Histidine-rich glycoprotein as an excellent biomarker for sepsis and beyond

Masahiro Nishibori1, Hidenori Wake2, Hiroshi Morimatsu3

  • 1Department of Pharmacology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, Okayama, 700-8558, Japan. mbori@md.okayama-u.ac.jp.

Related Concept Videos

Microsoft Excel: Plotting Mean, SD, and SE01:18

Microsoft Excel: Plotting Mean, SD, and SE

In Microsoft Excel, plotting the mean along with standard deviation (SD) and standard error (SE) helps visualize data variability and reliability. To plot these values, follow these steps:
First, calculate the mean, SD, and SE of your data. The mean is obtained using the formula `=AVERAGE(range)`, while SD can be calculated with `=STDEV.P(range)` for a population or `=STDEV.S(range)` for a sample. SE is calculated as `=SD/SQRT(n)`, where `n` is the sample size.
To plot these values, use a bar...
1.3K
Microsoft Excel: Student's t-Test01:25

Microsoft Excel: Student's t-Test

Student's t-test in Microsoft Excel is a statistical method used to compare the means of two groups to determine if they are significantly different from each other. It's commonly used to evaluate hypotheses, such as testing whether a treatment has an effect compared to a control group. Excel provides built-in functions to perform t-tests, making it accessible for users needing to conduct basic statistical analysis.
To conduct a t-test in Excel, use the T.TEST function or the "Data...
1.7K
Microsoft Excel: Pearson's Correlation01:18

Microsoft Excel: Pearson's Correlation

Microsoft Excel is a powerful tool for statistical analysis, including calculating Pearson's correlation coefficient, which measures the strength and direction of a linear relationship between two continuous variables. Pearson's correlation coefficient, often denoted as "r," ranges from -1 to 1. A value close to 1 indicates a strong positive correlation, meaning as one variable increases, the other does too. A value close to -1 indicates a strong negative correlation, implying...
2.1K
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
1.6K
Matrix Proteoglycans and Glycoproteins01:21

Matrix Proteoglycans and Glycoproteins

Proteoglycans are extensively glycosylated proteins, commonly found in the extracellular matrix, interwoven with collagen fibers. Hyaline cartilage, the most common type of cartilage in the body, consists of short and dispersed collagen fibers associated with large amounts of proteoglycans. These proteoglycans have long negative charges that attract cations, which in turn attract water molecules. This influx of ions and water molecules swells up the proteoglycan like a water-soaked gel that can...
5.1K
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.6K