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Three structurally similar catecholamines, adrenaline (AA), dopamine (DA) and noradrenaline (NA), which are neurotransmitters well known for their treatment of neural disorders and many other diseases, were investigated at a glassy carbon electrode (GCE) with the use of differential pulse stripping voltammetry (DPSV). The aim was to develop a simple, rapid and cost effective method of simultaneous analysis of these three substances in typical samples such as human urine. Each analyte showed typical reversible redox behaviour with the use of cyclic voltammetry in aqueous medium in the pH range of 4.0–7.9, and composite voltammograms of the three analytes were found to consist of three significantly overlapping peaks corresponding to the three individual substances. Thus, two- and three-way multi-variate data analysis methods were investigated. These included unfolding methods such as—partial least squares (UPLS), principal component regression (UPCR) and radial basis function-artificial neural networks (URBF-ANN), as well as trilinear models, such as parallel factor analysis (PARAFAC) and N-way PLS (NPLS). The results were compared with those obtained from two-way voltammetric data matrix with the use of conventional models, PLS, PCR and RBF-ANN. It was found that most of the three-way models, such as PARAFAC and UPLS, performed somewhat better than others on the basis of the %RPET (5.6∼5.9) and mean %Recovery (94∼102). The proposed methods were then applied for the determination of human urine samples spiked with the three catecholamines, and the results were satisfactory.

An electrochemical biosensor capable of direct detection of DNA damage induced by clenbuterol (CLB) has been developed. A glassy carbon electrode (GCE) was modified using reduced graphene oxide-Nafion and dsDNA to produce a dsDNA/RGO-Nafion/GCE sensor. The modified electrode was characterized by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV), and the results at each stage of the electrode construction were interpreted. They indicated that the electrochemical oxidation peak currents of guanine and adenine at the electrode (dsDNA/RGO-Nafion/GCE) significantly increased as compared with those at the untreated electrode (dsDNA/GCE). Based on this, the sensor was used to measure the change of the oxidation peak currents for guanine and adenine between the intact and damaged dsDNA in the sensor films, and the DNA damage was successfully detected. Furthermore, the plot of peak current decline for the guanine and adenine versus the concentration of CLB was linear in the range of 5.0 × 10−7 to 4.0 × 10−6 mol L−1, with a limit of detection (LOD) of 3.2 × 10−7 mol L−1, which provided a good method to determine CLB indirectly.

Nanostructured Co3O4 with near-cubic morphology was synthesised using the solvothermal method, and a non-enzymatic electrochemical glucose sensor (Co3O4–CuNPs/Pt) was successfully constructed by dropping and potentiostatic depositing technologies. The obtained Co3O4 and Co3O4–CuNPs were characterised and investigated by X-ray powder diffraction, scanning electron microscopy, transmission electron microscopy, energy dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy. Quantitative analysis of glucose was performed using the amperometric (i–t) method, and a plot of current difference versus concentration of glucose was linear in the range 0.5–336 μM, with a linear correlation coefficient (R2) of 0.9989 and limit of detection (LOD) of 0.43 μM. When the linear range was reduced to 0.5–76.5 μM, R2 and LOD were 0.9997 and 0.17 μM, respectively. The sensitivity of the sensor was evaluated as 3.58 × 104 and 4.03 × 104 μA μM−1 cm−2 for the above two linear ranges, respectively. This novel sensor produced satisfactory reproducibility and stability and was applied to monitor trace amounts of glucose in human serum samples.

A novel modified electrode has been successfully constructed with the use of a nano-composite mixture consisting of molybdenum disulfide (MoS2) and gold nanoparticles (AuNPs). Its application as a cholesterol biosensor was investigated. The morphology of the prepared MoS2-AuNPs nanoparticles were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscope (AFM), X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDS). The physicochemical properties of the modified electrode at each stage of the construction were characterized by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Quantitative analysis of cholesterol was carried out with the use of the amperometric i–t method, and the calibration plot for cholesterol was linear in the range of 0.5–48 μM with a limit of detection (LOD) of 0.26 ± 0.015 μM. The apparent Michaelis-Menten constant ( K M a p p ) and sensitivity were estimated to be 0.325 mM and 4460 μA mM−1 cm−2, respectively. This novel sensor produced satisfactory reproducibility and stability, and was used successfully for the quantitative analysis of cholesterol in egg yolk and pork liver samples.

