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What should be noted when drawing the ELISA standard curve?
The ELISA experiment will be conducted. How should the ELISA standard curve be drawn? Many customers have consulted us about what to pay attention to when drawing the standard curve of ELISA kits? Our company provides the following detailed explanation on this issue.
1、 Attention should be paid when testing standard curve samples
1. The concentration and other indicators of the sample are calculated based on the standard curve, so first of all, making the standard curve is more important than conducting formal experiments, otherwise the results of the subsequent experiments cannot be discussed.
2. The standard concentration range for setting the standard curve sample should have a relatively large span and be able to cover the concentration of the experimental sample you want to test, that is, the concentration of the sample should be within the standard curve concentration range, including the upper and lower limits. For the S-shaped standard curve, it is advisable to keep the concentration of the experimental sample within the steepest slope in the middle, that is, within the range where the curve is almost straight.
3. It is best to use the dilution ratio method to prepare the standard sample concentration in the standard curve, so as to ensure that the concentration of the standard sample will not deviate significantly.
4. When testing standard samples, they should be tested in increasing concentration order to reduce the impact of high concentration on low concentration and improve accuracy.
5. The sample size of the standard curve is generally 7 points, but at least 5 points must be ensured.
6. The correlation coefficient of the standard curve varies depending on the experimental requirements, but generally speaking, the correlation coefficient R should be at least greater than 0.98, and for some experiments, it should be at least 0.99 or even 0.999.
2、 What equation should be chosen to fit
The so-called "standard curve" used for immune testing is actually called a fitting curve, which is more appropriate. During immune testing, if the concentration of the standard point (which can be diluted by multiples or not) can show a linear relationship with the corresponding absorbance (OD) value, it is of course the most ideal. At this time, the fitting curve can be easily obtained through Excel and other methods to calculate the concentration value of the sample. But when we do immune testing, we rarely have such ideal situations. The concentration of the standard and the corresponding OD value often have an "S" curve relationship. In this case, we cannot use straight line fitting, and it is necessary to choose the fitting method.
Regarding the fitting methods of standard curves, although straight lines, quadratic curves, cubic curves, exponents, logarithms, etc. can all be used for curve fitting in ELISA and other biological reactions, they are only applicable to a part of the curve. Some are suitable for the first half, some for the second half, and some for the middle half. Logistic curves, on the other hand, have good applicability to the entire curve. Of course, if used for quantification, it is still better to use it in the middle section. Although none of these methods are universal, they can all be used. The key is which part of the S-shape your standard curve has achieved, and which part of the curve you want to test the concentration of the sample in. The low concentration part of the S-curve can be well fitted by a power equation, the medium low concentration part can be fitted by a linear equation, the middle part can be fitted by a logarithmic equation, and the middle and rear sections can be fitted by four parameters.
The most popular fitting method for immune testing internationally is the "four parameter logic fitting", which often accurately reflects the curve relationship between concentration and absorbance, thereby further obtaining the concentration value of the analyte in the sample.
In fact, within a long interval, logistic should be able to fit well. But it doesn't mean it's omnipotent. In fact, not only ELISA, but many other biological reactions have S-shaped curves that can also be fitted with logistic curves. But building a model is one thing, using it to quantify is another. If used for quantification, the middle section (steeper part) of the S-shaped curve is relatively good, while the flat parts at both ends may have large calculation errors, sometimes even significant.
For the above technical information, if you are unsure or have more information (including basic information/technical data/solutions), please feel free to contact our sales representative at any time. Our company provides a complete range of ELISA kits with guaranteed quality! Provide full technical guidance and free testing services.
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