The development of deep learning has motivated the advancement of unconventional computing that leverages analog physical systems such as analog electronics, spintronics, and photonics. These technologies have also led to the development of unique computational paradigms harnessing the features of analog devices, including compute-in-memory for nonvolatile devices and compute-in-sensor for analog electronics. What, then, are the computational paradigms that can exploit the characteristics of photonics? Optical computing has emerged as a promising candidate as it offers low-latency and low-power computation by utilizing the inherent parallelism of light. Additionally, the low-loss medium of optical fibers allows for the transmission of information over long distances. In this study, a remotely driven optical neural network that combines these advantageous features is demonstrated. Namely, computations can be executed with data transfer over a photonic network, which provides a computational paradigm named photonic compute-in-wire. As a proof-of-concept, an optoelectronic benchtop with a 20-km fiber access line are constructed, confirming good classification accuracy for image recognition tasks. The reported approach broadens the opportunities to utilize optical computation from local edge computing to in-network computing for low-latency and low-energy computation.

Recently, a review article by the research teams led by Professor Chen Shiyi from Huashan Hospital, Professor Dai Li Hua from the Affiliated City Dong Hospital, and Director Wu Guanghui from the Affiliated Ningde Hospital was published in the renowned journal Research. The study emphasizes how robotic exoskeletons can significantly improve cancer patients' mobility, muscle strength, and gait training, while also contributing to psychological recovery through personalized support and real-time feedback. This innovation is poised to reshape the future of cancer rehabilitation.

Recently, research teams led by Professor Cai Songhua from the Shenzhen Branch of the Cancer Hospital of the Chinese Academy of Medical Sciences, Professor Mao Wenjun from Wuxi People's Hospital, and Professor Tang Bufu from Zhongshan Hospital affiliated to Fudan University have focused on the immune microenvironment and lung cancer radiotherapy. They demonstrated a combined therapeutic approach targeting SPP1⁺ macrophages to enhance radiotherapy sensitivity, with the findings published under the title“ SPP1⁺ TAM: CD8⁺ T cell crosstalk associates with blocking radiotherapy efficacy in lung cancer” on Research.

Recently, Professor Jie Kong, Associate Professor Jin Liang, and their research team from Northwestern Polytechnical University have systematically reviewed the design strategies, printing processes, and application progress of magnetically responsive materials in 4D printing. This study thoroughly analyzes the working principles and performance optimization methods of magnetically responsive shape memory materials, and demonstrates their innovative applications in fields such as biomedical tissue engineering, robotics, and intelligent devices. The relevant work was published in Research under the title "4D Printing of Magnetically Responsive Materials and Their Applications" (Research, 2025, DOI: 10.34133/research.0847).