Researchers have succeeded in improving mobility efficiency by having the snake-like robot move using an “undulating motion” on uneven terrain and a “rolling motion” on level ground.

Researchers from the Earth-Life Science Institute (ELSI) and National Institute for Basic Biology have developed a new method to detect extraterrestrial life without relying on traditional biosignatures. By modelling how life might spread between planets, they demonstrate that life could be detected through statistical patterns across planetary populations rather than on individual planets. This "agnostic biosignature" approach could assist in guiding future searches for life beyond Earth.

Giant migrating contractions (GMCs) are powerful waves of colonic movement that propel intestinal contents toward the anus and are essential for defecation. Yet despite their physiological importance, the mechanisms that initiate these contractions—and particularly the factors that regulate spontaneous GMCs—have remained poorly understood. Now, a research team from Saitama University has identified ATP-P2X7 signaling as a previously unrecognized neural mechanism that drives colonic GMCs. The team was led by master’s students Ayano Gomi and Hozuki Shimosawa together with Professor Ichiro Sakata, and used Suncus murinus (suncus), an animal model that allows colonic motility to be examined under conscious conditions.

The Subaru Telescope observed the interstellar comet 3I/ATLAS (C/2025 N1) on January 7, 2026 (UT), after it made its closest approach to the Sun. By observing colors in the coma around the comet, astronomers could estimate the ratio of carbon dioxide to water. This ratio is much lower than that inferred from earlier observations by space telescopes. These findings suggest that the chemistry of the coma is evolving over time and offers clues to the structure of comet 3I/ATLAS.

A key question in physics is whether gravity follows quantum rules, but testing this is difficult because gravitational effects are so weak. Researchers from Kyushu University have theoretically proposed a method using momentum-squeezed states in optomechanical systems to amplify gravity-induced entanglement signals. This approach could make such signals easier to detect, paving the way for future experiments to determine whether gravity has a quantum nature.

Researchers at the University of Tokyo clarified how membrane lipid composition determines the surface charge of extracellular vesicles (EVs). They show that differences between exosomes and membrane-derived EVs arise from phospholipid asymmetry, particularly phosphatidylserine distribution. The study proposes zeta potential as a key indicator for EV classification and quality control, offering a foundation for standardization and rational design of EV-based therapeutics. This work was conducted as part of a JST COI-NEXT program, led by Innovation Center of NanoMedicine (iCONM).

Microplastic pollution is a growing environmental concern due to its widespread presence in oceans, rivers, and other water systems. Now, scientists from Shinshu University have introduced an eco-friendly water purification method using the natural slimy mucilage of nameko mushrooms, a common food in Japan. The results show that this natural material can effectively remove more than 90% of plastic particles from water in a very short time, offering a promising sustainable solution to plastic pollution.

Tomato yellow leaf curl disease (TYLCD), caused by begomoviruses, is a global problem in tomato production, affecting yield. While introduction of resistance genes is one of the strategies to control TYLCD, introduction of a single Ty-gene is inadequate in providing full protection against begomoviruses. Now, researchers have determined that a combination of Ty-1/Ty-3 and Ty-6 can fully protect tomato plants from begomoviruses, providing a promising strategy to improve tomato varieties and ensure their stable production.

Clinical interviewing is an essential skill in medical training, but often requires significant time and training. Generative artificial intelligence (AI) can be used to help accelerate this training; however, its effectiveness remains unclear. Now, a new study reports how AI-based assessment of medical interview transcripts closely matches human-based assessments. These findings suggest that AI could support more efficient and scalable training in medical education.