Researchers are one step closer to finding a common target for treating ALS - a fatal neurodegenerative disease that causes progressive muscle weakness.

Age-related memory decline is often linked to reduced activity and division of neural stem cells (NSCs), but the underlying molecular mechanisms remain unclear. In a recent study, researchers from Japan investigated age-related changes in mouse NSCs at the molecular level and found that a gene named Setd8 plays a key role in NSC aging. Targeting this gene could offer a promising strategy to combat early brain aging and neurodegenerative conditions.

Self-disclosure is vital for communication. In the present century, various innovative forms of communication have emerged, including video-conferencing and embodied virtual reality (VR). In this context, researchers from Japan have recently demonstrated that embodied VR, especially with unrealistic avatars, facilitates the revelation of personal feelings. Moreover, female-to-female pairing had the highest self-disclosure score, underlining the role of gender.

Immune checkpoint inhibitors have revolutionized cancer treatment, but not all patients respond equally. Now, researchers from Japan have explored why two anti-PD-L1 antibodies, which target the same immune pathway, produce vastly different therapeutic outcomes in a mouse cancer model. They found that an immune mechanism known as antibody-dependent cellular cytotoxicity can inadvertently destroy antitumor immune cells. These findings underscore the importance of selecting antibody drugs that minimize off-target effects to improve the efficacy of immunotherapy.

Chemotherapy-induced nausea and vomiting can severely impact patients’ quality of life and treatment adherence. In a major clinical trial, researchers from Japan tested whether a low, 5 mg dose of olanzapine taken at home after chemotherapy could reduce these side effects without causing heavy sedation. The study found that this approach significantly improved outcomes compared to placebo, offering a safer, more affordable strategy that could reshape supportive cancer care, especially in outpatient and resource-limited settings.

Schizophrenia is a mental disorder that causes hallucinations, delusions, and social and cognitive impairment. Animal models are valuable for understanding the mechanisms underlying schizophrenia. However, conventional behavioral assessments are limited by the need for human intervention and external stimuli. Researchers from Fujita Health University, Japan, have established a semi-naturalistic platform using the automated ‘IntelliCage’ system for the comprehensive assessment of schizophrenia-like behaviors. The model can enhance translational research in psychiatric disorders and improve therapeutic development.

A research team at Japan’s National Institutes for Quantum Science and Technology (QST) has demonstrated that electron beam (EB) irradiation can decompose polytetrafluoroethylene (PTFE) — a highly durable plastic known as Teflon — into gaseous components. This method drastically improves the energy efficiency compared to conventional recycling processes, offering a promising path toward reducing the environmental impact from per- and polyfluoroalkyl substances (PFAS).

Oxidative stress is considered to contribute to the development of cancer. However, a recent study in Japan showed that oxidative stress may suppress rather than cause cancer development in individuals with variants of the BRCA2 gene.

Addressing the global plastic waste crisis, particularly hard-to-recycle blended PET fibers, demands environmentally friendlier recycling methods. Researchers engineered a novel PET hydrolase PET2-21M and established large-scale production in yeast. This enzyme dramatically boosted PET bottle-grade PET breakdown. In parallel, its direct precursor PET2-14M-6Hot successfully degraded challenging blended fibers (PET/cotton, PET/PU) at moderate temperatures. This breakthrough offers a promising, energy-efficient path for a circular plastics economy, accelerating industrial-scale recycling of diverse polymer wastes.

Researchers at The University of Osaka developed a deep learning model for rapid building damage assessment after floods using satellite imagery. This research establishes the first systematic benchmark for this task and introduces a novel semi-supervised learning method achieving 74% of fully supervised performance with just 10% of the labeled data. A new, lightweight deep learning model named Simple Prior Attention Disaster Assessment Net or SPADANet significantly reduces missed damaged buildings, improving recall by over 9% compared to existing models. This work provides crucial design principles for future AI disaster response, enabling faster and more efficient life-saving operations.