Alzheimer disease (AD), a devastating neurodegenerative disorder, is pathologically defined by amyloid-β (Aβ) deposition and neurofibrillary tangles. Critically, concomitant cerebrovascular dysfunction compromises neuronal homeostasis and significantly accelerates AD progression by impairing the neurovascular unit. However, effective strategies to modulate this complex neurovascular pathology remain unclear. Here, we applied transcranial photobiomodulation (tPBM) with continuous-wave (CW) and 40-Hz pulsed light to target neurovascular pathology in 5xFAD mice. The results showed that both tPBM modalities comparably ameliorated cognitive dysfunction through distinct glial-mediated mechanisms. Specifically, CW light primarily enhanced astrocyte–vascular coupling, which ameliorated vascular dysfunction and protected synapses. In contrast, 40-Hz light predominantly drove spatial redistribution of microglia toward Aβ plaques, thereby enhancing localized amyloid clearance. These findings reveal complementary pathways for tPBM in AD intervention, highlighting that CW and 40-Hz light offer modality-specific therapeutic advantages: The former targets cerebrovascular dysfunction, while the latter addresses Aβ plaque deposition. Collectively, our study provides critical mechanistic insights for optimizing tPBM protocols, establishing a foundation for more precise and comprehensive AD interventions.

Steady-state visual evoked potential brain–computer interfaces offer a high-speed communication channel. However, traditional steady-state visual evoked potential paradigms often rely on strong flickering visual stimulation, which can lead to substantial visual fatigue. Moreover, the electroencephalography responses evoked by brightness flicker are spatially constrained and are primarily associated with occipital visual processing. This study presents a novel text sequence stimulation paradigm that combines periodic visual stimulation with orthographic information and elicits distinct occipital and occipitotemporal scalp response patterns relative to conventional brightness flicker. Frequency-sweep experiments were conducted to investigate the temporal, spatial, and spectral characteristics of the evoked responses. A comparison experiment further showed that text sequence stimulation is less sensitive to variations in stimulus size and luminance than conventional brightness flicker. Based on these findings, a 40-target speller was developed and validated through online experiments. The proposed paradigm achieved an information transfer rate of 235.12 ± 30.12 bits/min while significantly improving user comfort, as confirmed by questionnaire evaluations. These results suggest that text sequence stimulation offers a practical design direction for high-speed and more comfortable visual brain–computer interface.

How can we reopen blocked blood vessels quickly and safely when a clot forms in stroke, heart attack, deep-vein thrombosis, or pulmonary embolism? Current care relies on clot-dissolving drugs given through the bloodstream and catheter-based procedures that mechanically retrieve thrombi and/or deliver drugs locally. These methods can be lifesaving, but they are limited by residual distal microvascular obstruction, reduced efficacy against dense or lysis-resistant clots, and procedure-related complications such as hemorrhage and downstream embolization. This review compares 2 complementary technology paths: “tethered” catheter systems designed for rapid and operator-controlled reopening of large vessels, and “untethered” micro/nanoscale systems, including injectable carrier-based platforms and actively actuated micro/nanorobots, that can be actuated and guided by magnetic, ultrasound, or light energy to seek, penetrate, and disrupt clots at the microscale. Across reported studies, rationally engineered nanocarriers can improve clot targeting and local retention of thrombolytic payloads, while externally powered microrobots and microswarms enable active mixing and mechanical assistance, often reducing treatment time and lowering required drug doses in preclinical models. We further summarize imaging and tracking strategies that ensure feedback control of device position, energy delivery, and treatment endpoints. Finally, we discuss key translational barriers, including robust navigation under complex hemodynamics, reliable stopping and clearance, standardized safety windows, and seamless integration into established interventional workflows, thereby outlining actionable priorities that can steer this field toward clinical therapies.

