Fully united, easy, and economical sensor array for newborn babies' amino acids monitoring: Identification of amino acids in healthy and unhealthy with PKU newborn babies.

Amino acid (AA) disorders are the main class of inborn errors of metabolism with diverse medical presentations. This paper was aimed to provide a novel and efficient sensor array for the quantification and differentiation of AAs using different pH buffer solutions as sensor elements (SEs) and nanocurcumin (NC) in the role of a marker in biofluids of newborn babies. Amino and carboxyl groups along with the side chain of different AAs in different pH buffer solutions are protonated or deprotonated. This makes each AA molecule an acid (in the role of a proton donor), a hydrogen bonding donor, as well as a polar ion. So that, these differences may permit a profile differentiation-based sensor array for AAs discrimination. Using NC as a marker, the interactions between AA and NC in different pH buffer solutions (mainly involved in acid-base, hydrogen bonding, and π- π stacking interactions) result in absorbance changes, making a discriminate response profile for each AA. The results reveal that AAs can be discriminated successfully at three concentrations levels 10, 25, and 50 µM by linear discrimination analysis (LDA) and hierarchical clustering analysis (HCA). Complex AA mixtures are also capable to be classified. The results show that our sensor array can be potentially employed to the differentiation of AAs in biofluids of healthy and unhealthy newborn babies. It should be noted that the sensor array requires only common and available lab equipment and materials, which can be applied in AAs-related fundamental studies and clinical diagnosis.

Highly specific fingerprinting of alkaline earth metal ions by a tunable plasmonic nanosensor array based on nanoaggregation of metallochromic dyes-AuNPs.

Metal ions, specifically alkaline earth metal ions (AEMIs; Mg2+, Ca2+, Sr2+, and Ba2+), have essential roles in industrial processes, medical testing, and environmental evaluation; therefore, developing sensitive detection methods capable of their contents is highly required. To this aim, we have designed an absorbance nanosensor array using three metallochromic dyes decorated on AuNPs and have monitored variations in AuNP plasmonic profiles upon the addition of AEMIs in different buffer and pH solutions. The array is designed in a tunable size of 2 × 3 × 1(2/3); as the type buffer and pH of solution are fixed, the number of dyes can be changed in three individual modes, three binary modes, and a ternary mode, respectively. Owing to the different binding affinities of AEMIs toward dyes in different buffer and pH solutions, fingerprint-like plasmonic profiles with different levels of aggregation AuNPs were generated for all modes of array. These aggregation AuNP-based fingerprint profiles in the wavelengths of 500, 525, 550, 575, 600, 625, 650, 675, 700, 725, and 750 nm were used to discriminate the AEMIs by applying pattern recognition methods including linear discrimination analysis (LDA) and hierarchical clustering analysis (HCA) to identify each AEMI in the range 2.1-24.7 µM. Accordingly, limits of detection (LODs) values of 0.013 (±3.13), 0.014 (±2.99), 0.020 (±4.17), and 0.017 (±4.31) µM were obtained the Mg2+, Ca2+, Sr2+, and Ba2+, respectively. The results revealed that all the modes of array could well differentiate complex mixtures of the AEMIs. Our suggested array also exhibited a good performance in the differentiation of AEMIs in real samples and a certified reference material (CRM) sample.

Study of interaction of metal ions with methylthymol blue by chemometrics and quantum chemical calculations.

In this study, we determine the acidity constants of methylthymol blue (MTB) and association constants of its complexes with the ZnII, CuII, and FeII metal ions (MIs), through theoretical and experimental means. The complexes were characterized using UV-Visible absorption spectroscopy combined with soft/hard chemometrics methods and quantum chemical calculations. Quantum chemical calculations revealed that electronic transitions in the UV-Visible spectra of MTB have mixed n → π* and π → π* characters. The results of molar ratio and multivariate curve resolution alternating least squares (MCR-ALS) revealed the formation of successive 1:2 and 1:1 complexes (MI:MTB) for the ZnII and CuII systems. However, the formation of successive 1:1 and 2:1 complexes are suggested for FeII by the molar ratio and MCR-ALS. The majority of transitions observed in the UV-Visible spectra of the Zn(MTB) and Cu(MTB) complexes have ligand-to-ligand charge transfer (LLCT) characters. However, the transitions in the UV-Visible spectrum of the Fe(MTB) complex have LLCT and metal-to-ligand charge transfer (MLCT) characters. For the Fe2(MTB) complex, the lowest energy transition of has an LLCT character. However, its higher energy transitions are a mixture of LLCT, MLCT, and metal-to-metal charge transfer (MMCT) characters. The correlation between experimental and computed wavelengths revealed that the 1:1 complexes of ZnII and CuII prefer square pyramidal geometries. However, the FeII complexes always show octahedral geometry.

A 3×3 visible-light cross-reactive sensor array based on the nanoaggregation of curcumin in different pH and buffers for the multivariate identification and quantification of metal ions.

