A research team has developed an innovative biomimetic dual-mode magnetic resonance imaging (MRI) nanoprobe for detecting early-stage liver fibrosis in non-alcoholic fatty liver disease (NAFLD).
The work, using the Steady High Magnetic Field Facility (SHMFF), was recently published in Advanced Science. The team was led by Prof. Wang Junfeng at the High Magnetic Field Laboratory, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences.
NAFLD is a growing global health concern with even higher rates among individuals with obesity or type 2 diabetes. Detecting liver fibrosis early, before it becomes irreversible, is crucial for timely intervention and treatment. While MRI is a promising non-invasive tool for identifying liver fibrosis, traditional imaging techniques often lack the sensitivity to catch early-stage changes. Conventional contrast agents either face safety concerns or fail to target fibrotic tissues specifically.
The root-associated bacterium Exiguobacterium R2567 regulates tiller number by producing cyclo(Leu-Pro), which activates the rice strigolactone signaling pathway.
Mass General Brigham researchers found that interactions between immune and brain cells drive fear responses, but treatment with psychedelics like MDMA and psilocybin may reverse these effects.
The new study suggests that fear and the immune system are connected in previously unknown ways. The researchers found that the immune system can influence stress and fear behaviors by changing how brain cells communicate.
The investigators further showed that psychedelic treatments could target these neuroimmune interactions and reduce stress-induced fear in preclinical models and found similar results in human tissue samples. Results are published in Nature.
A new AI robot called π-0.5 uses 100 decentralized brains, known as π-nodes, to control its body with lightning-fast reflexes and smart, local decision-making. Instead of relying on a central processor or internet connection, each part of the robot—like fingers, joints, and muscles—can sense, think, and act independently in real time. Powered by a powerful vision-language-action model and trained on massive, diverse data, this smart muscle system allows the robot to understand and complete real-world tasks in homes, even ones it has never seen before.
Join our free AI content course here 👉 https://www.skool.com/ai-content-acce… the best AI news without the noise 👉 https://airevolutionx.beehiiv.com/ 🔍 What’s Inside: • A groundbreaking AI robot called π‑0.5 powered by 100 decentralized “π-nodes” embedded across its body • Each node acts as a mini-brain, sensing, deciding, and adjusting without needing Wi-Fi or a central processor • A powerful vision-language-action model lets the robot understand messy homes and complete complex tasks without pre-mapping 🎥 What You’ll See: • How π‑0.5 combines local reflexes with high-level planning to react in real time • The unique training process using over 400 hours of diverse, real-world data from homes, mobile robots, and human coaching • Real-world tests where the robot cleans, organizes, and adapts to brand-new spaces with near-human fluency 📊 Why It Matters: This new system redefines robot intelligence by merging biological-inspired reflexes with advanced AI planning. It’s a major step toward robots that can handle unpredictable environments, learn on the fly, and function naturally in everyday life—without relying on cloud servers or rigid programming. DISCLAIMER: This video explores cutting-edge robotics, decentralized AI design, and real-world generalization, revealing how distributed intelligence could transform how machines move, sense, and think. #robot #robotics #ai.
🔍 What’s Inside: • A groundbreaking AI robot called π‑0.5 powered by 100 decentralized “π-nodes” embedded across its body. • Each node acts as a mini-brain, sensing, deciding, and adjusting without needing Wi-Fi or a central processor. • A powerful vision-language-action model lets the robot understand messy homes and complete complex tasks without pre-mapping.
🎥 What You’ll See: • How π‑0.5 combines local reflexes with high-level planning to react in real time. • The unique training process using over 400 hours of diverse, real-world data from homes, mobile robots, and human coaching. • Real-world tests where the robot cleans, organizes, and adapts to brand-new spaces with near-human fluency.
Contemporary Amperex Technology Co., Limited (CATL), the largest battery manufacturer in the world with a 38% share of the global market, has just announced some fairly significant breakthroughs in battery tech that aren’t just theoretical; they’re already hitting the market.
Over the past few decades, solar cells have become increasingly widespread, with a growing number of individuals and businesses worldwide now relying on solar energy to power their homes or operations. Energy engineers worldwide have thus been trying to identify materials that are promising for the development of photovoltaics, are eco-friendly and non-toxic, and can also be easily sourced and processed.
These include kesterite-based materials, such as Cu₂ZnSnS₄ (CZTS), a class of semiconducting materials with a crystal structure that resembles that of the naturally occurring mineral kesterite. Kesterite solar cells could have various advantages over the conventional silicon-based photovoltaics that are most used today, including lower manufacturing costs, a less toxic composition and greater flexibility.
Despite their potential, kesterite solar cells developed to date attain significantly lower power conversion efficiencies (PCEs) than their silicon counterparts. This is in great part due to atomic-scale defects in kesterite-based materials that trap charge carriers and prompt non-radiative recombination, a process that causes energy losses and thus reduces the solar cells’ performance.
