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World Congress on Biosensors 2014
Biosensors 2014
Thursday, 26 September 2013
Article Usage Reports - New Service for Elsevier Journal Authors
Personalized dashboards provide metrics to gauge an article’s impact, provided directly to the authors. This service is now in the process of being offered to all journals on ScienceDirect.http://ow.ly/pc4JH
Just Published: Journal of Analytical and Applied Pyrolysis
A new issue of this journal has just
been published. To see abstracts of the papers it contains (with links through
to the full papers) click here:
Selected
papers from the latest issue:
Thermogravimetric monitoring of oil refinery sludge
26 September 2013,
06:14:49
Publication date: Available online 23
September 2013
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Agustín G. Barneto , Julia Moltó , José Ariza , Juan A. Conesa
The present work has two dimensions: analytical and environmental. On the one hand we proved that thermogravimetric analysis can be used to perform fast characterization of oil refinery sludge. To this end, thermogravimetric curves were deconvoluted by using autocatalytic kinetics to take into account acceleratory phases in a thermal degradation performed in oxygen-containing atmosphere or at high heating rates. Based on thermogravimetric results, oil refinery sludge was modeled in terms of various fractions (pseudo-components) which degrade as major oil cuts. On the other hand, as an alternative to landfill, we have seen that Soxhlet extraction allows recovery almost half of the weight of sludge as a mixture of hydrocarbons, similar to gas-oil, which burns without residue. This ensures both, waste inerting and significant reduction in sludge volume.
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Agustín G. Barneto , Julia Moltó , José Ariza , Juan A. Conesa
The present work has two dimensions: analytical and environmental. On the one hand we proved that thermogravimetric analysis can be used to perform fast characterization of oil refinery sludge. To this end, thermogravimetric curves were deconvoluted by using autocatalytic kinetics to take into account acceleratory phases in a thermal degradation performed in oxygen-containing atmosphere or at high heating rates. Based on thermogravimetric results, oil refinery sludge was modeled in terms of various fractions (pseudo-components) which degrade as major oil cuts. On the other hand, as an alternative to landfill, we have seen that Soxhlet extraction allows recovery almost half of the weight of sludge as a mixture of hydrocarbons, similar to gas-oil, which burns without residue. This ensures both, waste inerting and significant reduction in sludge volume.
Flame retardancy and thermal degradation behaviors of polypropylene composites with novel intumescent flame retardant and manganese dioxide
26 September 2013,
06:14:49
Publication date: Available online 23
September 2013
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Caimin Feng , Yi Zhang , Dong Liang , Siwei Liu , Zhenguo Chi , Jiarui Xu
The flame retardancy and thermal degradation behavior of polypropylene composites containing ammonium polyphosphate (APP), novel charring agent (CNCA-DA) and manganese dioxide (MnO2) were characterized by limiting oxygen index (LOI), UL-94 measurement, cone calorimeter test (CCT), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and energy dispersive spectrometry (EDS). It was found that a small amount of MnO2 could dramatically increase the LOI value, UL rating of the PP/IFR systems, and reduce the combustion parameters of PP/IFR system from CCT test, including peak heat release rate (p-HRR), total heat release (THR), and smoke production rate (SPR). The catalytic effectivity (CAT-EFF) results showed that when 1wt. % MnO2 was added, it had the highest CAT-EFF, and could promote the LOI value of the composites from 27.1 to 30.7. The TGA data revealed that MnO2 could change the degradation behavior of the IFR and PP/IFR, improve the thermal stability of the PP/IFR systems at high temperature and increase the char residue. The morphological structures observed by digital photos and SEM indicated that MnO2 could effectively help to form more continuous and compact intumescent char layer on the outer surface to protect the underlying materials from burning. The EDS results illustrated that the existence of MnO2 could promote to remain more P and O in the char layer.
