Osteogenesis imperfecta (OI) refers to a group of bone disorders in which certain genetic mutations affect the formation of healthy bones. In a new study, researchers have developed a novel mouse model bearing a substitution mutation at position 342 in the specificity protein 7 (Sp7) gene. Utilizing this model, they investigated the role of mature bone cells called osteocytes in OI and clarified the associations between impaired bone remodeling and osteocyte dendrite defects.

Wuhan, China – A landmark study published today in National Science Review introduces "Pore Science and Engineering" as a transformative paradigm for designing porous materials. Led by Prof. Bao-Lian Su (Wuhan University of Technology) and Prof. Ming-Yuan He (East China Normal University), the research systematically classifies two evolutionary stages of porous materials while proposing quantitative design principles for future applications in energy, catalysis, and environmental remediation.

Climate modeling leveraged by calibrating the so-called “soil color” parameter to enhance surface albedo simulation in the Weather Research and Forecasting model. This weakens land-atmosphere interactions with attenuated sensible heat and evapotranspiration, and suppresses water vapor flow into the Tibetan Plateau. Eventually, it reduces summertime precipitation wet bias by ~16% on the plateau. This study highlights the promise of enhancing climate modeling through the optimization of key land surface parameters, which is highly affordable through satellite remote sensing.

Researchers from Shenyang University of Chemical Technology explored the application potential of the Catal-GPT in catalyst design, which was built upon the qwen2 large language model, proposing a new paradigm for AI-driven catalyst development. The results showed that the qwen2 model could provide the complete preparation workflows and the detailed optimization suggestions through conversational interaction. Future work aims for cross-system adaptability to transform catalyst discovery from trial-and-error to precision targeting.

Here, researchers from Beijing Institute of Nanoenergy and Nanosystems (Chinese Academy of Sciences) and Yonsei University present the latest progress in neuromorphic computing by integrating various neural networks, including SVM, ANN, CNN, RNN, and RC. Starting from the structure of synapses and neurons, they explore how these networks can be combined with neuromorphic devices to replicate more complex brain-like computations. They also propose future development directions for neuromorphic devices, focusing on advancements in their structures, materials, and applications across diverse fields such as vision, touch, hearing, smell, pain and other senses.

A soft, LEGO-like hydrogel system enables reversible 3D information encoding through supramolecular assembly and orthogonal stimulus responses, allowing over 800 billion data configurations in a 5×5 array. This low-cost, reconfigurable platform supports dynamic data storage, masking, and rewriting.

With high surface-to-volume ratio, the abundant surface states and high carrier concentration are challenging the near-infrared photodetection behaviors of narrow band gap semiconductors nanowires. In this study, the narrow band gap semiconductor of Bi2O2Se nanosheets (NSs) is adopted to construct mixed-dimensional heterojunctions with GaSb nanowires (NWs) for demonstrating the impressive self-powered NIR photodetection. Benefiting from the built-in electric field of ~ 140 meV, the as-constructed NW/NS mixed-dimensional heterojunction self-powered photodetector shows the low dark current of 0.07 pA, high I_light/I_dark ratio of 82 and fast response times of < 2/2 ms at room temperature. The self-powered photodetector performance can be further enhanced by fabricating the NW array/NS mixed-dimensional heterojunction by using a contact printing technique. The excellent photodetection performance promises the as-constructed NW/NS mixed-dimensional heterojunction self-powered photodetector in imaging and photocommunication.

Scientists from the Institute of Genetics and Developmental Biology of the Chinese Academy of Sciences have reimagined the pollination process by developing a new system that uses gene editing to create flowers that can be easily pollinated by AI-controlled robots working round the clock.