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Figure 1. Chemical nose sensor. A sensor array composed of different recognition elements that possess varying binding affinities to different analytes provides the basis of this method. As a result, distinct patterns of analytes are generated based on different binding affinities of analytes toward the sensor array. These patterns (fingerprints of each analyte) are processed by multivariate analysis methods. After reducing the data matrix dimensions, different clusters of the analytes can be visualized, demonstrating a successful classification.
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Figure 2. Mechanism of detecting cancer cell types using green fluorescent protein-gold nanoparticle sensor array. (A) Structures of the NPs with different head groups R used as an array of recognition elements in the sensor. (B) Structure of GFP used as the transducer of the sensor array. (C) Schematic illustration of GFP-NP complexes for cell surface sensing. The fluorescence from GFP is turned off once GFP-NP complexes are formed due to the strong quenching property of gold NPs. Due to competitive binding between cells and GFP to the NPs, different amount of GFP are being released in the presence of different cell lines based on their binding affinities. GFP: Green fluorescent protein; MW: Molecular weight; NP: Nanoparticle; pl: Isolectric point. Adapted with permission from [ 26 ].
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Figure 3. Structures of magnetic glyconanoparticles with different carbohydrate ligands. MGNP: Magnetic glyconanoparticle. Data taken from [ 29 ].
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Figure 4. Plot generated from linear discriminant analysis plot for ten cell line differentiation using magnetic glyconanoparticle sensor array. 3D linear discriminant analysis plot of ΔT2 patterns generated from the magnetic glyconanoparticle array after different cell line incubations (105 cells/ml). ΔT2 patterns of different cell lines were reduced into simpler components, linear discriminants (LD1, LD2 and LD3). Full differentiation of the ten cell lines was achieved. LD: Linear discriminant. Adapted with permission from [ 29 ].
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Figure 5. Use of synthetic biomarker-conjugated nanoparticles for urinary monitoring. (A) Synthetic biomarker library conjugated onto nanoparticles (NPs). (B) Accumulation of NPs in disease tissues. Cleavage of the mass-encoded peptides from NPs by active proteases allows their filtration into the urine. (C) Detection of biomarker peptides in urine using LC-MS/MS. hv: UV light irradiation;...