Profiling single-cell level phagocytic activity distribution with blood lactate levels.

Area of Science:

• Immunology
• Cellular Biology
• Clinical Diagnostics

Background:

• Phagocytic activity is crucial for immune response but often overlooked in patient diagnosis.
• Understanding phagocytic capabilities in disease states remains incomplete.
• Blood lactate levels serve as a clinical marker for patient triage.

Purpose of the Study:

• To investigate the relationship between blood lactate levels and neutrophil phagocytic activity.
• To analyze phagocytic activity at a single-cell level in relation to lactate thresholds.
• To explore the potential of machine learning in differentiating phagocytic profiles.

Main Methods:

• Isolated neutrophils from blood samples (N=19) categorized by lactate levels (control vs. high-risk >2 mmol L⁻¹).
• Incubated neutrophils with fluorescent IgG-coated beads to quantify phagocytic activity.
• Employed statistical tests (T-test, PCA) and artificial neural networks (ANNs) for data analysis.

Main Results:

• Single neutrophils internalized up to 7 beads, with higher 7-bead internalization in the high-risk group (0.6% vs. 0.17%).
• No statistically significant difference in mean phagocytic activity (p=0.08) or clear group distinction via PCA.
• ANN models achieved AUC values below 0.7, indicating limited discriminatory power.

Conclusions:

• Single-cell analysis revealed nuanced phagocytic activity patterns related to lactate levels.
• Current methods show a trend but lack statistical significance for differentiating groups based on phagocytic activity alone.
• Future research necessitates integrating patient medical records for personalized phagocytic activity insights.