{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:14:35Z","timestamp":1772118875013,"version":"3.50.1"},"reference-count":100,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T00:00:00Z","timestamp":1756339200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000968","name":"AHA","doi-asserted-by":"publisher","award":["25CDA1451814"],"award-info":[{"award-number":["25CDA1451814"]}],"id":[{"id":"10.13039\/100000968","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Proteins"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>The exponential growth of biomedical and life sciences literature, including research on amyloid biology, has made it increasingly challenging to track new discoveries and gain a comprehensive understanding of the evolution of specific research fields. Advances in natural language models (NLM) and artificial intelligence (AI) approaches now enable large\u2010scale analysis of scientific publications, uncovering hidden patterns and facilitating data\u2010driven insights. Here, a two\u2010dimensional mapping of the global amyloid research landscape is presented, using the transformer\u2010based large language model PubMedBERT, in combination with t\u2010SNE and Latent Dirichlet Allocation (LDA), to analyze more than 140\u2009000 abstracts from the PubMed database. This analysis provides a comprehensive visualization of the amyloid field, capturing key trends such as the historical progression of amyloid research, the emergence of dominant subfields, the distribution of contributing authors and their respective countries, and the identification of latent research topics over time, including chemicals and small molecules. By integrating AI\u2010driven text analysis with large\u2010scale bibliometric data, this study offers a novel perspective on the evolution of amyloid research, facilitating a deeper interdisciplinary understanding. This work serves as a valuable interactive resource for researchers while highlighting the potential of machine learning\u2010driven literature mapping in identifying knowledge gaps and guiding future investigations.<\/jats:p>","DOI":"10.1002\/prot.70048","type":"journal-article","created":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T12:04:36Z","timestamp":1756382676000},"page":"660-671","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Evolving Landscape of Amyloid Research"],"prefix":"10.1002","volume":"94","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2186-8653","authenticated-orcid":false,"given":"Bernardo","family":"Bonilauri","sequence":"first","affiliation":[{"name":"Stanford Cardiovascular Institute Stanford University School of Medicine  Stanford California USA"},{"name":"Department of Medicine, Division of Cardiology Stanford University School of Medicine  Stanford California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,8,28]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1046\/j.1365\u20102141.2001.02999.x"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41580\u2010018\u20100060\u20108"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1006\/jsbi.2000.4221"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmb.2018.07.010"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/smll.202304031"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1074\/jbc.M109.047449"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature02261"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.biochem.75.101304.123901"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrm3810"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3458754"},{"issue":"86","key":"e_1_2_11_12_1","first-page":"2579","article-title":"Visualizing Data Using t\u2010SNE","volume":"9","author":"Maaten L.","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patter.2024.100968"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1162\/jmlr.2003.3.4-5.993"},{"key":"e_1_2_11_15_1","first-page":"2825","article-title":"Scikit\u2010Learn: Machine Learning in Python","volume":"12","author":"Pedregosa F.","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.6b00207"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkv1031"},{"key":"e_1_2_11_18_1","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkad976"},{"issue":"138","key":"e_1_2_11_19_1","first-page":"380","article-title":"On the Course of the Amyloid Degeneration","volume":"12","author":"Virchow R.","year":"1856","journal-title":"Medical Examination Review"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.1.957.659"},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.1177\/095952876705000105"},{"key":"e_1_2_11_22_1","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"e_1_2_11_23_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.172.3988.1150"},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.174.4010.712"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.76.8.4092"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/0014\u20105793(71)80506\u20109"},{"key":"e_1_2_11_27_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.74.9.4025"},{"key":"e_1_2_11_28_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.75.9.4499"},{"key":"e_1_2_11_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/0006\u2010291x(85)91948\u20105"},{"key":"e_1_2_11_30_1","doi-asserted-by":"publisher","DOI":"10.1172\/JCI111390"},{"key":"e_1_2_11_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/0006\u2010291X(81)90764\u20106"},{"key":"e_1_2_11_32_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.83.2.503"},{"key":"e_1_2_11_33_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.6801762"},{"key":"e_1_2_11_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/0092\u20108674(83)90168\u2010x"},{"key":"e_1_2_11_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0006\u2010291X(84)80190\u20104"},{"key":"e_1_2_11_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/0140\u20106736(93)93127\u2010M"},{"issue":"2","key":"e_1_2_11_37_1","first-page":"403","article-title":"Systemic Amyloidosis in Transgenic Mice Carrying the Human Mutant Transthyretin (Met30) Gene. 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