The liver is the body’s control tower for metabolism, powering vital functions like converting nutrients to glucose, storing fat and breaking down toxins. Over a third of the world, however, is thought to be affected by conditions including metabolic dysfunction-associated steatotic liver disease (MASLD), which jeopardize key liver functions as the condition progresses.

Hepatocyte organoids – the miniature, 3D models of the organ – hold immense promise for accelerating drug development and advancing regenerative therapies. In a study published in Nature, Keio University researchers unveiled a method to proliferate these hard-to-grow organoids by a million-fold in just 3-4 weeks while maintaining key liver functions. “These organoids are potentially the closest laboratory representations of the liver and its multifunctionality,” says senior author Professor Toshiro Sato of the Keio University School of Medicine.

Getting therapeutic drugs past the blood-brain barrier has long been a major challenge in treating brain diseases. Now, researchers from Japan have explored how cholesterol-modified heteroduplex oligonucleotides (Chol-HDOs) enhance drug delivery to the brain. Their study reveals that Chol-HDOs bind tightly to serum proteins, allowing them to persist in the bloodstream and cross into brain tissue. These findings offer insights into gene-targeting therapies and could help develop treatments for conditions like Alzheimer’s disease.

Complex protein interactions at synapses are essential for memory formation in our brains, but the mechanisms behind these processes remain poorly understood. Now, researchers from Japan have developed a computational model revealing new insights into the unique droplet-inside-droplet structures that memory-related proteins form at synapses. They discovered that the shape characteristics of a memory-related protein are crucial for the formation of these structures, which could shed light on the nature of various neurological disorders.

Multicolored optical switching is essential for potential advancements in telecommunication and optical computing. However, most materials typically exhibit only single-colored optical nonlinearity under intense laser illumination. To address this, researchers have demonstrated that exciting the multivalley semiconductor germanium with a single-color pulse laser enables ultrafast transparency switching across multiple wavelengths. This breakthrough could drive the development of ultrafast optical switches for future multiband communication and optical computing.

Kyoto, Japan -- There's a sensation that you experience -- near a plane taking off or a speaker bank at a concert -- from a sound so total that you feel it in your very being. When this happens, not only do your brain and ears perceive it, but your cells may also.

Technically speaking, sound is a simple phenomenon, consisting of compressional mechanical waves transmitted through substances, which exists universally in the non-equilibrated material world. Sound is also a vital source of environmental information for living beings, while its capacity to induce physiological responses at the cell level is only just beginning to be understood.

Following on previous work from 2018, a team of researchers at Kyoto University have been inspired by research in mechanobiology and body-conducted sound -- the sound environment in body tissues -- indicating that acoustic pressure transmitted by sound may be sufficient to induce cellular responses.

Development of ShotgunCSP: a crystal structure prediction algorithm combining machine learning and first-principles calculations.Achieved world-leading performance in crystal structure prediction benchmarks.A machine learning algorithm for predicting crystal symmetry dramatically improves the performance of structural predictions for complex and large-scale crystal systems.

Developed the machine learning algorithm E2T and its software for learning to learn for extrapolative prediction.Achieved outstanding extrapolative prediction performance in material property prediction tasks across diverse material systems.Demonstrated that models exposed to extensive extrapolative tasks can acquire the ability to rapidly adapt to new tasks.

An Osaka Metropolitan University researcher has developed an autonomous driving algorithm for agricultural robots used for greenhouse cultivation and other farm work.