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Exploration in the way of understanding the optical behavior and structure of carbon nanodots has been increased due to their vast application. Their emission dependency on excitation wavelengths is the more prevalent and controversial subject. In this report we considered the optical structure of hydrothermally synthesized carbon nanodots using citric acid and 2,3-diaminopyridine as precursors. The presence of different emission centers experimented through anion exchange chromatography which resulted in fractions with more unique optical structures. The quantum confinement effect and energy exchange between different types of carbon nanodots, due to aggregation in higher concentration levels, was studied applying a stepwise dilution experiment. Analysis of the experimental data was done through the parallel factor analysis and the trajectory pattern recognition which resolved more about optical interactions and the presence of different emission centers in different particles. Results from infrared spectroscopy confirmed the dominating density of carboxyl functional groups on the nanodots with negative surface charges and higher influence of amine groups on dots with positive surface charges.

Molecularly imprinted polymers are efficient and selective adsorbents which act as artificial receptors for desired compounds with the ability to recognize the size, shape, and functional groups of the compounds simultaneously. A molecularly imprinted polymer is prepared by the polymerization of functional monomers around a template (analyte) molecule. Afterward, the removal of the template from the polymer matrix leaves a selective cavity behind. The fabrication and development of molecularly imprinted polymers grew rapidly, due to their low cost, simple preparation, selectivity, sensitivity, and stable physicochemical properties. Traditionally, molecularly imprinted polymers can be synthesized using two main methods, namely bulk and surface imprinting. For more efficient use of the latter method, researchers have developed molecularly imprinted polymers grafted on the solid-phase matrix (substrate). This grafting technique would be particularly useful for surface imprinting of macromolecules, such as proteins. Cellulose fibers of papers with unique properties such as being abundant, retaining a porous structure, having good adsorption properties, and possessing hydroxyl groups naturally have gained much attention as substrate. The goal of this review is to introduce molecularly imprinted polymer-grafted or molecularly imprinted polymer-coated paper, as an interesting, simple, and efficient method in the detection and separation of small and large molecules. Therefore, in the present paper, several recent preparation techniques and applications of molecularly imprinted polymer-grafted paper are reviewed and discussed in detail. Graphical abstract Green, cost-effective, selective, and sensitive paper-based sensor prepared via grafting molecularly imprinted polymer on paper surface with the potential use for online detection trace of analytes in the point-of-care testing.

The excitation-emission fluorescence spectroscopy combined with three-way analysis was applied for discriminating the pure BSA and BSA/Fe 3 O(OAc) 6 ClO 4 (Fe) using unsupervised classification methods. Herein, the interaction of bovine serum albumin (BSA) and Fe clusters as an artificial enzyme is studied by extracting the intrinsic excitation-emission (EEM) fluorescence of BSA. The conformation of BSA changes with pH, temperature, and Fe concentration. Three-way fluorescence data were recorded for BSA and BSA/Fe during different days. The obtained results showed that the Fe clusters cause changes in the structure of BSA conformation as a function of pH, temperature, and Fe concentration. Also, the denaturation pathway of the BSA molecule is significantly different in the presence of Fe clusters. Both techniques of PARAFAC and PCA were used in the excitation-emission fluorescence matrices (EEM) of solutions at three different pH (5.0, 7.0, and 9.0) and temperatures (15.0, 25.0, and 35.0 °C) values. Also, we reported the results of the change in concentrations of Fe (4.0, 6.0, and 8.0 mg) using these methods. These three amino acids (tyrosine, tryptophan, and phenylalanine) indicate all datasets and their similarities and differences. The spectral differences were more remarkable in different pH values compared to different temperatures. Also, we could distinguish between the groups of protein samples properly in different concentrations of Fe using low-cost EEM spectral images and PARAFAC.

The nutrient composition and in vitro digestibility of twenty‐seven commercial pulse protein isolates (PI) and protein concentrates (PC) derived from pea, faba, and lentil, and two soy protein isolate controls were tested using consistent analytical methods to understand compositional variability amongst products manufactured by different suppliers. Principal component analysis (PCA) and maximum likelihood factor analysis (MLFA) were applied to model the compositional and amino acid data to determine where the variability between protein products lay. MLFA delineated between isolates and concentrates based upon protein and total dietary fibre content, while moisture and fat variability could be used to differentiate samples within the PI or PC groupings. PCA score charts distinguished between isolates and concentrates due to higher relative concentrations of amino acids in the isolates, with glutamine/glutamic acid contributing to this distinction. Separation according to crop type within PI and PC groupings based upon the arginine and phenylalanine content was also evident. Sodium, potassium, magnesium, and iron micronutrients also contributed to the variability between PI and PC samples. Calculated amino acid scores showed all samples contained sufficient concentrations of essential amino acids to meet FAO requirements established for preschool‐aged children. PI samples had higher in vitro digestibility than PC samples with minimal variability within the groupings. This work evaluated 27 commercial pulse protein concentrates (PC) and isolates (PI) derived from yellow pea (P), faba bean (F) or lentil (L) crops. The protein samples were analyzed for proximate composition, protein quality, and micronutrient density. Statistical analysis of analytical data demonstrated that PIs were distinguished from PCs based on their protein, total dietary fiber, Fe, Mg, K, Na, and Ni concentrations, as well as their increased in vitro protein digestibility. Within PI or PC groupings, samples were further distinguished from one another based on differences in moisture, fat, arginine, and phenylalanine content.

