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Automated quantification of lipid droplets in fatty liver tissue sections

Automated quantification of lipid droplets in fatty liver tissue sections
脂肪肝组织切片中脂滴的自动定量
批准号:
8013389
负责人:
PATRICK M MCDONOUGH
金额:
$9.48万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-03-22 至 2011-07-31

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中文摘要
翻译
描述(由申请人提供):非酒精性脂肪性肝病(NAFLD)是一种新兴的健康危机,由肝细胞(肝细胞)内脂质积累引起。该疾病与酒精性肝病相似,首先出现脂滴(脂肪变性),然后是肝细胞损伤(脂肪性肝炎)、细胞死亡、炎症和肝硬化。令人担忧的是,在美国,NAFLD的发病率可能高达普通人群的30%,肥胖、糖尿病和丙型肝炎病毒感染患者的发病率甚至更高,这表明肝功能障碍和肝功能衰竭的发病率很快就会急剧上升。世界各地的研究人员正在研究人类患者和各种动物模型中的脂肪肝,使用半定量评分技术来估计肝脏脂肪变性的程度。第一阶段STTR项目的目标是开发图像分析技术,以量化肝脏活检和组织切片图像中脂肪变性的等级、脂肪百分比以及脂滴的频率和大小。所提出的算法在识别脂肪变性的细微变化方面特别有用,这些变化可能发生在利用实验疗法的研究中。该算法将根据脂肪肝领域的权威扎卡里·古德曼(Zachary Goodman)博士从人类肝脏活检中获得的图像进行开发,并将为量化脂肪变性提供一种新的研究工具,这将引起人类健康这一关键领域的研究人员的高度兴趣。公共卫生相关性:“脂肪肝”是一种影响美国人口比例很高的疾病,特别是超重或肥胖人群。脂肪肝的特点是在构成肝脏的细胞内出现脂肪滴。作为脂肪肝研究方案的一部分,通常从肝脏中提取组织样本(活检),病理学家使用显微镜和某种分级标准对样本的脂肪含量进行分级,充其量是半定量的。该研究将开发一种快速、精确的自动定量肝活检脂肪含量的技术,这将有助于研究脂肪肝疾病的工作人员。
英文摘要
DESCRIPTION (provided by applicant): Non-alcoholic fatty liver disease (NAFLD) is emerging as a health crisis and is caused by the accumulation of lipid within liver cells (hepatocytes). The disease is similar to alcoholic liver disease, as lipid droplets (steatosis) appear first, followed by damage to the hepatocytes (steatohepatitis), cell death, inflammation, and cirrhosis. Alarmingly, the incidence of NAFLD in the US may be as high as 30% of the general population, and occurs at even higher incidence in patients suffering from obesity, diabetes, and hepatitis C viral infection, indicating that there will soon be a dramatic increase in the rates of liver dysfunction and failure. Researchers world-wide are studying fatty liver in human patients and in a variety of animal models, using semi-quantitative scoring techniques to estimate the degree of hepatic steatosis. The goal of this Phase I STTR project is to develop image-analysis techniques to quantify the grade of steatosis, percentage of fat, and the frequency and size of lipid droplets in images obtained from liver biopsies and tissue sections. The proposed algorithm will be particularly useful in recognizing subtle changes in steatosis which are likely to occur in studies utilizing experimental therapeutics. The algorithm will be developed with images obtained from human liver biopsies by Dr. Zachary Goodman, a leading authority on fatty liver and will provide a new research tool for quantifying steatosis that will be of high interest to researchers in this critical area of human health. PUBLIC HEALTH RELEVANCE: "Fatty liver disease" is a condition that affects a high proportion of the US population, particularly people that are overweight or obese. Fatty liver is characterized by the occurrence of fat droplets within the cells that make up the liver. Tissue samples (biopsies) are commonly taken from livers as part of the protocol for research studies on fatty liver disease, and the fat content of the samples are graded by pathologists, using microscopes and somewhat grading criteria, that is, at best, semi-quantitative. The proposed research will develop a technique for rapid and precise automatic quantitation of the fat content of liver biopsies, which will be an aid to workers investigating fatty liver disease.
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The Pain in a Dish Assay (PIDA): a high throughput system featuring human stem cell-derived nociceptors and dorsal horn neurons to test compounds for analgesic activity
  • 批准号:
    10759735
  • 项目类别:
  • 资助金额:
    $35.01万
  • 财政年份:
    2023
  • 负责人:
    PATRICK M MCDONOUGH
  • 依托单位:
海外基金