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Traditional data-driven fault diagnosis methods for unmanned aerial vehicles (UAVs) often struggle to in effectively extract fault features from complex vibration signals. To address this challenge, this paper proposes an enhanced fault diagnosis framework based on GraphSAGE, incorporating a self-attention mechanism (GraphSAGE-SA). Initially, a customized vibration data acquisition system was developed using MPU6050 sensors to capture vibration data across various operational conditions. Subsequently, the K-Nearest Neighbors (KNN) algorithm was employed to convert one-dimensional vibration signals into graph-structured data, revealing explicit topological relationships. The proposed GraphSAGE-SA model aggregates information from both nodes and neighbors via a hierarchical sampling process. The integrated self-attention mechanism then adaptively adjusts the importance of different neighbors, facilitating more precise feature extraction. Experimental validation conducted on a quadrotor UAV platform demonstrated that the proposed method achieves an impressive fault classification accuracy of 98%, surpassing conventional GraphSAGE variants by 3–12% and other graph-based approaches. This superior performance is attributed to the model’s ability to capture local structural patterns and global dependencies simultaneously, enabled by the attention mechanism. This research presents a novel and effective solution for intelligent fault diagnosis in UAVs and other complex mechanical systems. In real-world applications, timely and accurate fault diagnosis is essential for ensuring UAV operational safety, mission reliability, and preventing catastrophic failures.

Skin acts as an essential barrier, protecting organisms from their environment. For skin trauma caused by accidental injuries, rapid healing, personalization, and functionality are vital requirements in clinical, which are the bottlenecks hindering the translation of skin repair from benchside to bedside. Herein, we described a novel design and a proof‐of‐concept demonstration of an adaptive bioprinting robot to proceed rapid in situ bioprinting on a full‐thickness excisional wound in mice. The three‐dimensional (3D) scanning and closed‐loop visual system integrated in the robot and the multi‐degree‐of‐freedom mechanism provide immediate, precise, and complete wound coverage through stereotactic bioprinting, which hits the key requirements of rapid‐healing and personalization in skin repair. Combined with the robot, epidermal stem cells and skin‐derived precursors isolated from neonatal mice mixed with Matrigel were directly printed into the injured area to replicate the skin structure. Excisional wounds after bioprinting showed complete wound healing and functional skin tissue regeneration that closely resembling native skin, including epidermis, dermis, blood vessels, hair follicles and sebaceous glands etc. This study provides an effective strategy for skin repair through the combination of the novel robot and a bioactive bioink, and has a promising clinical translational potential for further applications.

Hypertension is a pathological condition of persistent high blood pressure (BP) of which the underlying neural mechanisms remain obscure. Here, we show that the afferent nerves in perirenal adipose tissue (PRAT) contribute to maintain pathological high BP, without affecting physiological BP. Bilateral PRAT ablation or denervation leads to a long-term reduction of high BP in spontaneous hypertensive rats (SHR), but has no effect on normal BP in control rats. Further, gain- and loss-of-function and neuron transcriptomics studies show that augmented activities and remodeling of L1-L2 dorsal root ganglia neurons are responsible for hypertension in SHR. Moreover, we went on to show that calcitonin gene-related peptide (CGRP) is a key endogenous suppressor of hypertension that is sequestered by pro-hypertensive PRAT in SHRs. Taken together, we identify PRAT afferent nerves as a pro-hypertensive node that sustains high BP via suppressing CGRP, thereby providing a therapeutic target to tackle primary hypertension. The sympathetic nervous system can contribute to the development of hypertension, but the neurogenic mechanisms involved are incompletely understood. Here the authors report that afferent nerves in the perirenal adipose tissue (PRAT) contribute to the maintenance of high blood pressure, and PRAT ablation, denervation or upregulation of calcitonin gene-related peptide reduce blood pressure in hypertensive rats.

The repair and regeneration of tissues and organs using engineered biomaterials has attracted great interest in tissue engineering and regenerative medicine. Recent advances in organoids and engineered organs technologies have enabled scientists to generate 3D tissue that recapitulate the structural and functional characteristics of native organs, opening up new avenues in regenerative medicine. The matrix is one of the most important aspects for improving organoids and engineered organs construction. However, the clinical application of these techniques remained a big challenge because current commercial matrix does not represent the complexity of native microenvironment, thereby limiting the optimal regenerative capacity. Decellularized extracellular matrix (dECM) is expected to maintain key native matrix biomolecules and is believed to hold enormous potential for regenerative medicine applications. Thus, it is worth investigating whether the dECM can be used as matrix for improving organoid and engineered organs construction. In this review, the characteristics of dECM and its preparation method were summarized. In addition, the present review highlights the applications of dECM in the fabrication of organoids and engineered organs. Graphical Abstract (Created with bioRender.com)

