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Researchers supported by the U.S. National Science Foundation have discovered that it is not how much of a key molecule that allows axolotls to regenerate limbs properly, it is how little. This new knowledge moves researchers closer to enabling tissue repair and, possibly, limb regeneration in humans.

“Axolotls are a species of salamander that have the ability to regrow limbs and repair organ tissue,” said Anna Allen, a program officer in the NSF Directorate for Biological Sciences. “Based on previous work, researchers knew that a particular molecule told cells to start the process of regrowth but how cells knew where they were along a limb and, therefore, what structure to build in that location remained a mystery.”

The new work, led by James Monaghan, a professor of biology and director of the Institute for Chemical Imaging of Living Systems at Northeastern University, shows that the key is how that critical molecule, retinoic acid, degrades. An enzyme whose only job is to destroy retinoic acid is extremely prevalent at the far end of the limb (the wrist) but much less prevalent at the shoulder, meaning the reverse for retinoic acid. It is this decreasing amount of retinoic acid that allows the cells to know if they are at the shoulder, mid-limb, or wrist.

Building on their findings, the researchers used CRISPR technology to turn off certain

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The U.S. National Science Foundation released the first Sexual Assault and Harassment Climate Survey (SAHCS) findings report for the United States Antarctic Program (USAP).

Results from the survey help expand agency understanding of sexual assault and harassment, bystander experience, as well as workplace satisfaction and cultural norms within the USAP community, and will inform NSF decisions and policies.

“NSF is committed to fostering and maintaining a culture free from sexual violence and harassment throughout the United States Antarctic Program,” said Special Assistant to the Director for SAHPR Renée Ferranti. “I’m grateful to those who participated in the survey, giving NSF a stronger understanding of how to build an environment where every member of the Antarctic community feels safe and supported.”

NSF will use the survey data as a baseline program metric and intends to provide SAHCS to USAP community members periodically. The results of the USAP SAHCS will help NSF to understand the incidence and prevalence of sexual misconduct in the USAP and to gather baseline data on sexual assault and sexual harassment and bystander experience, as well as workplace satisfaction and cultural norms data within the community so NSF can continue to improve ongoing prevention and response efforts.

In addition to the SAHCS, NSF implemented several new actions and policies following the release of a 2022 NSF-commissioned report focused on the prevalence of sexual assault

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Using the Gemini North telescope in Hawaii, astronomers have captured an image of comet 3I/ATLAS, an interstellar object that was first detected on July 1, 2025, by the Asteroid Terrestrial-impact Last Alert System (ATLAS) for which the comet was named. The letter “I” means “interstellar,” and “3” indicates it is only the third object from another star system ever observed. The observations will help scientists study the characteristics of this rare object’s origin, orbit and composition.

Gemini North is in Hawaii and is one half of the International Gemini Observatory, funded in part by the U.S. National Science Foundation. The imagery reveals the comet’s compact coma — a cloud of gas and dust surrounding its icy nucleus.

“The sensitivity and scheduling agility of the International Gemini Observatory has provided critical early characterization of this interstellar wanderer,” says Martin Still, NSF program director for the International Gemini Observatory. “We look forward to a bounty of new data and insights as this object warms itself on sunlight before continuing its cold, dark journey between the stars.”

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Artificial intelligence has transformed fields like medicine and finance, but it hasn’t gained much traction in manufacturing. Factories present a different challenge for AI: They are structured, fast-paced environments that rely on precision and critical timing. Success requires more than powerful algorithms; it demands deep, real-time understanding of complex systems, equipment and workflow. A new AI model designed specifically for manufacturing, seeks to address this challenge and revolutionize how factories operate.

With support from the U.S. National Science Foundation, a team led by California State University Northridge’s Autonomy Research Center for STEAHM has developed MaVila — short for Manufacturing, Vision and Language — an intelligent assistant that combines image analysis and natural language processing to help manufacturers detect problems, suggest improvements and communicate with machines in real time. Their goal is to create smarter, more adaptive manufacturing systems that can better support one of the most important sectors of the U.S. economy.

MaVila takes a different approach. Instead of relying on outside data, like information on the internet, it is trained with manufacturing-specific knowledge from the start. It learns directly from visual and language-based data in factory settings. The tool can “see” and “talk” — analyzing images of parts, describing defects in plain language, suggesting fixes and even communicating with machines to carry out automatic adjustments.

MaVila was trained using a specialized approach that required

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