AI offers ‘roadmap’ to plant genetics
Peer-Reviewed Publication
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 14-Dec-2025 17:11 ET (14-Dec-2025 22:11 GMT/UTC)
CSHL postdoc Iacopo Gentile has devised a new system for identifying redundant genes and predicting how certain genetic mutations may affect plant traits. The model provides plant breeders with a potential roadmap for future crop improvements.
Artificial carbon fixation is a promising pathway for achieving the carbon cycle and environment remediation. However, the sluggish kinetics of oxygen evolution reaction (OER) and poor selectivity of CO2 reduction seriously limited the overall conversion efficiencies of solar energy to chemical fuels. Herein, we demonstrated a facile and feasible strategy to rationally regulate the coordination environment and electronic structure of surface-active sites on both photoanode and cathode. More specifically, the defect engineering has been employed to reduce the coordination number of ultrathin FeNi catalysts decorated on BiVO4 photoanodes, resulting in one of the highest OER activities of 6.51 mA cm−2 (1.23 VRHE, AM 1.5G). Additionally, single-atom cobalt (II) phthalocyanine anchoring on the N-rich carbon substrates to increase Co–N coordination number remarkably promotes CO2 adsorption and activation for high selective CO production. Their integration achieved a record activity of 109.4 μmol cm−2 h−1 for CO production with a faradaic efficiency of > 90%, and an outstanding solar conversion efficiency of 5.41% has been achieved by further integrating a photovoltaic utilizing the sunlight (> 500 nm).
A new study shows that AI is revolutionizing colon cancer diagnosis, making detection easier, faster, less invasive, and more accurate. The research, based on a meta-analysis of studies published between 2020 and 2024, highlights how AI has been applied to colon cancer screening and analysis. Findings reveal significant gains in diagnostic precision, particularly in polyp detection during colonoscopies and in histopathological assessments, where deep learning models frequently outperform traditional methods.
Recently, addressing the inherent timescale mismatch challenge between fast and slow responses in optoelectronic sensors, a collaborative team from Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (Yukun ZHAO, Shulong LU, Min JIANG), Fudan University (Lifeng BIAN), and Suzhou University of Science and Technology (Jianya ZHANG) has proposed an innovative monolithic integration scheme. By combining surface defect introduction and local contact interface design with a gallium nitride (GaN) nanowire lift-off technique that eliminates the interference from the underlying silicon substrate, the team integrates fast and slow responses into a single device. This results in a transparent bifunctional device capable of self-driven detection and neural synaptic integration, with omnidirectional (360°) detection capability. As a photodetector, the device demonstrates the millisecond-level response speeds, while it exhibits the second- to minute-level relaxation time as an artificial synapse, achieving an over 1000-fold contrast in response dynamics. The device has been validated in the intelligent perception systems for humanoid robots successfully, advancing the development of multifunctional monolithic optoelectronic devices and providing a solid foundation for further research in related fields.
The work entitled "A dual-mode transparent device for 360° quasi-omnidirectional self-driven photodetection and efficient ultralow-power neuromorphic computing" was published in Light: Science & Applications.