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相关概念视频

Correlation and Regression00:53

Correlation and Regression

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In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
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Correlation01:09

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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
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Correlation and Causation01:27

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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
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The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable, x, and the dependent variable, y. Hence, it is also known as the Pearson product-moment correlation coefficient. It can be calculated using the following equation:
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Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
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探索两者之间的相关性

Xianhua Gu1, Honghong Shen2, Zheng Xiang3

  • 1Department of Gynecology Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, People's Republic of China.

Pharmacogenomics and personalized medicine
|June 7, 2023
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概括
此摘要是机器生成的。

在胃癌 (GC) 中高GPR176表达与预后不佳和免疫逃避相关. 这种孤儿G蛋白结合受体 (GPCR) 抑制CD8+T细胞,表明其作为胃癌患者预测生物标志物的作用.

关键词:
在 GPR176 中使用.胃癌 胃癌 是一种胃癌.免疫系统的逃脱是免疫逃脱.免疫疗法 免疫疗法瘤微环境是一个微环境.

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科学领域:

  • 在瘤学瘤学.
  • 免疫学 免疫学 免疫学
  • 遗传学 是一个遗传学.

背景情况:

  • 胃肠道癌症,包括胃癌 (GC),受到G蛋白结合受体176 (GPR176) 的显著影响.
  • GPR176在调节瘤免疫力和GC患者结局方面的精确作用仍然在很大程度上未被描述.

研究的目的:

  • 为了研究GPR176在胃癌组织和正常的胃粘膜中的表达模式.
  • 评估GPR176表达,患者预后和GC中的瘤免疫透之间的关联.

主要方法:

  • 利用癌症基因组图集 (TCGA) 和基因表达总汇 (GEO) 数据库进行表达分析.
  • 进行免疫组织化学和定量实时聚合酶链反应 (qRT-PCR) 进行验证.
  • 采用卡普兰-梅尔,后勤回归和考克斯回归分析来评估临床相关性和预后价值.

主要成果:

  • 与正常组织相比,胃癌组织表现出明显更高的GPR176表达.
  • 在GC患者中,高GPR176表达与较差的10年整体存活 (OS) 有关 (p < 0.001).
  • 根据TIDE和IPS分析,GPR176表达与CD8+T细胞透负相关,并与增加的免疫逃避有关.

结论:

  • GPR176作为一种有价值的预测生物标志物,用于胃癌患者不良预后.
  • 通过抑制CD8+ T细胞增殖,GPR176有助于GC中的免疫逃避.