{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T16:45:23Z","timestamp":1778690723692,"version":"3.51.4"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100019188","name":"HORIZON EUROPE Excellent Science","doi-asserted-by":"publisher","award":["GA 812830"],"award-info":[{"award-number":["GA 812830"]}],"id":[{"id":"10.13039\/100019188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100019188","name":"HORIZON EUROPE Excellent Science","doi-asserted-by":"publisher","award":["GA 812829"],"award-info":[{"award-number":["GA 812829"]}],"id":[{"id":"10.13039\/100019188","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013209","name":"HFRI","doi-asserted-by":"crossref","award":["06204"],"award-info":[{"award-number":["06204"]}],"id":[{"id":"10.13039\/501100013209","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>In fluorescence microscopy, co-localization refers to the spatial overlap between different fluorescent labels in cells. The degree of overlap between two or more channels in a microscope may reveal a physical interaction or topological functional interconnection between molecules. Recent advances in the imaging field require the development of specialized computational analysis software for the unbiased assessment of fluorescently labelled microscopy images.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Here we present SpotitPy, a semi-automated image analysis tool for 2D object-based co-localization. SpotitPy allows the user to select fluorescent labels and perform a semi-automated and robust segmentation of the region of interest in distinct cell types. The workflow integrates advanced pre-processing manipulations for de-noising and in-depth semi-automated quantification of the co-localized fluorescent labels in two different channels. We validated SpotitPy by quantitatively assessing the presence of cytoplasmic ribonucleoprotein granules, e.g. <jats:italic>processing (P) bodies,<\/jats:italic> under conditions that challenge mRNA translation, thus highlighting SpotitPy benefits for semi-automatic, accurate analysis of large image datasets in eukaryotic cells. SpotitPy comes in a command line interface or a simple graphical user interphase and can be used as a standalone application.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Overall, we present a novel and user-friendly tool that performs a semi-automated image analysis for 2D object-based co-localization. SpotitPy can provide reproducible and robust\u00a0quantifications for large datasets within a limited timeframe. The software is open-source and can be found in the GitHub project repository: (<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/alexiaales\/SpotitPy\">https:\/\/github.com\/alexiaales\/SpotitPy<\/jats:ext-link>).<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-022-04988-1","type":"journal-article","created":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T12:05:59Z","timestamp":1666353959000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["SpotitPy: a semi-automated tool for object-based co-localization of fluorescent labels in microscopy images"],"prefix":"10.1186","volume":"23","author":[{"given":"Alexia","family":"Akalestou-Clocher","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vivian","family":"Kalamara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pantelis","family":"Topalis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3200-5004","authenticated-orcid":false,"given":"George A.","family":"Garinis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,10,21]]},"reference":[{"key":"4988_CR1","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/S1387-2656(05)11007-2","volume":"11","author":"M Monici","year":"2005","unstructured":"Monici M. Cell and tissue autofluorescence research and diagnostic applications. Biotechnol Annu Rev. 2005;11:227\u201356.","journal-title":"Biotechnol Annu Rev"},{"issue":"4","key":"4988_CR2","doi-asserted-by":"publisher","first-page":"C723","DOI":"10.1152\/ajpcell.00462.2010","volume":"300","author":"KW Dunn","year":"2011","unstructured":"Dunn KW, Kamocka MM, McDonald JH. A practical guide to evaluating colocalization in biological microscopy. Am J Physiol Cell Physiol. 