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Akademický článek

Insights into human norovirus cultivation in human intestinal enteroids

Autor: Khalil Ettayebi, Gurpreet Kaur, Ketki Patil, Janam Dave, B. Vijayalakshmi Ayyar, Victoria R. Tenge, Frederick H. Neill, Xi-Lei Zeng, Allison L. Speer, Sara C. Di Rienzi, Robert A. Britton, Sarah E. Blutt, Sue E. Crawford, Sasirekha Ramani, Robert L. Atmar, Mary K. Estes

Publikováno v: mSphere, Vol 9, Iss 11 (2024)

ABSTRACT Human noroviruses (HuNoVs) are a significant cause of epidemic and sporadic acute gastroenteritis worldwide. The lack of a reproducible culture system hindered the study of HuNoV replication and pathogenesis for almost a half-century. This b

Externí odkaz: https://doaj.org/article/3d0e1d0e5f0242be94157b70bb712693

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Akademický článek

A multi-cycle approach via DuoStim is beneficial to treat couples indicated to PGT-M plus PGT-A. A propensity score matching-based case series

Autor: Vaiarelli, Alberto ^{a, ⁎}, Cimadomo, Danilo ^a, Blancafort, Claudia ^b, Trabucco, Elisabetta ^c, Alviggi, Erminia ^c, Vallefuoco, Roberta ^c, Livi, Claudia ^d, Benini, Francesca ^d, Canosa, Stefano ^e, Llácer, Joaquín ^b, Ruffa, Alessandro ^a, Borini, Andrea ^f, Capalbo, Antonio ^g, Rienzi, Laura ^{a, h}, Gennarelli, Gianluca ^{e, i, 1}, Maria Ubaldi, Filippo ^{a, 1}

Publikováno v: In European Journal of Obstetrics & Gynecology and Reproductive Biology December 2024 303:272-278

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Akademický článek

A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development

Autor: S. Canosa, N. Licheri, L. Bergandi, G. Gennarelli, C. Paschero, M. Beccuti, D. Cimadomo, G. Coticchio, L. Rienzi, C. Benedetto, F. Cordero, A. Revelli

Publikováno v: Journal of Ovarian Research, Vol 17, Iss 1, Pp 1-11 (2024)

Abstract Background Artificial Intelligence entails the application of computer algorithms to the huge and heterogeneous amount of morphodynamic data produced by Time-Lapse Technology. In this context, Machine Learning (ML) methods were developed in

Externí odkaz: https://doaj.org/article/15441f78ac0b41e8aaa4b13095ba94a0

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Akademický článek

Quantitative Standardized Expansion Assay: An Artificial Intelligence-Powered Morphometric Description of Blastocyst Expansion and Zona Thinning Dynamics

Autor: Danilo Cimadomo, Samuele Trio, Tamara Canosi, Federica Innocenti, Gaia Saturno, Marilena Taggi, Daria Maria Soscia, Laura Albricci, Ben Kantor, Michael Dvorkin, Anna Svensson, Thomas Huang, Alberto Vaiarelli, Gianluca Gennarelli, Laura Rienzi

Publikováno v: Life, Vol 14, Iss 11, p 1396 (2024)

Artificial intelligence applied to time-lapse microscopy may revolutionize embryo selection in IVF by automating data collection and standardizing the assessments. In this context, blastocyst expansion dynamics, although being associated with reprodu

Externí odkaz: https://doaj.org/article/51ad0277ad4140889b420bcabbf95137

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