The treatment of maxillofacial tumors requires coordinated resection and reconstruction. Conventional template-guided open osteotomy techniques may increase the risk of tissue injury. Additionally, the accuracy of titanium plate-based reconstruction is limited by the lack of standardized positional criteria, thereby potentially affecting alignment consistency. To address these challenges, we propose a maxillofacial tumor treatment system termed RAMRS, comprising 2 modules: robot-assisted osteotomy and augmented reality-guided reconstruction (ARR). Within therobot-assisted osteotomy module, a hand–eye calibration framework is used to support robotic arm positioning, while preoperative CT-to-patient spatial alignment is achieved through an optical probe-mediated registration method, supporting robot-assisted osteotomy according to the preoperative plan. The ARR module incorporates a rotating-caliper-based calibration compensation framework to reduce marker registration errors caused by manual instability or fiducial marker deformation. Subsequently, quick-response markers are used to achieve spatial alignment between the preoperative 3-dimensional model and the intraoperative defective mandible, and the virtual mandibular model is projected onto a display visible to the surgeon, thereby providing intuitive intraoperative guidance. Validation experiments were conducted on cadaveric and ex vivo specimens. The results demonstrated favorable accuracy in osteotomy and reconstruction alignment in the evaluated experiments, while the ARR module achieved low 2-dimensional fusion error for augmented reality visualization. These findings support the feasibility of the proposed workflow in preclinical settings.

Subcortical vascular cognitive impairment (SVCI) is a heterogeneous cognitive impairment caused by small vessel disease. Diagnosis of SVCI remains challenging when neuropsychological assessment is impractical. This study proposes a diffusion tensor imaging (DTI)-based DenseNet to identify SVCI from subcortical ischemic vascular disease (SIVD) and to profile multidomain cognitive risks. We collected neuropsychological scales and DTI from 134 SVCI and 171 SIVD patients in our internal dataset for model development. An external target-domain dataset of 90 SVCI and 103 SIVD patients was used for unsupervised domain adaptation (UDA). Within this dataset, 45 SVCI and 53 SIVD patients were used for unlabeled UDA fitting; the remaining 45 SVCI and 50 SIVD patients were held out as a target-domain test set. Model-generated salient maps identified white matter (WM) regions associated with SVCI. Mutual information (MI) maps between DTI and 6 neuropsychological scales were computed to identify structural correlates of cognitive domains for cognitive profiling. We computed structural similarity index measure (SSIM) between individual-level salient maps derived from DenseNet and the MI maps for unsupervised clustering to stratify domain-specific cognitive impairment risk in SVCI. The DenseNet achieves high accuracy (0.902 internal, 0.926 target-domain) with AUCs of 0.951 and 0.942, respectively. SVCI probabilities reflect cognitive severity, and salient maps are associated with neuropsychological performance. Regarding cognitive profiling, each cognitive domain is divided into low, moderate, and high subgroups, with significantly different SSIM. Our DTI-based study demonstrates accurate SVCI identification and individualized multi-domain cognitive profiling. This offers a complementary framework to support diagnosis and personalized intervention.

Cyborg insect is a living insect equipped with electronic devices for allowing remote control of their movement. Due to their small size and locomotor capability, cyborg insects have potential advantages for application in cluttered environments where human cannot operate. Past studies have proposed various cyborg insects using different insect species and custom-made controllers equipped with sensors for desirable tasks. Those cyborg insects were usually equipped with the electronic devices on the back, leading to the loss of useful body shape of the platform organism. Although the body shape of animals is known to contribute to effective locomotion in their living environments, it has been unexamined how the arrangement of electronics to cyborg insect affects its locomotion. Here, we developed a miniature wireless controller that is fully implantable to small insects and demonstrated that the implantation of electronic device enhances traversal performance of the cyborg cockroach. The developed wireless controller was 10 mm in width, 10 mm in length, and 3 mm in height. It served sub-1 GHz communication and electrical signal output for maneuvering locomotion of cockroach. The cockroach with the implant maintained the innate tendency and traversal performance in gap negotiation comparable to intact animals, whereas the cyborg cockroach with the electronics mounted on the back exhibited degraded performance. The automatic stimulation algorithm successfully navigated the cockroach with the implant to the target with a success rate of 90.9%. The proposed technique will boost the capability of cyborg insects in challenging terrains in real scenarios.

