急性缺血性脑卒中(AIS)是一种严重影响人类健康相关的疾病,其拥有高发病率和高死亡率,并与吸烟、高脂饮食等不良生活习惯相关,人工智能(AI)比如机器学习(ML)和深度学习(DL),可以实现从临床及辅助检查尤其是成像学检查中提取特征数据,经过算法处理,得出可信结果。近几年AI更多地应用于医院系统的工作中,并成为临床工作及科研项目有力的帮手。本文全面综述了AI预测急性缺血性脑卒中(AIS)患者在经过血管内治疗,尤其是经过血栓切除术治疗后的预后情况,从而实现精准有效的临床管理和护理决策。此外,本文还批判性地评估了现有研究的局限性,并且指出了新的研究方向,最终目标是提高AIS患者的生存率。Acute ischemic stroke (AIS) is a serious human health-related disease that is characterized by elevated morbidity and mortality rates. It is often linked to detrimental lifestyle behaviors, including smoking and high-fat dietary intake. The advent of artificial intelligence (AI), encompassing machine learning (ML) and deep learning (DL) methodologies, facilitates the extraction and analysis of feature data derived from clinical and ancillary assessments, particularly imaging studies. These data are processed through sophisticated algorithms to yield reliable outcomes. In recent years, AI has been increasingly integrated into hospital systems, emerging as a formidable tool in both clinical practice and research initiatives. This paper presents a comprehensive analysis of AI applications in predicting the prognosis of acute ischemic stroke (AIS) patients following endovascular interventions, with a particular focus on thrombectomy procedures. The objective is to enhance the accuracy and efficacy of clinical management and care decision-making processes. Furthermore, the study critically examines the limitations inherent in current research and identifies prospective avenues for future investigation, ultimately aiming to improve the survival outcomes of AIS patients.
肥胖与众多生殖系统疾病密切相关,如月经不调、生殖细胞质量下降以及流产等。肥胖通过DNA甲基化、组蛋白修饰以及非编码RNA表达等表观遗传学途径广泛影响卵母细胞和胚胎发育成熟的关键过程,这种影响不仅局限于胚胎发育阶段,还可能通过表观遗传修饰的跨代遗传对后代健康带来不良后果。本文对与母源肥胖导致卵母细胞质量下降相关的表观遗传学机制的研究进展进行综述,并联系已报道的相关机制提出干预标靶,以期改善表观遗传修饰对卵母细胞质量的消极影响。Obesity is closely associated with numerous reproductive system disorders, such as irregular menstruation, decreased germ cell quality, and miscarriages. Obesity broadly affects key processes in oocyte and embryo developmental maturation through epigenetic pathways, including DNA methylation, histone modification, and non-coding RNA expression. This impact is not limited to the embryonic development stage but may also lead to adverse outcomes for offspring health through the transgenerational inheritance of epigenetic modifications. This article reviews the research progress on the epigenetic mechanisms related to decreased oocyte quality caused by maternal obesity and proposes intervention targets based on reported related mechanisms, aiming to mitigate the negative effects of epigenetic modifications on oocyte quality.
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