A strong red fluorescent nanocomposite, consisting of graphite-like carbon nitride nanosheets (g-C3N4 NSs) and serum albumin-capped Au nanoclusters (AuNCs), was synthesized. Dopamine (DA) can quench the red fluorescence of the nanocomposite, based on the Forster resonance energy transfer (FRET) mechanism. In this quenching process, the energy is transferred from the fluorescent g-C3N4 NSs-AuNCs to the oxidized DA quinine molecules (DA is easily oxidated to form DA quinine in air). The red fluorescence emission at 420 nm decreases dramatically and the quenching ratio (F0 – F)/F0 is linearly related to the concentration of DA in the range of 0.05–8.0 μmol L−1 with a detection limit of 0.018 μmol L−1 (S/N = 3). Additionally, this sensor has a potential of application to assay the DA in the real samples, such as human serum and human urine.

A novel 3D nano-flower-like Cu/multi-layer molybdenum disulfide composite (CuNFs/MoS2) modified glassy carbon electrode (GCE) has been successfully constructed. It was a highly sensitive and selective non-enzymatic hydrogen peroxide (H2O2) and glucose biosensor. The morphology of the obtained CuNFs-MoS2 nano-particles was investigated with the use of a scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDS). The physicochemical properties of the modified electrode were characterized at each of the construction stages with the use of an electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) techniques. The new sensor combined the advantages of MoS2 and CuNFs, and exhibited high electro-catalytic activity toward H2O2 and glucose. Quantitative analysis of H2O2 and glucose was carried out with the use of the amperometric i-t method. Linear ranges were obtained between 0.04-1.88 μM and 1.88-35.6 μM for H2O2 and 1-20 μM and 20-70 μM for glucose, and their corresponding limits of detection (LOD) were 0.021 μM and 0.32 μM. This novel sensor was successfully applied for the quantitative analysis of H2O2 in tap water and glucose in human serum samples.

The interactions of the sugars glucose and lactose with the transport protein bovine serum albumin (BSA) were investigated using fluorescence, FT-IR and circular dichroism (CD) techniques. The results indicated that glucose could be bonded and transported by BSA, mainly involving hydrogen bonds and van der Waals interactions (ΔH = -86.13 kJ mol(-1)). The obtained fluorescence data from the binding of sugar and BSA were processed by the multivariate curve resolution-alternating least squares (MCR-ALS) method, and the extracted concentration profiles showed that the equilibrium constant, rglucose:BSA, was about 7. However, the binding of lactose to BSA did not quench the fluorescence significantly, and this indicated that lactose could not be directly transported by BSA. The binding experiments were further performed using the fluorescence titration method in the presence of calcium and BSA. Calcium was added so that the calcium/BSA reactions could be studied in the presence or absence of glucose, lactose or hydrolysis products. The results showed that hydrolyzed lactose seemed to enhance calcium absorption in bovine animals. It would also appear that for children, lactose provides better nutrition; however, glucose is better for adults.

Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of spectra of the jujube (Zizyphus jujuba Mill.) fruit samples from four geographical regions. Prediction models were developed for the quantitative prediction of the contents of jujube fruit, i.e., total sugar, total acid, total phenolic content, and total antioxidant activity. Four pattern recognition methods, principal component analysis (PCA), linear discriminant analysis (LDA), least squares-support vector machines (LS-SVM), and back propagation-artificial neural networks (BP-ANN), were used for the geographical origin classification. Furthermore, three multivariate calibration models based on the standard normal variate (SNV) pretreated NIR spectroscopy, partial least squares (PLS), BP-ANN, and LS-SVM were constructed for quantitative analysis of the four analytes described above. PCA provided a useful qualitative plot of the four types of NIR spectra from the fruit. The LS-SVM model produced best quantitative prediction results. Thus, NIR spectroscopy in conjunction with chemometrics, is a very useful and rapid technique for the discrimination of jujube fruit.

