Researchers have developed an AI-based system that automatically and objectively detects the moment when fish experience loss of equilibrium (LOE) due to temperature stress. The system combines DeepLabCut, a deep-learning AI that captures animal posture from video, with ResNet34, a deep-learning AI-based image-classification technology. Their system is expected to help predict the effects of climate change on fish. The research team was led by Specially Appointed Lecturer Tomoya Nakayama and Yoshiya Matsuo (a master’s student at the time) of the Institute of Transformative Bio-Molecules (WPI-ITbM) at Nagoya University, in collaboration with Associate Professor Tatsuto Hasegawa and Takuya Kato (a master’s student at the time) of the University of Fukui. Their research was published in the journal Scientific Reports on September 10, 2026.

Kyoto, Japan -- Amphibian larvae -- often known as tadpoles -- exhibit a behavior known as social aggregation, where they gather together as a way to avoid predators. These interactions are evidence of their association preferences, or their tendency to recognize members of their own species. Some varieties of tadpoles have even shown a preference for their siblings.

These association preferences and kin recognition in tadpoles have become a key topic in understanding the evolution of social behavior. Recent studies have suggested that microorganisms may be influencing communication through animal body odors, indicating the possibility that pond water rich in microbes may also affect social behavior. Yet whether this sociality is innate, shaped by early life experiences, or the aquatic environment, has remained unclear.

This uncertainty motivated Kazuko Hase at Kyoto University to investigate how early-life social experiences and the aquatic environment influence the development of sociality.

Kyoto, Japan -- As tiny as they are, marine plankton play pivotal roles in biogeochemical cycles and in sustaining aquatic ecosystems, producing around half of the oxygen on Earth and also acting as carbon sinks. When they die, their decomposing cells produce dissolved organic carbon that can be transformed and stored in the ocean for thousands of years, so understanding plankton mortality is essential for uncovering the mechanisms behind marine ecosystems.

However, assessing the death of a particular plankton population out of a community consisting of hundreds of coexisting species poses a complex challenge. A team of researchers at Kyoto University addressed this by focusing on viral infection and cell lysis, the process through which a cell's membrane breaks down and releases its genetic information into the environment.

First, the team developed a method for measuring plankton lysis by growing cultures of two phytoplankton species, diatoms and raphidophytes, in a seawater-based medium, and then extracting rRNA and quantifying it using digital PCR. Since rRNA released into seawater degrades over time, the researchers added a culture of spike-in ribosomes to the medium and measured the degradation rate constant. The resulting flux model incorporated both changes in host cell-free rRNA and the degradation constant, making it possible to accurately assess the rate of cell lysis.