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Colorimetric Sensor Array Design for Classification and Detection of Nanoparticles and Some Biomolecules

Ghasemi, Forough | 2016

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 48797 (03)
  4. University: Sharif University of Technology
  5. Department: Chemistry
  6. Advisor(s): Hormozi Nezhad, Mohammad Reza
  7. Abstract:
  8. In the first part of this research, we reported a liquid sensor array for detection and classification of biological thiols, based on aggregation of gold nanoparticles (AuNPs) with different coatings as sensor elements. Thiol mediated aggregation of AuNPs was visualized via UV–vis spectra. The spectral changes, as a consequence of aggregation of AuNPs, made a unique pattern of spectra for each analyte and allowed for the selective detection and discrimination of the biological molecules. HCA and PCA analysis demonstrated the discrimination of various thiols of different concentrations (i.e. 10–800 mmol L-1 for cysteine, 200–700 mmol L-1 for both glutathione and glutathione disulfide). Furthermore, the proposed sensor array could efficiently discriminate the individual thiols and their mixtures. Finally, it was found that the array was accurately successful to detect various thiols in plasma sample. In the second part of this research, we revealed that catecholamines, under alkaline condition, are transformed to fluorescent products and quinone-like compounds which affect quantum dots’spectra Spectral evolution of fluorescent products and changes in spectra of thioglycolic acid-capped quantum dots were employed to design an efficient and low-cost sensor array. Proposed sensor array is capable to discriminate three important catecholamines of different concentrations (i.e. 2.5-20, 5-20 and 2.5-30 μmol L-1 for norepinephrine, L-DOPA and dopamine, respectively). The sensor array could successfully discriminate single catecholamines from their mixtures. Such a sensor array can be used for efficient detection of catecholamines in urine sample for early diagnosis applications. In the third part of this research, we have proposed a colorimetric approach, which is able to detect NPs with various physicochemical properties (i.e. quantum dots, carboxylated polystyrene NPs, plain silica nanoparticles and AuNPs). Classification analysis reveals that the NPs have high dimensionality and, consequently, the ability to discriminate among large types of NPs over a wide range of concentrations (i.e. seven different NPs in concentrations from 200 to 1000 ng mL-1). In order to consider the detection capability of the sensor on NPs with diffretnt shape and size, we produced four different types of gold NPs (i.e. spherical (20 nm and 30 nm) and rod shapes (aspect ratios of 4 and 20)). Color difference maps provide differentiation of each NP at different concentrations (i.e. 10-1000 and 25-1000 ng mL-1 for rod-shaped NPs with aspect ratios of 20 and 4, respectively, and 250-1000 ng mL-1 for both spherical NPs). In the forth part of this research, we have developed a colorimetric sensor array for the discrimination and detection of different diseases (e.g., lzheimer’s disease and multiple sclerosis (MS)) based on the personalized disease-specific protein corona (PDSPC) on the surface of various sphere-shaped gold nanoparticles (i.e., four AuNPs with the same size but different surface coatings, including citrate, cysteine, cysteamine and thiolated polyethylene glycol). Using a variety of techniques, including sodium dodecyl sulfate polyacrylamide gel electrophoresis, dynamic light scattering, Zetasizer, and UV-visible spectra, we found that the PDSPC-nanoparticle complexes obtained from different human serums had distinct protein compositions and contents. The array responses were analyzed using chemometrics and statistical methods, and the results demonstrated the capability of the sensor to unambiguously discriminate and detect different type of diseases. The developed sensor array might pave a new way for the easy, cheap and fast detection of diseases. In the fifth part of this research, a fluorometric chiral recognition assay was developed for cysteine. It was shown that the rate of aggregation of CdTe QDs is quite different in presence of D- and L-cysteine. The chiral assay took advantage of the aggregation rate of unmodified QDs for enantioselective recognition of cysteine. On the basis of emission color change of QDs because of aggregation, proposed method allows the chiral detection of cysteine by the naked eye. A good linear relationship was obtained between emission signal at 530 nm and enantiomeric excess of D-cysteine (with correlation coefficient of 0.9993). So, this novel chiral sensor could be successfully applied for the measurement of enantiomeric excess. The response of the unmodified CdTe Q s in presence of other α-amino acids including arginine, tryptophan, tyrosine, proline and histidine is small and the same for D- and L- form of each kind of amino acids
  9. Keywords:
  10. Quantum Dots ; Nanoparticles ; Biomolcule Recognition ; Colorimetric Sensor ; Multivariate Methods ; Sensors Array ; Enantiomers

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