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Rheumatoid arthritis (RA) and arthrofibrosis (AF) are both chronic synovial hyperplasia diseases that result in joint stiffness and contractures. They shared similar symptoms and many common features in pathogenesis. Our study aims to perform a comprehensive analysis between RA and AF and identify novel drugs for clinical use. Based on the text mining approaches, we performed a correlation analysis of 12 common joint diseases including arthrofibrosis, gouty arthritis, infectious arthritis, juvenile idiopathic arthritis, osteoarthritis, post infectious arthropathies, post traumatic osteoarthritis, psoriatic arthritis, reactive arthritis, rheumatoid arthritis, septic arthritis, and transient arthritis. 5 bulk sequencing datasets and 4 single-cell sequencing datasets of RA and AF were integrated and analyzed. A novel drug repositioning method was found for drug screening, and text mining approaches were used to verify the identified drugs. RA and AF performed the highest gene similarity (0.77) and functional ontology similarity (0.84) among all 12 joint diseases. We figured out that they share the same key pathogenic cell including CD34 + sublining fibroblasts (CD34-SLF) and DKK3 + sublining fibroblasts (DKK3-SLF). Potential therapeutic target database (PTTD) was established with the differential expressed genes (DEGs) of these key pathogenic cells. Based on the PTTD, 15 potential drugs for AF and 16 potential drugs for RA were identified. This work provides a new perspective on AF and RA study which enhances our understanding of their pathogenesis. It also shed light on their underlying mechanism and open new avenues for drug repositioning studies. [ABSTRACT FROM AUTHOR]

The rapid development of industrial and information technology is driving the demand to improve the applicability and hydraulic performance of centrifugal pumps in various applications. Enhancing the rotational speed of pumps can simultaneously increase the head and reduce the impeller diameter, thereby reducing the pump size and weight and also improving pump efficiency. This paper reviews the current application status of high-speed pumps using low-temperature thermosensitive fluids, which have been applied in fields such as novel energy-saving cooling technologies, aerospace, chemical industries, and cryogenic engineering. Due to operational constraints and thermal effects, there are inherent challenges that still need to be addressed for high-speed pumps. Based on numerical simulation and experimental research for different working fluids, the results regarding cavitation within the inducer have been categorized and summarized. Improvements to cavitation models, the mechanism of unsteady cavity shedding, vortex generation and cavitation suppression, and the impact of cavitation on pump performance were examined. Subsequently, the thermal properties and cavitation thermal effects of low-temperature thermosensitive fluids were analyzed. In response to the application requirements of pump-driven two-phase cooling systems in data centers, a high-speed refrigerant pump employing hydrodynamic bearings has been proposed. Experimental results indicate that the prototype achieves a head of 56.5 m and an efficiency of 36.1% at design conditions (n = 7000 rpm, Q = 1.5 m3/h). The prototype features a variable frequency motor, allowing for a wider operational range, and has successfully passed both on/off and continuous operation tests. These findings provide valuable insights for improving the performance of high-speed refrigerant pumps in relevant applications. [ABSTRACT FROM AUTHOR]

This study utilized high-speed camera and large eddy simulation methods to explore the cavitating flow mechanisms and turbulence structures of R134a refrigerant inside a Venturi tube under varying cavitation numbers (CNs). Data-driven modal analysis approaches, proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD), were introduced to identify and extract the energy hierarchy and transient characteristics within the cavitating flow. The analysis of grayscale images indicated that the cavitating flow gradually transitioned from quasi-periodic to unsteady flow as the CN decreased, and the severity of cavitation correlates with lower peak frequencies. The POD analysis facilitated the extraction of coherent structures in the cavity's temporal evolution, and the results indicate that the quasi-ordering shedding and collapse of large-scale cavity clouds predominantly occur under low cavitation intensity conditions. As the CN increases, the influence of small-scale cavity shedding becomes more significant. The first 30 most energetic modes occupied over 75% of the entire energy, and they were used to reconstruct the cavitating flow, achieving good consistency with transient flow snapshots. Additionally, the DMD results of the cavitating flow yield three frequency spans, including several prominent characteristic frequencies. These spans are closely linked to the cavity cloud structures of varying scales, unveiling the structural characteristics of unsteady cavitating flow. [ABSTRACT FROM AUTHOR]