Continuous tool operation with a myoelectric prosthetic hand is considerably more complex than discrete grasping tasks. This complexity arises because the control system must maintain stable, adaptive, and coordinated motions under varying loads and unpredictable interactions. In human motor control, this stability is achieved through a biological sensorimotor closed loop, where tactile feedback continuously modulates neural signals to adapt to environmental changes. Inspired by these mechanisms for reducing grasp instability caused by external shocks, this study designed a multimodal controller termed the tactile, kinesthetic, and electromyography (EMG) bionic gripping controller (TKE-BGC). It integrates tactile, kinematic, and EMG information. Initially, multimodal data—encompassing tactile signals, joint angles, and EMG patterns—were collected from able-bodied users during tool manipulation via a data glove. Subsequently, the TKE-BGC model was trained on these data, utilizing a Transformer encoder to extract high-level features and a multilayer perceptron to predict joint angles in real time. Based on this controller, this paper presents a prosthetic control framework developed through human skill transfer. Unlike conventional fixed force or force follows strategies that struggle with dynamic impacts or tracking delays, this framework enables robust end-to-end adaptive control. Tested across 4 seen and unseen tool operation tasks, the proposed method demonstrated precise detailed performance. Specifically, it significantly reduced the number of tool drops and shortened task completion times compared to the baseline methods. Furthermore, it achieved human-like average contact forces and substantially lowered the user’s physical workload, requiring noticeably less muscle effort than the force follows strategy (e.g., average EMG amplitude, 0.0023 versus 0.0124). By rapidly adjusting grip force through feedback and effectively mitigating instability, this research holds significant practical value in enhancing the daily independence of amputees and supporting their vocational rehabilitation and reemployment.

The limitations of biohybrid and mechanical robots, including insufficient control accuracy, limited flexibility, long-term stability, and endurance, have spurred considerable research interest in cyborg animals, which leverage the innate locomotion capabilities, physiological systems, and natural intelligence of organisms to perform tasks with high adaptability, superior performance, and extended endurance. This study provides a comprehensive overview of cyborg animals within the framework of animal taxonomy, summarizing the current state of research from a zoological perspective. Subsequently, the effect of different control techniques on the locomotion performance of cyborg animals was examined, with a special emphasis on 2 prominent research areas: brain–computer interfaces and muscle-receptor electrical stimulation. In addition, the role of advances in electronic backpack design and navigation control algorithms in enabling closed-loop control and applications, including swarm robotics, environmental exploration, and human–machine interaction, is also introduced, offering valuable insights for developing cyborg animals. This study highlights 4 critical aspects essential for the future advancement of cyborg animals by synthesizing recent progress and clarifying technical distinctions: adaptation between control strategies and animals, biocompatibility and stability of electronic backpacks, construction of interactive hybrid robotic systems, and ethical and welfare considerations related to the experimental animals, with the hope of facilitating the optimization and application of cyborg animal systems.

Mechanical stimulation is essential in tissue engineering and regenerative medicine for proper tissue maturation. However, conventional uniaxial platforms fail to reproduce the multiaxial loading experienced in vivo. In this study, we present a humanoid robotic bioreactor capable of delivering human-like shoulder motions to engineered tendon constructs, enabling controlled multiaxial stimulation with real-time strain monitoring. Human mesenchymal stem cells were cultured on decellularized tendon scaffolds and subjected to adduction–abduction loading at peak strains of approximately 3.5% and 9.5% under external forces of 25 and 50 N, respectively. Strain levels were directly quantified in situ using a flexible sensor integrated within the bioreactor. The transparent bioreactor membrane allowed noninvasive observation while simultaneously applying mechanical stimulation over 14 d, with continuous assessment of cellular morphology without fixation. Compared with static and traditional uniaxial controls, the robot motions enhance cell alignment and activation of mechanotransduction pathways while inducing notable gene and protein expression changes, particularly within the PI3K–Akt signaling pathway. Although dynamic loading resulted in a moderate reduction in cell viability, the transcriptional profile was consistent with mechanically driven phenotypic adaptation toward tenogenic-related programs rather than dominant signatures of acute cytotoxic damage. These findings demonstrate that replicating human-like multiaxial mechanics in vitro fundamentally alters cellular mechanosensing and may provide a mechanobiological foundation for the future development of more physiologically relevant tendon grafts.