Figure 5. Macrophage polarization affects ligand distinguishability uniquely.

(A) Confusion fraction derived from both the LSTM and XGBoost models between the host ligand (TNF) and the pathogen ligands (R848, poly(I:C), Pam3CSK, Flagellin, CpG, FSL1, and LPS) in the IL-4 and M0 polarization states shows larger increase with R848, poly(I:C), CpG, and LPS stimulation.

(B) PCA projection of the 18 signaling codons from the single-cell responses to TNF and R848 with M0 and IL-4 polarization; dispersion measure in red (average pairwise distance between classes divided by average pairwise distance within classes) illustrates convergence of stimulus responses with IL-4 polarization.

(C) Decreased early phase activity and duration feature distributions of R848 responses with IL-4 polarization contribute to convergence; log2 fold reduction in Jensen-Shannon distance between ligand responses with polarization in red.

(D) Confusion fraction derived from both the LSTM and XGBoost models between the viral ligands (R848, poly(I:C)) and the bacterial ligands (Pam3CSK, Flagellin, CpG, FSL1, and LPS) in the IFNβ polarization state; illustrates greatest confusion between poly(I:C) and LPS.

(E) PCA projection of the single-cell responses to poly(I:C) and LPS with M0 and IFNβ polarization illustrates convergence with IFNβ polarization.

(F) Decreased peak activation speed of LPS and decreased oscillations of poly(I:C) (PIC) contribute to convergence of stimulus responses with polarization.

(G) Average confusion fraction within viral and bacterial ligands normalized to M0 performance from the same LSTM and XGBoost models shows greater relative viral ligand confusion with polarization compared with bacterial.

(H) PCA projection of the single-cell responses to R848 and poly(I:C) with M0 and IL-13 polarization illustrates convergence of stimulus responses with IL-13 polarization.

(I) Decreased duration and increased oscillations of R848 responses contribute to convergence of stimulus responses with polarization.