[PSO+: nonlinear fitting fluorescence data based on particle swarm optimizing combine with other iteration...

Area of Science:

• Biotechnology
• Molecular Biology
• Analytical Chemistry

Background:

• Convective polymerase chain reaction (CCPCR) utilizes thermal convection for nucleic acid amplification.
• Real-time detection in CCPCR relies on fluorescence intensity, but thermal convection instability causes curve jitter.
• This jitter complicates accurate quantification and cycle threshold (CT value) determination.

Purpose of the Study:

• To develop a method for stable and accurate real-time quantitative detection in CCPCR.
• To overcome the limitations of fluorescence curve instability and jitter.
• To enable reliable initial nucleic acid concentration determination.

Main Methods:

• Real-time fluorescence detection integrated into the CCPCR system.
• Application of a dynamic double S-type function model for curve fitting.
• Utilization of a hybrid PSO+ algorithm (Particle Swarm Optimization combined with traditional methods) for parameter optimization.

Main Results:

• The proposed method effectively smooths the fluorescence curves, mitigating jitter caused by thermal convection instability.
• The double S-type function model provides a robust fit, achieving an R-squared value of 0.9998.
• The optimized algorithm overcomes the limitations of standard curve-fitting techniques, preventing local optima and improving accuracy.

Conclusions:

• The developed dynamic curve-fitting method significantly enhances the quantitative accuracy of real-time fluorescent CCPCR.
• This approach offers a reliable solution for determining initial nucleic acid concentrations.
• The study provides a valuable framework for future advancements in quantitative detection technologies.