The initiative, dubbed Precision Learning for On-target Weed control, is led by Christopher Voigt alongside academic partners and the company Robigo under the federal STREAM program. Researchers are leveraging generative artificial intelligence to model billions of prospective molecules, such as small interfering RNA and chemical compounds, that specifically target plant enzymes like EPSP synthase. These candidates are designed to minimize ecological harm, human toxicity, and production costs while circumventing weed resistance mutations. The most promising computational predictions will undergo physical validation by a dedicated high-throughput screening team to refine subsequent model ite…
Key points
The project aims to develop effective replacements for widely used agrochemicals that are…: The project aims to develop effective replacements for widely used agrochemicals that are currently losing efficacy against resistant weed species.
Creating domestic alternatives helps mitigate national security vulnerabilities tied to f…: Creating domestic alternatives helps mitigate national security vulnerabilities tied to foreign imports of phosphorus used for glyphosate manufacturing.
New candidates will be optimized to lower risks of cancer, endocrine disruption, and meta…: New candidates will be optimized to lower risks of cancer, endocrine disruption, and metabolic disorders linked to conventional herbicide exposure.
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MIT researchers will lead an up to $53 million effort, awarded by the U.S. Advanced Research Projects Agency for Health (ARPA-H) as part of its STREAM (Systems for Tracking and Resilience in Efficient Agricultural-input Management) program, to develop next-generation weed killers that help farmers and protect human health.
More than 1 billion pounds of herbicide are used in the United States every year. Herbicides help farmers by preventing significant crop loss due to weeds, and they enable regenerative farming practices that protect the soil, but some weeds are becoming resistant to the most common herbicides.
Exposure to herbicides may contribute to increased risk of cancer, metabolic and endocrine disorders, and other adverse health outcomes. Farm workers can be exposed from frequent herbicide use, but many U.S. residents are also exposed to these chemicals in small amounts through food and drinking water.
The MIT-led research team will develop new generative artificial intelligence tools to help them discover herbicide alternatives that are more effective and developed with human health in mind. Such alternatives could also help to reduce U.S. dependency on imported…
Navigating the dynamics of exchange often triggers unwanted feelings of obligation, reciprocity, and scorekeeping rather than pure joy. Offering presents grants people total control over timing, costs, and choices while fostering connection, but accepting items frequently provokes stress regarding unspoken debts. Understanding these psychological triggers helps individuals manage the tension inherent in unequal social rituals.
International researchers have successfully synthesized and isolated stable oxoboranes, ending a decades-long struggle to capture compounds containing a boron-oxygen triple bond. The computational analysis led by Indian scientists helped unlock the reaction pathways that make these elusive chemical structures viable. This fundamental milestone expands experimental access to rare bonding motifs and paves the way for isolating other highly unstable molecules.
Researchers at the LHCb experiment tracked an extraordinarily scarce transformation where a beauty quark and down antiquark annihilate into twin muons. Detecting such subtle events provides physicists with an indirect method to test for hypothetical particles and forces that are far too heavy for particle accelerators to produce directly. The long-awaited result sets stricter experimental boundaries as scientists attempt to uncover phenomena operating beyond the Standard Model.