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Rationale: Prostate cancer has become one of the most threatening malignant tumors in men, leading to an imperative need to develop effective and safe therapies. Because of the unique metabolism of tumor cells, the tumor microenvironment (TME) exhibits distinctive properties compared with normal tissues, among which the pH difference has been utilized as an ideal antitumor strategy. Herein, we introduce a reactive oxygen species (ROS)-controlled-release nanosystem with TME-responsiveness by applying hollow mesoporous silica nanoparticles (HMSNs) as carriers loaded with calcium peroxide (CaO 2 ) and coated with polyacrylic acid (PAA) to construct the functional material CaO 2 @HMSNs-PAA. The differences in pH values and exogenous ROS scavenging abilities between the tumor tissue and normal tissues and the dual pH-responsiveness from CaO 2 and PAA lay a scientific foundation for the application of CaO 2 @HMSNs-PAA in the tumor-selective therapy for prostate cancer. Methods: The morphology and the structure of the nanosystem were characterized by the transmission electron microscope, scanning electron microscope, energy-dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, zeta potential, dynamic light scattering measurement, low-angle X-ray diffraction patterns and nitrogen adsorption/desorption isotherm. The CaO 2 loading capacity and release profiles in different buffer solutions were determined by inductively coupled plasma-mass spectrometry. The in vitro intracellular uptake of CaO 2 @HMSNs-PAA was explored on the PC-3 prostate cancer cell line via confocal laser scanning microscopy. The CCK-8 cell proliferation assay was conducted to evaluate the cytotoxicity of CaO 2 @HMSNs-PAA against PC-3 cells. ROS produced by CaO 2 @HMSNs-PAA was observed by a fluorescence microscope. The flow cytometry was utilized to analyze the apoptosis of PC-3 cells induced by CaO 2 @HMSNs-PAA. The Western blot analysis was performed to detect expressions of critical mitochondria-mediated apoptosis markers in PC-3 cells after incubation with CaO 2 @HMSNs-PAA. The in vivo biosafety and antitumor efficacy were evaluated out on BALB/c mice and BALB/c nude mice subcutaneously transplanted with PC-3 cells, respectively. Results: Comprehensive characterizations indicated the successful synthesis of CaO 2 @HMSNs-PAA with significant TME-responsiveness. The experimental results demonstrated that the well-developed nanocarrier could efficiently deliver CaO 2 to the tumor site and release ROS in response to the decreased pH value of TME, exerting ideal antitumor effects both in vitro and ...

The planetary gearbox is at the heart of most rotating machinery. The premature failure and subsequent downtime of a planetary gearbox not only seriously affects the reliability and safety of the entire rotating machinery but also results in severe accidents and economic losses in industrial applications. It is an important and challenging task to accurately detect failures in a planetary gearbox at an early stage to ensure the safety and reliability of the mechanical transmission system. In this paper, a novel method based on wavelet packet energy (WPE) and modulation signal bispectrum (MSB) analysis is proposed for planetary gearbox early fault diagnostics. First, the vibration signal is decomposed into different time-frequency subspaces using wavelet packet decomposition (WPD). The WPE is calculated in each time-frequency subspace. Secondly, the relatively high energy vectors are selected from a WPE matrix to obtain a reconstructed signal. The reconstructed signal is then subjected to MSB analysis to obtain the fault characteristic frequency for fault diagnosis of the planetary gearbox. The validity of the proposed method is carried out through analyzing the vibration signals of the test planetary gearbox in two fault cases. One fault is a chipped sun gear tooth and the other is an inner-race fault in the planet gear bearing. The results show that the proposed method is feasible and effective for early fault diagnosis in planetary gearboxes.

Transient impulses are important information for machinery fault diagnosis. However, the transient features contained in the vibration signals generated by planetary gearboxes are usually immersed by a large amount of background noise and harmonic components. Even mathematical morphology (MM) is an excellent anti-noise signal processing method that can directly extract the geometry of impulse features in the time domain, but the four basic operators of MM can only extract one-way impulses while cannot extract the bidirectional impulses effectively at the same time. To accurately extract the impulse feature information, a novel method for fault detection of planetary gearbox based on an enhanced average (EAVG) filter and modulated signal bispectrum (MSB) is proposed. Firstly, the properties of the extracted impulses based on the four basic operators of MM will be divided into two categories of enhanced average operators. The four EAVG filters consist of the average weighted combination of enhanced average operators, and then the best EAVG filter is selected based on correlation coefficient to implement on the original vibration signal. It allows EAVG filter to extract positive and negative impulses of vibration signal, thereby improving the accuracy of planetary gearbox fault detection.Subsequently, the performance of the EAVG filter is influenced by the length of its structural element (SE), which is adaptively determined using an indicator based kurtosis. Then, the EAVG filter selects the optimal SE length to eliminate the interference of background noise and harmonic components to enhance the impulse components of the vibration signal. However, the nonlinear modulation components that are related to the fault types and severities are not extracted exactly and still remained in the filtered signal by EAVG. Finally, the MSB is utilized to the EAVG filtered signal to decompose the modulated components and extract the fault features. The advantages of EAVG over average (AVG) filter are clarified in the simulation study. In addition, the EAVG-MSB is validated by analyzing the vibration signals of planetary gearboxes with sun gear chipped tooth, sun gear misalignment and bearing inner race fault. The results indicate that the EAVG-MSB is effective and accurate in feature extraction compared with the combination morphological filter-hat transform (CMFH) and average combination difference morphological filter (ACDIF), and the feasibility of the EAVG-MSB are proved for planetary gearbox condition monitoring and fault diagnosis.