{"paper_id":"366ba553-76fe-48c3-a8d7-3c18d5262056","body_text":"Single cell profiling of transcriptomic changes during in vitro maturation of human oocytes | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Single cell profiling of transcriptomic changes during in vitro maturation of human oocytes Hiroki Takeuchi, Mari Yamamoto, Megumi Fukui, Tadashi Maezawa, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-292144/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 In vitro maturation of human oocytes is widely used for infertility treatment. However, the success rate of maturation varies depending on patients and molecular mechanisms underlying successful maturation remain unclear. Especially, gene expression profiles of oocytes at each maturation stage need to be revealed to understand the differential developmental abilities of oocytes. Here, we show transcriptomes of human oocytes during in vitro maturation by single cell RNA-seq analyses. Hundreds of transcripts dynamically altered their expression, and we identify molecular pathways and upstream regulators that may govern oocyte maturation. Furthermore, oocytes that are delayed in their maturation show distinct transcriptomes. Finally, we reveal genes whose transcripts are enriched in each maturation stage and that can be used for selecting an oocyte with a high developmental potential. Taken together, our work uncovers transcriptomic changes during human oocyte maturation and provides a molecular insight into the differential developmental potential of each oocyte. Developmental Biology Human oocyte Single cell RNA-sequencing Oocyte maturation Transcriptome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Full Text Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the latest manuscript can be downloaded and accessed as a PDF. Additional Declarations No competing interests reported. Supplementary Files Supplementaryinformation.pdf TableS1.xlsx TableS2.xlsx TableS3.xlsx TableS4.xlsx TableS5.xlsx TableS6.xlsx TableS7.xlsx TableS8.xlsx TableS9.xlsx TableS10.xlsx 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies 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-292144\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":15052474,\"identity\":\"a9aa78a0-5c0c-471f-b116-63289315e0f7\",\"order_by\":0,\"name\":\"Hiroki Takeuchi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Mie University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Hiroki\",\"middleName\":\"\",\"lastName\":\"Takeuchi\",\"suffix\":\"\"},{\"id\":15052475,\"identity\":\"005dbf28-942b-43b2-bf6a-9d85316d9b43\",\"order_by\":1,\"name\":\"Mari Yamamoto\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Kindai University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mari\",\"middleName\":\"\",\"lastName\":\"Yamamoto\",\"suffix\":\"\"},{\"id\":15052476,\"identity\":\"486fa018-9280-4a11-8f56-864322ee0dfd\",\"order_by\":2,\"name\":\"Megumi Fukui\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Mie University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Megumi\",\"middleName\":\"\",\"lastName\":\"Fukui\",\"suffix\":\"\"},{\"id\":15052477,\"identity\":\"2dfbfdd4-f10f-4bda-88df-da731b515419\",\"order_by\":3,\"name\":\"Tadashi Maezawa\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Mie University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Tadashi\",\"middleName\":\"\",\"lastName\":\"Maezawa\",\"suffix\":\"\"},{\"id\":15052478,\"identity\":\"b21e2485-eb0d-4745-880a-3e043158ef32\",\"order_by\":4,\"name\":\"Mikiko Nishioka\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Mie University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mikiko\",\"middleName\":\"\",\"lastName\":\"Nishioka\",\"suffix\":\"\"},{\"id\":15052479,\"identity\":\"ea404d81-1068-4239-801c-698ab77df33d\",\"order_by\":5,\"name\":\"Eiji Kondo\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Mie University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Eiji\",\"middleName\":\"\",\"lastName\":\"Kondo\",\"suffix\":\"\"},{\"id\":15052480,\"identity\":\"80b24fbe-af27-4dda-a167-426fe4765b35\",\"order_by\":6,\"name\":\"Tomoaki