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Background Carotid atherosclerosis (CAS) is a significant indicator of early systemic atherosclerosis. Previous studies have demonstrated a close relationship between elevated remnant cholesterol (RC) levels and the pathogenesis of CAS. However, limited information is available regarding the association between RC and the development of CAS in menopausal women. Objective To investigate the correlation between RC and the pathogenesis of CAS in menopausal women. Methods A total of 307 menopausal women from Fengxiang Town, Anding District, Dingxi City were selected as the research subjects. These women had participated in the national high-risk stroke screening project and completed carotid artery ultrasound examination between January 2020 and October 2023. General information on the ordinary people was collected and participants' characteristics of the carotid artery intima were analyzed by means of using color doppler ultrasound. Based on the cervical ultrasound results, the subjects were divided into CAS group and non-CAS group. Spearman rank correlation analysis was used to explore the correlation between RC and other risk factors for CAS. Furthermore, multifactor Logistic regression was employed to analyze and explore the correlation between RC and CAS in menopausal women. Results The findings revealed that participants in the CAS group (n=130) has higher levels than those in the non-CAS group (n=177) in terms of menopausal female age, history of stroke and transient ischemic attack (TIA), fasting plasma glucose (FPG), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), RC and pulse pressure (P

In this paper, an additive margin network with adaptive feature recalibration, AMNets, for handling a wide range of visual tasks, is proposed. The new AMNets consists of three improvements on convolutional neural networks: (1) squeeze‐and‐excitation mechanism was embedded into the the residual block of single layer to improve the performance of the classification, (2) softmax loss was replaced by the additive margin softmax loss to minimize intra‐class variance and maximize inter‐class variance, and (3) Adam optimizer was exploited to update iteratively the network parameters. Experiments on the Brain Stroke CT Image Dataset show that our additive margin network is quite effective to improve state‐of‐the‐art algorithms. Network algorithms have been extensively used in medical image field to pursuit a more accuracy of disease recognition. This paper proposes AMNets, an additive margin network with adaptive feature recalibration for handling a wide range of visual tasks in medicine. [ABSTRACT FROM AUTHOR]

Background : Extracorporeal life support echniques as an Adjunct to Advanced Cardiac Life Support is usually suitable for complex heart surgery such as cardiopulmonary bypass (CPB). Cerebral perfusion is a clinically feasible neuroprotective strategy; however, the lack of a reliable small animal model. Methods : Based on the rat model of ECLS we evaluate the effects of ECLS-CP using HE staining, Nissl staining, TUNEL staining and ELISA. Result : We found that ECLS combined with the cerebral perfusion model did not cause brain injury and immune inflammation. There was no difference between the two by a left carotid artery or right carotid artery CP. Conclusion : These experimental results can provide the experimental basis for selecting blood vessels for ECLS patients and clinical CP to offers a trustworthy animal model for future exploration of applying brain perfusion strategies during ECLS-CP., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.