Near-infrared (NIR) spectroscopy is a well-known, rapid and non-destructive technique suitable for analyses of many different food products. In this work, it was used to develop a novel method for the analysis of dehydrated tomato samples, collected from four different producers. The NIR spectra from such samples were discriminated according to the four production sources, with the use of principal component analysis (PCA). Also, hierarchical cluster analysis (HCA), linear discriminant analysis (LDA) and K-nearest neighbors (KNN) were successfully used for pattern recognition. The prediction rates were 100% for assigning producers to samples. Two multivariate calibration models—partial least squares regression (PLSR) and radial basis function neural networks (RBF-NN), were applied for quantitative analysis. NIRS calibration models were established for the determination of lycopene and total acid, sugar, phenols and antioxidant activity in dehydrated tomatoes. These calibrations were then used for prediction of unknown, dehydrated tomato samples with satisfactory results. The RBF-NN results were better than those obtained from the PLSR models, and the better predictions suggested that the novel NIR spectroscopic method supported by chemometrics, is suitable for the discrimination and prediction of the five quality parameters in the dehydrated tomato products.

An uncomplicated and sensitive kinetic spectrofluorometric method was developed for the simultaneous analysis of sibutramine, indapamide, and hydrochlorothiazide commonly found in weight-reducing health foods. The mentioned compounds were oxidized by cerium(IV) ammonium sulfate dissolved in an acidic solution. The kinetic-fluorescence spectrum of the produced cerium(III) was recorded between 0 and 600 s reaction time at the excitation wavelength of 250 nm. It was found that the fluorescence intensity was proportional to the concentration of the compounds, and their linear ranges were 0.005–0.12, 0.03–1.44 and 0.01–0.20 μg mL−1; the corresponding detection limits were 1.6, 8.3 and 6.0 ng mL−1 for sibutramine, indapamide and hydrochlorothiazide, respectively. The measured three- and two-way data of the mixtures were processed by chemometrics (included methods: parallel factor analysis (PARAFAC), partial least squares (PLS), principal component regression (PCR), and radial basis function-artificial neural network (RBF-ANN)). The proposed method was applied for the simultaneous determination of the analytes in weight-reducing food samples, and the results were comparable with those from the reference HPLC method.

Bulk graphitic carbon nitride (g-C3N4) was obtained by pyrolysis of urea at 600 °C. The material was then subjected to protonation and exfoliation to obtain strongly fluorescent g-C3N4 nanosheets. These nanosheets are representing a two-dimensional layered material that emits strong blue fluorescence peaking at 434 nm, and their quantum yield of up to 10.3 % is much higher than that of bulk g-C3N4 (6.0 %). It was found that Cu(II) ions quench the fluorescence of the nanosheets due to photo-induced electron transfer (PET), probably the result of the stronger binding affinity between Cu(II) and the nitrogen and oxygen functional groups of the nanosheets. The probe responds to Cu(II) in the 0.01 to 0.4 nM concentration range, with a 8 pM detection limit. The method was applied to the determination of Cu(II) in spiked water samples.

A simple, environmentally friendly hydrothermal method was used to prepare strongly luminescent, nitrogen-doped carbon dots (NCDs) with the use of Chinese yams as a source of carbon and nitrogen. Such NCDs have an average size of 2.7±1.4 nm; they emit blue light at 420 nm and have a quantum yield of up to 9.3%. Thus, carboxyfluorescein (FAM)-DNA macro-molecules were assembled on the surfaces of the NCDs, and stabilised by strong π-π stacking; the so formed hybrid nano-sensors were found to have an ultra-sensitive response to 6-mercaptopurine (6-MP). A strong emission and enhancement of yellow radiation was observed from FAM. Furthermore, due to the specific interactions between DNA and Hg(2+), which resulted in the formation of the T-Hg(2+)-T (T: thymine base) complex - a large, conjugated system, which formed between NCDs, DNA and 6-MP, was broken up. Thus, the fluorescence from FAM was quenched. The detection limits for 6-MP and Hg(2+) were 0.67 and 1.26 nM, respectively. The proposed method was applied for the determination of 6-MP in human serum and Hg(2+) in water samples with satisfactory results.

