• • scRNA-seq resolves transcriptional heterogeneity that bulk RNA-seq averages away: bulk RNA-seq measures pooled mRNA from whole tissues, whereas droplet-based platforms (10× Genomics, BD) generate per-cell expression profiles, enabling detection of rare pathogenic subpopulations such as SPP1+ chondrocytes in human osteoarthritis (Qu et al., Comput Biol Med, 2023, 160: 106926) that would be masked in bulk data; this matters clinically because target identification for TCM interventions requires cell-type-specific resolution to avoid false-negative target discovery.
• • Macrophage M1/M2 polarization states in rheumatoid arthritis synovium are quantifiable at single-cell resolution (Cutolo et al., Front Immunol, 2022, 13: 867260), providing a direct pharmacodynamic readout for TCM formulations whose anti-inflammatory effects were previously assessed only by bulk cytokine levels; this enables dose-response mapping of multi-component herbal extracts against specific macrophage states rather than global inflammation scores.
• • Clonal associations between lymphocyte subsets and functional states in RA synovium have been resolved by scRNA-seq (Dunlap et al., Nat Commun, 2024, 15: 4991), establishing that T-cell clonal expansion is linked to discrete functional states; for TCM development, this creates a pathway to identify whether herbal compounds act on clonal selection, effector differentiation, or both, a distinction impossible with bulk transcriptomics.
• • Peripheral blood mononuclear cell atlases and cell-cell communication networks in RA patients have been constructed via scRNA-seq (Song et al., J Immunol Res, 2023, 2023: 6300633), enabling ligand-receptor interaction inference at single-cell resolution (Wilk et al., Nat Biotechnol, 2024, 42(3): 470-483); this is operationally significant because TCM's multi-target mechanism can be mapped onto specific intercellular signaling axes, providing a rational basis for formulation design rather than empirical combination.