Researchers from the University of Kobe and the Tokyo Institute of Science in Japan have developed a method that uses artificial intelligence to track the human immune response to infections and vaccines. This method, named "LM-QASAS," compares the sequences of antibodies present in a person's blood before and after infection or vaccination. The focus is on a variable part of the antibody known as "CDR-H3," which plays a crucial role in recognizing viruses.
The researchers used a specialized language model called "AbLang2" to convert antibody sequences into digital representations. This helps identify similar sequences in properties, even if they are not identical. The model then searches for groups of antibodies that appear during the peak immune response and later decline. These are considered potential indicators of antibodies that participated in fighting the infection.
The researchers tested the method using data from ten people infected with COVID-19 or vaccinated against it. The results showed that the sequences identified by the system were more similar to known antibodies targeting the SARS-CoV-2 virus compared to randomly selected sequences. This demonstrates the potential of the AI method to track immune responses.
The researchers were able to use data from nine people to create an internal reference to track the immune response of a tenth person without relying on external databases. This approach may contribute to studying the body's response to new viruses and diseases and evaluating vaccine effectiveness. It may also aid in research on autoimmune diseases and cancer.
The researchers acknowledge that the technology is still in its early stages and needs to be tested on larger numbers of people. They also need to improve its ability to detect weak immune responses before evaluating its broader use. AI-based methods like this provide new tools for researchers to understand changes in the immune system.
The study's findings were reported by the Egyptian Radio and Television Union. According to the report, the AI method may help identify antibodies that play a role in resisting viruses. This could lead to the development of more accurate methods for studying diseases and vaccine responses.
The researchers' work has implications for the future of immune system research and vaccine development. As the technology advances, it may enable more precise and personalized approaches to disease prevention and treatment. The study's results demonstrate the potential of AI to enhance our understanding of the immune system and improve public health.
Key points
- Researchers develop AI method to track human immune response to infections and vaccines
- The method uses a specialized language model to convert antibody sequences into digital representations
- The technology has implications for vaccine development and disease prevention