Traumatic brain injury (TBI)-induced neuroinflammation, driven by inflammatory microglial polarization, continues to pose a significant regenerative and clinical challenge. Small extracellular vesicles (sEVs) have demonstrated great potential in mitigating post-TBI inflammation. Nevertheless, the limited yield and efficacy of sEVs produced via conventional two-dimensional (2D) culture systems (2D-sEVs) substantially hinder their clinical applicability. Moreover, effective strategies for the therapeutic application of sEVs in TBI treatment, along with an understanding of their underlying mechanisms, remain largely unexplored. In this study, we employed a 3D coaxial bioprinting method to encapsulate adipose-derived stem cells (ADSCs) within a hydrogel microfiber, facilitating 3D culturing and large-scale production of 3D-sEVs. Additionally, we utilized GelMA hydrogel for the sustained release of 3D-sEVs and evaluated their effects in LPS-activated microglia as well as in a TBI mouse model. Our results demonstrated that 3D culture significantly enhanced sEV production. GelMA improved sEV stability and prolonged sEV release up to 30 days in vivo. Compared to 2D-sEVs, 3D-sEVs offered superior therapeutic benefits. Specifically, 3D-sEVs substantially reduced neuroinflammation and brain tissue loss while accelerating motor function recovery in TBI mice. Furthermore, 3D-sEVs shifted pro-inflammatory microglia toward an anti-inflammatory polarization state, as evidenced by elevated expression levels of IL-4, IL-10, TGF-β, Arg1, and CD206, alongside reduced expression of IL-6, IL-1β, TNF-α, iNOS, and CD86, both in vitro and in vivo. Additionally, 3D-sEVs attenuated chemotaxis and migration in LPS-activated microglia. Further mechanistic exploration through RNA-seq, proteomic profiling, and GAS6 knockdown in 3D-sEVs, revealed that 3D-sEVs deliver growth arrest-specific protein 6 (GAS6) to modulate the transition of microglia from a pro-inflammatory to an anti-inflammatory state, thereby mitigating neuroinflammation following TBI. Our findings underscore the therapeutic promise of sEVs derived from 3D-cultured ADSCs in treating TBI via modulating microglia polarization. Graphical abstract

In the field of bone tissue engineering, the development of effective strategies for bone defect repair remains a major challenge. Herein, we report a novel approach involving the integration of high-yield 3D bioprinted adipose-derived stem cell small extracellular vesicles (3D-sEVs) into an injectable HAMA-CPC hydrogel (HAMA-CPC@3D-sEVs). In vitro, HAMA-CPC@3D-sEVs significantly promoted the proliferation, migration, and osteogenic differentiation of bone marrow stromal cells (BMSCs) and promoted angiogenesis in human umbilical vein endothelial cells (HUVECs). In vivo, in a rat tibial defect model, this treatment strongly promoted bone regeneration, increasing the bone volume fraction (BV/TV), bone volume (BV), and trabecular thickness (Tb.Th) at 4 weeks post-surgery. Mechanistically, proteomic analysis revealed that NAMPT in 3D-sEVs upregulated S1PR1 in HUVECs, leading to increased VEGF expression and angiogenesis. These findings suggest that 3D-sEVs-functionalized HAMA-CPC hydrogels have good potential for bone defect repair. Graphical abstract Schematic diagram of the overall study design of HAMA-CPC@3D-sEVs for the bone regeneration in rat

