{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T19:31:18Z","timestamp":1793043078531,"version":"4.5.0"},"reference-count":30,"publisher":"The Mass Spectrometry Society of Japan","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mass Spectrometry"],"published-print":{"date-parts":[[2025,5,28]]},"DOI":"10.5702\/massspectrometry.a0174","type":"journal-article","created":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T22:08:29Z","timestamp":1748038109000},"page":"A0174-A0174","source":"Crossref","is-referenced-by-count":3,"title":["An Effective Approach to Mass Spectrometry Imaging Data Partitioning Using UMAP and k-Means Clustering"],"prefix":"10.5702","volume":"14","author":[{"given":"Shinichi","family":"Yamaguchi","sequence":"first","affiliation":[{"name":"Shimadzu Corporation"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masaya","family":"Ikegawa","sequence":"additional","affiliation":[{"name":"Department of Medical Life Systems, Faculty of Life and Medical Sciences, Doshisha University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"3680","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"1) I. Markovi\u0107, I. Luki\u0107, M. Luki\u0107, E. Pavi\u010di\u0107, S. Mr\u0111enovi\u0107, A. Kotris, B. Dmitrovi\u0107, \u017d Debeljak. Differentiation of the chronic lymphocytic leukemia response to ibrutinib and acalabrutinib treatment by single-cell MALDI-TOF MS imaging. <i>J. Pharm. Biomed. Anal.<\/i> 255: 116664, 2025.","DOI":"10.1016\/j.jpba.2025.116664"},{"key":"2","doi-asserted-by":"crossref","unstructured":"2) P. Chen, B. Chen, M. He, Y. Zhou, L. Lei, J. Han, B. Zhou, L. Hu, B. Hu. Nanoplastics and nano-ZnO facilitate Cd accumulation in zebrafish larvae <i>via<\/i> a distinct pathway: Revelation by LA-ICP-MS imaging. <i>Chin. Chem. Lett.<\/i> 36: 109908, 2025.","DOI":"10.1016\/j.cclet.2024.109908"},{"key":"3","doi-asserted-by":"crossref","unstructured":"3) J. Doungchawee, L. J. Castellanos-Garc\u00eda, K. N. Sikora, X. Zhang, Y. Liu, D. K. Agrohia, T. Jantarat, J. D. Lauterbach, V. M. Rotello, R. W. Vachet. Mass spectrometry imaging reveals that gold nanomaterial surface chemistry affects transport and excretion in mice over time. <i>Chemical &amp; Biomedical Imaging<\/i>: 4c0082, 2025.","DOI":"10.1021\/cbmi.4c00082"},{"key":"4","doi-asserted-by":"crossref","unstructured":"4) P. Geladi, B. Sethson, J. Nystr\u00f6m, T. Lillhonga, T. Lestander, J. Burger. Chemometrics in spectroscopy: Part 2. Examples. <i>Spectrochim. Acta B At. Spectrosc.<\/i> 59: 1347\u20131357, 2004.","DOI":"10.1016\/S0584-8547(04)00167-3"},{"key":"5","doi-asserted-by":"crossref","unstructured":"5) P. Geladi. Chemometrics in spectroscopy. Part 1. Classical chemometrics. <i>Spectrochim. Acta B At. Spectrosc.<\/i> 58: 767\u2013782, 2003.","DOI":"10.1016\/S0584-8547(03)00037-5"},{"key":"6","doi-asserted-by":"crossref","unstructured":"6) P. Geladi, K. Esbensen. Can image analysis provide information useful in chemistry? <i>J. Chemometr.<\/i> 3: 419\u2013429, 1989.","DOI":"10.1002\/cem.1180030209"},{"key":"7","doi-asserted-by":"crossref","unstructured":"7) P. Geladi, H. Grahn. in Multivariate Analysis in the Pharmaceutical Industry, Elsevier, 2018, pp. 13\u201334.","DOI":"10.1016\/B978-0-12-811065-2.00003-5"},{"key":"8","doi-asserted-by":"crossref","unstructured":"8) P. Geladi, H. Grahn, K. Esbensen, E. Bengtsson. Image analysis in chemistry II. Multivariate image analysis. <i>Trends Analyt. Chem.<\/i> 11: 121\u2013130, 1992.","DOI":"10.1016\/0165-9936(92)85010-3"},{"key":"9","unstructured":"9) P. Geladi, H. F. Grahn. Multivariate Image Analysis, R. A. Meyers, John Wiley &amp; Sons Ltd, Hoboken, New Jersey, USA, 2006."