Question about ELISA sample values â€‹â€‹below the blank value

In ELISA experiments, a sample value below the blank value is a recurring problem. When the sample value is lower than the sensitivity of the kit, it is prone to the phenomenon that the sample value is lower than the blank value, especially in the detection of serum and plasma samples. The reason is mainly in two aspects, one is the error and the other is the matrix effect. The principles and solutions for different influencing factors are analyzed one by one below.
First, the error Error
Errors fall into three categories, system errors, random errors, and gross errors. Among these three types of errors, the systematic error has no effect on the difference between the sample value and the blank value. The ELISA sample values â€‹â€‹below the blank value are mainly derived from random errors and gross errors in error.

1, random error Random Error
Uncontrollable causes cause the measured values â€‹â€‹to produce randomly distributed errors, subject to a statistically normal distribution. Statistically, the measured value has a 99% confidence limit of Â±3SD. If the CV value is 20%, the boundary of the random error is Â±60%, that is, the sample value is 20% of the CV value. Below 60% of the blank value, there may be a random error, especially if the blank value has only one value.
The random error cannot be eliminated, and the mean obtained by multiple measurements can only be approximated to the true value as much as possible. Solution 1 to reduce the random error is to increase the number of repetitions of the blank value. It is generally considered that the blank value is repeated 10 times, and the measured mean is close to the true value.
Option 2 is to improve the experimental skills and also effectively reduce the impact of random errors. If the CV value is 5% and the sample value approaches zero, the sample value will not be statistically lower than the blank value by 15%.
2, gross error Gross Error
The error of error is mainly caused by the negligence of the measurer and the undue error. Negligence errors can be avoided. For the problem that the ELISA sample value is lower than the blank value, the cause of the error is mostly due to the repeated loading of the blank hole HRP or the contamination or the washing is not clean, resulting in a high blank value. In contrast, the sample value is lower than the blank value. value. The solution is to repeat the experiment and standardize the operation.
Second, the matrix effect Matrix Effect
In the analysis, the matrix refers to components other than the analyte in the sample. The matrix often has significant interference with the analytical process of the analyte and affects the accuracy of the analytical results. These effects and interferences are called matrix effects. During the development of the ELISA kit, the standard product cannot use human or animal serum or plasma as a dilution of the standard curve, and only the mimics can be used. There are differences in the protein abundance, complexity, pH and other factors between the simulated and tested samples. When the matrix of the sample reduces the binding of the antigen-antibody compared to its mimetic, a phenomenon in which the sample value is lower than the blank value is produced. Causes the sample value to fail to calculate the value, or the value is negative.
The most common method of removing the matrix effect at present is to establish a calibration curve by using a standard sample of known analyte concentration while keeping the matrix in the sample as constant as possible.
When a single sample or a small number of sample values â€‹â€‹is lower than the blank value, it may be the cause of the error. In this case, repeating should be added to improve the operation skill. When a large number of samples are below the blank value, the influence of the matrix effect should be considered, and a calibration curve should be established to be corrected.
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In ELISA experiments, a sample value below the blank value is a recurring problem. When the sample value is lower than the sensitivity of the kit, it is prone to the phenomenon that the sample value is lower than the blank value, especially in the detection of serum and plasma samples. The reason is mainly in two aspects, one is the error and the other is the matrix effect. The principles and solutions for different influencing factors are analyzed one by one below. First, the error Error Errors fall into three categories, system errors, random errors, and gross errors. Among these three types of errors, the systematic error has no effect on the difference between the sample value and the blank value. The ELISA sample values â€‹â€‹below the blank value are mainly derived from random errors and gross errors in error.
1, random error Random Error Uncontrollable causes cause the measured values â€‹â€‹to produce randomly distributed errors, subject to a statistically normal distribution. Statistically, the measured value has a 99% confidence limit of Â±3SD. If the CV value is 20%, the boundary of the random error is Â±60%, that is, the sample value is 20% of the CV value. Below 60% of the blank value, there may be a random error, especially if the blank value has only one value. The random error cannot be eliminated, and the mean obtained by multiple measurements can only be approximated to the true value as much as possible. Solution 1 to reduce the random error is to increase the number of repetitions of the blank value. It is generally considered that the blank value is repeated 10 times, and the measured mean is close to the true value. Option 2 is to improve the experimental skills and also effectively reduce the impact of random errors. If the CV value is 5% and the sample value approaches zero, the sample value will not be statistically lower than the blank value by 15%. 2, gross error Gross Error The error of error is mainly caused by the negligence of the measurer and the undue error. Negligence errors can be avoided. For the problem that the ELISA sample value is lower than the blank value, the cause of the error is mostly due to the repeated loading of the blank hole HRP or the contamination or the washing is not clean, resulting in a high blank value. In contrast, the sample value is lower than the blank value. value. The solution is to repeat the experiment and standardize the operation.
Second, the matrix effect Matrix Effect In the analysis, the matrix refers to components other than the analyte in the sample. The matrix often has significant interference with the analytical process of the analyte and affects the accuracy of the analytical results. These effects and interferences are called matrix effects. During the development of the ELISA kit, the standard product cannot use human or animal serum or plasma as a dilution of the standard curve, and only the mimics can be used. There are differences in the protein abundance, complexity, pH and other factors between the simulated and tested samples. When the matrix of the sample reduces the binding of the antigen-antibody compared to its mimetic, a phenomenon in which the sample value is lower than the blank value is produced. Causes the sample value to fail to calculate the value, or the value is negative. The most common method of removing the matrix effect at present is to establish a calibration curve by using a standard sample of known analyte concentration while keeping the matrix in the sample as constant as possible. When a single sample or a small number of sample values â€‹â€‹is lower than the blank value, it may be the cause of the error. In this case, repeating should be added to improve the operation skill. When a large number of samples are below the blank value, the influence of the matrix effect should be considered, and a calibration curve should be established to be corrected.