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2,047 results on '"Li, Xinxin"'

8. Comparing survival outcomes between neoadjuvant and adjuvant chemotherapy within T2N1M0 stage hormone receptor-positive, HER2-negative breast cancer: a retrospective cohort study based on SEER database

Author

Shang, Yuhang, Wang, Xuelian, Liu, Yansong, Cheng, Weilun, Duan, Yunqiang, Fang, Zhengbo, Liu, Jiangwei, Kong, Fanjing, Wang, Ting, Yu, Tianshui, Hu, Anbang, Zhang, Jiarui, Zhang, Hanyu, Li, Mingcui, Rong, Zhiyuan, Li, Yanling, Shakila, Suborna S., Li, Xinxin, Feng, Jianyuan, Ma, Fei, and Guo, Baoliang

Published
2024
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12. Nanoparticles and their application in the diagnosis of hepatocellular carcinoma

Author

Li Xinxin, Cao Weihua, Zhang Ziyu, Wang Shiyu, Jiang Tingting, Deng Wen, Yang Liu, Bi Xiaoyue, Lin Yanjie, Lu Yao, Zhang Lu, Xu Mengjiao, Yi Wei, Xie Yao, and Li Minghui

Subjects
hepatocellular carcinoma, nanoparticles, nanobiotechnology, diagnosis, surface engineering of nanoparticles, Technology, Chemical technology, TP1-1185, Physical and theoretical chemistry, QD450-801
Abstract

Most patients are at advanced stages when they are diagnosed with hepatocellular carcinoma, leading to poor prognosis and a low 5-year survival rate. Serological markers, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography, and liver biopsy are the common clinical diagnostic techniques for liver cancer. Effective interventions in the early stage will be beneficial to improve the prognosis of liver cancer patients and reduce the global burden. Therefore, it is urgent to develop new diagnostic methods to improve the diagnosis and management of liver cancer. Nanotechnology has become a new frontier subject in medical detection along with the application of nanomaterials in the manufacture of drug carriers, diagnostic tools, and therapeutic devices. Many studies have shown that nanoparticles (NPs) can be applied to the clinical diagnosis of liver cancer in combination with existing technologies, providing a new method for the early diagnosis of liver cancer. In this review, we elaborate on the theoretical basis and characteristics of NPs in the diagnosis of liver cancer, and the research progress and prospects of NPs in the diagnosis of liver cancer are summarized.

Published
2024
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32. Optimization and Scheduling of Integrated Energy Systems With Carbon Capture and Storage-Power to Gas Based on Information Gap Decision Theory

Author

ZHAO Zhenyu, BAO Geriletu, and LI Xinxin

Subjects
integrated energy system, scenario generation, information gap decision theory(igdt), carbon capture and storage(ccs), power to gas(p2g), stepped carbon trading, Applications of electric power, TK4001-4102, Production of electric energy or power. Powerplants. Central stations, TK1001-1841, Science
Abstract

ObjectivesThe main issue in the current rational optimization of integrated energy systems is to adopt technological means to improve energy conversion efficiency, reduce system energy waste and regional environmental pollution, in order to scientifically coordinate the optimization goals of economic, stability, and low-carbon operation of the integrated energy system. To this end, a low-carbon optimization strategy for a carbon capture and storage (CCS)two-stage power to gas (P2G)integrated energy system based on scenario generation and information gap decision theory (IGDT) was proposed.MethodsAt the technical level, by finely modeling the two-stage conversion from power to gas, the efficiency of hydrogen energy utilization was improved, and a combined heating and power (CHP)-CCS-P2G coupling model was established. At the market mechanism level, a tiered carbon trading model was introduced to reduce CO2 emissions in the system. Finally, based on the IGDT, an optimization scheduling model was constructed for different risk preferences.ResultsTaking a typical integrated energy system as an example, the simulation results show that the proposed model can improve the wind and solar energy consumption rate, achieve low-carbon, economic, and stable operation of the system.ConclusionsThis optimization strategy can effectively help decision-makers develop scheduling plans under risk avoidance and risk pursuit strategies based on their risk preferences, achieving a balance between system uncertainty and economy.

Published
2024
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33. Research progress in the artificial intelligence-assisted measurement of myocardial strain

Author

LI Xinxin, BIAN Yize, ZHAO Hang, and JIANG Meng

Subjects
myocardial strain, artificial intelligence (ai), myocardial damage, Medicine
Abstract

Myocardial strain is a dimensionless parameter reflecting the degree of deformation of the whole or local myocardium under stress, which can quantitatively detect myocardial injury and guide the early diagnosis, intervention and prognostic assessment of cardiac diseases. Cardiac ultrasound, cardiac CT and cardiac magnetic resonance can all be used for strain imaging and analysis, with two-dimensional speckle-tracking echocardiography being the most widely used means of myocardial strain detection today. However, due to inter-observer variations in manual analysis of myocardial strain and differences in the imaging systems and analysis software, the consistency and reproducibility of measured strain values among vendors are poor, limiting the clinical application of myocardial strain. Artificial intelligence (AI) can overcome the defects of strain measurement to a certain extent through automatic strain calculation and image quality assessment, which has a broad developmental prospect. This review focuses on the progress of AI-assisted measurement of myocardial strain in ultrasound, magnetic resonance, and other imaging modalities, as well as its application to disease diagnosis and patient prognosis assessment. This will improve the efficiency and consistency of strain measurement and promote the routine application of myocardial strain to clinical practice, which will play an incremental role in assessing myocardial injury and cardiac function. However, most of the current studies involve small sample sizes and lack external validation, and the reliability of their results needs to be further verified.

Published
2024
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