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Heterophilic Blocking Reagent Principle

Heterophilic samples refer to serum or plasma samples with specific antibodies that can bind to the animal antibodies used in immunoassays. The interference caused by heterophilic antibodies is commonly reported as false positives, but false negatives have also been reported. Common heterophilic antibodies include Human Anti-mouse Antibody (HAMA) and rheumatoid factor (RF).

 

As shown in Figure 1, in a normal sandwich immunoassay, the analyte is bound by the antibody, resulting in a positive result.

As shown in Figure 2, in a sandwich immunoassay, heterophilic antibodies can cause false positive results.


                       

                                                                                Figure 1                                                                                     Figure 2


Blockers can bind to non-specific reactive substances in the reagents, thereby eliminating false positive results. The principle of eliminating false positive results by blockers is that non-specific reactive substances (such as non-specific antibodies) in the reagents may bind to non-specific substances (such as heterophilic antibodies) in the sample, resulting in false positive results. Blockers can bind to these non-specific reactive substances, preventing them from binding to non-specific substances in the sample, thereby reducing the occurrence of false positive results.

Blockers are usually added to the reagents, and their role is to competitively bind to non-specific reactive substances in the reagents, thereby preventing them from binding to non-specific substances in the sample. This can reduce the possibility of the reagents binding to non-specific substances in the sample, thereby reducing the occurrence of false positive results.

It should be noted that the selection of blockers should be determined based on the nature of non-specific reactive substances in the reagents and the specific situation of the reagents. The concentration of blockers added also needs to be optimized rigorously to ensure the best effect of eliminating false positive results.


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