Ikeda\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Mie University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Tomoaki\",\"middleName\":\"\",\"lastName\":\"Ikeda\",\"suffix\":\"\"},{\"id\":15052481,\"identity\":\"86face2b-e432-4eca-953f-51f8c655b952\",\"order_by\":7,\"name\":\"Kazuya Matsumoto\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Kindai University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kazuya\",\"middleName\":\"\",\"lastName\":\"Matsumoto\",\"suffix\":\"\"},{\"id\":15052482,\"identity\":\"57c0c742-c879-4a14-9c03-9f39fb1812c5\",\"order_by\":8,\"name\":\"Kei Miyamoto\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIie2Qv0oDQRCH5zjRKqlnOY2vkBCIEQ+f5ZbAbmNsbIMsBFL5pxPEl7hqWw8WNs3BtStW12ijcGUsAu55wSp7Yie4HwyzDHzMbxbA4/mDIASi7j2AXdsytNVMwp+U4W+UBioaZVNtkDu1wI+zmKdLTSvIx+fdpRKwmsHekUOJIrog15JN05wpBIMXJKciuNIQHovtSs8q2JFqKjMuECqkaWZDdgSEfUfCWiFrqfioeJ2vvpSiFMG6RamDRXZLMjJM18FoaqgI27aQBzo/OZBs8Ghe2DjJkd6bUqh9jc5b8JmXT+8yPiS3bGgqfUlvCl6Wb7N44voxyw5+P5NNt5Fw0ncrYbV1fNqieDwez//iEx3DZDyviWcWAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Kindai University\",\"correspondingAuthor\":true,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kei\",\"middleName\":\"\",\"lastName\":\"Miyamoto\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2021-03-03 00:59:04\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-292144/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-292144/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":7039810,\"identity\":\"cf61e143-a308-4387-b8ff-4f18a3a169a5\",\"added_by\":\"auto\",\"created_at\":\"2021-03-17 00:17:30\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":251601,\"visible\":true,\"origin\":\"\",\"legend\":\"Transcriptomic changes of human oocytes during in vitro maturation. a A schematic diagram of human oocyte retrieval for single cell RNA-seq analyses. Ten oocytes were collected from 7 patients. b Representative images of human oocytes at different maturation stages. The bottom panels show higher magnification images of the regions indicated in the top panels by dashed boxes. DNA was stained by DAPI. Scale bars represent 20 μm for whole oocyte images and 10 μm for enlarged images. c PCA of the gene expression profiles (3-4 biological replicates per each maturation stage). Blue dots: GV samples, Orange dots: MI samples, and Green dots: MII samples. d Hierarchical clustering dendrogram generated using the gene expression profiles of human oocytes at different maturation stages. Spearman correlation was used. e, f Heatmaps depicting the gene expression levels of DEGs identified in the indicated comparisons. Color key with z-score is shown. (e) shows upregulated genes in MI (GV vs MI), MII (MI vs MII), and MII (GV vs MII) samples, while (f) indicates downregulated genes in the same comparisons. g Heatmaps depicting the gene expression levels of Tubulin-related and myosin-related genes. GV; oocytes at the germinal vesicle stage, MI; maturating oocytes at the metaphase I stage, MII; oocytes at the metaphase II stage.\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-292144/v1/cdada3631ec5273bcccfb86d.png\"},{\"id\":7039813,\"identity\":\"bbb2348e-25ce-479c-9f6d-b7e9e1c6704b\",\"added_by\":\"auto\",\"created_at\":\"2021-03-17 00:17:30\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":375060,\"visible\":true,\"origin\":\"\",\"legend\":\"Gene regulatory networks that are associated with dynamic transcriptome changes during human oocyte maturation. a Canonical pathways predicted by IPA using the DEG list of GV vs MI or GV vs MII. Significant terms are indicated in red colors: darker the color more significant the term is (P \\u003c 0.05, Fisher's exact test). Closely related terms are connected to each other. A green arrow indicates Sirtuin signaling pathway as explained in the relevant text. b Downstream targets of AKT were found in the DEG list by IPA. Gene regulatory networks of AKT in human oocytes were predicted. c Downstream targets of HIF1A were found in the DEG list by IPA. Blue arrows mean ‘Leads to inhibition’, orange arrows mean ‘Leads to activation’, a yellow arrow means ‘Inconsistent with state of downstream molecules’, black arrows mean ‘Effect not predicted’. Molecules colored green, red and blue show ‘downregulated’, ‘upregulated’, and ‘predicted inhibition’, respectively.