| dc.contributor.author | Ueda, Hiroki R | |
| dc.contributor.author | Ertürk, Ali | |
| dc.contributor.author | Chung, Kwanghun | |
| dc.contributor.author | Gradinaru, Viviana | |
| dc.contributor.author | Chédotal, Alain | |
| dc.contributor.author | Tomancak, Pavel | |
| dc.contributor.author | Keller, Philipp J | |
| dc.date.accessioned | 2021-10-27T20:05:45Z | |
| dc.date.available | 2021-10-27T20:05:45Z | |
| dc.date.issued | 2020 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/134611 | |
| dc.description.abstract | © 2020, Springer Nature Limited. State-of-the-art tissue-clearing methods provide subcellular-level optical access to intact tissues from individual organs and even to some entire mammals. When combined with light-sheet microscopy and automated approaches to image analysis, existing tissue-clearing methods can speed up and may reduce the cost of conventional histology by several orders of magnitude. In addition, tissue-clearing chemistry allows whole-organ antibody labelling, which can be applied even to thick human tissues. By combining the most powerful labelling, clearing, imaging and data-analysis tools, scientists are extracting structural and functional cellular and subcellular information on complex mammalian bodies and large human specimens at an accelerated pace. The rapid generation of terabyte-scale imaging data furthermore creates a high demand for efficient computational approaches that tackle challenges in large-scale data analysis and management. In this Review, we discuss how tissue-clearing methods could provide an unbiased, system-level view of mammalian bodies and human specimens and discuss future opportunities for the use of these methods in human neuroscience. | |
| dc.language.iso | en | |
| dc.publisher | Springer Science and Business Media LLC | |
| dc.relation.isversionof | 10.1038/S41583-019-0250-1 | |
| dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| dc.source | PMC | |
| dc.title | Tissue clearing and its applications in neuroscience | |
| dc.type | Article | |
| dc.contributor.department | Massachusetts Institute of Technology. Institute for Medical Engineering & Science | |
| dc.contributor.department | Picower Institute for Learning and Memory | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Chemical Engineering | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences | |
| dc.relation.journal | Nature Reviews Neuroscience | |
| dc.eprint.version | Author's final manuscript | |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | |
| dc.date.updated | 2021-06-08T18:24:35Z | |
| dspace.orderedauthors | Ueda, HR; Ertürk, A; Chung, K; Gradinaru, V; Chédotal, A; Tomancak, P; Keller, PJ | |
| dspace.date.submission | 2021-06-08T18:24:36Z | |
| mit.journal.volume | 21 | |
| mit.journal.issue | 2 | |
| mit.license | OPEN_ACCESS_POLICY | |
| mit.metadata.status | Authority Work and Publication Information Needed | |