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Caimin Feng , Yi Zhang , Dong Liang , Siwei Liu , Zhenguo Chi , Jiarui Xu
The flame retardancy and thermal degradation behavior of polypropylene composites containing ammonium polyphosphate (APP), novel charring agent (CNCA-DA) and manganese dioxide (MnO2) were characterized by limiting oxygen index (LOI), UL-94 measurement, cone calorimeter test (CCT), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and energy dispersive spectrometry (EDS). It was found that a small amount of MnO2 could dramatically increase the LOI value, UL rating of the PP/IFR systems, and reduce the combustion parameters of PP/IFR system from CCT test, including peak heat release rate (p-HRR), total heat release (THR), and smoke production rate (SPR). The catalytic effectivity (CAT-EFF) results showed that when 1wt. % MnO2 was added, it had the highest CAT-EFF, and could promote the LOI value of the composites from 27.1 to 30.7. The TGA data revealed that MnO2 could change the degradation behavior of the IFR and PP/IFR, improve the thermal stability of the PP/IFR systems at high temperature and increase the char residue. The morphological structures observed by digital photos and SEM indicated that MnO2 could effectively help to form more continuous and compact intumescent char layer on the outer surface to protect the underlying materials from burning. The EDS results illustrated that the existence of MnO2 could promote to remain more P and O in the char layer.
Mössbauer studies on thermal decomposition of rubidium bis(citrato)ferrate(III) precursor prepared by precursor method
26 September 2013,
06:14:49
Publication date: Available online 23
September 2013
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Manik Gupta , Munish Gupta , Vivek Sheel Jaswal , B.S Randhawa
Thermal decomposition studies of rubidium bis(citrato)ferrate(III) trihydrate precursor has been carried out in flowing air atmosphere from ambient temperature to 900°C. The precursor material was prepared by using solution based precursor method and different physico-chemical techniques i.e. simultaneous Thermogravimetry- Differential Thermogravimetry - Differential Thermal Analysis (TG-DTG-DTA), X-Ray Diffraction (powder), Transmission Electron Microscopy (TEM), Infra-red (IR) and Mössbauer spectroscopy have been employed to characterize the intermediates and end product. After dehydration, anhydrous precursor undergoes exothermic decomposition to yield various intermediates like metal carbonate, metal oxide and α-Fe2O3, followed by a solid-state reaction to form final ferrite product above 800°C. XRD study reveals the formation of pure and nanosized rubidium ferrites with α-LiFeO2 type geometry. TEM micrograph confirms the nanosized particles with average size of 65nm. For the sake of comparison, similar ferrite has also been prepared by the combustion method at a comparatively lower temperature (600 0C) and in less time.
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Manik Gupta , Munish Gupta , Vivek Sheel Jaswal , B.S Randhawa
Thermal decomposition studies of rubidium bis(citrato)ferrate(III) trihydrate precursor has been carried out in flowing air atmosphere from ambient temperature to 900°C. The precursor material was prepared by using solution based precursor method and different physico-chemical techniques i.e. simultaneous Thermogravimetry- Differential Thermogravimetry - Differential Thermal Analysis (TG-DTG-DTA), X-Ray Diffraction (powder), Transmission Electron Microscopy (TEM), Infra-red (IR) and Mössbauer spectroscopy have been employed to characterize the intermediates and end product. After dehydration, anhydrous precursor undergoes exothermic decomposition to yield various intermediates like metal carbonate, metal oxide and α-Fe2O3, followed by a solid-state reaction to form final ferrite product above 800°C. XRD study reveals the formation of pure and nanosized rubidium ferrites with α-LiFeO2 type geometry. TEM micrograph confirms the nanosized particles with average size of 65nm. For the sake of comparison, similar ferrite has also been prepared by the combustion method at a comparatively lower temperature (600 0C) and in less time.
Pyrolysis of propane for CVI of pyrocarbon Part IV: Main Pathways involved in and pyrocarbon deposit
26 September 2013,
06:14:49
Publication date: Available online 23
September 2013
Source:Journal of Analytical and Applied Pyrolysis
Author(s): I. Ziegler-Devin , R. Fournet , R. Lacroix , P.M. Marquaire
A detailed kinetic mechanism modeling both gas and surface reactions involved in Chemical Vapor Deposition (CVD) of pyrocarbon has been developed. Simulated results have been validated by comparison with experimental data. Pyrolytic carbon deposit was realized on carbon fibers by the pyrolysis of propane at low pressure (< 3kPa) and high temperature (≈ 1200K). The kinetic mechanism consists in 608 gaseous and 275 surface elementary steps, and is efficient to predict both pyrocarbon deposit rate and gas phase composition vs. temperatures, residence time ranging and fibers surface to reactant volume ratio. In this paper, the main pyrocarbon deposition pathways are proposed by using flow rate and sensitivity analyses. In our experimental conditions, pyrocarbon seems to be mainly formed by the deposition of small unsaturated species (such as acetylene and ethylene) and methyl radicals. Pyrocarbon deposition rate is controlled by the gas phase composition (H2, CH3, C2H2 and C2H4) and a few surface key reactions.
