Multiway chemometric decomposition of EEM of fluorescence of CdTe quantum dots obtained as function of pH

Kinetic Determination of Acetylsalicylic Acid Using a CdTe/AgInS2 Photoluminescence Probe and Different Chemometric Models

The combination of multiple quantum dots (QDs) in a multi-emitter nanoprobe can be envisaged as a promising sensing scheme, as it enables obtaining a collective response of individual emitters towards a given analyte and allows for achieving specific analyte-response profiles. The processing of these profiles using adequate chemometric methods empowers a more sensitive, reliable and selective determination of the target analyte. In this work, we developed a kinetic fluorometric method consisting of a dual CdTe/AgInS₂ quantum dots photoluminescence probe for the determination of acetylsalicylic acid (ASA). The fluorometric response was acquired as second-order time-based excitation/emission matrices that were subsequently processed using chemometric methods seeking to assure the second-order advantage. The data obtained in this work are considered second-order data as they have a three-dimensional size, I × J × K (where I represents the samples' number, J the fluorescence emission wavelength while K represents the time). In order to select the most adequate chemometric method regarding the obtained data structure, different chemometric models were tested, namely unfolded partial least squares (U-PLS), N-way partial least squares (N-PLS), multilayer feed-forward neural networks (MLF-NNs) and radial basis function neural networks (RBF-NNs).

A tutorial on multi-way data processing of excitation-emission fluorescence matrices acquired from semiconductor quantum dots sensing platforms

This tutorial demonstrates how to exploit the second-order advantage on excitation-emission fluorescence matrices (EEFMs) acquired from sensing platforms based on analyte-triggered semiconductor quantum dots (QDs) fluorescence modulation (quenching/enhancing). The advantage in processing such second-order EEFMs data from complex samples, seeking successful quantification, is comprehensively addressed. It is worth emphasizing that, aiming to exploit the second-order advantage, the selection of the most appropriate advanced chemometric model should rely on the matching between the data structure and the physicochemical chemometric model assumption. In this sense, the achievement of second-order advantage after EEFMs' processing is extensively addressed throughout this tutorial taking into consideration three different analytical situations, each involving a specific data structure: i) parallel factor analysis (PARAFAC), which is applied in a real dataset stacked in a three-way data array containing a trilinear data structure acquired from QDs-based detection with non-selective species; ii) multivariate curve resolution - alternating least-squares (MCR-ALS), which is also employed in a real dataset arranged in an augmented data matrix containing non-trilinear data structure acquired from QDs-based detection with a single breaking mode caused by background signals; iii) unfolded partial least-squares with residual bilinearization (U-PLS/RBL), which is applied in a dataset containing non-trilinear data acquired from a classical fluorescence system with two breaking modes caused by inner filter effect (IFE) in both instrumental modes (excitation and emission). The latter challenging data structure can be acquired via fluorescence quenching from IFE-based sensing platforms and chemometrically handled in two main steps. First, a set of calibration EEFMs data is converted into an unfolded data matrix during the unfolding process, followed by applying U-PLS model. Second, a post-calibration procedure using RBL analysis is applied to a test sample of EEFM maintained in its matrix form, in order to handle potential interferents. In the last section, the state-of-the-art of second-order EEFMs data acquired from semiconductor QDs-based sensing platforms and coupled to multi-way fluorescence data processing to accomplish a successful quantification, even with substantial interfering species, is critically reviewed.

PARAFAC study of L-cys@CdTe QDs interaction to BSA, cytochrome c and trypsin: An approach through electrostatic and covalent bonds

Utilizing fluorescence spectroscopy, non-covalent and covalent interactions of L-cys@CdTe quantum dots to bovine serum albumin (BSA), cytochrome c and trypsin were investigated. L-cys@CdTe QDs with the emission maximum at 530 nm and an average diameter of 2.6 nm were synthesized in the aqueous medium. Formaldehyde, N-(3-dimethylaminopropyl)-N-ethylcarbodiimide hydrochloride (EDC) with N-hydroxysuccinimide (NHS), and glutaraldehyde was applied as cross-linkers. In the case of both electrostatic and covalent strategies PARAFAC, as a powerful multi-way chemometrics technique, was utilized to analyze fluorescence excitation-emission (EEM) spectra. For non-covalent and covalent bonding, two and three significant components composed the PARAFAC models. Resolved EEM shows that in the presence of formaldehyde, a new component with an emission peak similar to BSA was obtained. Using EDC-NHS cross-linker, the fluorescence peak of the newly formed component was in a distinct wavelength with similar emission intensity, compared to L-cys@CdTe QDs and BSA. Employing glutaraldehyde, a distinguished component was easily detected at emission wavelengths higher than that of L-cys@CdTe QDs and proteins. It was concluded that the choice of cross-linker is a critical step to create different emission spectra when dealing with nano-bio-conjugations. This study shows that glutaraldehyde cross-linker leads to increase sensitivity, selectivity, and accuracy of protein analysis.

Metabolic tumor profiling with pH, oxygen, and glucose chemosensors on a quantum dot scaffold

Acidity, hypoxia, and glucose levels characterize the tumor microenvironment rendering pH, pO2, and pGlucose, respectively, important indicators of tumor health. To this end, understanding how these parameters change can be a powerful tool for the development of novel and effective therapeutics. We have designed optical chemosensors that feature a quantum dot and an analyte-responsive dye. These noninvasive chemosensors permit pH, oxygen, and glucose to be monitored dynamically within the tumor microenvironment by using multiphoton imaging.

Multiway study of hybridization in nanoscale semiconductor labeled DNA based on fluorescence resonance energy transfer

The resolution of the ternary-binary complex competition of a target sequence and of its two complementary probes in sandwich DNA hybridization is reported. To achieve this goal, Fluorescence Resonance Energy Transfer (FRET) between oligonucleotide-functionalized quantum dot (QD) nanoprobes (QD donor-QD acceptor) upon hybridization with a label free target was monitored by two-dimensional photoluminescence excitation spectroscopy (2D-PLE). Detection of a target oligonucleotide strand, using sandwiched nanoassembly in a separation-free format, was performed with the appearance of a new feature in the photoluminescence excitation (PLE) plot. From the obtained data, energy transfer efficiency and Förster radius (R0) were calculated. In particular, our results demonstrated that energy transfer by using QD donor-QD acceptor FRET pairs is more efficient in comparison with QD donor-organic dye acceptor pairs. Soft and model based analysis of 2D-PLE data was implemented by means of PARAFAC and hard trilinear decomposition (HTD), allowing to fit a proper model for FRET-based sandwich DNA hybridization systems. This study is the first successful application of a multiway chemometric technique to consider FRET based DNA hybridization in sandwiched nanoassemblies. A multi-equilibria model was properly fitted to the data and confirmed there is a competition between ternary and binary complex formation. Equilibrium constants of DNA hybridization in sandwiched nanoassemblies were estimated for the first time. Equilibrium constants illustrated that the extent of hybridization in one side on the target strand depends on hybridization conditions on the other side of the strand. Effects of guanine (G) and cytosine (C) contents of strands on the extent and rate of hybridization were investigated. In addition to equilibrium constants of binary and ternary complexes, the pure profiles of all resolved structures were estimated. Ultimately, the described method calculated the analytical concentration of probes as a measure of surface modification yield with DNA using nonlinear fit analysis, without using any calibration sample.