2011;300(4):C723-742.","journal-title":"Am J Physiol Cell Physiol"},{"key":"4988_CR3","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/j.compbiomed.2019.02.024","volume":"107","author":"A Sauvat","year":"2019","unstructured":"Sauvat A, Leduc M, Muller K, Kepp O, Kroemer G. ColocalizR: an open-source application for cell-based high-throughput colocalization analysis. Comput Biol Med. 2019;107:227\u201334.","journal-title":"Comput Biol Med"},{"issue":"1","key":"4988_CR4","doi-asserted-by":"publisher","first-page":"8879","DOI":"10.1038\/s41598-017-08786-1","volume":"7","author":"M Khushi","year":"2017","unstructured":"Khushi M, Napier CE, Smyth CM, Reddel RR, Arthur JW. MatCol: a tool to measure fluorescence signal colocalisation in biological systems. Sci Rep. 2017;7(1):8879.","journal-title":"Sci Rep"},{"issue":"1","key":"4988_CR5","doi-asserted-by":"publisher","first-page":"15764","DOI":"10.1038\/s41598-018-33592-8","volume":"8","author":"W Stauffer","year":"2018","unstructured":"Stauffer W, Sheng H, Lim HN. EzColocalization: an ImageJ plugin for visualizing and measuring colocalization in cells and organisms. Sci Rep. 2018;8(1):15764.","journal-title":"Sci Rep"},{"key":"4988_CR6","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.ymeth.2016.11.016","volume":"115","author":"JF Gilles","year":"2017","unstructured":"Gilles JF, Dos Santos M, Boudier T, Bolte S, Heck N. DiAna, an ImageJ tool for object-based 3D co-localization and distance analysis. Methods. 2017;115:55\u201364.","journal-title":"Methods"},{"issue":"3","key":"4988_CR7","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1111\/j.1365-2818.2006.01706.x","volume":"224","author":"S Bolte","year":"2006","unstructured":"Bolte S, Cordeli\u00e8res FP. A guided tour into subcellular colocalization analysis in light microscopy. J Microsc. 2006;224(3):213\u201332.","journal-title":"J Microsc"},{"key":"4988_CR8","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1016\/B978-0-12-420138-5.00021-5","volume":"123","author":"FP Cordelieres","year":"2014","unstructured":"Cordelieres FP, Bolte S. Experimenters\u2019 guide to colocalization studies: finding a way through indicators and quantifiers, in practice. Methods Cell Biol. 2014;123:395\u2013408.","journal-title":"Methods Cell Biol"},{"issue":"Pt 3","key":"4988_CR9","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1242\/jcs.103.3.857","volume":"103","author":"EM Manders","year":"1992","unstructured":"Manders EM, Stap J, Brakenhoff GJ, van Driel R, Aten JA. Dynamics of three-dimensional replication patterns during the S-phase, analysed by double labelling of DNA and confocal microscopy. J Cell Sci. 1992;103(Pt 3):857\u201362.","journal-title":"J Cell Sci"},{"issue":"6","key":"4988_CR10","doi-asserted-by":"publisher","first-page":"3993","DOI":"10.1529\/biophysj.103.038422","volume":"86","author":"SV Costes","year":"2004","unstructured":"Costes SV, Daelemans D, Cho EH, Dobbin Z, Pavlakis G, Lockett S. Automatic and quantitative measurement of protein-protein colocalization in live cells. Biophys J. 2004;86(6):3993\u20134003.","journal-title":"Biophys J"},{"issue":"Pt 4","key":"4988_CR11","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1242\/jcs.109.4.787","volume":"109","author":"B van Steensel","year":"1996","unstructured":"van Steensel B, van Binnendijk EP, Hornsby CD, van der Voort HT, Krozowski ZS, de Kloet ER, van Driel R. Partial colocalization of glucocorticoid and mineralocorticoid receptors in discrete compartments in nuclei of rat hippocampus neurons. J Cell Sci. 1996;109(Pt 4):787\u201392.","journal-title":"J Cell Sci"},{"issue":"16","key":"4988_CR12","doi-asserted-by":"publisher","first-page":"4070","DOI":"10.1523\/JNEUROSCI.0346-04.2004","volume":"24","author":"Q Li","year":"2004","unstructured":"Li Q, Lau A, Morris TJ, Guo L, Fordyce CB, Stanley EF. A syntaxin 1, G\u03b1o, and N-type calcium channel complex at a presynaptic nerve terminal: analysis by quantitative immunocolocalization. J Neurosci. 