Research on outdoor, mobile, and self-powered temperature-control devices has always been highly regarded. These devices can reduce energy consumption for cooling and heating, and they have broad market prospects. On this basis, a rotary disc-shaped triboelectric nanogenerator (TENG) with a maximum open-circuit voltage of 6913 V, a maximum short-circuit current of 85 μA, and a maximum transferred charge of 1.3 μC was prepared. We synthesized a ferroelectric ceramic composed of 0.15PbTiO3–0.85PbSc0.5Ta0.5O3 (0.15PT–0.85PST), which exhibited excellent electrothermal effects at room temperature. By quenching, the electrothermal effect (ΔTmax) and energy harvesting properties of the device were 1.574 K and 0.542 J/cm3, respectively. Then, for the first time, we proposed a self-powered temperature quantification control system with a rotary disc-shaped TENG. This device effectively harnessed wind and water energy, in addition to other types of energy. The system consisted of energy collecting cups, a rotating disc-shaped FEP–rabbit fur TENG, a circuit management module, and a ferroelectric ceramic chip array. Through the circuit management module, the system converted external wind energy into a high-voltage electric field at the two ends of the 0.15PT–0.85PST ceramic chip to fully stimulate the electrothermal effect. At a speed of 200 rpm, the temperature change in the insulated cup within 276 s was 0.49 K, and the volume of the insulated cup was 300 times greater than that of the 0.15PT–0.85PST ceramic chip. Compared with the results reported in previous work, the cooling and heating times were both reduced by 31%, and the temperature changes for both cooling and heating increased by 81%. Moreover, the heating and cooling temperatures of the device optimized on this basis were increased to 1.19 K and 0.93 K, respectively. The great improvement in the temperature variation performance confirmed the great potential of the device for commercialization. This research could serve as a reference for reducing energy consumption for cooling and heating, and it meets the international energy policies of carbon dioxide emission peaking and carbon neutrality.

Due to their special anatomical and physiological features, central nervous system diseases still presented challenges, despite the fact that some advances have been made in early diagnosis and precision medicine. One of the complexities in treating tumors is the tumor microenvironment, which includes mesenchymal stem cells (MSCs) that exhibit tumor tropism and can be used for cell therapy. However, whether MSCs promote or suppress gliomas is still unclear, especially in glioma microenvironments. In this study, a coaxial microfiber was designed to mimic the tumor microenvironment and to reveal the effect of MSCs on glioma cells. The fiber shell was composed of MSCs and alginate, and the core was filled with U87MG (glioblastoma) cells and gelatin methacrylate. This Shell-MSC/Core-U87MG microenvironment improved the proliferation, survival, invasion, metastasis, and drug resistance of glioma cells, while simultaneously maintaining the stemness of glioma cells. In summary, coaxial extrusion bioprinted Shell-MSC/Core-U87MG microfiber is an ideal platform for tumor and stromal cell coculture to observe tumor biological behavior in vitro. Graphic abstract

Self-powered photodetectors are of significance for the development of low-energy-consumption and environment-friendly Internet of Things. The performance of semiconductor-based self-powered photodetectors is limited by the low quality of junctions. Here, a novel strategy was proposed for developing high-performance self-powered photodetectors with boosted electrostatic potential. The proposed self-powered ultraviolet (UV) photodetector consisted of an indium tin oxide and titanium dioxide (ITO/TiO2) heterojunction and an electret film (poly tetra fluoroethylene, PTFE). The PTFE layer introduces a built-in electrostatic field to highly enhance the photovoltaic effect, and its high internal resistance greatly reduces the dark current, and thus remarkable performances were achieved. The self-powered UV photodetector with PTFE demonstrated an extremely high on–off ratio of 2.49 × 105, a responsivity of 76.87 mA/W, a response rise time of 7.44 ms, and a decay time of 3.75 ms. Furthermore, the device exhibited exceptional stability from room temperature to 70 °C. Compared with the conventional ITO/TiO2 heterojunction without the PTFE layer, the photoresponse of the detector improved by 442-fold, and the light–dark ratio was increased by 8.40 × 105 times. In addition, the detector is simple, easy to fabricate, and low cost. Therefore, it can be used on a large scale. The electrostatic modulation effect is universal for various types of semiconductor junctions and is expected to inspire more innovative applications in optoelectronic and microelectronic devices.

Channel prediction permits to acquire channel state information (CSI) without signaling overhead. However, almost all existing channel prediction methods necessitate the deployment of a dedicated model to accommodate a specific configuration. Leveraging the powerful modeling and multi-task learning capabilities of foundation models, we propose the first space-time-frequency (STF) wireless foundation model (WiFo) to address time-frequency channel prediction tasks in a unified manner. Specifically, WiFo is initially pre-trained over massive and extensive diverse CSI datasets. Then, the model will be instantly used for channel prediction under various CSI configurations without any fine-tuning. We propose a masked autoencoder (MAE)-based network structure for WiFo to handle heterogeneous STF CSI data, and design several mask reconstruction tasks for self-supervised pre-training to capture the inherent 3D variations of CSI. To fully unleash its predictive power, we build a large-scale heterogeneous simulated CSI dataset consisting of 160k CSI samples for pre-training. Simulations validate its superior unified learning performance across multiple datasets and demonstrate its state-of-the-art (SOTA) zero-shot generalization performance via comparisons with other full-shot baselines.