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Three-section landslides are renowned for their immense size, concealed development process, and devastating impact. This study conducted physical model tests to simulate one special geological structure called a three-section-within landslide. The failure process and precursory characteristics of the tested samples were meticulously analyzed using video imagery, micro-seismic (MS) signals, and acoustic emission (AE) signals, with a focus on event activity, intensity, and frequency. A novel classification method based on AE waveform characteristics was proposed, categorizing AE signals into burst signals and continuous signals. The findings reveal distinct differences in the evolution of these signals. Burst signals appeared exclusively during the crack propagation and failure stages. During these stages, the cumulative AE hits of burst signals increased gradually, with amplitude rising and then declining. High-amplitude burst signals were predominantly distributed in the middle- and high-frequency bands. In contrast, cumulative AE hits of continuous signals escalated rapidly, with amplitude monotonously increasing, and high-amplitude continuous signals were primarily distributed in the low-frequency band. The emergence of burst signals and high-frequency AE signals indicated the generation of microcracks, serving as early-warning indicators. Notably, the early-warning points of AE signals were detected earlier than those of video imagery and MS signals. Furthermore, the early-warning point of burst signals occurred earlier than those of continuous signals, and the early-warning point of the classification method preceded that of overall AE signals.
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BACKGROUND: Augmented reality is a new technology that, when applied to spinal surgery, offers the potential for efficient, safe, and accurate placement of pedicle screws. This study investigated whether augmented reality combined with a guide board improved the safety and accuracy of pedicle screw placement compared to traditional free-hand screw placement. METHODS: Four trainers were divided into augmented reality navigation and free-hand groups. Each group consisted of a novice and an experienced spine surgeon. A total of 80 pedicle screws were implanted. First, the AR group reconstructed the 3D model and planned the screw insertion route according to the CT data of L2 lumbar vertebrae. Next, the Microsoft HoloLens™ 2 was used to identify the vertebral model, and the planned virtual path was superimposed on the real cone model. Next, the screw was placed according to the projected trajectory. Finally, Micron Tracker was used to measure the deviation of screws from the preoperatively planned trajectory, and pedicle screws were evaluated using the Gertzbein-Robbins scale. RESULTS: In the augmented reality group, the linear deviation of experienced doctors and novices was 1.59 ± 0.39 mm and 1.73 ± 0.52 mm, and the angle deviation was 2.72 ± 0.61° and 2.87 ± 0.63°, respectively. In the free-hand group, the linear deviation of experienced doctors and novices was 2.88 ± 0.58mm and 5.25 ± 0.62mm, and the angle deviation was 4.41 ± 1.18° and 7.15 ±1.45°, respectively. The screw accuracy rate was 97.5% in the augmented reality navigation group and 77.5% in the free-hand group. CONCLUSIONS: Augmented reality navigation improves the accuracy and safety of pedicle screw implantation compared with the traditional free-hand method and can assist inexperienced doctors in completing the surgery.
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A "signal-off" Electrochemiluminescence (ECL) biosensing platform based on Glutathione-Au nanoclusters covered reduced graphene oxide (GSH-Au NCs@rGO) and Au nanoparticles functionalized copper oxide (Au@CuO) was fabricated. The GSH ligand protected Au NCs were spontaneously adsorbed on the rGO surface via Van der Waals force. As ECL emitters, GSH-Au NCs@rGO not only support more luminophores and immobilization of bioreceptor units also facilitates mass transfer, accelerating ECL excitation to obtain a higher ECL signal intensity. Remarkably, Au@CuO with good biocompatibility was first applied as a quenching probe. Au@CuO (acceptor)-dependent resonance energy transfers (RET) with GSH-Au NCs@rGO (donor) could effectively quenched the ECL intensity to a reasonable range for requirements of trace analysis. The proposed ECL biosensing platform was evaluated with cardiac troponin I (cTnI) as a model analyte, achieving a low detection limit of 54.95 fg/mL. This strategy may provide as new approaches for the sensitive detection of biomarkers in the early clinical diagnosis of diseases.
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Técnicas Biosensibles , Nanopartículas del Metal , Cobre , Técnicas Electroquímicas , Glutatión , Oro , Límite de Detección , Mediciones Luminiscentes , ÓxidosRESUMEN
A sandwich-type electrochemical immunosensor was designed utilizing ferrocene-functionalized cuprous oxide superparticles (Au/Fc@CuxO SPs) as the signal label and graphene supported by hollow carbon balls (HCNs-GR) as the substrate. The CuxO SPs possess a superparticle structure with synergistic properties of isotropy and promising catalytic activity. Ferrocene (Fc) was deposited on the CuxO SPs to act as the electronic transmission medium. The Au/Fc@CuxO SPs played a pivotal role in improving the sensitivity of the immunosensor. The graphene supported by hollow carbon balls (HCNs-GR) was used to modify the electrode surface. The embedding of hollow carbon nanospheres (HCNs) reduced the decrease of the effective surface area caused by the stacking of graphene nanotubes. Meanwhile, the load of carbon balls further increases the surface area of graphene, enabled HCNs-GR to immobilize antibodies more effectively, improved the sensitivity of the immunosensor. The proposed immunosensor showed a linear range from 500 fg/mL to 100 ng/mL, with the detection limit to 25.7 fg/mL.