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Wheat is the most widely grown crop globally, providing 20% of all human calories and protein. Achieving step changes in genetic yield potential is crucial to ensure food security, but efforts are thwarted by an apparent trade-off between grain size and number. Expansins are proteins that play important roles in plant growth by enhancing stress relaxation in the cell wall, which constrains cell expansion. Here, we describe how targeted overexpression of an α-expansin in early developing wheat seeds leads to a significant increase in grain size without a negative effect on grain number, resulting in a yield boost under field conditions. The best-performing transgenic line yielded 12.3% higher average grain weight than the control, and this translated to an increase in grain yield of 11.3% in field experiments using an agronomically appropriate plant density. This targeted transgenic approach provides an opportunity to overcome a common bottleneck to yield improvement across many crops.
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http://dx.doi.org/10.1111/nph.17048 | DOI Listing |
Plant Biotechnol J
September 2025
State Key Laboratory for Quality and Safety of Agro-Products, Key Laboratory of Biotechnology in Plant Protection of MARA, Key Laboratory of Green Plant Protection of Zhejiang Province, Institute of Virology and Biotechnology, Zhejiang Academy of Agricultural Sciences, Hangzhou, China.
Plants balance resource energy allocation between growth and immunity to ensure survival and reproduction under limited availability. This study reveals that rice cultivars with elevated sucrose levels boost resistance to the fungal pathogen Magnaporthe oryzae by accumulating the phytoalexin sakuranetin, regulated by the transcription factor STOREKEEPER (OsSTK). OsSTK binds to the promoter region of OsNOMT (Naringenin-7-O-Methyltransferase) to drive sakuranetin biosynthesis.
View Article and Find Full Text PDFPlant J
September 2025
Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Key laboratory of Jiangsu Province for Agrobiology, East China Branch of National Center of Technology Innovation for Saline-Alkali Tolerant Rice, Nanjing, 210014, China.
Rice, as a vital food crop, faces persistent challenges in breeding programs aimed at achieving stable high yield under environmental stresses due to intrinsic trade-off mechanisms. This study functionally characterizes NARROW AND LONGER GRAIN 14 (NLG14), which encodes a spermine synthase. Loss-of-function nlg14 mutants exhibit slender grains due to enhanced cell expansion and proliferation, alongside significantly improved grain quality-manifested as reduced chalkiness, lower amylose/protein content, higher gel consistency, and superior taste value.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
August 2025
The physiological signals obtained from advanced sensors, combined with deep learning techniques for classification and regression tasks, have become a core driving force in enhancing smart healthcare. Recently, dense prediction tasks for physiological signals-aimed at generating predictions that are closely aligned with the input signal to enable fine-grained analysis-have garnered increasing attention. The UNet family, often combined with sophisticated task-specific customizations, has become a popular choice to improve prediction performance.
View Article and Find Full Text PDFNanomaterials (Basel)
August 2025
Institute of High Pressure Physics, School of Physical Scientific and Technology, Ningbo University, Ningbo 315211, China.
Achieving simultaneous enhancement of Vickers hardness and fracture toughness remains a critical challenge in designing oxide ceramic materials due to their partially antagonistic nature. In this study, we address this trade-off by tailoring the microstructure of zirconia (ZrO) ceramics through YO doping and high-pressure high-temperature (HPHT) sintering. Nanostructured composites were synthesized using 50 nm monoclinic ZrO and varying YO contents (3, 5, and 7 mol%) under 5 GPa at temperatures ranging from 400 to 2000 °C.
View Article and Find Full Text PDFProc IEEE Int Symp Biomed Imaging
April 2025
Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, USA.
While functional Magnetic Resonance Imaging (fMRI) offers valuable insights into cognitive processes, its inherent spatial limitations pose challenges for detailed analysis of the fine-grained functional architecture of the brain. More specifically, MRI scanner and sequence specifications impose a trade-off between temporal resolution, spatial resolution, signal-to-noise ratio, and scan time. Deep Learning (DL) Super-Resolution (SR) methods have emerged as a promising solution to enhance fMRI resolution, generating high-resolution (HR) images from low-resolution (LR) images typically acquired with lower scanning times.
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