong\u003e Heatmap of cell-type-specific TE loci across ccRCC samples. \u003cstrong\u003ed, e\u003c/strong\u003e Discovery and Validation datasets highlighting the tumor-specific activity of the L1PA2 locus (chr20:8595101-8601127) in ccRCC. \u003cstrong\u003ef \u003c/strong\u003eCoverage plots showing ccRCC-specific chromatin accessibility upstream of the L1PA2 locus, localized within an intron of the PLCB1 gene. \u003cstrong\u003eg\u003c/strong\u003e Survival analysis using TCGA-ATAC KIRC data, demonstrating lower progression-free survival (PFI) for patients with high accessibility at the L1PA2 locus (Log-rank p = 0.038). \u003cstrong\u003eh \u003c/strong\u003eUMAP analysis showing intertumoral heterogeneity of ccRCC cells, with separate clusters formed for individual patients.\u003c/p\u003e","description":"","filename":"Jeongetal.Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-6574738/v1/59a58dda840ac1d7b4cbaa50.png"},{"id":82311551,"identity":"ba16d268-427b-4533-9a8d-151ebfb38504","added_by":"auto","created_at":"2025-05-09 01:56:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":240512,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTE loci and inter-patient heterogeneity in breast cancer (BRCA).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e UMAP plot displaying distinct clustering patterns of TE loci across 24 BRCA patient samples using a cluster-free analysis approach. b. heatmap \u003cstrong\u003ec\u003c/strong\u003e Identification of six prognostic TE loci associated with overall survival using singleCellHaystack analysis. \u003cstrong\u003ed\u003c/strong\u003eKaplan-Meier survival analysis showing that low accessibility at the identified TE loci correlates with reduced overall survival in BRCA patients.\u003c/p\u003e","description":"","filename":"Jeongetal.Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-6574738/v1/8479c7cfa7a8fece8f7da685.png"},{"id":83072464,"identity":"285c5380-ebab-4e50-a2d7-194af7a0167a","added_by":"auto","created_at":"2025-05-19 17:01:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1479213,"visible":true,"origin":"","legend":"","description":"","filename":"JeongetalManuscriptCLEANGenomeBiology.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6574738/v1_covered_08e65627-ac77-4f1b-8840-ef3c084398ef.pdf"},{"id":82311546,"identity":"cff9bda2-f8af-4358-a606-1c3f5e69bc7e","added_by":"auto","created_at":"2025-05-09 01:56:41","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14827,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6574738/v1/47b181c98b9d804f9deb9c25.xlsx"},{"id":82311895,"identity":"5ac9c9a2-efff-49e0-982f-e52d55fbda4f","added_by":"auto","created_at":"2025-05-09 02:04:41","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1405097,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure S1. Cell type-specific activity scores of known marker genes in PBMCs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUMAP visualization of activity scores (log\u003csub\u003e2\u003c/sub\u003e-transformed normalized counts) for known marker genes used in cell type annotation of PBMC samples: MS4A1 (B cells), MAL (naive CD4⁺ T cells), CD8A (CD8⁺ T cells), FLT3 (dendritic cells), and NCR1 (NK cells). Each panel highlights expression enrichment in distinct clusters corresponding to specific immune cell types, serving as validation of the manual cell type annotations performed in this study.\u003c/p\u003e","description":"","filename":"Jeongetal.SupplementaryFigS1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6574738/v1/16e976dd305aba327a5f686d.pdf"},{"id":82311556,"identity":"69e4ca33-61ad-476f-b56e-332f3430b47e","added_by":"auto","created_at":"2025-05-09 01:56:41","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1974254,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure S2. Cell-type-specific activity of LTR2B loci across PBMC populations.\u003c/strong\u003e\u003cbr\u003e\nUMAP projections showing the normalized activity of selected LTR2B loci that exhibit distinct enrichment patterns across specific immune cell types. \u003cstrong\u003ea\u003c/strong\u003eIn B cells, loci such as chr1:247639458-247639957(-), chr12:9865526-9865858(-), and chr19:42022622-42023127(-) display strong activity. \u003cstrong\u003eb\u003c/strong\u003e In CD8⁺ T cells, activity is concentrated at chr6:130581267-130581755(+). \u003cstrong\u003ec\u003c/strong\u003eMonocyte-enriched loci include chr7:134856015-134856493(+), chr17:27220612-27221082(+), and chr19:55470072-55470495(-). These visualizations expand upon the representative examples provided in Fig. 2e and offer a broader view of the locus-specific activity landscape of LTR2B elements within the PBMC dataset, underscoring their differential regulation across immune lineages.\u003c/p\u003e","description":"","filename":"Jeongetal.SupplementaryFigS2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6574738/v1/ae5146766c7e1dd77ee63e85.pdf"},{"id":82312393,"identity":"7b77527a-7e7d-4ef3-9bdd-02ae19b6bea7","added_by":"auto","created_at":"2025-05-09 02:12:42","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":436886,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure S3. Prognostic value of a tumor-specific SVA-F locus in ccRCC.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKaplan-Meier survival analysis using TCGA-KIRC ATAC-seq data indicates that lower accessibility at the SVA-F locus chr8:9153426-9154908(-) is significantly associated with poorer PFI in clear cell renal cell carcinoma (Log-rank p-value = 0.017). This suggests a potential functional or regulatory role of the locus in ccRCC tumor heterogeneity and prognosis.\u003c/p\u003e","description":"","filename":"Jeongetal.SupplementaryFigS3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6574738/v1/bf9ca65fd514587c96712989.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"scTELL: A Single-Cell ATAC-seq Tool for Locus-Specific Transposable Element Identification in Chromatin Accessibility","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6574738/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6574738/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTransposable elements (TEs) are essential genomic entities that play the roles of eukaryotic genome regulators and are involved in controlling gene expression patterns, cell-type specialization, and diseases. Recent improvements of single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) have enhanced the chromatin accessibility investigation with cell type specificity. However, existing techniques do not address the locus-specific activity of TEs. Here, we present scTELL (single-cell Transposable Element Locus-Level analysis), a bioinformatics tool for the analysis of TE accessibility at the single-cell level. Based on the distribution of scATAC-seq peaks, scTELL enablesusers with the ability to analyze the locus-specific TE activity in relation to cellular heterogeneity as well as changes in regulatory dynamics occurring across different samples. Through scTELL, we mapped TEs in both quiescent healthy peripheral blood mononuclear cells (PBMC) and in cancer cells: clear cell renal cell carcinoma (ccRCC) and breast cancer (BRCA), defining cell type-specific and tumor-specific TE groups. L1PA2 expression in ccRCC consistently exhibited the locus-specific pattern and predicted cancer progression and patient survival. Likewise, in BRCA, scTELL identified prognostic TE loci whose accessibility profiles are associated with patient survival. These results reveal that TEs can alter tumor heterogeneity and point to TEs as a prognostic factor. The scTELL framework provides a new way of determining the regulatory roles of TEs in various biological settings and improving the knowledge of the role of TEs in both normal and pathological cellular conditions.\u003c/p\u003e","manuscriptTitle":"scTELL: A Single-Cell ATAC-seq Tool for Locus-Specific Transposable Element Identification in Chromatin Accessibility","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 01:56:36","doi":"10.21203/rs.3.rs-6574738/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a5d90043-0d1a-4fb2-bdf6-3702c2e33246","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-19T03:53:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 01:56:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6574738","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6574738","identity":"rs-6574738","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}