Tungsten disulfide (WS2) is a two-dimensional transition metal dichalcogenide, which is of particular interest because it has highly anisotropic bonding, which leads to strongly anisotropic electrical and mechanical properties. Thus, in this work, a simple hydrothermal process was developed to produce photoluminescence from WS2 dots. This was achieved in the presence of sodium tungstate and reduced L-glutathione; the emitted fluorescence produced a quantum yield as high as 0.066. The WS2 dots and the associated fluorescence were investigated with the use of transmission electron microscopy, atomic force microscopy, X-ray photoelectron spectroscopy, Fourier transform infrared and UV-vis spectroscopies. The WS2 dots were used as a fluorescent probe to analyze nitrofurazone (NFZ). The associated fluorescence resonance energy transfer (FRET) mechanism was also investigated and the emitted fluorescence was found to be linear in the range of 0.17-166 μmol L(-1) with a detection limit of 0.055 μmol L(-1). The proposed method was successfully applied for analysis of NFZ in nasal drops and water samples.

This work demonstrates how near-infrared reflectance spectroscopy (NIR) in combination with chemometrics can be used to analyse and discriminate powdered, pure and adulterated sweet potato samples. Thus, the principal component analysis (PCA) method, which is able to produce diagrams of objects as a function of PC scores, was able to distinguish and group the NIRS from the many different types of potato sample. Other methods such as the radial basis function-partial least squares (RBF-PLS) as well the successive projection algorithm (SPA) combination, distinguished the purple and white sweet potato varieties from each other as well as, importantly, from the different adulterated purple sweet potato samples. Furthermore, the total anthocyanin (TA) and total antioxidant activity (TAA) parameters were also analysed quantitatively in these samples, and high residual prediction deviation (RPD) values were noted. Also, the two recognition methods, k-nearest neighbours (KNN) and linear discriminant analysis (LDA), were able to discriminate the sweet potato samples. Thus, overall this work demonstrated that NIRS combined with chemometrics methods can be employed for the identification of purple sweet potato, white sweet potato and their adulterated samples; in addition, quantitative analysis for TA and TAA in such samples can be successfully performed.

An electrochemical biosensor capable of indirect detection of DNA damage induced by any one of the three endocrine-disrupting compounds (EDCs) – bisphenol A (BPA), 4-nonylphenol (NP) and 4- t -octylphenol (OP), has been researched and developed. The methylene blue (MB) dye was used as the redox indicator. The glassy carbon electrode (GCE) was modified by the assembled dsDNA/graphene oxide-chitosan/gold nano-particles to produce a dsDNA/GO-CS/AuNPs/GCE sensor. It was characterized with the use of electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and scanning electron microscopy (SEM) techniques. The loading/release of the MB dye by the dsDNA/GO-CS/AuNPs film was investigated, and the results showed that the process was reversible. Based on this, the sensor was used to measure the difference between the loading capabilities of intact and damaged dsDNA in the films. The sensor was then successfully applied to detect DNA damage electrochemically. The differential pulse voltammetry (DPV) peak current ratio for MB, observed before and after DNA damage, increased linearly in the presence the BPA, NP or OP compounds; the treatment range was 10–60 min, and the respective damage rates were 0.0069, 0.0044 and 0.0031 min −1 , respectively. These results were confirmed by the binding constants: 2.09 × 10 6 M −1 (BPA-DNA), 1.28 × 10 6 M −1 (NP-DNA) and 9.33 × 10 5 M −1 (OP-DNA), all of which were obtained with the use of differential pulse stripping voltammetry (DPSV).

