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The neurological complications following cardiovascular surgery can significantly affect the prognosis of patients. As a convenient and non⁃invasive intraoperative neurological monitoring method, transcranial Doppler ultrasonography (TCD) can provide real⁃time assessment of cerebral hemodynamics and microemboli signals, guide the development of neuroprotective strategies, and reduce the brain injury events. This review systematically summarizes the basic methods and technical performance of TCD monitoring, its clinical application in cardiovascular surgery, as well as the main limitations and future trends of this technology, in order to improve perioperative safety.

Brain and heart comorbidity is one of the major public health problems in China, which seriously threatens national health. After many years of exploration, the concept of "synchronous treatment for brain and heart" has become more and more accepted. This article summarizes the pathophysiological mechanism of brain ⁃ heart interaction, the clinical and research practice of the theory of "synchronous treatment for brain and heart", and its future development direction, and jointly help the diagnosis and treatment of brain and heart comorbidity.

Objective To investigate whether serum cystatin C (Cys C) is a potential risk factor for motoric cognitive risk syndrome (MCR) in Chinese elderly. Methods A total of 1592 elderly people were included in the subcohort from Rugao Longevity and Aging Study (RuLAS) at the third follow⁃up in 2019. The presence of subjective memory complaints was assessed by Geriatric Depression Scale (GDS⁃15) and the presence of slow walking speed was assessed by the 5⁃Meter Walking Speed Test. The presence of both symptoms was determined as MCR (n = 132). According to the serum Cys C level, the patients with serum Cys C level < 1.06 mg/L were classified as low level group (n = 794), and the patients with serum Cys C level ≥ 1.06 mg/L were classified as middle and high level group (n = 798). Univariate and multivariate stepwise Logistic regression were used to analyze whether elevated serum Cys C levels increased the risk of MCR. Results Compared with non⁃MCR group, MCR group had higher age (P = 0.041), female proportion (P = 0.027), farmer occupation (P = 0.044), married status (P = 0.034), cerebral vascular disease (P = 0.015), higher Cys C level (P = 0.023). Compared with the Cys C low level group, the Cys C middle and high level group had higher age (P = 0.000), male (P = 0.000), hypertension (P = 0.006), MCR (P = 0.049), and lower farmer proportion (P = 0.001); there was significant difference in smoking status (P = 0.041). Logistic regression analysis showed that increased Cys C level was a risk factor for the occurrence of MCR (OR = 1.419, 95%CI: 1.027-1.962; P = 0.034). Conclusions The incidence of MCR is higher in older people, female, farmers and the elderly with the history of cerebral vascular disease, and increased Cys C level is a potential risk factor for MCR.

Frailty is a geriatric syndrome caused by a decrease in multi ⁃ system physiological reserve and function, which reduces the elderly's ability to stress the internal and external environment and maintain homeostasis, and increases the risk of adverse health events. The incidence of frailty and pre ⁃ frailty in stroke patients is the highest and significantly higher than that in non ⁃ stroke patients, while the prevalence of cerebrovascular disease in frailty patients is also significantly increased and the prognosis is worse. This paper intends to review the potential association between frailty and cerebrovascular disease.

Schistosomiasis is a tropical disease that poses a significant risk to hundreds of millions of people, yet often goes unnoticed. While praziquantel, a widely used anti‐schistosome drug, has a low cost and a high cure rate, it has several drawbacks. These include ineffectiveness against schistosome larvae, reduced efficacy in young children, and emerging drug resistance. Discovering new and active anti‐schistosome small molecules is therefore critical, but this process presents the challenge of low accuracy in computer‐aided methods. To address this issue, we proposed GNN‐DDAS, a novel deep learning framework based on graph neural networks (GNN), designed for drug discovery to identify active anti‐schistosome (DDAS) small molecules. Initially, a multi‐layer perceptron was used to derive sequence features from various representations of small molecule SMILES. Next, GNN was employed to extract structural features from molecular graphs. Finally, the extracted sequence and structural features were then concatenated and fed into a fully connected network to predict active anti‐schistosome small molecules. Experimental results showed that GNN‐DDAS exhibited superior performance compared to the benchmark methods on both benchmark and real‐world application datasets. Additionally, the use of GNNExplainer model allowed us to analyze the key substructure features of small molecules, providing insight into the effectiveness of GNN‐DDAS. Overall, GNN‐DDAS provided a promising solution for discovering new and active anti‐schistosome small molecules. [ABSTRACT FROM AUTHOR]

The female infant in this case study was admitted to the hospital 4 hours after birth due to preterm birth and respiratory distress. On the third day after birth, peripherally inserted central venous catheter (PICC) catheterization was performed. On day 42, thrombus was found at the entrance of the right atrium from the inferior vena cava during a cardiac ultrasound, and it was considered to be related to PICC placement. Low-molecular-weight heparin and urokinase were given. After two weeks of treatment, ultrasonic monitoring showed thrombus shrinkage. No bleeding or pulmonary embolism occurred during the treatment. The patient discharged after improvement. This article mainly introduces a multidisciplinary team approach to diagnosis and treatment of PICC-related thrombosis in neonates. [ABSTRACT FROM AUTHOR]

The Guanzhong Plain of Shaanxi Province is a severely afflicted hemorrhagic fever with renal syndrome (HFRS) epidemic area, while HFRS prevalence has decreased in most epidemic areas in China. Little information is available regarding the leading fine-scale influencing factors in this highly HFRS-concentrated area and the roles of natural environmental and socioeconomic factors. To investigate this, two regions in the Guanzhong Plain, that is, the Chang'an District and Hu County, with similar geographical environments, different levels of economic development, and high epidemic prevalence, were chosen as representative areas of the HFRS epidemic. Maximum entropy models were constructed based on HFRS cases and fine-scale influencing factors, including meteorological, natural environmental, and socioeconomic factors, from 2014 to 2016. More than 95% of the HFRS cases in the study area were located in the northern plains, which has an altitude of less than 800 m, with topography contributed 84.1% of the impact on the spatial differentiation of the HFRS epidemic. In the northern plains, precipitation and population density jointly affected the spatial differentiation of the HFRS epidemic, with contribution rates of 60.7% and 28.0%, respectively. By comparing the influencing factors of the northern plains of Chang'an District and Hu County, we found that precipitation and the normalized difference vegetation index (NDVI) dominated the HFRS epidemic in the relatively developed Chang'an District, while land-use type, temperature, precipitation and population density dominated the HFRS epidemic in the relatively undeveloped Hu County. Topography was the primary key factor for HFRS prevalence in the Chang'an District and Hu County, and the spatial differentiation of HFRS was dominated by precipitation and population density in the northern plains. Compared with the influencing factors of the relatively developed Chang'an District, the developing Hu County was more affected by socioeconomic factors. When formulating targeted HFRS epidemic prevention and control strategies in the targeted areas, it is crucial to consider the local economic development state and combine natural environmental factors, including the meteorological environment and vegetation coverage. [ABSTRACT FROM AUTHOR]