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Nature
Resumen/Descripción – provisto por la editorial en inglés
Nature is a weekly international journal publishing the finest peer-reviewed research in all fields of science and technology on the basis of its originality, importance, interdisciplinary interest, timeliness, accessibility, elegance and surprising conclusions. Nature also provides rapid, authoritative, insightful and arresting news and interpretation of topical and coming trends affecting science, scientists and the wider public.Palabras clave – provistas por la editorial
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Información
Tipo de recurso:
revistas
ISSN impreso
0028-0836
ISSN electrónico
1476-4687
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
1869-
Tabla de contenidos
Phosphorus-mediated sp2–sp3 couplings for C–H fluoroalkylation of azines
Xuan Zhang
; Kyle G. Nottingham; Chirag Patel; Juan V. Alegre-Requena; Jeffrey N. Levy; Robert S. Paton
; Andrew McNally
Palabras clave: Multidisciplinary.
Pp. 217-222
Mesozoic cupules and the origin of the angiosperm second integument
Gongle Shi
; Fabiany Herrera
; Patrick S. Herendeen
; Elizabeth G. Clark
; Peter R. Crane
Palabras clave: Multidisciplinary.
Pp. 223-226
Evolutionary and biomedical insights from a marmoset diploid genome assembly
Chentao Yang; Yang Zhou
; Stephanie Marcus; Giulio Formenti
; Lucie A. Bergeron; Zhenzhen Song; Xupeng Bi; Juraj Bergman
; Marjolaine Marie C. Rousselle; Chengran Zhou
; Long Zhou; Yuan Deng; Miaoquan Fang; Duo Xie
; Yuanzhen Zhu; Shangjin Tan; Jacquelyn Mountcastle
; Bettina Haase; Jennifer Balacco; Jonathan Wood; William Chow; Arang Rhie
; Martin Pippel
; Margaret M. Fabiszak
; Sergey Koren
; Olivier Fedrigo
; Winrich A. Freiwald
; Kerstin Howe
; Huanming Yang; Adam M. Phillippy
; Mikkel Heide Schierup
; Erich D. Jarvis
; Guojie Zhang
<jats:title>Abstract</jats:title><jats:p>The accurate and complete assembly of both haplotype sequences of a diploid organism is essential to understanding the role of variation in genome functions, phenotypes and diseases<jats:sup>1</jats:sup>. Here, using a trio-binning approach, we present a high-quality, diploid reference genome, with both haplotypes assembled independently at the chromosome level, for the common marmoset (<jats:italic>Callithrix jacchus</jats:italic>), an primate model system that is widely used in biomedical research<jats:sup>2,3</jats:sup>. The full spectrum of heterozygosity between the two haplotypes involves 1.36% of the genome—much higher than the 0.13% indicated by the standard estimation based on single-nucleotide heterozygosity alone. The de novo mutation rate is 0.43 × 10<jats:sup>−8</jats:sup> per site per generation, and the paternal inherited genome acquired twice as many mutations as the maternal. Our diploid assembly enabled us to discover a recent expansion of the sex-differentiation region and unique evolutionary changes in the marmoset Y chromosome. In addition, we identified many genes with signatures of positive selection that might have contributed to the evolution of <jats:italic>Callithrix</jats:italic> biological features. Brain-related genes were highly conserved between marmosets and humans, although several genes experienced lineage-specific copy number variations or diversifying selection, with implications for the use of marmosets as a model system.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 227-233
Reconstruction of ancient microbial genomes from the human gut
Marsha C. Wibowo
; Zhen Yang; Maxime Borry
; Alexander Hübner; Kun D. Huang; Braden T. Tierney
; Samuel Zimmerman; Francisco Barajas-Olmos; Cecilia Contreras-Cubas; Humberto García-Ortiz
; Angélica Martínez-Hernández; Jacob M. Luber; Philipp Kirstahler; Tre Blohm
; Francis E. Smiley; Richard Arnold; Sonia A. Ballal; Sünje Johanna Pamp
; Julia Russ; Frank Maixner; Omar Rota-Stabelli
; Nicola Segata
; Karl Reinhard; Lorena Orozco
; Christina Warinner; Meradeth Snow; Steven LeBlanc; Aleksandar D. Kostic
<jats:title>Abstract</jats:title><jats:p>Loss of gut microbial diversity<jats:sup>1–6</jats:sup> in industrial populations is associated with chronic diseases<jats:sup>7</jats:sup>, underscoring the importance of studying our ancestral gut microbiome. However, relatively little is known about the composition of pre-industrial gut microbiomes. Here we performed a large-scale de novo assembly of microbial genomes from palaeofaeces. From eight authenticated human palaeofaeces samples (1,000–2,000 years old) with well-preserved DNA from southwestern USA and Mexico, we reconstructed 498 medium- and high-quality microbial genomes. Among the 181 genomes with the strongest evidence of being ancient and of human gut origin, 39% represent previously undescribed species-level genome bins. Tip dating suggests an approximate diversification timeline for the key human symbiont <jats:italic>Methanobrevibacter smithii</jats:italic>. In comparison to 789 present-day human gut microbiome samples from eight countries, the palaeofaeces samples are more similar to non-industrialized than industrialized human gut microbiomes. Functional profiling of the palaeofaeces samples reveals a markedly lower abundance of antibiotic-resistance and mucin-degrading genes, as well as enrichment of mobile genetic elements relative to industrial gut microbiomes. This study facilitates the discovery and characterization of previously undescribed gut microorganisms from ancient microbiomes and the investigation of the evolutionary history of the human gut microbiota through genome reconstruction from palaeofaeces.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 234-239
SARS-CoV-2 uses a multipronged strategy to impede host protein synthesis
Yaara Finkel
; Avi Gluck; Aharon Nachshon; Roni Winkler; Tal Fisher; Batsheva Rozman; Orel Mizrahi; Yoav Lubelsky
; Binyamin Zuckerman
; Boris Slobodin; Yfat Yahalom-Ronen; Hadas Tamir; Igor Ulitsky
; Tomer Israely
; Nir Paran
; Michal Schwartz
; Noam Stern-Ginossar
Palabras clave: Multidisciplinary.