A simple and rapid method of analysis for mercury ions (Hg 2+ ) and cysteine (Cys) was developed with the use of graphene quantum dots (GQDs) as a fluorescent probe. In the presence of GQDs, Hg 2+ cations are absorbed on their negatively charged surface by means of electrostatic interactions. Thus, the fluorescence (FL) of the GQDs would be significantly quenched as a result of the FL charge transfer, e.g. 92% quenching at 450 nm occurs for a 5 μmol L −1 Hg 2+ solution. However, when Cys was added, a significant FL enhancement was observed (510% at 450 nm for a 8.0 μmol L −1 Cys solution), and Hg 2+ combined with Cys rather than with the GQDs in an aqueous solution. This occurred because a strong metal thiol bond formed, displacing the weak electrostatic interactions, and this resulted in an FL enhancement of the GQDs. The limits of detection (LOD) for Hg 2+ and Cys were 0.439 nmol L −1 and 4.5 nmol L −1 , respectively. Also, this method was used successfully to analyze Hg 2+ and Cys in spiked water samples.

In this study, complex substances such as Mint (Mentha haplocalyx Briq.) samples from different growing regions in China were analyzed for phenolic compounds by high-performance liquid chromatography with diode array detection and for the volatile aroma compounds by gas chromatography with mass spectrometry. Chemometrics methods, e.g. principal component analysis, back-propagation artificial neural networks, and partial least squares discriminant analysis, were applied to resolve complex chromatographic profiles of Mint samples. A total of 49 aroma components and 23 phenolic compounds were identified in 79 Mint samples. Principal component analysis score plots from gas chromatography with mass spectrometry and high-performance liquid chromatography with diode array detection data sets showed a clear distinction among Mint from three different regions in China. Classification results showed that satisfactory performance of prediction ability for back-propagation artificial neural networks and partial least squares discriminant analysis. The major compounds that contributed to the discrimination were chlorogenic acid, unknown 3, kaempherol 7-O-rutinoside, salvianolic acid L, hesperidin, diosmetin, unknown 6 and pebrellin in Mint according to regression coefficients of the partial least squares discriminant analysis model. This study indicated that the proposed strategy could provide a simple and rapid technique to distinguish clearly complex profiles from samples such as Mint.

Flos Chrysanthemum tea contains flavonoids, essential oils and caffeoylquinic acids. These substances are pharmacologically active but this activity is cultivar dependent. Seventy-six Flos Chrysanthemum samples collected from four cultivars (Hangju, Taiju, Gongju and Boju) were discriminated with the use of results from high performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS). A two-dimensional chromatographic fingerprint dataset of the four kinds of Flos Chrysanthemum cultivar was built from the combined GC/HPLC profiles and thirty variables were selected. Principal component analysis (PCA) and kernel – PCA (KPCA) were used for feature extraction. The score mapping graph indicated that these two PCA methods effectively extracted most information from the samples, and the four Flos Chrysanthemum cultivars were qualitatively differentiated. Furthermore, four supervised pattern recognition techniques, radial basis function-neural network analysis (RBF-NN), least squares support vector machines (LS-SVM), linear discriminant analysis (LDA) and K-nearest neighbors (KNN), successfully predicted the validation of the samples.

A novel electrochemical sensor was constructed by depositing copper/copper oxide nano-particles on a glassy carbon electrode (GCE) to produce a Cu@CuO/GCE. The morphology and composition of this modified electrode were characterized with the use of scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD) techniques. The electrochemical properties of the novel modified GCE electrode were studied using various electrochemical techniques such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The catalytic performance of the sensor was studied with the use of differential pulse voltammetry (DPV) under optimized conditions. The constructed Cu@CuO/GCE sensor showed significantly better electrocatalytic activity for the analysis of the H 2 O 2 in comparison to the Cu/GCE or GCE. The novel sensor produced a linear response for H 2 O 2 analysis in the range of 0.005–8 mM and the detection limit was 0.23 μM (S/N = 3). Satisfactory results were obtained for H 2 O 2 analyses of tap and lake waters. This performance compares very favorably with the results from several other commonly used techniques for analysis of H 2 O 2 .