Here, a facilely constructed 3 × 3 visible-light cross reactive sensor array based on nanoaggregation of curcumin (Cur) is proposed for the identification and quantification of metal ions (MIs). Synthesis of nanocurcumin (NCur) was characterized by UV-Vis spectrophotometry, transmission electron microscopy (TEM) and Fourier transform infrared (FT-IR). The average particle size was estimated about 5.21 ± 1.13 nm) n = 50 (. Our sensor array consists of nine receptors with distinct but overlapping specificities for 11 MIs: Al3+, Cd2+, Co2+, Cu2+, Hg2+, Fe2+, Fe3+, Mn2+, Ni2+, Pb2+, and Zn2+. The receptors include the nine solutions of NCur at three buffers of phosphate, ammonium, and tris each at three pH of 7, 8, and 9 (in total 9 receptors). On account of different pH and buffers, NCur-MI binding affinities can be distinguished by monitoring the UV-Vis absorbance changes. These changes are optical fingerprints that can be used to identify each MI. The absorption values in sixteen wavelengths (i.e. 332, 352, 372, 392, 412, 432, 452, 472, 492, 512, 532, 552, 572, 592, 612, and 632 nm) are considered as analytical signals to quantitatively evaluate of the absorbance responses of the sensor array. A color difference map is provided to qualitatively visualize of the colorimetric sensor array responses. Under optimal conditions, the MIs are successfully discriminated in the range of 4-48 µmol L-1. The limit of detections (LODs) values ranged from 0.47 (for Fe3+) to 1.40 µmol L-1 (for Pb2+). Furthermore, two different mixing sets of the MIs are prepared for multivariate multicomponent analysis. Finally, the suggested sensor array is employed to evaluate its practicability in the discrimination of MIs in samples of river water and serum. Moreover, it can identify the MIs in these samples. The sensor array presents a simple, save time, cost-effective, and environmentally friendly method for the identification and quantification of MIs.

Facile Approach to Fabricate a Chemical Sensor Array Based on Nanocurcumin-Metal Ions Aggregates: Detection and Identification of DNA Nucleobases.

Here, a three-channel absorbance sensor array based on the nanocurcumin-metal ion (NCur-MI) aggregates is designed for the detection and identification of deoxyribonucleic acid nucleobases (DNA NBs) for the first time. For this purpose, the binding affinities of some of MIs (i.e., Co2+, Cr3+, Cu2+, Fe2+, Fe3+, Hg2+, Mn2+, Ni2+, V3+, and Zn2+) to the NCur to induce the aggregation were evaluated under various experimental conditions. Further studies reveal that in the presence of DNA NBs, the aggregates of NCur-Co2+, NCur-Ni2+, and NCur-Zn2+ show the diverse absorbance responses to the deaggregation of NCur depending on the binding affinity of each of DNA NBs to the metal ions Co2+, Ni2+, and Zn2+. These responses are distinguishable from one another. Thus, clear differentiation among the DNA NBs is achieved by linear discriminant analysis and hierarchical clustering analysis to generate clustering maps. The discriminatory capacity of the sensor array for the identification of the DNA NBs is tested in the ranges of 2.4-16 and 5.6-10.4 µM. Furthermore, a mixed set of the DNA NBs was prepared for multivariate multicomponent analysis. Finally, the practicability of the sensor array is confirmed by the discrimination of the DNA NBs in an animal DNA sample. It should be noted that the proposed array is the first example to fabricate an NCur-based sensor array for the simultaneous detection of DNA NBs.

Simultaneous optical detection of human serum albumin and transferrin in body fluids.

A nanocurcumin (NCur)-VO2+ ensemble-based optical nanoprobe is proposed for monitoring of human serum albumin (HSA) and transferrin (TF) in biofluids of serum and urine. The determination strategy of HSA and TF is based on the decrease of the absorbance/color intensity of NCur in the presence of VO2+ due to the formation of NCur-VO2+ ensemble. This leads to aggregation of the NCur and the color change of solution from orange to pale pink. Upon addition of HSA or TF, release of VO2+ from NCur-VO2+ ensemble occurs due to their stronger binding affinities to VO2+ in competition with the NCur. This leads to deaggregation of the NCur and recovery of the decreased absorption/color intensity within a defined time range. The absorption changes at λ = 455 and the color of NCur solution can be monitored spectrophotometrically or visually by a smartphone camera, respectively. Under optimal conditions, the analytical signals increase linearly in the ranges 50-200 nM (LOD = 11 nM) and 20-140 nM (LOD = 8 nM) for HSA and TF, respectively. The difference in the different affinities between the HSA and the TF for binding to VO2+ produces the unique time profiles of each protein. Therefore, the simultaneous determination of HSA and TF is provided by using the least-square support-vector machine (LS-SVM) model. The good recoveries and small errors of predicted values suggest that the nanoprobe is capable to resolve binary mixtures of HSA and TF. The method was applied to the simultaneous determination of HSA and TF in serum and urine samples. Graphical abstract.

Enhanced Sensitivity to Detection Nanomolar Level of Cu2+ Compared to Spectrophotometry Method by Functionalized Gold Nanoparticles: Design of Sensor Assisted by Exploiting First-order Data with Chemometrics.