Pp. 240-245
Multilevel proteomics reveals host perturbations by SARS-CoV-2 and SARS-CoV
Alexey Stukalov; Virginie Girault
; Vincent Grass
; Ozge Karayel
; Valter Bergant
; Christian Urban
; Darya A. Haas
; Yiqi Huang
; Lila Oubraham
; Anqi Wang; M. Sabri Hamad; Antonio Piras; Fynn M. Hansen; Maria C. Tanzer; Igor Paron; Luca Zinzula
; Thomas Engleitner; Maria Reinecke; Teresa M. Lavacca
; Rosina Ehmann; Roman Wölfel; Jörg Jores
; Bernhard Kuster
; Ulrike Protzer
; Roland Rad
; John Ziebuhr
; Volker Thiel
; Pietro Scaturro
; Matthias Mann
; Andreas Pichlmair
Palabras clave: Multidisciplinary.
Pp. 246-252
Adjuvanting a subunit COVID-19 vaccine to induce protective immunity
Prabhu S. Arunachalam; Alexandra C. Walls
; Nadia Golden; Caroline Atyeo; Stephanie Fischinger
; Chunfeng Li; Pyone Aye; Mary Jane Navarro; Lilin Lai; Venkata Viswanadh Edara
; Katharina Röltgen
; Kenneth Rogers; Lisa Shirreff; Douglas E. Ferrell; Samuel Wrenn; Deleah Pettie
; John C. Kraft
; Marcos C. Miranda; Elizabeth Kepl
; Claire Sydeman; Natalie Brunette; Michael Murphy
; Brooke Fiala; Lauren Carter; Alexander G. White; Meera Trisal; Ching-Lin Hsieh; Kasi Russell-Lodrigue
; Christopher Monjure; Jason Dufour; Skye Spencer
; Lara Doyle-Meyers; Rudolph P. Bohm; Nicholas J. Maness
; Chad Roy
; Jessica A. Plante; Kenneth S. Plante; Alex Zhu
; Matthew J. Gorman; Sally Shin
; Xiaoying Shen; Jane Fontenot; Shakti Gupta; Derek T. O’Hagan; Robbert Van Der Most; Rino Rappuoli
; Robert L. Coffman; David Novack; Jason S. McLellan
; Shankar Subramaniam; David Montefiori; Scott D. Boyd
; JoAnne L. Flynn
; Galit Alter
; Francois Villinger; Harry Kleanthous; Jay Rappaport; Mehul S. Suthar; Neil P. King
; David Veesler
; Bali Pulendran
Palabras clave: Multidisciplinary.
Pp. 253-258
High-dimensional characterization of post-acute sequelae of COVID-19
Ziyad Al-Aly
; Yan Xie
; Benjamin Bowe
Palabras clave: Multidisciplinary.
