Integrated subcellular localization of functional fluorescence probes and functional analysis in motile spermatozoa...

Area of Science:

• Biomedical Engineering
• Reproductive Biology
• Computational Biology

Background:

• Conventional semen analysis lacks molecular-level detail for male infertility assessment.
• Current computer-aided sperm analysis struggles with live-cell fluorescence quantification.
• There's a need for advanced methods to evaluate sperm functional competence at the molecular level.

Purpose of the Study:

• To develop an integrated computational-imaging platform for precise, molecular-level sperm analysis.
• To enable simultaneous quantification of intracellular pH (pHi) and mitochondrial DNA G-quadruplexes (mtDNA G4s) in sperm.
• To correlate molecular signatures with sperm functional outcomes for improved diagnostics.

Main Methods:

• Utilized a fine-tuned You Only Look Once version 8 (YOLOv8) architecture on the EVISEN dataset.
• Implemented dual-probe fluorescence microscopy image segmentation for live-cell analysis.
• Developed automated algorithms for localizing fluorescent foci and discriminating sperm regions.

Main Results:

• Successfully quantified simultaneous intracellular pH (pHi) and mtDNA G-quadruplexes (mtDNA G4s).
• Automated localization and discrimination of fluorescent signals in sperm head and principal piece.
• Revealed significant correlations between fluorescence intensity ratios and sperm functional competence.

Conclusions:

• AI-enhanced multimodal sperm analysis offers a novel approach for molecular phenotyping.
• The integrated platform provides a transformative tool for mechanistically informed male infertility diagnostics.
• This technology advances the precise assessment of sperm functional competence beyond conventional parameters.