},{"key":"10","doi-asserted-by":"crossref","unstructured":"10) P. Geladi, H. Grahn, K. H. Esbensen. in Partial Least Squares Path Modeling (Ed: H. Latan, R. Noonan), Springer International Publishing, Cham, 2017, pp. 339\u2013365.","DOI":"10.1007\/978-3-319-64069-3_16"},{"key":"11","doi-asserted-by":"crossref","unstructured":"11) P. Fragu, J. Clerc, C. Brian\u00e7on, C. Fourr\u00e9, J. Jeusset, S. Halpern. Recent developments in medical applications of SIMS microscopy. <i>Micron<\/i> 25: 361\u2013370, 1994.","DOI":"10.1016\/0968-4328(94)90005-1"},{"key":"12","doi-asserted-by":"crossref","unstructured":"12) P. Fragu, C. Brian\u00e7on, C. Fourr\u00e9, J. Clerc, O. Casiraghi, J. Jeusset, F. Omri, S. Halpern. SIMS microscopy in the biomedical field. <i>Biol. Cell<\/i> 74: 5\u201318, 1992.","DOI":"10.1016\/0248-4900(92)90004-K"},{"key":"13","doi-asserted-by":"crossref","unstructured":"13) J. S. Becker, M. V. Zoriy, C. Pickhardt, N. Palomero-Gallagher, K. Zilles. Imaging of copper, zinc, and other elements in thin section of human brain samples (hippocampus) by laser ablation inductively coupled plasma mass spectrometry. <i>Anal. Chem.<\/i> 77: 3208\u20133216, 2005.","DOI":"10.1021\/ac040184q"},{"key":"14","doi-asserted-by":"crossref","unstructured":"14) J. S. Becker, M. V. Zoriy, M. Dehnhardt, C. Pickhardt, K. Zilles. Copper, zinc, phosphorus and sulfur distribution in thin section of rat brain tissues measured by laser ablation inductively coupled plasma mass spectrometry: Possibility for small-size tumor analysis. <i>J. Anal. At. Spectrom.<\/i> 20: 912\u2013917, 2005.","DOI":"10.1039\/b504978b"},{"key":"15","doi-asserted-by":"crossref","unstructured":"15) M. V. Zoriy, M. Dehnhardt, G. Reifenberger, K. Zilles, J. S. Becker. Imaging of Cu, Zn, Pb and U in human brain tumor resections by laser ablation inductively coupled plasma mass spectrometry. <i>Int. J. Mass Spectrom.<\/i> 257: 27\u201333, 2006.","DOI":"10.1016\/j.ijms.2006.06.005"},{"key":"16","doi-asserted-by":"crossref","unstructured":"16) R. M. Caprioli, T. B. Farmer, J. Gile. Molecular imaging of biological samples: Localization of peptides and proteins using MALDI-TOF MS. <i>Anal. Chem.<\/i> 69: 4751\u20134760, 1997.","DOI":"10.1021\/ac970888i"},{"key":"17","doi-asserted-by":"crossref","unstructured":"17) R. W. Garden, J. V. Sweedler. Heterogeneity within MALDI samples as revealed by mass spectrometric imaging. <i>Anal. Chem.<\/i> 72: 30\u201336, 2000.","DOI":"10.1021\/ac9908997"},{"key":"18","doi-asserted-by":"crossref","unstructured":"18) S. A. Schwartz, R. J. Weil, M. D. Johnson, S. A. Toms, R. M. Caprioli. Protein profiling in brain tumors using mass spectrometry: Feasibility of a new technique for the analysis of protein expression. <i>Clin. Cancer Res.<\/i> 10: 981\u2013987, 2004.","DOI":"10.1158\/1078-0432.CCR-0927-3"},{"key":"19","doi-asserted-by":"crossref","unstructured":"19) J. M. Fonville, C. L. Carter, L. Pizarro, R. T. Steven, A. D. Palmer, R. L. Griffiths, P. F. Lalor, J. C. Lindon, J. K. Nicholson, E. Holmes, J. Bunch. Hyperspectral visualization of mass spectrometry imaging data. <i>Anal. Chem.<\/i> 85: 1415\u20131423, 2013.","DOI":"10.1021\/ac302330a"},{"key":"20","unstructured":"20) L. van der Maaten, G. Hinton. Visualizing data using t-SNE. <i>J. Mach. Learn. Res.<\/i> 9: 2579\u20132605, 2008"},{"key":"21","doi-asserted-by":"crossref","unstructured":"21) L. McInnes, J. Healy, J. Melville. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. 2018.","DOI":"10.21105\/joss.00861"},{"key":"22","doi-asserted-by":"crossref","unstructured":"22) T. Smets, T. De Keyser, T. Tousseyn, E. Waelkens, B. De Moor. Correspondence-aware manifold learning for microscopic and spatial omics imaging: A novel data fusion method bringing mass spectrometry imaging to a cellular resolution. <i>Anal. Chem.