ELISA sample value is lower than the blank value of the problem solution - Database & Sql Blog Articles

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During ELISA experiments, it's common to encounter situations where the sample value is lower than the blank value. This issue can be confusing and may affect the reliability of your results, especially when working with serum or plasma samples.

This phenomenon often occurs when the sample’s concentration is below the detection sensitivity of the kit. In such cases, the measured signal might not be strong enough, leading to a situation where the sample value appears to be lower than the blank.

The main causes behind this problem typically fall into two categories: experimental errors and matrix effects.

1. Experimental Errors

Experimental errors can be divided into three types: systematic errors, random errors, and gross errors. Among these, systematic errors don't affect the difference between the sample and blank values. However, random and gross errors are more likely to cause the sample value to drop below the blank value.

Random Errors

Random errors occur due to uncontrollable factors and result in variability that follows a normal distribution. With a coefficient of variation (CV) of 20%, the random error range could be as high as ±60%. If the CV is 5%, then the sample value may not fall below the blank by more than 15% if the measurement is accurate. To reduce the impact of random errors, you can increase the number of blank measurements (typically 10 repetitions), which helps bring the average closer to the true value.

Gross Errors

Gross errors are usually caused by human mistakes, such as improper pipetting, contamination, or incomplete washing. These errors can lead to an abnormally high blank value, making the sample appear lower in comparison. The best solution is to repeat the experiment and strictly follow standardized procedures.

2. Matrix Effects

Matrix effects refer to interferences from other components in the sample besides the analyte. These effects can significantly impact the accuracy of the ELISA results. During the development of ELISA kits, standard curves are usually prepared using simulated matrices rather than real biological samples like serum or plasma. Differences in protein content, pH, and other factors between the simulated and actual samples can lead to reduced antigen-antibody binding, resulting in lower sample values compared to the blank.

To address this, it's recommended to use a calibration curve that closely matches the matrix of the test samples. When only a few samples show low values, improving technique and repeating the experiment can help. For widespread issues, establishing a proper calibration curve is essential to correct for matrix interference.

In summary, encountering a sample value lower than the blank during ELISA is a common challenge. Understanding the root causes—whether related to experimental errors or matrix effects—and applying appropriate solutions can greatly improve the accuracy and consistency of your results.

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