A simple, sensitive and efficient colorimetric assay platform for the determination of Cu2+ was proposed with the aim of developing sensitive detection based on the aggregation of AuNPs in presence of a histamine H2-receptor antagonist (famotidine, FAM) as recognition site. This study is the first to demonstrate that the molar extinction coefficients of the complexes formed by FAM and Cu2+ are very low (by analyzing the chemometrics methods on the first order data arising from different metal to ligand ratio method), leading to the undesirable sensitivity of FAM-based assays. To resolve the problem of low sensitivity, the colorimetry method based on the Cu2+-induced aggregation of AuNPs functionalized with FAM was introduced. This procedure is accompanied by a color change from bright red to blue which can be observed with the naked eyes. Detection sensitivity obtained by the developed method increased about 100 fold compared with the spectrophotometry method. This sensor exhibited a good linear relation between the absorbance ratios at 670 to 520nm (A670/520) and the concentration in the range 2-110nM with LOD=0.76nM. The satisfactory analytical performance of the proposed sensor facilitates the development of simple and affordable UV-Vis chemosensors for environmental applications.

Application of a new version of GA-RBF neural network for simultaneous spectrophotometric determination of Zn(II), Fe(II), Co(II) and Cu(II) in real samples: An exploratory study of their complexation abilities toward MTB.

The current study for the first time is devoted to the application of whole space genetic algorithm-radial basis function network (wsGA-RBFN) method to determine the content micro minerals of Zn(2+), Fe(2+), Co(2+) and Cu(2+) based on their complexes formation with methylthymol blue (MTB) spectrophotometrically in various pharmaceutical products and vegetable samples. Advantage of wsGA-RBFN compared to GA-RBFN is that centers can be located in any point of the samples spaces. Initially, the parameters controlling behavior of the system were investigated and optimum conditions were selected. Then, an exploratory analysis of complex systems was carried out by chemometrics approaches such as SVD, EFA, MCR-ALS and RAFA. The optimal parameters and conditions for constructing the proposed model of wsGA-RBFN were obtained from processing the data set of synthetic samples. Finally, wsGA-RBFN was successfully applied to the simultaneous determination of Zn(2+), Fe(2+), Co(2+) and Cu(2+) in tomato, white cabbage, red cabbage and lettuce and pharmaceutical products included iron, zinc, multi complete and B12 ampoule.

Simultaneously detection of calcium and magnesium in various samples by calmagite and chemometrics data processing.

The current study describes results of the application of radial basis function-partial least squares (RBF-PLS), partial robust M-regression (PRM), singular value decomposition (SVD), evolving factor analysis (EFA), multivariate curve resolution with alternating least squares (MCR-ALS) and rank annihilation factor analysis (RAFA) methods for the purposes of simultaneous determination of trace amounts calcium (Ca(2+)) and magnesium (Mg(2+)) and exploratory analysis based on their colored complexes formation with 1-(1-hydroxy-4-methyl-2-phenylazo)-2-naphthol-4-sulfonic acid (calmagite) as chromomeric reagent. The complex formation Ca(2+) and Mg(2+) with calmagite was investigated under pH10.20. The performance of RBF-PLS model in detection of minerals was compared with PRM as a linear model. The pure concentration and spectral profiles were obtained using MCR-ALS. EFA and SVD were used to distinguish the number species. The stability constants of the complexes were derived using RAFA. Finally, RBF-PLS was utilized for simultaneous determination of minerals in pharmaceutical formulation and various vegetable samples.

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values.

Vanillin (VA), vanillic acid (VAI) and syringaldehyde (SIA) are important food additives as flavor enhancers. The current study for the first time is devote to the application of partial least square (PLS-1), partial robust M-regression (PRM) and feed forward neural networks (FFNNs) as linear and nonlinear chemometric methods for the simultaneous detection of binary and ternary mixtures of VA, VAI and SIA using data extracted directly from UV-spectra with overlapped peaks of individual analytes. Under the optimum experimental conditions, for each compound a linear calibration was obtained in the concentration range of 0.61-20.99 [LOD=0.12], 0.67-23.19 [LOD=0.13] and 0.73-25.12 [LOD=0.15] µgmL(-1) for VA, VAI and SIA, respectively. Four calibration sets of standard samples were designed by combination of a full and fractional factorial designs with the use of the seven and three levels for each factor for binary and ternary mixtures, respectively. The results of this study reveal that both the methods of PLS-1 and PRM are similar in terms of predict ability each binary mixtures. The resolution of ternary mixture has been accomplished by FFNNs. Multivariate curve resolution-alternating least squares (MCR-ALS) was applied for the description of spectra from the acid-base titration systems each individual compound, i.e. the resolution of the complex overlapping spectra as well as to interpret the extracted spectral and concentration profiles of any pure chemical species identified. Evolving factor analysis (EFA) and singular value decomposition (SVD) were used to distinguish the number of chemical species. Subsequently, their corresponding dissociation constants were derived. Finally, FFNNs has been used to detection active compounds in real and spiked water samples.