<\/i> 93: 3452\u20133460, 2021.","DOI":"10.1021\/acs.analchem.0c04759"},{"key":"23","doi-asserted-by":"crossref","unstructured":"23) T. Smets, N. Verbeeck, M. Claesen, A. Asperger, G. Griffioen, T. Tousseyn, W. Waelput, E. Waelkens, B.  De Moor. Evaluation of distance metrics and spatial autocorrelation in uniform manifold approximation and projection applied to mass spectrometry imaging data. <i>Anal. Chem.<\/i> 91: 5706\u20135714, 2019.","DOI":"10.1021\/acs.analchem.8b05827"},{"key":"24","doi-asserted-by":"crossref","unstructured":"24) T. Smets, E. Waelkens, B.  De Moor. Prioritization of <i>m\/z<\/i>-values in mass spectrometry imaging profiles obtained using uniform manifold approximation and projection for dimensionality reduction. <i>Anal. Chem.<\/i> 92: 5240\u20135248, 2020.","DOI":"10.1021\/acs.analchem.9b05764"},{"key":"25","doi-asserted-by":"crossref","unstructured":"25) W. Wu, J. Hou, Z. Zhang, F. Li, R. Zhang, L. Gao, H. Ni, T. Zhang, H. Long, M. Lei, B. Shen, J. Yan, R. Huang, Z. Zeng, W. Wu. Information entropy-based strategy for the quantitative evaluation of extensive hyperspectral images to better unveil spatial heterogeneity in mass spectrometry imaging. <i>Anal. Chem.<\/i> 94: 10355\u201310366, 2022.","DOI":"10.1021\/acs.analchem.2c00370"},{"key":"26","doi-asserted-by":"crossref","unstructured":"26) L. Guo, X. Liu, C. Zhao, Z. Hu, X. Xu, K. K. Cheng, P. Zhou, Y. Xiao, M. Shah, J. Xu, J. Dong, Z. Cai. iSegMSI: An interactive strategy to improve spatial segmentation of mass spectrometry imaging data. <i>Anal. Chem.<\/i> 94: 14522\u201314529, 2022.","DOI":"10.1021\/acs.analchem.2c01456"},{"key":"27","doi-asserted-by":"crossref","unstructured":"27) T. Alexandrov. MALDI imaging mass spectrometry: Statistical data analysis and current computational challenges. <i>BMC Bioinformatics<\/i> 13(Suppl 16): S11, 2012.","DOI":"10.1186\/1471-2105-13-S16-S11"},{"key":"28","doi-asserted-by":"crossref","unstructured":"28) H. Hu, R. Yin, H. M. Brown, J. Laskin. Spatial segmentation of mass spectrometry imaging data by combining multivariate clustering and univariate thresholding. <i>Anal. Chem.<\/i> 93: 3477\u20133485, 2021.","DOI":"10.1021\/acs.analchem.0c04798"},{"key":"29","doi-asserted-by":"crossref","unstructured":"29) Y. Tsuji, S. Yamaguchi, T. Nakamura, M. Ikegawa. Mass spectrometry imaging (MSI) delineates thymus-centric metabolism <i>in vivo<\/i> as an effect of systemic administration of dexamethasone. <i>Appl. Sci. (Basel)<\/i> 11: 11038, 2021.","DOI":"10.3390\/app112211038"},{"key":"30","doi-asserted-by":"crossref","unstructured":"30) C. Guijas, J. R. Montenegro-Burke, X. Domingo-Almenara, A. Palermo, B. Warth, G. Hermann, G. Koellensperger, T. Huan, W. Uritboonthai, A. E. Aisporna, D. W. Wolan, M. E. Spilker, H. P. Benton, G. Siuzdak. METLIN: A technology platform for identifying knowns and unknowns. <i>Anal. Chem.<\/i> 90: 3156\u20133164, 2018.","DOI":"10.1021\/acs.analchem.7b04424"}],"container-title":["Mass Spectrometry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/massspectrometry\/14\/1\/14_A0174\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T04:39:52Z","timestamp":1748666392000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/massspectrometry\/14\/1\/14_A0174\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,28]]},"references-count":30,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.5702\/massspectrometry.a0174","relation":{},"ISSN":["2186-5116","2187-137X"],"issn-type":[{"value":"2186-5116","type":"electronic"},{"value":"2187-137X","type":"print"}],"subject":[],"published":{"date-parts":[[2025,5,28]]},"article-number":"A0174"}}