Source:Journal of Analytical and Applied Pyrolysis
Author(s): I. Ziegler-Devin , R. Fournet , R. Lacroix , P.M. Marquaire
A detailed kinetic mechanism modeling both gas and surface reactions involved in Chemical Vapor Deposition (CVD) of pyrocarbon has been developed. Simulated results have been validated by comparison with experimental data. Pyrolytic carbon deposit was realized on carbon fibers by the pyrolysis of propane at low pressure (< 3kPa) and high temperature (≈ 1200K). The kinetic mechanism consists in 608 gaseous and 275 surface elementary steps, and is efficient to predict both pyrocarbon deposit rate and gas phase composition vs. temperatures, residence time ranging and fibers surface to reactant volume ratio. In this paper, the main pyrocarbon deposition pathways are proposed by using flow rate and sensitivity analyses. In our experimental conditions, pyrocarbon seems to be mainly formed by the deposition of small unsaturated species (such as acetylene and ethylene) and methyl radicals. Pyrocarbon deposition rate is controlled by the gas phase composition (H2, CH3, C2H2 and C2H4) and a few surface key reactions.
Hydrothermal wood processing using borax decahydrate and sodium borohydride
26 September 2013,
06:14:49
Publication date: Available online 21
September 2013
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Kubilay Tekin , Mehmet K. Akalın , Sema Bektaş , Selhan Karagöz
Hydrothermal liquefaction experiments were carried out at 250, 300 and 350°C with the use of an additive (either borax decahydrate (Na2B4O7.10H2O) or sodium borohydride (NaBH4).) The effects of both temperature and types of additives on the product distributions and bio-crude compositions were viewed. The use of additives (either Na2B4O7.10H2O or NaBH4) increased bio-crude yields at all liquefaction temperatures. The highest bio-crude yield was achieved with Na2B4O7.10H2O at 300°C. The use of additives (either Na2B4O7.10H2O or NaBH4) decreased the char yield at 300 and 350°C. The heating values of ether extracts from all experimental runs including the runs without additives were close to each other. However, the heating values of the acetone extracts from chemical runs were higher than the heating values of the non-chemical run. The highest heating value of the acetone extract was 28.05MJ.kg−1 and it was obtained from the run with Na2B4O7.10H2O at 300°C. The identified compounds in ether extracts and acetone extracts were mainly oxygenated compounds. The compositions of ether extracts and acetone extracts were affected when using additives.
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Kubilay Tekin , Mehmet K. Akalın , Sema Bektaş , Selhan Karagöz
Hydrothermal liquefaction experiments were carried out at 250, 300 and 350°C with the use of an additive (either borax decahydrate (Na2B4O7.10H2O) or sodium borohydride (NaBH4).) The effects of both temperature and types of additives on the product distributions and bio-crude compositions were viewed. The use of additives (either Na2B4O7.10H2O or NaBH4) increased bio-crude yields at all liquefaction temperatures. The highest bio-crude yield was achieved with Na2B4O7.10H2O at 300°C. The use of additives (either Na2B4O7.10H2O or NaBH4) decreased the char yield at 300 and 350°C. The heating values of ether extracts from all experimental runs including the runs without additives were close to each other. However, the heating values of the acetone extracts from chemical runs were higher than the heating values of the non-chemical run. The highest heating value of the acetone extract was 28.05MJ.kg−1 and it was obtained from the run with Na2B4O7.10H2O at 300°C. The identified compounds in ether extracts and acetone extracts were mainly oxygenated compounds. The compositions of ether extracts and acetone extracts were affected when using additives.