To address the growing concern of honey adulteration in Canada and globally, a quantitative NMR method was developed to analyze 424 honey samples collected across Canada as part of two surveys in 2018 and 2019 led by the Canadian Food Inspection Agency. Based on a robust and reproducible methodology, NMR data were recorded in triplicate on a 700 MHz NMR spectrometer equipped with a cryoprobe, and the data analysis led to the identification and quantification of 33 compounds characteristic of the chemical composition of honey. The high proportion of Canadian honey in the library provided a unique opportunity to apply multivariate statistical methods including PCA, PLS-DA, and SIMCA in order to differentiate Canadian samples from the rest of the world. Through satisfactory model validation, both PLS-DA as a discriminant modeling technique and SIMCA as a class modeling method proved to be reliable at differentiating Canadian honey from a diverse set of honeys with various countries of origins and floral types. The replacement method of optimization was successfully applied for variable selection, and trigonelline, proline, and ethanol at a lower extent were identified as potential chemical markers for the discrimination of Canadian and non-Canadian honeys.

Sixteen commercially wet‐extracted protein isolates and 13 commercially air‐classified protein concentrates were evaluated for their particle size, physicochemical properties (protein solubility, differential scanning calorimetry, surface hydrophobicity, and surface charge) and functional properties (water holding capacity, oil absorption capacity, emulsifying capacity and stability, foaming capacity and stability, and least gelling concentration). Protein concentrates exhibited lower average values for particle size, surface charge, surface hydrophobicity, and water holding capacity, but higher values for oil absorption capacity, protein solubility, emulsion capacity and stability, as well as foaming capacity and stability, compared to protein isolates. Intensive processing appeared to denature proteins in most isolates, leading to reduced functional properties. Changes in pH and the addition of 2% NaCl influenced the properties of both protein isolates and concentrates. Protein solubility, emulsion capacity and stability, and foaming stability of the protein samples were superior at pH 10, followed by pH 3. The addition of 2% NaCl enhanced foaming capacity and reduced the least gelling concentration. A significant interaction between sample and treatment conditions (p < 0.001) in protein isolates and protein concentrates was observed. Crop type differences in protein solubility, oil emulsion capacity and foaming stability of protein concentrates under certain conditions were detected using maximum likelihood factor analysis (MFLA). However, these differences were not evident in protein isolates, possibly due to more variable processing conditions. This study evaluated the physicochemical and functional properties of commercially produced protein concentrates and isolates from pea, lentil, faba bean, and soybean, using air‐classification and wet fractionation. Protein concentrates showed significant differences in physicochemical and functional characteristics compared with isolates. Maximum likelihood factor analysis revealed crop‐specific variations in solubility, oil emulsion capacity, and foaming stability among concentrates under certain conditions. These differences were not evident in isolates, likely due to greater variability in processing.

In this work, solid-surface fluorescence spectra of Rhodamine B (RhB) and fluorescein (FLU), two extensively used fluorophores, were studied and their concentrations were semi-quantitatively determined using the three-dimensional excitation–emission matrix (3D-EEM) data. In order to measure the solid fluorescence spectra, a trace amount of fluorophores was physically adsorbed on a piece of filter paper as a fluorescent paper, and the fluorescence spectra were recorded from the surface of the fluorescent paper instead of the inner parts of the solution. The spectral measurement was performed utilizing a routine spectrofluorimeter designed to measure the fluorescence of solution only by placing the fluorescent paper in a simple handmade holder at an adjusted incident angle of radiation. The results revealed a significant increase in the fluorescence intensity of the fluorescent paper strip compared to the solution phase. Moreover, in the RhB–FLU paper strip the forster resonance energy transfer was observed between FLU and RhB, similar to the observed phenomenon in the solution phase. For quantifying fluorophores, the EEM data were successfully resolved by applying multivariate partial least squares and parallel factor analysis (PARAFAC) modeling, and the results were compared with the univariate method. This study may provide a general guideline in further developing the solid fluorescence measurement of concentrated solutions or solid samples that have fluorescence measurement limitations such as high self-absorption and highly scattered spectra by using a conventional spectrofluorimeter, and also of biological samples where a trace amount of the analyte is available and high sensitivity is required. Graphical abstract

