2020-2022年食蟹猴健康体检血清生化数据及参考区间

本数据集为2020-2022年中国科学院昆明动物研究所实验动物中心饲育食蟹猴健康体检的血清生化数据。对不同性别及年龄段（1-3岁、4-12岁）个体，基于分位法计算各指标95%参考区间，进一步通过Bootstrap方法计算置信区间。《2020-2022食蟹猴健康体检血清生化数据》数据项包括序号、品种、性别、年龄、血清生化（17项）；《2020-2022食蟹猴健康体检血清生化数据参考区间》数据项包括指标、原始样本数、移除异常值数、最终样本数、异常值百分比（%）、均值、中位数、标准差、2.5%分位数、97.5%分位数、参考区间、2.5%置信区间下限、2.5%置信区间上限、97.5%置信区间下限、97.5%置信区间上限。
数据质量：中国科学院单位研究所实验动物中心于2008年通过国际AAALAC认证，2018年全国首家通过CNAS认可，实验动物管理达到国际管理规范。中心配备先进的全自动生化分析仪，严格按照国际标准进行设备校准和维护。所有检测项目均采用经过验证的检测方法，确保检测结果的准确性和重现性。严格遵循标准化采样、处理、检测流程，确保样品从采集到检测全过程的标准化管理。建立了完善的样品保存和运输条件控制体系，最大程度减少预分析变异。本数据获取得到中国科学院昆明动物研究所实验动物福利伦理委员会批准（IACUC-PE-2020-03-001，IACUC-PE-2021-12-001，IACUC-PE-2022-12-001）。
数据来源：本数据来源于中国科学院昆明动物研究所实验动物中心临床检验平台（仪器型号为Dimension全自动生化分析仪 E-100），原始数据由仪器自动产生并采集。
数据生产方式：a.原始数据由检测平台产生（仪器型号为Dimension全自动生化分析仪 E-100），未经加工处理。

b.参考区间分析由R（Version 4.5.0）计算产生，使用异常值剔除+分位数法计算参考区间：先通过IQR/Z-score等方法检测并剔除异常值，然后计算剔除异常值后数据的2.5%-97.5%分位数作为95%参考区间，并用Bootstrap方法计算置信区间。
时间范围：2020年10月5日至2022年9月15日

This dataset contains serum biochemistry data from routine health examinations of captive cynomolgus monkeys (Macaca fascicularis) reared at the Laboratory Animal Center of Kunming Institute of Zoology, Chinese Academy of Sciences, covering the period from 2020 to 2022. For individuals of different sexes and age groups (1–3 years old, 4–12 years old), the 95% reference intervals for each indicator were calculated using the quantile method, and confidence intervals were further estimated via the Bootstrap method.

There are two associated datasets:
1. *2020–2022 Serum Biochemistry Data from Health Examinations of Cynomolgus Monkeys*, which includes the following data items: serial number, breed, sex, age, and 17 serum biochemistry indicators.
2. *2020–2022 Reference Intervals for Serum Biochemistry Data from Health Examinations of Cynomolgus Monkeys*, which includes the following data items: indicator name, original sample size, number of outliers removed, final sample size, outlier percentage (%), mean value, median, standard deviation, 2.5th percentile, 97.5th percentile, reference interval, lower bound of the 2.5% confidence interval, upper bound of the 2.5% confidence interval, lower bound of the 97.5% confidence interval, upper bound of the 97.5% confidence interval.

### Data Quality Assurance
The Laboratory Animal Center of Kunming Institute of Zoology, Chinese Academy of Sciences obtained international AAALAC (Association for Assessment and Accreditation of Laboratory Animal Care International) accreditation in 2008, and became the first institution in China to pass CNAS (China National Accreditation Service for Conformity Assessment) accreditation in 2018, ensuring its laboratory animal management complies with international standards. The center is equipped with advanced fully automatic biochemical analyzers, and strictly calibrates and maintains the equipment in accordance with international standards. All detection assays are validated to ensure the accuracy and reproducibility of test results. Standardized sampling, processing, and testing workflows are strictly followed to achieve standardized management of the entire sample lifecycle from collection to testing. A comprehensive system for sample storage and transportation condition control is established to minimize pre-analytical variability. This dataset was approved by the Institutional Animal Care and Use Committee (IACUC) of Kunming Institute of Zoology, Chinese Academy of Sciences, with approval numbers: IACUC-PE-2020-03-001, IACUC-PE-2021-12-001, IACUC-PE-2022-12-001.

### Data Source
This dataset was derived from the clinical testing platform of the Laboratory Animal Center of Kunming Institute of Zoology, Chinese Academy of Sciences, using the Dimension fully automatic biochemical analyzer (model E-100). Raw data was automatically generated and collected by the instrument.

### Data Generation Workflow
1. Raw data: Generated by the clinical testing platform (Dimension fully automatic biochemical analyzer, model E-100) without any post-processing.
2. Reference interval analysis: Calculated using R (Version 4.5.0). The reference intervals were derived using the outlier removal + quantile method: first, outliers were detected and removed via methods such as interquartile range (IQR) and Z-score, then the 2.5th–97.5th percentiles of the outlier-free dataset were calculated to establish the 95% reference interval. The Bootstrap method was used to calculate the confidence intervals.

### Time Scope
October 5, 2020 to September 15, 2022

搜集汇总

背景与挑战

背景概述

本数据集涵盖2020年至2022年中国科学院昆明动物研究所实验动物中心饲育的食蟹猴健康体检血清生化数据，包括17项生化指标，并基于分位法和Bootstrap方法计算了不同性别和年龄段的95%参考区间及置信区间。数据来源于标准化临床检验平台，通过国际认证和伦理审批，确保高质量和可靠性，适用于动物学和医学研究。