Optimizing Micromixer Surfaces To Deter Biofouling

Using computational modeling, we show that the dynamic interplay between a flowing fluid and the appropriately designed surface relief pattern can inhibit the fouling of the substrate. We specifically focus on surfaces that are decorated with three-dimensional (3D) chevron or sawtooth “micromixer” patterns and model the fouling agents (e.g., cells) as spherical microcapsules. The interaction between the imposed shear flow and the chevrons on the surface generates 3D vortices in the system. We pinpoint a range of shear rates where the forces from these vortices can rupture the bonds between the two mobile microcapsules near the surface. Notably, the patterned surface offers fewer points of attachment than a flat substrate, and the shear flows readily transport the separated capsules away from the layer. We contrast the performance of surfaces that encompass rectangular posts, chevrons, and asymmetric sawtooth patterns and thereby identify the geometric factors that cause the sawtooth structure to be most effective at disrupting the bonding between the capsules. By breaking up nascent clusters of contaminant cells, these 3D relief patterns can play a vital role in disrupting the biofouling of surfaces immersed in flowing fluids

Additional file 2 of Comprehensive analysis of the differences between left- and right-side colorectal cancer and respective prognostic prediction

Additional file 2: Fig. S2. (A) The comparison of immune infiltration levels between high-risk and low-risk groups in L_cancer patients, based on CIBERSORT. (B) The Stromal Score difference, Immune Score difference, ESTIMATE Score difference, and tumor purity difference between high-risk and low-risk groups in L_cancer patients. (C) The immune checkpoint-related gene expression levels in high-risk and low-risk groups in L_cancer patients. (D) The tumor mutation burden difference between high-risk and low-risk groups in L_cancer patients. (E) HLA-related gene expression level between high-risk and low-risk groups in L_cancer patients. (Notes: ns P>0.05)