Graphical abstract
Thermal Deoxygenation and Pyrolysis of Oleic Acid
26 September 2013,
06:14:49
Publication date: Available online 20
September 2013
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Justice Asomaning , Paolo Mussone , David C. Bressler
The primary objective of this work was to study the pyrolytic conversion of mono unsaturated fatty acids to hydrocarbon products for use as renewable chemicals and fuels. Oleic acid (cis-9-octadecenoic acid) was selected as a model mono unsaturated compound. Batch pyrolysis reactions were conducted over a combination of temperatures from 350 to 450°C and times ranging from 0.5 to 8h. Gas chromatography and mass spectroscopy were used to analyze and identify products in the gas and liquid product fractions. Analysis of the gas phase showed concurrent production of CO and CO2, indicating that deoxygenation reaction proceeded through both decarbonylation and decarboxylation mechanisms. The gas product contained also alkanes and alkenes with carbon numbers ranging from C1 to C5. Analysis of the liquid fraction revealed series of n-alkanes, alkenes and fatty acids, including stearic acid. The presence of the unsaturation resulted in cracking at the allylic C-C and predominance of C6 to C10 hydrocarbons and C9 and C10 fatty acids. This work uncovers the dominant reaction pathways in the pyrolysis of mono unsaturated free fatty acids and demonstrates the viability of this non-catalyzed conversion technology to produce renewable hydrocarbons compatible with the existing petrochemical infrastructure.
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Justice Asomaning , Paolo Mussone , David C. Bressler
The primary objective of this work was to study the pyrolytic conversion of mono unsaturated fatty acids to hydrocarbon products for use as renewable chemicals and fuels. Oleic acid (cis-9-octadecenoic acid) was selected as a model mono unsaturated compound. Batch pyrolysis reactions were conducted over a combination of temperatures from 350 to 450°C and times ranging from 0.5 to 8h. Gas chromatography and mass spectroscopy were used to analyze and identify products in the gas and liquid product fractions. Analysis of the gas phase showed concurrent production of CO and CO2, indicating that deoxygenation reaction proceeded through both decarbonylation and decarboxylation mechanisms. The gas product contained also alkanes and alkenes with carbon numbers ranging from C1 to C5. Analysis of the liquid fraction revealed series of n-alkanes, alkenes and fatty acids, including stearic acid. The presence of the unsaturation resulted in cracking at the allylic C-C and predominance of C6 to C10 hydrocarbons and C9 and C10 fatty acids. This work uncovers the dominant reaction pathways in the pyrolysis of mono unsaturated free fatty acids and demonstrates the viability of this non-catalyzed conversion technology to produce renewable hydrocarbons compatible with the existing petrochemical infrastructure.
Pyrolysis Temperature-Dependent Release of Dissolved Organic Carbon from Plant, Manure, and Biorefinery Wastes
26 September 2013,
06:14:49
Publication date: Available online 19
September 2013
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Minori Uchimiya , Tsutomu Ohno , Zhongqi He
Limited information is available to understand the chemical structure of biochar's labile dissolved organic carbon (DOC) fraction that will alter soil organic carbon (SOC) composition. This study utilized the high sensitivity of fluorescence excitation-emission (EEM) spectrophotometry to understand the structural changes in biochar-derived DOC as a function of (1) chemical property of feedstock and (2) pyrolysis temperature (350-800°C). Regardless of feedstock (almond shell, broiler litter, lignin, cottonseed hull, and pecan shell), low temperature (350-400°C) pyrolysis shifted EEM of hot water (80°C for 16h) extracts towards longer emission wavelengths, higher aromaticity regions. Five component parallel factor (PARAFAC) modeling of EEM afforded: (C1) (poly)phenolic pyrolysis products and other water-soluble aromatic structures similar to fulvic-like SOC; (C2-C3) aromatic structures similar to humic-like SOC having low water solubility that decomposed above 350°C; (C4) carboxyl and other transient thermochemical conversion intermediates that decomposed above 500°C; and (C5) thermally stable DOC fraction of lignin-rich biomass (pecan shell and lignin). Relative contribution of fulvic-like component exceeded that of humic-like components, and increased as a function of pyrolysis temperature. The C4 showed disproportionately high contributions to 500°C broiler litter and cottonseed hull biochars. The carboxyl-enriched DOC of biochars pyrolyzed at 350-500°C can have diverse environmental consequences, including the mobilization of heavy metals.