Pp. 259-264
Swarm Learning for decentralized and confidential clinical machine learning
Stefanie Warnat-Herresthal
; Hartmut Schultze
; Krishnaprasad Lingadahalli Shastry; Sathyanarayanan Manamohan
; Saikat Mukherjee; Vishesh Garg
; Ravi Sarveswara; Kristian Händler; Peter Pickkers; N. Ahmad Aziz
; Sofia Ktena; Florian Tran
; Michael Bitzer; Stephan Ossowski; Nicolas Casadei
; Christian Herr
; Daniel Petersheim; Uta Behrends; Fabian Kern
; Tobias Fehlmann
; Philipp Schommers; Clara Lehmann; Max Augustin
; Jan Rybniker; Janine Altmüller; Neha Mishra; Joana P. Bernardes; Benjamin Krämer; Lorenzo Bonaguro
; Jonas Schulte-Schrepping; Elena De Domenico
; Christian Siever
; Michael Kraut; Milind Desai; Bruno Monnet; Maria Saridaki; Charles Martin Siegel; Anna Drews; Melanie Nuesch-Germano; Heidi Theis
; Jan Heyckendorf; Stefan Schreiber; Sarah Kim-Hellmuth; Paul Balfanz; Thomas Eggermann; Peter Boor; Ralf Hausmann; Hannah Kuhn; Susanne Isfort; Julia Carolin Stingl; Günther Schmalzing; Christiane K. Kuhl; Rainer Röhrig; Gernot Marx; Stefan Uhlig; Edgar Dahl; Dirk Müller-Wieland; Michael Dreher; Nikolaus Marx; Jacob Nattermann; Dirk Skowasch; Ingo Kurth
; Andreas Keller
; Robert Bals; Peter Nürnberg; Olaf Rieß; Philip Rosenstiel; Mihai G. Netea
; Fabian Theis
; Sach Mukherjee; Michael Backes; Anna C. Aschenbrenner
; Thomas Ulas
; Angel Angelov; Alexander Bartholomäus; Anke Becker; Daniela Bezdan; Conny Blumert; Ezio Bonifacio; Peer Bork; Bunk Boyke; Helmut Blum; Thomas Clavel; Maria Colome-Tatche; Markus Cornberg; Inti Alberto De La Rosa Velázquez; Andreas Diefenbach; Alexander Dilthey; Nicole Fischer; Konrad Förstner; Sören Franzenburg; Julia-Stefanie Frick; Gisela Gabernet; Julien Gagneur; Tina Ganzenmueller; Marie Gauder; Janina Geißert; Alexander Goesmann; Siri Göpel; Adam Grundhoff; Hajo Grundmann; Torsten Hain; Frank Hanses; Ute Hehr; André Heimbach; Marius Hoeper; Friedemann Horn; Daniel Hübschmann; Michael Hummel; Thomas Iftner; Angelika Iftner; Thomas Illig; Stefan Janssen; Jörn Kalinowski; René Kallies; Birte Kehr; Oliver T. Keppler; Christoph Klein; Michael Knop; Oliver Kohlbacher; Karl Köhrer; Jan Korbel; Peter G. Kremsner; Denise Kühnert; Markus Landthaler; Yang Li; Kerstin U. Ludwig; Oliwia Makarewicz; Manja Marz; Alice C. McHardy; Christian Mertes; Maximilian Münchhoff; Sven Nahnsen; Markus Nöthen; Francine Ntoumi; Jörg Overmann; Silke Peter; Klaus Pfeffer; Isabell Pink; Anna R. Poetsch; Ulrike Protzer; Alfred Pühler; Nikolaus Rajewsky; Markus Ralser; Kristin Reiche; Stephan Ripke; Ulisses Nunes da Rocha; Antoine-Emmanuel Saliba; Leif Erik Sander; Birgit Sawitzki; Simone Scheithauer; Philipp Schiffer; Jonathan Schmid-Burgk; Wulf Schneider; Eva-Christina Schulte; Alexander Sczyrba; Mariam L. Sharaf; Yogesh Singh; Michael Sonnabend; Oliver Stegle; Jens Stoye; Janne Vehreschild; Thirumalaisamy P. Velavan; Jörg Vogel; Sonja Volland; Max von Kleist; Andreas Walker; Jörn Walter; Dagmar Wieczorek; Sylke Winkler; John Ziebuhr; Monique M. B. Breteler
; Evangelos J. Giamarellos-Bourboulis
; Matthijs Kox
; Matthias Becker
; Sorin Cheran; Michael S. Woodacre; Eng Lim Goh
; Joachim L. Schultze
; ;
<jats:title>Abstract</jats:title><jats:p>Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine<jats:sup>1,2</jats:sup>. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes<jats:sup>3</jats:sup>. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation<jats:sup>4,5</jats:sup>. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 265-270
PIK3CA and CCM mutations fuel cavernomas through a cancer-like mechanism
Aileen A. Ren
; Daniel A. Snellings
; Yourong S. Su; Courtney C. Hong
; Marco Castro
; Alan T. Tang
; Matthew R. Detter
; Nicholas Hobson; Romuald Girard
; Sharbel Romanos; Rhonda Lightle; Thomas Moore; Robert Shenkar
; Christian Benavides; M. Makenzie Beaman
; Helge Müller-Fielitz
; Mei Chen; Patricia Mericko; Jisheng Yang; Derek C. Sung
; Michael T. Lawton; J. Michael Ruppert; Markus Schwaninger
; Jakob Körbelin
; Michael Potente
; Issam A. Awad; Douglas A. Marchuk
; Mark L. Kahn
Palabras clave: Multidisciplinary.
Pp. 271-276