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Brassinosteroids (BRs) are key phytohormones influencing soybean development, yet their role in symbiosis remains unclear. Here, the RNA-Seq was used to identify important gene associated with BRs and symbiotic nitrogen fixation, and the function of candidate gene was verified by transgenic hairy roots. The result shows that the RNA-Seq analysis was conducted in which BR signaling was found to suppress nodule formation and many DEGs enriched in immunity-related pathways.

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Two-dimensional (2D) hybrid materials, particularly those based on boron nitride (BN) and graphene oxide (GO), have attracted significant attention for energy applications owing to their distinct structural and electronic properties. BN/GO composites uniquely combine the mechanical strength, thermal stability and electrical insulation of BN with the high conductivity and flexibility of GO, creating advanced materials ideal for the fabrication of batteries, supercapacitors and fuel cells. These hybrids offer synergistic effects, enhanced charge transport, increased surface area, and improved chemical stability, making them promising candidates for high-performance energy systems.

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Objective: In England, through the Genomic Medicine Service Alliances (GMSAs), a national transformation project aims to embed robust pathways to deliver universal Lynch syndrome (LS) testing for patients with colorectal and endometrial cancers. Prior to commencement of the project, there was evidence of variation and low testing levels in eligible patients which is consistent with other health systems; however, we believe this is amenable to systematic improvement with responsibility for testing delivery by local cancer teams supported by regional infrastructure.

Methods And Analysis: A project team and national oversight group was formed in May 2021 with membership including 21×cancer alliances, 7×GMSAs, charities and other stakeholders who agreed key performance indicators.

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Background: Heart failure should be diagnosed as early as possible. Although deep learning models can predict one or more echocardiographic findings from electrocardiograms (ECGs), such analyses are not comprehensive.

Objectives: This study aimed to develop a deep learning model for comprehensive prediction of echocardiographic findings from ECGs.

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