Source:Journal of Analytical and Applied Pyrolysis
Author(s): Minori Uchimiya , Tsutomu Ohno , Zhongqi He
Limited information is available to understand the chemical structure of biochar's labile dissolved organic carbon (DOC) fraction that will alter soil organic carbon (SOC) composition. This study utilized the high sensitivity of fluorescence excitation-emission (EEM) spectrophotometry to understand the structural changes in biochar-derived DOC as a function of (1) chemical property of feedstock and (2) pyrolysis temperature (350-800°C). Regardless of feedstock (almond shell, broiler litter, lignin, cottonseed hull, and pecan shell), low temperature (350-400°C) pyrolysis shifted EEM of hot water (80°C for 16h) extracts towards longer emission wavelengths, higher aromaticity regions. Five component parallel factor (PARAFAC) modeling of EEM afforded: (C1) (poly)phenolic pyrolysis products and other water-soluble aromatic structures similar to fulvic-like SOC; (C2-C3) aromatic structures similar to humic-like SOC having low water solubility that decomposed above 350°C; (C4) carboxyl and other transient thermochemical conversion intermediates that decomposed above 500°C; and (C5) thermally stable DOC fraction of lignin-rich biomass (pecan shell and lignin). Relative contribution of fulvic-like component exceeded that of humic-like components, and increased as a function of pyrolysis temperature. The C4 showed disproportionately high contributions to 500°C broiler litter and cottonseed hull biochars. The carboxyl-enriched DOC of biochars pyrolyzed at 350-500°C can have diverse environmental consequences, including the mobilization of heavy metals.
Secure Storage of Blood Fraction Samples
Uppsala Biobank began its operations in September 2008 and is a collaboration between Uppsala County Council, as represented by Uppsala University Hospital, and Uppsala University (Faculty of Medicine). Uppsala Biobank was founded to provide an organised central collection of samples that are gathered, stored and registered for the purpose of being conserved for scientific studies, treatment, and investigations.
Maria Storgärds, Project Leader at Uppsala Biobank commented “We have about 80,000 aliquots stored today. Our collection is increasing by approximately 4000 aliquots per month indicating the number of stored samples will be at least doubled within 2-4 years.” She continued “Our aim is to ensure blood, plasma and serum samples are processed from patient to cold storage in our biobank in less than 4 hours. However in a 4-hour period we seldom have 12 new samples (96 aliquots) to store. Because of this the ability of the Micronic Capcluster system to securely cap a single tube, a row of tubes or even a complete 96-tube rack in a single action perfectly suited us". She added "The low profile of Micronic 96-tube storage racks and compact size of their 0.50ml 2D-coded tubes has allowed us to optimise use of our valuable freezer space and usefully is also fully automation compatible".
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Wednesday, 25 September 2013
Just Published: Chemometrics and Intelligent Laboratory Systems
A new issue of this journal has just
been published. To see abstracts of the papers it contains (with links through
to the full papers) click here:
Selected
papers from the latest issue:
A real-time hyper-accuracy integrative approach to peak identification using lifting-based wavelet and Gaussian model for field mobile mass spectrometer
25 September 2013,
09:32:08
Publication date: 15 October
2013
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Cuiping Li , Jiuqiang Han , Qibin Huang , Ning Mu , Baoqiang Li , Bingqing Cao
Field mobile mass spectrometer is pivotal apparatus for real-time qualitative and quantitative analyses of chemical substances in situ environment pollution detection. To solve spectrum peak signal interfered by complicated noise, and to recognize irregular peak shape as well as quick monitoring, a real-time denoising and hyper-accuracy peak identification integrative approach for field mobile mass spectrometer using lifting-based wavelet transform (LWT) and Gaussian model has been developed. First, LWT was applied to eliminate the noise and to search for mass peak parameters in raw spectral peak data. Then, fitting the irregular mass peaks with Gaussian multi-peaks, a regular spectrum signal was obtained for further processing. Both of synthetic and apparatus experiment results show that LWT is a fast and effective denoising and peak identification method and retained the original peak features. The denoising effect (SNR/RMSE) by LWT was superior to Savitzky–Golay method used widely by experimental mass spectrometer, and the processing time was shortened obviously. Moreover integrated with Gaussian fitting algorithm, the peak parameters (the peak area A, centroid c, and half peak's width w) had been optimized. As the result, qualitative and quantitative accuracies of FMMS increased consequently. In addition, the approach achieved data compression.