\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-292144/v1/ed5073d6001753a0f1cfaf74.png\"},{\"id\":7039855,\"identity\":\"7f8ae75a-b5ff-433d-a093-da20746f607e\",\"added_by\":\"auto\",\"created_at\":\"2021-03-17 00:20:30\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":324113,\"visible\":true,\"origin\":\"\",\"legend\":\"Human oocytes that are delayed in their maturation show different transcriptomes from those matured in an earlier timing. a PCA of the gene expression profiles (3-4 biological replicates per each category). The top left image in the rectangle includes samples collected on the day for oocyte retrieval (Fig. 1a) (GV, MI and MII). Nine delayed oocytes were collected from 7 patients. Blue dots: GV samples, light blue dots: MI samples, dark orange dots: MII samples, light orange dots: dGV samples, dark green dots: dMI samples, and light green dots: dMII samples. b, c Heatmaps depicting the gene expression levels of DEGs identified in the indicated comparisons. (b) shows upregulated genes in dGV (GV vs dGV), dMI (MI vs dMI), and dMII (MII vs dMII) samples, while (c) indicates downregulated genes in the same comparisons. Color key with z-score is shown. dGV; oocytes that were at the germinal vesicle stage the day after oocyte retrieval, dMI; oocytes that were at the metaphase I\\n545 stage the day after oocyte retrieval, dMII; oocytes that were at the metaphase II stage the day after ocyte retrieval.\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-292144/v1/0d412f82ce169afce496f50c.png\"},{\"id\":7039854,\"identity\":\"1100b664-b596-410a-8a41-0cecdcbec512\",\"added_by\":\"auto\",\"created_at\":\"2021-03-17 00:20:30\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":116641,\"visible\":true,\"origin\":\"\",\"legend\":\"Gene regulatory networks are altered in the human oocytes that are delayed in their maturation. a Canonical pathways predicted by IPA using the DEG list of MII vs dMII. Significant terms are indicated in red colors: darker the color more significant the term is (P \\u003c 0.05, Fisher's exact test). Closely related terms are connected to each other. A green arrow indicates Sirtuin signaling pathway as explained in the relevant text. b Downstream targets of SMARCA4 were found in the DEG list by IPA. Gene regulatory networks of SMARCA4 in human oocytes were predicted. SMARCA4 affects molecules indicated at the end of arrows, blue arrows mean ‘Leads to inhibition’, black arrows mean ‘Effect not predicted’. Molecules colored green, red and blue show ‘downregulated’, ‘upregulated’, and ‘predicted inhibition’, respectively.\",\"description\":\"\",\"filename\":\"4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-292144/v1/5949b9c166b51d9c62b32c30.png\"},{\"id\":7039819,\"identity\":\"585899b1-1e1a-4ec3-8778-2f97f99917d6\",\"added_by\":\"auto\",\"created_at\":\"2021-03-17 00:17:31\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":233619,\"visible\":true,\"origin\":\"\",\"legend\":\"Gene regulatory networks that are altered in different patients. a, b Heatmaps depicting the gene expression levels of DEGs identified in the indicated comparisons. (a) shows upregulated genes in MII2 (MII1 vs MII2), MII3 (MII2 vs MII3), and MII1 (MII3 vs MII1) samples, while (b) indicates downregulated genes in the same comparisons. Color key with z-score is shown. c Canonical pathways predicted by IPA using the DEG list of MII1 vs MII2 or MII1 vs MII3. Significant terms are indicated in red colors: darker the color more significant the term is (P \\u003c 0.05, Fisher's exact test). Closely related terms are connected to each other. Green arrows indicate commonly misregulated pathways.