2004;24(16):4070\u201381.","journal-title":"J Neurosci"},{"issue":"10","key":"4988_CR13","doi-asserted-by":"publisher","first-page":"R100","DOI":"10.1186\/gb-2006-7-10-r100","volume":"7","author":"AE Carpenter","year":"2006","unstructured":"Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, Guertin DA, Chang JH, Lindquist RA, Moffat J, et al. Cell Profiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 2006;7(10):R100.","journal-title":"Genome Biol"},{"issue":"7","key":"4988_CR14","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1038\/nmeth.2047","volume":"9","author":"P Kankaanpaa","year":"2012","unstructured":"Kankaanpaa P, Paavolainen L, Tiitta S, Karjalainen M, Paivarinne J, Nieminen J, Marjomaki V, Heino J, White DJ. BioImageXD: an open, general-purpose and high-throughput image-processing platform. Nat Methods. 2012;9(7):683\u20139.","journal-title":"Nat Methods"},{"issue":"6","key":"4988_CR15","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1002\/cyto.a.22629","volume":"87","author":"T Lagache","year":"2015","unstructured":"Lagache T, Sauvonnet N, Danglot L, Olivo-Marin JC. Statistical analysis of molecule colocalization in bioimaging. Cytom A. 2015;87(6):568\u201379.","journal-title":"Cytom A"},{"issue":"1","key":"4988_CR16","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1186\/s13007-021-00810-w","volume":"17","author":"AK Basak","year":"2021","unstructured":"Basak AK, Mirzaei M, Strzalka K, Yamada K. Texture feature extraction from microscope images enables a robust estimation of ER body phenotype in Arabidopsis. Plant Methods. 2021;17(1):109.","journal-title":"Plant Methods"},{"issue":"Suppl 2","key":"4988_CR17","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1186\/s12859-016-1446-2","volume":"18","author":"RP Theart","year":"2017","unstructured":"Theart RP, Loos B, Niesler TR. Virtual reality assisted microscopy data visualization and colocalization analysis. BMC Bioinform. 2017;18(Suppl 2):64.","journal-title":"BMC Bioinform"},{"issue":"1","key":"4988_CR18","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1038\/s41592-020-01018-x","volume":"18","author":"C Stringer","year":"2021","unstructured":"Stringer C, Wang T, Michaelos M, Pachitariu M. Cellpose: a generalist algorithm for cellular segmentation. Nat Methods. 2021;18(1):100\u20136.","journal-title":"Nat Methods"},{"issue":"1","key":"4988_CR19","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1007\/s10278-019-00200-8","volume":"33","author":"M Kowal","year":"2020","unstructured":"Kowal M, Zejmo M, Skobel M, Korbicz J, Monczak R. Cell nuclei segmentation in cytological images using convolutional neural network and seeded watershed algorithm. J Digit Imaging. 2020;33(1):231\u201342.","journal-title":"J Digit Imaging"},{"key":"4988_CR20","first-page":"3201","volume":"2021","author":"S Lin","year":"2021","unstructured":"Lin S, Norouzi N. An effective deep learning framework for cell segmentation in microscopy images. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021:3201\u20134.","journal-title":"Annu Int Conf IEEE Eng Med Biol Soc"},{"key":"4988_CR21","unstructured":"Van Rossum G, Drake F. Python 3 reference manual, CreateSpace, Scotts Valley. In. 2009."},{"key":"4988_CR22","unstructured":"Raybaut P. Spyder-documentation. Available online at: pythonhosted org 2009."