Nanoswimmers statistical mechanics: Unlocking whole-blood viscosity sensing for tumor microenvironment

The ability to sense the biological microenvironment surrounding early-stage tumor tissues is critical for tumorigenesis tracing and tumor detection and treatment. An efficient tumor microenvironment (TME) sensing strategy remains a significant challenge. We propose a novel "seeing is sensing" approach that has the potential to discern the whole-blood viscosity (WBV) information of the TME by using a swarm of nanoswimmers (NS).

In this study, we employ statistical mechanics methods to derive the relationship between the aggregation of NS in the microscale and their macroscopic concentration distribution. We utilize the finite difference method to develop a discrete numerical model of the NS diffusion in the blood. We further develop a novel model for TME sensing that can dynamically detect the WBV by analyzing the kinematic motion of the NS swarm, which enables real-time detection of WBV by observing the Full Width at Half Maximum (FWHM) of the NS swarm motion.

The viscosity value obtained with our sensing method is benchmarked against the gold standard results obtained from the Brookfield viscometer. The measurements obtained from both methods exhibit an excellent correlation, with a coefficient of determination (R²) of 0.9617. Furthermore, the constructed Bland-Altman plot reveals that the majority of observed data points lie within the limits of agreement of the 95% clinical confidence interval (lower limit of agreement = -0.0660, upper limit of agreement = 0.1130), thus validating the feasibility of our sensing strategy.

We present a new sensing strategy that utilizes the diffusion dynamics of the NS swarm within the vascular network to infer variations in WBV. Comparative analysis with gold standard data substantiates the accuracy and applicability of this method in assessing WBV parameters in the vicinity of tumor tissues. Our work demonstrates relevant prospects for visualizing, comprehending, and evaluating the pathological progression of blood-related disorders in real-time.