The research team led by Associate Professor Lin-Lin Bu from Wuhan University School and Hospital of Stomatology, has published a comprehensive review entitled “Triaptosis and Cancer: Next Hope?” in the journal Research. This article systematically elaborates the triaptosis pathway from molecular mechanism to therapeutic application, detailing its signaling cascade, discussing the central role of oxidative stress homeostasis in cancer, and offering a forward-looking perspective on future directions—collectively underscoring the compelling potential of triaptosis as a novel anticancer strategy.

Recently, Prof. Andrea Alù from the City University of New York and Dr. Guangwei Hu from Nanyang Technological University in Singapore summarized previous representative work in the field of terahertz topologies and reconfigurable metamaterial devices, discussed design and integration methods for existing reconfigurable terahertz topology platforms, and explored potential avenues for future research and development. The findings were published as the cover paper titled “Topological and Reconfigurable Terahertz Metadevices” in Research (Research, 2025 DOI: 10.34133/research.0882).

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.