Actinomycin D (Act D), an oncogenic c-Myc promoter binder, interferes with the action of RNA polymerase. There is great demand for high-throughput technology able to monitor the activity of DNA-binding drugs. To this end, binding of 7-aminoactinomycin D (7AAD) to the duplex c-Myc promoter was investigated by use of 2D-photoluminescence emission (2D-PLE), and the resulting data were subjected to analysis by use of convenient and powerful multi-way approaches. Fluorescence measurements were performed by use of the quantum dot (QD)-conjugated c-Myc promoter. Intercalation of 7AAD within duplex base pairs resulted in efficient energy transfer from drug to QD via fluorescence resonance energy transfer (FRET). Multi-way analysis of the three-way data array obtained from titration experiments was performed by use of restricted Tucker3 and hard trilinear decomposition (HTD). These techniques enable analysis of high-dimensional and complex data from nanobiological systems which include several spectrally overlapped structures. It was almost impossible to obtain robust and meaningful information about the FRET process for such high overlap data by use of classical analysis. The soft approach had the important advantage over univariate classical methods of enabling us to investigate the source of variance in the fluorescence signal of the DNA–drug complex. It was established that hard trilinear decomposition analysis of FRET-measured data overcomes the problem of rank deficiency, enabling calculation of concentration profiles and pure spectra for all species, including non-fluorophores. The hard modeling approach was also used for determination of equilibrium constants for the hybridization and intercalation equilibria, using nonlinear fit data analysis. The intercalation constant 3.6 × 10 6  mol −1  L and hybridization stability 1.0 × 10 8  mol −1  L obtained were in good agreement with values reported in the literature. The analytical concentration of the QD-labeled DNA was determined by use of nonlinear fitting, without using external standard calibration samples. This study was a successful application of multi-way chemometric methods to investigation of nano-biotechnological systems where several overlapped species coexist in solution. Figure ᅟ

The 8–17E DNAzyme is a temperature-dependent DNA metalloenzyme catalyzing RNA trans esterification in the presence of Pb2+ metal ions. Labeling the stems of the substrate and DNAzyme with the Cy3 and Cy5 respectively, the considered DNAzyme was studied by the fluorescence spectroscopy. The temperature-dependent variability of the Pb2+-specific 8–17E DNAzyme catalytic sensor was investigated trough a number of successive temperature fluctuations from 4 to 25 °C to obtain information. Investigating underlined biochemical system reveals that in this sensor, free single strands Enzyme (Cy5-E) and Substrate (Cy3-S) have higher fluorescence intensities than hybridized forms, suggesting that the fluorophores are in a contact quenched. Increasing the temperature has three effects: 1) Fluorescence intensities for the free fluorophores were reduced, 2) stability of the hybridized form was reduced and cleavage of substrate in presence of Pb2+was occurred, and 3) conformation of ES hybridized form was changed (before cleavage). As a result of conformation changes in ES, S was more affected than E in the ES. Pb2+ ion shows quenching effect on both fluorophores and in the absence of N2(g) purge the effect was more considerable. A main goal that we had in mind was to find if significantly lower concentrations of Pb2+ and ES, compared to previous reports, can generate any observable cleavage in substrate. Analysis of the cleavage reaction for 50 nM ES indicates that S is cleaved at 25 °C in presence of N2(g) and 0.5 μM Pb2+, while in same condition no apparent change occurs in the 4 or 10 °C. The rapid, sensitive and low cost strategy presented here can be applicable to study temperature-dependent behavior of other nucleic acid-based biosensors.

The aim of this work is modeling the activities of 67 E. coli dihydrofolate reductase (DHFR) inhibitors 2,4-diamino-5-(substituted benzyl) pyramidines by optimization of correlation weights of local graph invariants (cwlgis), assisting genetic algorithm (GA). The relationship between the descriptors and molecular activities was modeled using radial basis function partial least squares (rbfPLS). Proper relation between activities and the optimized molecular descriptors were shown, Rtraining = 0.92 and rtest = 0.85. The results indicate promising potential for the optimization of a correlation weights scheme. It is the first application of GA in optimization of cwlgis. The study also shows the ability of rbfPLS, combined with GA, in a factor-based nonlinear QSAR modeling using simple flexible descriptors.