A Label-Free Smartphone-Based Platform for Monitoring Dynamic Cellular Responses to Treatment On-a-Chip

Quantitative hydrodynamic biomarkers derived from oscillatory microfluidic stimulation have recently emerged as a label-free approach for cell viability assessment under conventional laboratory microscopy. Building upon this previously validated laboratory-based methodology for binary viability assessment, this work extends the framework toward the quantitative evaluation of treatment-induced modulation of cellular health using a portable smartphone-based imaging platform. Cell motion is monitored under controlled oscillatory flow and processed offline through a custom Digital Particle Image Velocimetry (DPIV)-based algorithm, reconstructing the average longitudinal cell velocity and extracting hydrodynamic biomarkers in the time and frequency domains. The technological transfer from conventional microscopy to smartphone-based imaging is validated through a comprehensive statistical framework, confirming statistical equivalence between the two acquisition platforms (TOST, <tex-math notation="LaTeX">p-value< 0.05 </tex-math>) while revealing no significant platform effect (ANOVA, <tex-math notation="LaTeX">p-value> 0.45 </tex-math>), thereby demonstrating platform-independent biomarker estimation. The proposed framework is subsequently applied to monitor the progressive effects of 5-azacytidine (5-AzaC) and hydrogen peroxide ( <tex-math notation="LaTeX">H₂O₂ </tex-math>) treatments on HL60 cells after 24 h and 48 h of exposure. The extracted hydrodynamic biomarkers reveal statistically significant treatment- and exposure duration-dependent cellular hydrodynamic responses (ANOVA, <tex-math notation="LaTeX">p </tex-math>-value < 0.0001), distinguishing the progressive modulation induced by the two treatments, in agreement with the corresponding changes in cell metabolic activity measured by the standard MTT assay. Furthermore, unsupervised clustering demonstrates a clear separability among the five investigated biological states within the extracted hydrodynamic biomarker space, particularly at higher flow amplitudes. These results establish a proof-of-concept portable platform for label-free monitoring of treatment-induced modulation of cellular physiological state, paving the way toward future point-of-care applications.