In vitro cultured 3D models of CRC have been demonstrated to hold considerable worth in drug discovery, drug resistance analysis, and in studying cell-cell and cell-matrix interactions that occur in the tumor microenvironment. The 3D models resemble the in vivo physiological microenvironment by replicating the cell type composition and tissue architecture. Molecularly imprinted polymers (MIPs) have been investigated for use instead of antibodies against small non-immunogenic structures, such as sialic acid (SA). Glyco-conjugates including SA are present on all cells, and often deregulated on cancer cells. Here, we present a novel approach for targeting and detecting colorectal cancer cells (CRC) by using in vitro cultured HT29 3D spheroids co-cultured in vitro with either fluorescent MIPs targeting SA, SA-MIPs, or the two lectins targeting SA, MAL I, and SNA. Both formaldehyde-fixed and viable HT29 3D spheroids with or without SA-MIPs were imaged in 3D by confocal microscopy. The results revealed a preserved cell morphology and viability of the HT29 3D spheroids co-cultured in vitro with SA-MIPs. However, the lectins MAL I and SNA targeting the α-2,3 or α-2,6 SA glycosidic linkages, respectively, affected the cell viability when co-cultured with the viable HT29 3D spheroids, and no living cells could be detected. Here, we have shown that the SA-MIPs could be used as a safe and low-cost diagnostic tool for targeting and detecting cancer cells in a physiologically relevant 3D cancer model in vitro.

The prevailing form of bacterial infection is within the urinary tract, encompassing a wide array of bacteria that harness the urinary metabolome for their growth. Through their metabolic actions, the chemical composition of the growth medium undergoes modifications as the bacteria metabolize urine compounds, leading to the subsequent release of metabolites. These changes can indirectly indicate the existence and proliferation of bacterial organisms. Here, we investigate the use of an electronic tongue, a powerful analytical instrument based on a combination of non-selective chemical sensors with a partial specificity for data gathering combined with principal component analysis, to distinguish between infected and non-infected artificial urine samples. Three prevalent bacteria found in urinary tract infections were investigated, Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis. Furthermore, the electronic tongue analysis was supplemented with ¹H NMR spectroscopy and flow cytometry. Bacteria-specific changes in compound consumption allowed for a qualitative differentiation between artificial urine medium and bacterial growth.