\",\"description\":\"\",\"filename\":\"5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-292144/v1/d07d4a191e68c92293274abd.png\"},{\"id\":7039822,\"identity\":\"5603e455-1d30-4f79-bb0d-5a02109a8121\",\"added_by\":\"auto\",\"created_at\":\"2021-03-17 00:17:31\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":187044,\"visible\":true,\"origin\":\"\",\"legend\":\"Marker genes for human GV and MII oocytes and potential biomarkers for MII oocyteswith high quality. a A heatmap of gene expression levels after clustering based on expression patterns. Twenty clusters were generated and clusters 5, 9, 12, and 16 are indicated. Color key indicates log2FC(FoldChange). b Venn diagrams showing the numbers of total and overlapping genes among genes that belong to cluster 5, upregulated genes in the GV vs MI comparison, and upregulated genes in the GV vs MII comparison. c Venn diagrams showing the numbers of total and overlapping genes among genes that belong to clusters 9, 12, and 16, upregulated genes in the GV vs MII comparison, and upregulated genes in the MI vs MII comparison. d A heatmap depicting the gene expression levels of candidate genes for human MII oocytes with high quality. Gene symbols are listed. Color key with z-score is shown. \",\"description\":\"\",\"filename\":\"6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-292144/v1/d255dff4ca6d27b99d96ff2b.png\"},{\"id\":13608041,\"identity\":\"36357330-ece5-4c87-957a-33d5fce0f8a6\",\"added_by\":\"auto\",\"created_at\":\"2021-09-17 06:14:32\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1742705,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-292144/v1_covered.pdf\"},{\"id\":7039974,\"identity\":\"a37d59d6-3fa4-4a9d-b84b-e101c051f777\",\"added_by\":\"auto\",\"created_at\":\"2021-03-17 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maturation of human oocytes\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"Full Text\",\"content\":\"Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the latest manuscript can be downloaded and \\u003ca href='/article/rs-292144/latest.pdf' target='_blank'\\u003e accessed as a PDF.\\u003c/a\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":false,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":true,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"Human oocyte, Single cell RNA-sequencing, Oocyte maturation, Transcriptome \",\"lastPublishedDoi\":\"10.21203/rs.3.rs-292144/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-292144/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"In vitro maturation of human oocytes is widely used for infertility treatment. However, the success rate of maturation varies depending on patients and molecular mechanisms underlying successful maturation remain unclear. Especially, gene expression profiles of oocytes at each maturation stage need to be revealed to understand the differential developmental abilities of oocytes. Here, we show transcriptomes of human oocytes during in vitro maturation by single cell RNA-seq analyses. Hundreds of transcripts dynamically altered their expression, and we identify molecular pathways and upstream regulators that may govern oocyte maturation. Furthermore, oocytes that are delayed in their maturation show distinct transcriptomes. Finally, we reveal genes whose transcripts are enriched in each maturation stage and that can be used for selecting an oocyte with a high developmental potential. Taken together, our work uncovers transcriptomic changes during human oocyte maturation and provides a molecular insight into the differential developmental potential of each oocyte.\",\"manuscriptTitle\":\"Single cell profiling of transcriptomic changes during in vitro maturation of human oocytes\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2021-03-17 00:17:27\",\"doi\":\"10.21203/rs.3.rs-292144/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"b43e2294-c4a1-41a3-97cf-b045c0a40019\",\"owner\":[],\"postedDate\":\"March 17th, 2021\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":3021080,\"name\":\"Developmental Biology\"}],\"tags\":[],\"updatedAt\":\"2021-03-31T05:29:10+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2021-03-17 00:17:27\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-292144\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-292144\",\"identity\":\"rs-292144\",\"version\":[\"v1\"]},\"buildId\":\"GqpaHPwrfC8PjnIFayRh5\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}