Brain-machine interfaces are promising tools to restore lost motor functions and probe brain functional mechanisms. As the number of recording electrodes has been exponentially rising, the signal processing capability of brain-machine interfaces is falling behind. One of the key bottlenecks is that they adopt conventional von Neumann architecture with digital computation that is fundamentally different from the working principle of human brain. In this work, we present a memristor-based neural signal analysis system, where the bio-plausible characteristics of memristors are utilized to analyze signals in the analog domain with high efficiency. As a proof-of-concept demonstration, memristor arrays are used to implement the filtering and identification of epilepsy-related neural signals, achieving a high accuracy of 93.46%. Remarkably, our memristor-based system shows nearly 400× improvements in the power efficiency compared to state-of-the-art complementary metal-oxide-semiconductor systems. This work demonstrates the feasibility of using memristors for high-performance neural signal analysis in next-generation brain-machine interfaces.
Fully implantable neural interfaces with massive recording channels bring the gospel to patients with motor or speech function loss. As the number of recording channels rapidly increases, conventional complementary metal-oxide semiconductor (CMOS) chips for neural signal processing face severe challenges on parallelism scalability, computational cost, and power consumption. In this work, we propose a previously unexplored approach for parallel processing of multichannel neural signals in memristor arrays, taking advantage of their rich dynamic characteristics. The critical information of neural signal waveform is extracted and encoded in the memristor conductance modulation. A signal segmentation scheme is developed to adapt to device variations. To verify the fidelity of the processed results, seizure prediction is further demonstrated, with high accuracy above 95% and also more than 1000× improvement in power efficiency compared with CMOS counterparts. This work suggests that memristor arrays could be a promising multichannel signal processing module for future implantable neural interfaces.
Bone scaffolds play an important role in promoting the healing of large bone defects. However, the type of scaffold material, type of drug loaded into the scaffold, and method of preparation have a significant impact on the scaffold's properties. In this study, we developed a composite scaffold comprising sodium alginate (SA), chitosan (CS), and hydroxyapatite (HA). The composite stent carries vascular endothelial growth factor (VEGF), wrapped in internal microspheres, and vancomycin (VAN). The microspheres are wrapped in an outer matrix formed by SA, CS, and HA, whereas the outer matrix carries VAN. Using Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction, and scanning electron microscopy analyses, we studied the contraction rate, swelling, porosity, mechanical properties, degradation, and drug release ability of all the composite scaffolds. The best scaffold, as demonstrated by the results of these studies, was the HA6(SA/CS)4@VAN/VEGF scaffold. The antibacterial ability of the HA6(SA/CS)4@VAN/VEGF scaffold was determined using Staphylococcus aureus (S. aureus). Cytotoxicity, cell adhesion, and osteogenic properties of the HA6(SA/CS)4@VAN/VEGF scaffold were studied using bone marrow mesenchymal stem cells. The results indicate that the HA6(SA/CS)4@VAN/VEGF scaffold exhibits good physical, chemical, antibacterial, and osteogenic properties, and is, thus, a new type of bone scaffold composite material with good osteogenic potential.
Background: Ginsenosides are pharmacologically active compounds that are often extracted from the Panax plant for their medicinal properties. Ginsenosides have multiple effects, including antitumor effects which have been widely studied. In recent years, studies have found that ginsenosides promote proliferation and osteogenesis of osteoblastrelated cells, as well as inhibit the activity of osteoclasts. Main body: We briefly introduces the molecules and BMP, WNT, and RANKL signalling pathways involved in bone formation and bone resorption. Next, recent studies on the mechanism of action of ginsenosides in bone remodelling are reviewed from three perspectives: the effects on proliferation of osteoblast-related cells, effects on osteogenesis and effects on osteoclasts. To expedite the development of drugs containing ginsenosides, we summarize the multiple beneficial roles of various types of ginsenosides in bone remodelling; including the promotion of bone formation, inhibition of bone resorption, and anti-inflammatory and antioxidant effects. Conclusion: Many ginsenosides can promote bone formation and inhibit bone resorption, such as Rb1, Rb2 and Re. Ginsenosides have the potential to be new drugs for the treatment of osteoporosis, promote fracture healing and are strong candidates for cytokines in the tissue-engineered bone. This review provides a theoretical basis for clinical drug applications and proposes several future directions for exploring the beneficial role of ginseng compounds in bone remodelling.
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