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Nature Biotechnology
Resumen/Descripción – provisto por la editorial en inglés
Nature Biotechnology is a monthly journal covering the science and business of biotechnology. It publishes new concepts in technology/methodology of relevance to the biological, biomedical, agricultural and environmental sciences as well as covers the commercial, political, ethical, legal, and societal aspects of this research. The first function is fulfilled by the peer-reviewed research section, the second by the expository efforts in the front of the journal. We provide researchers with news about business; we provide the business community with news about research developments.Palabras clave – provistas por la editorial
No disponibles.
Disponibilidad
| Institución detectada | Período | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No detectada | desde jul. 2012 / hasta dic. 2023 | Nature.com |
Información
Tipo de recurso:
revistas
ISSN impreso
1087-0156
ISSN electrónico
1546-1696
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
1996-
Cobertura temática
Tabla de contenidos
Synapse-tuned CARs enhance immune cell anti-tumor activity
Peter J. Chockley
; Jorge Ibanez-Vega; Giedre Krenciute; Lindsay J. Talbot; Stephen Gottschalk
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Generating ‘smarter’ biotechnology
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Deconvolution of clinical variance in CAR-T cell pharmacology and response
Daniel C. Kirouac; Cole Zmurchok; Avisek Deyati; Jordan Sicherman; Chris Bond; Peter W. Zandstra
<jats:title>Abstract</jats:title><jats:p>Chimeric antigen receptor T cell (CAR-T) expansion and persistence vary widely among patients and predict both efficacy and toxicity. However, the mechanisms underlying clinical outcomes and patient variability are poorly defined. In this study, we developed a mathematical description of T cell responses wherein transitions among memory, effector and exhausted T cell states are coordinately regulated by tumor antigen engagement. The model is trained using clinical data from CAR-T products in different hematological malignancies and identifies cell-intrinsic differences in the turnover rate of memory cells and cytotoxic potency of effectors as the primary determinants of clinical response. Using a machine learning workflow, we demonstrate that product-intrinsic differences can accurately predict patient outcomes based on pre-infusion transcriptomes, and additional pharmacological variance arises from cellular interactions with patient tumors. We found that transcriptional signatures outperform T cell immunophenotyping as predictive of clinical response for two CD19-targeted CAR-T products in three indications, enabling a new phase of predictive CAR-T product development.</jats:p>
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Interstrand crosslinking of homologous repair template DNA enhances gene editing in human cells
Hannah I. Ghasemi; Julien Bacal; Amanda C. Yoon; Katherine U. Tavasoli; Carmen Cruz; Jonathan T. Vu; Brooke M. Gardner; Chris D. Richardson
<jats:title>Abstract</jats:title><jats:p>We describe a strategy to boost the efficiency of gene editing via homology-directed repair (HDR) by covalently modifying the template DNA with interstrand crosslinks. Crosslinked templates (xHDRTs) increase Cas9-mediated editing efficiencies by up to fivefold in K562, HEK293T, U2OS, iPS and primary T cells. Increased editing from xHDRTs is driven by events on the template molecule and requires ataxia telangiectasia and Rad3-related (ATR) kinase and components of the Fanconi anemia pathway.</jats:p>
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
scPrisma infers, filters and enhances topological signals in single-cell data using spectral template matching
Jonathan Karin; Yonathan Bornfeld; Mor Nitzan
<jats:title>Abstract</jats:title><jats:p>Single-cell RNA sequencing has been instrumental in uncovering cellular spatiotemporal context. This task is challenging as cells simultaneously encode multiple, potentially cross-interfering, biological signals. Here we propose scPrisma, a spectral computational method that uses topological priors to decouple, enhance and filter different classes of biological processes in single-cell data, such as periodic and linear signals. We apply scPrisma to the analysis of the cell cycle in HeLa cells, circadian rhythm and spatial zonation in liver lobules, diurnal cycle in <jats:italic>Chlamydomonas</jats:italic> and circadian rhythm in the suprachiasmatic nucleus in the brain. scPrisma can be used to distinguish mixed cellular populations by specific characteristics such as cell type and uncover regulatory networks and cell–cell interactions specific to predefined biological signals, such as the circadian rhythm. We show scPrisma’s flexibility in incorporating prior knowledge, inference of topologically informative genes and generalization to additional diverse templates and systems. scPrisma can be used as a stand-alone workflow for signal analysis and as a prior step for downstream single-cell analysis.</jats:p>
