Shifting the life cycle of grain crops from annual to perennial would usher in a new era of agriculture that is more environmentally friendly, resilient to climate change, and capable of soil carbon sequestration. Despite decades of work, transforming the annual grain crop wheat (Triticum aestivum) into a perennial has yet to be realized. Direct domestication of wild perennial grass relatives of wheat, such as Thinopyrum intermedium, is an alternative approach. Here we highlight protein coding sequences in the recently released T. intermedium genome sequence that may be orthologous to domestication genes identified in annual grain crops. Their presence suggests a roadmap for the accelerated domestication of this plant using new breeding technologies.
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http://dx.doi.org/10.1016/j.tplants.2020.02.004 | DOI Listing |
Mamm Genome
January 2025
Phenomics Australia, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia.
Research infrastructure is critical for advancing knowledge of health and disease, fostering innovation through world-class, cutting-edge facilities and technical expertise. Phenomics Australia is Australia's national research infrastructure provider responsible for accelerating advances in mammalian functional genomics and precision medicine through the development and delivery of services and expertise in engineered disease model production, phenotyping, and biobanking. These capabilities and resources are enabled by Australia's National Collaborative Research Infrastructure Strategy and primarily support health and medical research for significant healthcare and economic benefits.
View Article and Find Full Text PDFTher Adv Rare Dis
January 2025
SynGAP Research Fund, 2856 Curie Pl., San Diego, CA 92122, USA.
-related disorder (SRD) is a developmental and epileptic encephalopathy caused by a disruption of the gene. At the beginning of 2024, it is one of many rare monogenic brain disorders without disease-modifying treatments, but that is changing. This article chronicles the last 5 years, beginning when treatments for SRD were not publicly in development, to the start of 2024 when many SRD-specific treatments are advancing.
View Article and Find Full Text PDFJ Neurotrauma
January 2025
Zuckerberg San Francisco General Hosptial and Trauma Center, University of California, San Francisco, San Francisco, California, USA.
Outpatient care following nonhospitalized traumatic brain injury (TBI) is variable, and often sparse. The National Academies of Sciences, Engineering, and Medicine's 2022 report on highlighted the need to improve the consistency and quality of TBI care in the community. In response, the present study aimed to identify existing evidence-based guidance and specific clinical actions over the days to months following nonhospitalized TBI that should be prioritized for implementation in primary care.
View Article and Find Full Text PDFArXiv
November 2024
Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA.
Empirical investigation of the quintillion-scale, functionally diverse antibody repertoires that can be generated synthetically or naturally is critical for identifying potential biotherapeutic leads, yet remains burdensome. We present high-throughput nanophotonics- and bioprinter-enabled screening (HT-NaBS), a multiplexed assay for large-scale, sample-efficient, and rapid characterization of antibody libraries. Our platform is built upon independently addressable pixelated nanoantennas exhibiting wavelength-scale mode volumes, high-quality factors (high-Q) exceeding 5000, and pattern densities exceeding one million sensors per square centimeter.
View Article and Find Full Text PDFJ Chem Theory Comput
December 2024
RIKEN Center for Computational Science, Kobe 650-0047, Japan.
The abundant demand for deep learning compute resources has created a renaissance in low-precision hardware. Going forward, it will be essential for simulation software to run on this new generation of machines without sacrificing scientific fidelity. In this paper, we examine the precision requirements of a representative kernel from quantum chemistry calculations: the calculation of the single-particle density matrix from a given mean-field Hamiltonian (i.
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