},{"issue":"2","key":"4988_CR23","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1109\/MCSE.2011.37","volume":"13","author":"S Van Der Walt","year":"2011","unstructured":"Van Der Walt S, Colbert SC, Varoquaux G. The NumPy array: a structure for efficient numerical computation. Comput Sci Eng. 2011;13(2):22\u201330.","journal-title":"Comput Sci Eng"},{"issue":"9","key":"4988_CR24","first-page":"1","volume":"14","author":"W McKinney","year":"2011","unstructured":"McKinney W. pandas: a foundational Python library for data analysis and statistics. Python High Perform Sci Comput. 2011;14(9):1\u20139.","journal-title":"Python High Perform Sci Comput"},{"key":"4988_CR25","unstructured":"Tosi S. Matplotlib for Python developers, Packt Publishing Ltd; 2009."},{"key":"4988_CR26","unstructured":"Allan D, Caswell T, Keim N, van der Wel C. Trackpy v0. 3.2. Zenodo org 2016."},{"issue":"1","key":"4988_CR27","doi-asserted-by":"publisher","first-page":"3153","DOI":"10.1038\/s41467-021-23505-1","volume":"12","author":"E Goulielmaki","year":"2021","unstructured":"Goulielmaki E, Tsekrekou M, Batsiotos N, Ascensao-Ferreira M, Ledaki E, Stratigi K, Chatzinikolaou G, Topalis P, Kosteas T, Altmuller J, et al. The splicing factor XAB2 interacts with ERCC1-XPF and XPG for R-loop processing. Nat Commun. 2021;12(1):3153.","journal-title":"Nat Commun"},{"issue":"47","key":"4988_CR28","doi-asserted-by":"publisher","first-page":"eabj5769","DOI":"10.1126\/sciadv.abj5769","volume":"7","author":"O Chatzidoukaki","year":"2021","unstructured":"Chatzidoukaki O, Stratigi K, Goulielmaki E, Niotis G, Akalestou-Clocher A, Gkirtzimanaki K, Zafeiropoulos A, Altmuller J, Topalis P, Garinis GA. R-loops trigger the release of cytoplasmic ssDNAs leading to chronic inflammation upon DNA damage. Sci Adv. 2021;7(47):eabj5769.","journal-title":"Sci Adv"},{"issue":"1","key":"4988_CR29","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1038\/s41467-019-13894-9","volume":"11","author":"E Goulielmaki","year":"2020","unstructured":"Goulielmaki E, Ioannidou A, Tsekrekou M, Stratigi K, Poutakidou IK, Gkirtzimanaki K, Aivaliotis M, Evangelou K, Topalis P, Altmuller J, et al. Tissue-infiltrating macrophages mediate an exosome-based metabolic reprogramming upon DNA damage. Nat Commun. 2020;11(1):42.","journal-title":"Nat Commun"},{"issue":"5","key":"4988_CR30","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1038\/ncb3499","volume":"19","author":"G Chatzinikolaou","year":"2017","unstructured":"Chatzinikolaou G, Apostolou Z, Aid-Pavlidis T, Ioannidou A, Karakasilioti I, Papadopoulos GL, Aivaliotis M, Tsekrekou M, Strouboulis J, Kosteas T, et al. ERCC1-XPF cooperates with CTCF and cohesin to facilitate the developmental silencing of imprinted genes. Nat Cell Biol. 2017;19(5):421\u201332.","journal-title":"Nat Cell Biol"},{"issue":"3","key":"4988_CR31","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1016\/j.cmet.2013.08.011","volume":"18","author":"I Karakasilioti","year":"2013","unstructured":"Karakasilioti I, Kamileri I, Chatzinikolaou G, Kosteas T, Vergadi E, Robinson AR, Tsamardinos I, Rozgaja TA, Siakouli S, Tsatsanis C, et al. DNA damage triggers a chronic autoinflammatory response, leading to fat depletion in NER progeria. Cell Metab. 2013;18(3):403\u201315.","journal-title":"Cell Metab"},{"issue":"8","key":"4988_CR32","doi-asserted-by":"publisher","first-page":"2995","DOI":"10.1073\/pnas.1114941109","volume":"109","author":"I Kamileri","year":"2012","unstructured":"Kamileri I, Karakasilioti I, Sideri A, Kosteas T, Tatarakis A, Talianidis I, Garinis GA. Defective transcription initiation causes postnatal growth failure in a mouse model of nucleotide excision repair (NER) progeria. Proc Natl Acad Sci U S A. 2012;109(8):2995\u20133000.","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"1","key":"4988_CR33","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1186\/s12859-019-2880-8","volume":"20","author":"T Vicar","year":"2019","unstructured":"Vicar T, Balvan J, Jaros J, Jug F, Kolar R, Masarik M, Gumulec J. Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison. BMC Bioinform. 2019;20(1):360.","journal-title":"BMC Bioinform"},{"issue":"4","key":"4988_CR34","doi-asserted-by":"publisher","first-page":"e0250093","DOI":"10.1371\/journal.pone.0250093","volume":"16","author":"F Englbrecht","year":"2021","unstructured":"Englbrecht F, Ruider IE, Bausch AR. Automatic image annotation for fluorescent cell nuclei segmentation. PLoS ONE. 2021;16(4):e0250093.","journal-title":"PLoS ONE"},{"key":"4988_CR35","doi-asserted-by":"publisher","first-page":"e453","DOI":"10.7717\/peerj.453","volume":"2","author":"S van der Walt","year":"2014","unstructured":"van der Walt S, Schonberger JL, Nunez-Iglesias J, Boulogne F, Warner JD, Yager N, Gouillart E, Yu T. scikit-image c: scikit-image: image processing in Python. PeerJ. 2014;2:e453.","journal-title":"PeerJ"},{"issue":"2","key":"4988_CR36","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1364\/BOE.413181","volume":"12","author":"M Hupfel","year":"2021","unstructured":"Hupfel M, Yu Kobitski A, Zhang W, Nienhaus GU. Wavelet-based background and noise subtraction for fluorescence microscopy images. Biomed Opt Express. 2021;12(2):969\u201380.","journal-title":"Biomed Opt Express"},{"issue":"8","key":"4988_CR37","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1016\/j.tig.2018.05.005","volume":"34","author":"N Standart","year":"2018","unstructured":"Standart N, Weil D. P-Bodies: Cytosolic droplets for coordinated mRNA storage. Trends Genet: TIG. 2018;34(8):612\u201326.","journal-title":"Trends Genet: TIG"},{"issue":"7","key":"4988_CR38","doi-asserted-by":"publisher","first-page":"2607","DOI":"10.3390\/ijms21072607","volume":"21","author":"BH Marcon","year":"2020","unstructured":"Marcon BH, Rebelatto CK, Cofre AR, Dallagiovanna B, Correa A. DDX6 helicase behavior and protein partners in human adipose tissue-derived stem cells during early adipogenesis and osteogenesis. Int J Mol Sci. 2020;21(7):2607.","journal-title":"Int J Mol Sci"},{"issue":"1","key":"4988_CR39","doi-asserted-by":"publisher","first-page":"6789","DOI":"10.1038\/s41467-021-27160-4","volume":"12","author":"PR Smith","year":"2021","unstructured":"Smith PR, Loerch S, Kunder N, Stanowick AD, Lou TF, Campbell ZT. Functionally distinct roles for eEF2K in the control of ribosome availability and p-body abundance. Nat Commun. 2021;12(1):6789.","journal-title":"Nat Commun"},{"issue":"61","key":"4988_CR40","doi-asserted-by":"publisher","first-page":"103302","DOI":"10.18632\/oncotarget.21871","volume":"8","author":"SD Hardy","year":"2017","unstructured":"Hardy SD, Shinde A, Wang WH, Wendt MK, Geahlen RL. Regulation of epithelial-mesenchymal transition and metastasis by TGF-beta, P-bodies, and autophagy. Oncotarget. 2017;8(61):103302\u201314.","journal-title":"Oncotarget"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04988-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-022-04988-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04988-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T12:06:22Z","timestamp":1666353982000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-022-04988-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,21]]},"references-count":40,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["4988"],"URL":"https:\/\/doi.org\/10.1186\/s12859-022-04988-1","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,21]]},"assertion":[{"value":"18 May 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 October 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 October 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All animal studies were approved by an independent Animal Ethical Committee at the Foundation of Research and Technology\u2014Hellas (FORTH).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not Applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"439"}}