We systematically review 34 relevant studies between 2015 and 2025 following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, focusing on the combination of multimodal wearable sensing with learning models.

The University of Osaka D3 Center and NEC Corporation (NEC; TSE: 6701) have jointly commenced a demonstration aimed at the application of a wide-area distributed campus AI processing platform that enables on-demand use of GPU’s from compute servers. This demonstration will leverage NEC's "ExpEther," a technology that transmits signals from IT equipment with high reliability and low latency, to build a high-performance AI processing platform that can connect and disconnect compute servers and GPUs on-demand, even when they are in different buildings across campus.

Human action recognition (HAR) is crucial for the development of efficient computer vision, where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks across sensor-processor interfaces. However, the absence of interactions among versatile biomimicking functionalities within a single device, which was developed for specific vision tasks, restricts the computational capacity, practicality, and scalability of in-sensor vision computing. Here, we propose a bioinspired vision sensor composed of a GaN/AlN-based ultrathin quantum-disks-in-nanowires (QD-NWs) array to mimic not only Parvo cells for high-contrast vision and Magno cells for dynamic vision in the human retina but also the synergistic activity between the two cells for in-sensor vision computing. By simply tuning the applied bias voltage on each QD-NW-array-based pixel, we achieve two biosimilar photoresponse characteristics with slow and fast reactions to light stimuli that enhance the in-sensor image quality and HAR efficiency, respectively. Strikingly, the interplay and synergistic interaction of the two photoresponse modes within a single device markedly increased the HAR recognition accuracy from 51.4% to 81.4% owing to the integrated artificial vision system. The demonstration of an intelligent vision sensor offers a promising device platform for the development of highly efficient HAR systems and future smart optoelectronics.

Emerging ferroptosis–immunotherapy strategies, integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics, demonstrate significant potential in managing primary, recurrent, and metastatic malignancies. Mechanistically, ferroptosis induction not only directly eliminates tumor cells but also promotes immunogenic cell death (ICD), eliciting damage-associated molecular patterns (DAMPs) release to activate partial antitumor immunity. However, standalone ferroptosis therapy fails to initiate robust systemic antitumor immune responses due to inherent limitations: low tumor immunogenicity, immunosuppressive microenvironment constraints, and tumor microenvironment (TME)-associated physiological barriers (e.g., hypoxia, dense extracellular matrix). To address these challenges, synergistic approaches have been developed to enhance immune cell infiltration and reestablish immunosurveillance, encompassing (1) direct amplification of antitumor immunity, (2) disruption of immunosuppressive tumor niches, and (3) biophysical hallmark remodeling in TME. Rational nanocarrier design has emerged as a critical enabler for overcoming biological delivery barriers and optimizing therapeutic efficacy. Unlike prior studies solely addressing ferroptosis or nanotechnology in tumor therapy, this work first systematically outlines the synergistic potential of nanoparticles in combined ferroptosis–immunotherapy strategies. It advances multidimensional nanoplatform design principles for material selection, structural configuration, physicochemical modulation, multifunctional integration, and artificial intelligence-enabled design, providing a scientific basis for efficacy optimization. Moreover, it examines translational challenges of ferroptosis–immunotherapy nanoplatforms across preclinical and clinical stages, proposing actionable solutions while envisioning future onco-immunotherapy directions. Collectively, it provides systematic insights into advanced nanomaterial design principles and therapeutic optimization strategies, offering a roadmap for accelerating clinical translation in onco-immunotherapy research.