Molybdenum disulfide (MoS2) is an emerging material with some unique physical and electronic properties somewhat comparable to those of graphene. It was prepared with the use of a simple hydrothermal process, and has a layered structure similar to that of graphene. Also, it has a peroxidase-like catalytic activity and is able to catalyze the oxidation of the colorless peroxidase substrate, 3,3',5,5'-tetramethylbenzidine (TMB), in the presence of H2O2 to produce a blue product. This reaction used MoS2 as a useful peroxidase, which involved a colorimetric method for trace analysis of H2O2 in water, e.g. lake waters. This method is uncomplicated, inexpensive and highly sensitive for H2O2 in the 0.125-1.75 μM range (LOD: 0.08 μM). It is also quite stable in the presence of many common inorganic and organic potentially interfering compounds, e.g. metal ions as well as amino acids and sugars.

A novel, uncomplicated method for the analysis of lead (Pb2+) and mercury (Hg2+) ions has been developed with the use of gold nano-rods (AuNRs), which were combined with ssDNA. The AuNR–ssDNA assembly was stabilized by electrostatic interactions. The ssDNA has a random coil structure, which was changed to G-quartet and hairpin-like structures after binding with Pb2+ and Hg2+ ions, respectively. The bonding with lead and mercury caused the ssDNA assembled AuNRs (ssDNA–AuNRs) to disperse, and this increased the surface plasmon resonance (SPR) absorption of the AuNRs. Changes in the UV-vis spectral intensities allowed the selective detection of Pb2+ and Hg2+ ions at concentrations as low as 19.8 nM and 3.2 nM, respectively. Linear correlations were observed between the UV-vis spectra and the Pb2+ and Hg2+ analytes in the concentration ranges of 25–250 nM (R2 = 0.9971) for Pb2+ and 4–40 nM (R2 = 0.9956) for Hg2+, respectively. The literature suggests that the novel method is another example in which the ssDNA–AuNR assembly has been used for trace analysis of Pb2+ and Hg2+.

A novel combined near- and mid-infrared (NIR and MIR) spectroscopic method has been researched and developed for the analysis of complex substances such as the Traditional Chinese Medicine (TCM), Illicium verum Hook. F. (IVHF), and its noxious adulterant, Iuicium lanceolatum A.C. Smith (ILACS). Three types of spectral matrix were submitted for classification with the use of the linear discriminant analysis (LDA) method. The data were pretreated with either the successive projections algorithm (SPA) or the discrete wavelet transform (DWT) method. The SPA method performed somewhat better, principally because it required less spectral features for its pretreatment model. Thus, NIR or MIR matrix as well as the combined NIR/MIR one, were pretreated by the SPA method, and then analysed by LDA. This approach enabled the prediction and classification of the IVHF, ILACS and mixed samples. The MIR spectral data produced somewhat better classification rates than the NIR data. However, the best results were obtained from the combined NIR/MIR data matrix with 95-100% correct classifications for calibration, validation and prediction. Principal component analysis (PCA) of the three types of spectral data supported the results obtained with the LDA classification method.

A novel 3D nano-flower-like Cu/multi-layer molybdenum disulfide composite (CuNFs/MoS2) modified glassy carbon electrode (GCE) has been successfully constructed. It was a highly sensitive and selective non-enzymatic hydrogen peroxide (H2O2) and glucose biosensor. The morphology of the obtained CuNFs-MoS2 nano-particles was investigated with the use of a scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDS). The physicochemical properties of the modified electrode were characterized at each of the construction stages with the use of an electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) techniques. The new sensor combined the advantages of MoS2 and CuNFs, and exhibited high electro-catalytic activity toward H2O2 and glucose. Quantitative analysis of H2O2 and glucose was carried out with the use of the amperometric i-t method. Linear ranges were obtained between 0.04-1.88 μM and 1.88-35.6 μM for H2O2 and 1-20 μM and 20-70 μM for glucose, and their corresponding limits of detection (LOD) were 0.021 μM and 0.32 μM. This novel sensor was successfully applied for the quantitative analysis of H2O2 in tap water and glucose in human serum samples.

