Promoting the proliferation of osteoarthritis chondrocytes by resolvin D1 regulating the NLRP3/caspase-1 signaling pathway.

Osteoarthritis (OA) is a degenerative joint disease commonly found in middle-aged and older people. Chondrocytes are the only cells in joint cartilage that are difficult to heal after pyroptosis, and they will aggravate the wear and tear of joint cartilage and affect the progression of OA. Pyroptosis is a novel form of programmed cell death, and the classical pyroptosis pathway is a programmed cell death pattern mediated by inflammatory cysteine protease-1. Activation of NLRP3 leads to activation and cleavage of caspase-1 precursors, which in turn leads to activation and cleavage of GSDMD proteins and the release of proinflammatory factors. Resolvin D1 (RvD1) is a specialized pro-resolving mediator (SPM) derived from omega-3 unsaturated fatty acids that reduces inflammation and catabolic responses in OA chondrocytes. However, it is unclear whether RvD1 promotes OA chondrocyte proliferation and thus joint cartilage repair. Our results show that RvD1 regulates the NLRP3/caspase-1 signaling pathway by inhibiting the expression of caspase-1, promoting the proliferation of OA chondrocytes, promoting the repair of articular cartilage in rats and delaying the progression of osteoarthritis.

Assembling Hybrid Energetic Materials with Controllable Interfacial Microstructures by Electrospray.

Constructing hybrid energetic materials (HEMs) consisting of nanothermites and organic high explosives is an efficient strategy to regulate the reactivity of energetic composites. To investigate the role of interfacial microstructures in determining the reactivity of HEMs, we employ electrospray, one ramification of electrohydrodynamic atomization, to assemble Al/CuO and hexanitrohexaazaisowurtzitane (CL-20) into composites with various morphologies from different solvent systems. The morphology and compositional information of the assembled clay-like or granular HEMs, which are obtained from ketone, ester, or mixtures of alcohol and ether, are confirmed by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). The phase transition of CL-20 due to the fast evaporation of charged droplets and insufficient time for recrystallization is studied by Fourier transform infrared spectroscopy (FTIR). Thermogravimetric-differential scanning calorimetry (TG-DSC) is applied to investigate the thermodynamic behaviors and synergistic effect of the nanothermite and high explosive. Enhancements in combustion performance and pressurization characteristics of the as-sprayed HEMs have been observed through open burn tests and pressure cell tests. Granular HEMs show high gas generation and high pressurization rate, while nitrocellulose (NC) fibers existing in the clay-like HEMs would weaken the reactivity to a certain extent. HEMs obtained from the mixture of n-propanol and diethyl ether, in which nano-CL-20 exists as independent particles rather than a matrix, exhibit high gas generation but low pressurization rate. The results indicate that the energy releasing performance of the prepared HEMs can be readily regulated by constructing various interfacial microstructures to satisfy the broad requirements of energy sources.

Gait recognition using radon transform and linear discriminant analysis.

A new feature extraction process is proposed for gait representation and recognition. The new system is based on the Radon transform of binary silhouettes. For each gait sequence, the transformed silhouettes are used for the computation of a template. The set of all templates is subsequently subjected to linear discriminant analysis and subspace projection. In this manner, each gait sequence is described using a low-dimensional feature vector consisting of selected Radon template coefficients. Given a test feature vector, gait recognition and verification is achieved by appropriately comparing it to feature vectors in a reference gait database. By using the new system on the Gait Challenge database, very considerable improvements in recognition performance are seen in comparison to state-of-the-art methods for gait recognition.