相关实验视频
Updated: May 16, 2025

11:39
A Quantitative Fitness Analysis Workflow
Published on: August 13, 2012
14.4K
在工业生物工艺监测中用于高通量代谢物分析的定量H NMR优化
Yingting Shi1, Yuxiang Wan2, Yiru Wang3
1Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
Analytical and bioanalytical chemistry
|April 1, 2025
概括
本研究引入了一种用于生物过程监测的快速定量1H NMR (qNMR) 方法. 优化的技术显著减少了分析时间,同时保持了对代谢物量化的高准确性.
科学领域:
- 分析化学 分析化学
- 生物技术是生物技术.
- 工艺工程是过程工程.
背景情况:
- 定量1HNMR (qNMR) 对于生物过程监测非常有价值,因为它可以全面检测代谢物.
- 传统的qNMR方法耗时,阻碍了高通量生物过程分析.
- 代谢物纵向放松时间 (T1) 导致实验持续时间较长.
研究的目的:
- 开发一种高通量1H qNMR方法,用于高效的生物过程分析.
- 为了减少qNMR的分析时间,而不会影响量化准确性.
- 提供一种可用于优化生物工艺和提高产量的方法.
主要方法:
- 实施了短暂的放松延迟 (D1),以加速1H qNMR实验.
- 使用修正因子 (k) 来考虑不完全的代谢物放松.
- 量化了使用光谱解卷与峰值拟合和MCR-ALS的27种代谢物.
主要成果:
- 开发的高通量qNMR方法在各种D1值中表现出高精度和准确性.
- 量化极限 (LOQ) 从0.008到0.13毫米不等,检测极限 (LOD) 从0.024到0.38毫米不等.
- 为了平衡分析时间和分析性能,确定了4秒的最佳D1值.
结论:
- 开发的高通量1H qNMR方法适用于快速的生物过程监测和控制.
- 这种方法为优化中国仓鼠卵巢 (CHO) 细胞培养过程提供了宝贵的见解.
- 这种方法可以显著提高生物工艺的整体产量和效率.
相关概念视频
Quantitative Analysis
227
Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...
227
Qualitative Analysis
195
Qualitative analysis is the process of identifying elements, ions, or compounds in an unknown sample. It is the first and most fundamental type of analysis based on the hierarchy of analytical goals. This hierarchy is significant as it provides a structured approach to scientific research, with qualitative analysis serving as the initial step, providing essential information before moving on to quantitative or other forms of analysis.
There are two main approaches to qualitative analysis:...
There are two main approaches to qualitative analysis:...
195
Statistical Analysis: Overview
5.3K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
5.3K
Development of Analytical Methods
359
An analytical methodology can be divided into four sequential steps: technique, method, procedure, and protocol. A technique is a scientific principle that rationalizes a specific phenomenon through chemical measurements. Adapting a technique for analyzing a sample of interest is termed a method. The procedure outlines the directions for performing the analysis via an analytical method. The protocol is the detailed guidelines on the procedure, which should be strictly followed to obtain the...
359
Statistical Methods for Analyzing Epidemiological Data
250
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
250
How Data are Classified: Numerical Data
27.3K
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
27.3K

