From root to shoot: How silicon powers plant resilience
Peer-Reviewed Publication
Updates every hour. Last Updated: 6-May-2025 08:09 ET (6-May-2025 12:09 GMT/UTC)
A breakthrough study reveals that the Shoot-Silicon-Signal (SSS) protein plays a crucial role in managing silicon uptake and distribution in rice and other grasses. This study sheds light on how SSS helps plants adapt to environmental stresses. Understanding the role of silicon could provide valuable information on crop resilience and solutions to enhance agricultural productivity and sustainability, especially in the face of climate change.
Businesses are increasingly shifting toward online marketing. However, the effects of offline and online marketing on consumer behavior have not been comparatively examined. A team of Japanese researchers demonstrated that offline promotional media increase cognitive engagement and consequently promote consumers’ behavioral responses (e.g., coupon redemptions), especially those with low brand attachment. Although offline marketing was associated with high costs, it increased product sales. Thus, marketing teams should recalibrate their views on offline marketing.
V-161, a novel compound targeting the Na+-V-ATPase enzyme in vancomycin-resistant Enterococcus faecium (VRE), significantly reduces bacterial growth and colonization. A recent study has demonstrated a promising approach for fighting antibiotic resistance by identifying a compound, V-161, that inhibits a sodium-pumping enzyme critical for VRE survival under alkaline conditions in the intestine while preserving beneficial bacteria. This breakthrough offers hope for treating hospital infections and tackling the global threat of antibiotic-resistant bacteria.
A recent study at Earth-Life Science Institute (ELSI) at Institute of Science Tokyo has developed a theoretical model that uncovers the dual role of polyploidy—organisms carrying extra genome copies—in evolution. Their findings reveal that polyploidy can stabilise populations in predictable environments, where the evolution of novel traits is not required, enabling organisms to adapt and thrive in challenging conditions by accelerating evolutionary innovation. This breakthrough offers fresh insights into evolutionary mechanisms and their implications for microbiology, biotechnology, and medicine.
A new computational tool improves the analysis of genetic data, making it easier and faster to study the evolutionary relationships between species.
The earliest neural networks, which have later evolved into the large language models (LLMs) revolutionizing our society, were developed to study how information is processed in our brains. Ironically, as these models became more sophisticated, the information processing pathways within also became increasingly opaque, with some models today having trillions of tunable parameters.
But now, members of the Cognitive Neurorobotics Research Unit at the Okinawa Institute of Science and Technology (OIST) have created an embodied intelligence model with a novel architecture that allows researchers access to the various internal states of the neural network, and which appears to learn how to generalize in the same ways that children do.