Search

To respond to travel demand in the MaaS system, improve transport efficiency, and optimize the framework of MaaS, we propose a travel demand response model based on a spatiotemporal preference clustering algorithm that considers the impact of travel preferences and features of the MaaS system to improve travel demand response and achieve full coverage of travel demands. Specifically, in the MaaS system, the time preference hierarchical clustering algorithm is optimized with travel preference as the perception factor and preference priority order as the iteration index. Then, we cluster the departure and arrival times of reservation demand points and iteratively analyze the discrete points to obtain the set of reservation demand points with convergent time dimensions under similar preferences. Then, the spatial preference DBSCAN clustering algorithm is improved with travel preference and preference priority order as the iteration indices, and spatial clustering of the time-dense points are updated by the silhouette coefficient to obtain reservation demand points with similar spatiotemporal preference and respond to the demands. Meanwhile, traffic resources are coordinated by the MaaS system and the flexible means of transport are deployed to spatiotemporal discrete points to achieve full coverage of travel demand. Simulation shows that when the neighborhood range is 0.5 km and the least number of reservation demand sites is 3, our spatiotemporal model achieves a response rate of reservation demand points at 95%, and a demand coverage rate of 100%, which is 15% and 6.7% higher than the hierarchical clustering model and the DBSCAN clustering model, respectively. The demand response rate is also improved compared to the spatiotemporal clustering model in the customized bus model. The model and algorithm have some applicability and can be applied to areas with fixed, semifixed and flexible route transport, thereby considerably improving the travel demand response efficiency and transport service quality. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is a common malignant tumor around the world. Studying the unique constitution of CRC patients is conducive to the application of personalized medical treatment for CRC. The most common types of constitution in CRC are cold and heat constitution. A previous study has suggested that the malignant progression in cold and heat constitution CRC are different; however, the mechanism remains unclear. The tumor microenvironment (TME) is likely to vary with each individual constitution, which may affect the tumor growth in different constitutions. The extracellular matrix (ECM), the most important component of TME, plays a critical role in disease progression and outcome in patients with CRC. Moreover, collagen, the major component of the ECM, determines the main functional characteristics of ECM and tissue fibrosis caused by collagen deposition, which is one of the signs of CRC malignant progression. This study aimed to explore the mechanisms leading to different colorectal carcinogenesis paradigms between the cold constitution and heat constitution within the context of ECM collagen deposition. We established the CRC rat models and enrolled 30 CRC patients with cold and heat constitution. The collagen-related parameters were detected by using Sirius red staining combined with polarized light microscope, and expressions of collagen (COL I and COL III) and lysyl oxidase (LOX and LOXL2) were determined using immunohistochemistry, while the mRNA levels of COL1A1, COL3A1, LOX, and LOXL2 were measured by qRT-PCR. We found that a higher degree of collagen deposition in the cold-constitution group. The results suggest cold and heat constitution may affect the colorectal carcinogenesis paradigm by influencing the early collagen deposition in colon tissue. The study may provide an effective idea for clinicians to improve the prognosis of CRC patients with different constitutions. [ABSTRACT FROM AUTHOR]

Chondrocytes are the sole cellular constituents of normal cartilage. The degeneration and apoptosis of these cells are considered the main cause of osteoarthritis (OA). Previous studies have suggested that the enhancement of autophagy in chondrocytes can delay the progression of osteoarthritis by affecting intracellular metabolic activity, i.e., by regulating the metabolism of nutrients, which can delay cell aging and death. In this review, we explored the relationship between autophagy and chondrocyte metabolism and provided new ideas for the prevention and treatment of OA. [ABSTRACT FROM AUTHOR]