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Integrative analysis of multimodal mass spectrometry data in MZmine 3
Robin Schmid; Steffen Heuckeroth; Ansgar Korf; Aleksandr Smirnov; Owen Myers; Thomas S. Dyrlund; Roman Bushuiev; Kevin J. Murray; Nils Hoffmann; Miaoshan Lu; Abinesh Sarvepalli; Zheng Zhang; Markus Fleischauer; Kai Dührkop; Mark Wesner; Shawn J. Hoogstra; Edward Rudt; Olena Mokshyna; Corinna Brungs; Kirill Ponomarov; Lana Mutabdžija; Tito Damiani; Chris J. Pudney; Mark Earll; Patrick O. Helmer; Timothy R. Fallon; Tobias Schulze; Albert Rivas-Ubach; Aivett Bilbao; Henning Richter; Louis-Félix Nothias; Mingxun Wang; Matej Orešič; Jing-Ke Weng; Sebastian Böcker; Astrid Jeibmann; Heiko Hayen; Uwe Karst; Pieter C. Dorrestein; Daniel Petras; Xiuxia Du; Tomáš Pluskal
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Microfluidics-free single-cell genomics with templated emulsification
Iain C. Clark; Kristina M. Fontanez; Robert H. Meltzer; Yi Xue; Corey Hayford; Aaron May-Zhang; Chris D’Amato; Ahmad Osman; Jesse Q. Zhang; Pabodha Hettige; Jacob S. A. Ishibashi; Cyrille L. Delley; Daniel W. Weisgerber; Joseph M. Replogle; Marco Jost; Kiet T. Phong; Vanessa E. Kennedy; Cheryl A. C. Peretz; Esther A. Kim; Siyou Song; William Karlon; Jonathan S. Weissman; Catherine C. Smith; Zev J. Gartner; Adam R. Abate
<jats:title>Abstract</jats:title><jats:p>Current single-cell RNA-sequencing approaches have limitations that stem from the microfluidic devices or fluid handling steps required for sample processing. We develop a method that does not require specialized microfluidic devices, expertise or hardware. Our approach is based on particle-templated emulsification, which allows single-cell encapsulation and barcoding of cDNA in uniform droplet emulsions with only a vortexer. Particle-templated instant partition sequencing (PIP-seq) accommodates a wide range of emulsification formats, including microwell plates and large-volume conical tubes, enabling thousands of samples or millions of cells to be processed in minutes. We demonstrate that PIP-seq produces high-purity transcriptomes in mouse–human mixing studies, is compatible with multiomics measurements and can accurately characterize cell types in human breast tissue compared to a commercial microfluidic platform. Single-cell transcriptional profiling of mixed phenotype acute leukemia using PIP-seq reveals the emergence of heterogeneity within chemotherapy-resistant cell subsets that were hidden by standard immunophenotyping. PIP-seq is a simple, flexible and scalable next-generation workflow that extends single-cell sequencing to new applications.</jats:p>
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
High-resolution alignment of single-cell and spatial transcriptomes with CytoSPACE
Milad R. Vahid; Erin L. Brown; Chloé B. Steen; Wubing Zhang; Hyun Soo Jeon; Minji Kang; Andrew J. Gentles; Aaron M. Newman
<jats:title>Abstract</jats:title><jats:p>Recent studies have emphasized the importance of single-cell spatial biology, yet available assays for spatial transcriptomics have limited gene recovery or low spatial resolution. Here we introduce CytoSPACE, an optimization method for mapping individual cells from a single-cell RNA sequencing atlas to spatial expression profiles. Across diverse platforms and tissue types, we show that CytoSPACE outperforms previous methods with respect to noise tolerance and accuracy, enabling tissue cartography at single-cell resolution.</jats:p>
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
Trans-segmental imaging in the spinal cord of behaving mice
Pavel Shekhtmeyster; Daniela Duarte; Erin M. Carey; Alexander Ngo; Grace Gao; Jack A. Olmstead; Nicholas A. Nelson; Axel Nimmerjahn
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible
The next generation of single-cell sequencing methods can be microfluidics-free
Palabras clave: Biomedical Engineering; Molecular Medicine; Applied Microbiology and Biotechnology; Bioengineering; Biotechnology.
Pp. No disponible