Alzheimer’s disease (AD) is one of the most common age-associated pathologies, which inevitably leads to dementia and death. The aggregation of β-amyloid (Aβ) peptides on plaques in brain tissue is strongly associated with AD. The possible link between aluminum and AD still remains controversial. In this work, the aggregation of Aβ40 induced by Al(III) was investigated with the use of the fluorescence quenching method, UV–visible and circular dichroism spectroscopies as well as the atomic force microscopy technique. The results demonstrated that Al(III) induced the transformation of the initial random coil structure to the β-sheet configuration in the Aβ40 peptides. These structural changes facilitated the aggregation of Aβ40. Also, the binding constant was calculated with the use of the multivariate curve resolution-alternating least squares (MCR-ALS) chemometrics method. Keywords: Alzheimer’s disease, β-Amyloid peptides, Spectroscopy, Chemometrics

The Chinese yam ( Dioscorea opposita) is a basic food in Asia and especially China. Consequently, an uncomplicated, reliable method should be available for the analysis of the quality and origin of the yams. Thus, near-infrared (NIR) and mid-infrared (mid-IR) spectroscopic methods were developed to discriminate among Chinese yam samples collected from four geographical regions. The yam samples were analyzed also for total sugar, polysaccharides, and flavonoids. These three analytes were used to compare the performance of the analytical methods. Overlapping spectra were resolved using chemometrics methods. Such spectra were compared qualitatively using principal component analysis (PCA) and quantitatively using partial least squares (PLS) and least squares-support vector machine (LS-SVM) models. We discriminated among the four sets of yam data using PCA, and the NIR data performed somewhat better than the mid-IR data. We constructed the PLS and LS-SVM calibration models for the prediction of the three key variables, and the LS-SVM model produced better results. Also, the NIR prediction model produced better outcomes than the mid-IR prediction model. Thus, both infrared (IR) techniques performed well for the analysis of the three key analytes, and the samples were qualitatively discriminated according to their provinces of origin. Both techniques may be recommended for the analysis of Chinese yams, although the NIR technique would be preferred.

A magnetic and fluorescent nano-composite was prepared. It comprised of a core of Fe3O4 nanoparticles (NPs), a silica shell and satellitic Au nano-clusters (AuNCs) capped with bovine serum albumin (BSA). This nano-composite has many desirable properties, e.g. magnetism, red emission, high water solubility, and high resistance to photo-bleaching. On addition of the analyte, 6-mercaptopurine (6-MP) or indeed other similar thiols, AuNCs formed aggregates because the existing cross-links within the Fe3O4 NPs@SiO2 and AuNC structure were broken in favor of the gold-thiol bonds. On suitable irradiation of such aggregates, red fluorescence was emitted at 613 nm. It decreased significantly as a function of the added 6-MP concentration, and the quenching ratio (F0 - F) / F0 was related linearly to the concentration of 6-MP in the range of 0.01 to 0.5 μmol L(-1). The detection limit was 0.004 μmol L(-1) (S/N=3). The method was strongly selective for 6-MP in the presence of oxidants, phenols, heavy-metal ions, and especially bio-thiols.

In this study, complex substances such as Mint (Mentha haplocalyx Briq.) samples from different growing regions in China were analyzed for phenolic compounds by high-performance liquid chromatography with diode array detection and for the volatile aroma compounds by gas chromatography with mass spectrometry. Chemometrics methods, e.g. principal component analysis, back-propagation artificial neural networks, and partial least squares discriminant analysis, were applied to resolve complex chromatographic profiles of Mint samples. A total of 49 aroma components and 23 phenolic compounds were identified in 79 Mint samples. Principal component analysis score plots from gas chromatography with mass spectrometry and high-performance liquid chromatography with diode array detection data sets showed a clear distinction among Mint from three different regions in China. Classification results showed that satisfactory performance of prediction ability for back-propagation artificial neural networks and partial least squares discriminant analysis. The major compounds that contributed to the discrimination were chlorogenic acid, unknown 3, kaempherol 7-O-rutinoside, salvianolic acid L, hesperidin, diosmetin, unknown 6 and pebrellin in Mint according to regression coefficients of the partial least squares discriminant analysis model. This study indicated that the proposed strategy could provide a simple and rapid technique to distinguish clearly complex profiles from samples such as Mint.