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Cellular and transcriptional diversity over the course of human lactation

dc.contributor.authorNyquist, Sarah K
dc.contributor.authorGao, Patricia
dc.contributor.authorHaining, Tessa KJ
dc.contributor.authorRetchin, Michael R
dc.contributor.authorGolan, Yarden
dc.contributor.authorDrake, Riley S
dc.contributor.authorKolb, Kellie
dc.contributor.authorMead, Benjamin E
dc.contributor.authorAhituv, Nadav
dc.contributor.authorMartinez, Micaela E
dc.contributor.authorShalek, Alex K
dc.contributor.authorBerger, Bonnie
dc.contributor.authorGoods, Brittany A
dc.date.accessioned2022-09-27T18:17:43Z
dc.date.available2022-09-27T18:17:43Z
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/1721.1/145591
dc.description.abstract<jats:title>Significance</jats:title> <jats:p>Human breast milk is the nutritional food source evolved specifically to meet the needs of infants, but much remains to be learned about its composition and changes over the course of lactation. Our description of the cellular components of breast milk, their associations with maternal–infant dyad metadata, and quantification of alterations at the gene and pathway levels provide a longitudinal picture of human breast milk cells across lactational time. These results pave the way for improved therapeutic support of healthy lactation and milk production.</jats:p>en_US
dc.language.isoen
dc.publisherProceedings of the National Academy of Sciencesen_US
dc.relation.isversionof10.1073/PNAS.2121720119en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePNASen_US
dc.titleCellular and transcriptional diversity over the course of human lactationen_US
dc.typeArticleen_US
dc.identifier.citationNyquist, Sarah K, Gao, Patricia, Haining, Tessa KJ, Retchin, Michael R, Golan, Yarden et al. 2022. "Cellular and transcriptional diversity over the course of human lactation." Proceedings of the National Academy of Sciences of the United States of America, 119 (15).
dc.contributor.departmentMassachusetts Institute of Technology. Computational and Systems Biology Program
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistry
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Medical Engineering & Science
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.contributor.departmentRagon Institute of MGH, MIT and Harvard
dc.contributor.departmentKoch Institute for Integrative Cancer Research at MIT
dc.relation.journalProceedings of the National Academy of Sciences of the United States of Americaen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-09-27T18:13:17Z
dspace.orderedauthorsNyquist, SK; Gao, P; Haining, TKJ; Retchin, MR; Golan, Y; Drake, RS; Kolb, K; Mead, BE; Ahituv, N; Martinez, ME; Shalek, AK; Berger, B; Goods, BAen_US
dspace.date.submission2022-09-27T18:13:20Z
mit.journal.volume119en_US
mit.journal.issue15en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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