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用于评估草酸钙晶体聚集程度的聚集指数的定义及系统分析。

Defining and Systematic Analyses of Aggregation Indices to Evaluate Degree of Calcium Oxalate Crystal Aggregation.

作者信息

Chaiyarit Sakdithep, Thongboonkerd Visith

机构信息

Medical Proteomics Unit, Office for Research and Development, Faculty of Medicine Siriraj Hospital; and Center for Research in Complex Systems Science, Mahidol University, Bangkok, Thailand.

出版信息

Front Chem. 2017 Dec 7;5:113. doi: 10.3389/fchem.2017.00113. eCollection 2017.

DOI:10.3389/fchem.2017.00113
PMID:29270403
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5725413/
Abstract

Crystal aggregation is one of the most crucial steps in kidney stone pathogenesis. However, previous studies of crystal aggregation were rarely done and quantitative analysis of aggregation degree was handicapped by a lack of the standard measurement. We thus performed an assay to generate aggregation of calcium oxalate monohydrate (COM) crystals with various concentrations (25-800 μg/ml) in saturated aggregation buffer. The crystal aggregates were analyzed by microscopic examination, UV-visible spectrophotometry, and GraphPad Prism6 software to define a total of 12 aggregation indices (including number of aggregates, aggregated mass index, optical density, aggregation coefficient, span, number of aggregates at plateau time-point, aggregated area index, aggregated diameter index, aggregated symmetry index, time constant, half-life, and rate constant). The data showed linear correlation between crystal concentration and almost all of these indices, except only for rate constant. Among these, number of aggregates provided the greatest regression coefficient ( = 0.997; < 0.001), whereas the equally second rank included aggregated mass index and optical density ( = 0.993; < 0.001 and = -0.993; < 0.001, respectively) and the equally forth were aggregation coefficient and span ( = 0.991; < 0.001 for both). These five indices are thus recommended as the most appropriate indices for quantitative analysis of COM crystal aggregation .

摘要

晶体聚集是肾结石发病机制中最关键的步骤之一。然而,以往关于晶体聚集的研究很少,且由于缺乏标准测量方法,聚集程度的定量分析受到阻碍。因此,我们进行了一项实验,在饱和聚集缓冲液中生成不同浓度(25 - 800μg/ml)的一水合草酸钙(COM)晶体聚集物。通过显微镜检查、紫外可见分光光度法和GraphPad Prism6软件对晶体聚集体进行分析,以确定总共12个聚集指数(包括聚集体数量、聚集质量指数、光密度、聚集系数、跨度、平台期时间点的聚集体数量、聚集面积指数、聚集直径指数、聚集对称指数、时间常数、半衰期和速率常数)。数据显示,除速率常数外,晶体浓度与几乎所有这些指数之间均呈线性相关。其中,聚集体数量的回归系数最大( = 0.997; < 0.001),其次是聚集质量指数和光密度并列第二(分别为 = 0.993; < 0.001和 = -0.993; < 0.001),聚集系数和跨度并列第四(两者均为 = 0.991; < 0.001)。因此,推荐这五个指数作为COM晶体聚集定量分析的最合适指数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/f4067931436f/fchem-05-00113-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/841abab2478a/fchem-05-00113-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/c4ac943c8793/fchem-05-00113-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/ce89441c79df/fchem-05-00113-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/776703a105ec/fchem-05-00113-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/f4067931436f/fchem-05-00113-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/841abab2478a/fchem-05-00113-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/c4ac943c8793/fchem-05-00113-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/ce89441c79df/fchem-05-00113-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/776703a105ec/fchem-05-00113-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f66/5725413/f4067931436f/fchem-05-00113-g0005.jpg

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