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Cuiping Li , Jiuqiang Han , Qibin Huang , Ning Mu , Baoqiang Li , Bingqing Cao
Field mobile mass spectrometer is pivotal apparatus for real-time qualitative and quantitative analyses of chemical substances in situ environment pollution detection. To solve spectrum peak signal interfered by complicated noise, and to recognize irregular peak shape as well as quick monitoring, a real-time denoising and hyper-accuracy peak identification integrative approach for field mobile mass spectrometer using lifting-based wavelet transform (LWT) and Gaussian model has been developed. First, LWT was applied to eliminate the noise and to search for mass peak parameters in raw spectral peak data. Then, fitting the irregular mass peaks with Gaussian multi-peaks, a regular spectrum signal was obtained for further processing. Both of synthetic and apparatus experiment results show that LWT is a fast and effective denoising and peak identification method and retained the original peak features. The denoising effect (SNR/RMSE) by LWT was superior to Savitzky–Golay method used widely by experimental mass spectrometer, and the processing time was shortened obviously. Moreover integrated with Gaussian fitting algorithm, the peak parameters (the peak area A, centroid c, and half peak's width w) had been optimized. As the result, qualitative and quantitative accuracies of FMMS increased consequently. In addition, the approach achieved data compression.
Coefficient of variation, signal-to-noise ratio, and effects of normalization in validation of biomarkers from NMR-based metabonomics studies
25 September 2013,
09:32:08
Publication date: 15 October
2013
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Bo Wang , Aaron M. Goodpaster , Michael A. Kennedy
A primary goal of metabonomics research is biomarker discovery for human diseases based on differences in metabolic profiles between healthy and diseased patient populations. One of the most significant challenges in biomarker discovery is validation, which implicitly depends on the coefficient of variation (CV) associated with the measurement technique. This paper investigates how the CV of metabolite resonances measured by nuclear magnetic resonance spectroscopy (NMR) depends on signal-to-noise ratio (SNR) and normalization method. CVs were calculated for NMR resonance peaks in a series of NMR spectra of five synthetic urine samples collected over an eight-month period. An inverse correlation was detected between SNR and CV for all normalization methods. Small peaks with SNR<15 tended to have larger CVs (15–30%) compared to peaks with the highest SNR>150, which typically had smaller CVs (5–10%). The inverse relationship between CV and SNR roughly obeyed a log10 dependence. Quotient normalization (QN) tended to produce smaller CVs for smaller peaks, but larger CVs for the strongest peaks in the data, compared to no normalization, normalization to total intensity (NTI) or normalization to an internal standard (NIS). Consequently, quotient normalization appears optimal for validating low concentration metabolites. NTI or NIS appear superior to QN for samples that have very small variation in total signal intensity. While the inverse relationship between CV and log10(SNR) did not strictly hold for all metabolites, weaker concentration metabolites will likely require more rigorous validation as potential biomarkers since they tend to have poorer reproducibility.
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Bo Wang , Aaron M. Goodpaster , Michael A. Kennedy
A primary goal of metabonomics research is biomarker discovery for human diseases based on differences in metabolic profiles between healthy and diseased patient populations. One of the most significant challenges in biomarker discovery is validation, which implicitly depends on the coefficient of variation (CV) associated with the measurement technique. This paper investigates how the CV of metabolite resonances measured by nuclear magnetic resonance spectroscopy (NMR) depends on signal-to-noise ratio (SNR) and normalization method. CVs were calculated for NMR resonance peaks in a series of NMR spectra of five synthetic urine samples collected over an eight-month period. An inverse correlation was detected between SNR and CV for all normalization methods. Small peaks with SNR<15 tended to have larger CVs (15–30%) compared to peaks with the highest SNR>150, which typically had smaller CVs (5–10%). The inverse relationship between CV and SNR roughly obeyed a log10 dependence. Quotient normalization (QN) tended to produce smaller CVs for smaller peaks, but larger CVs for the strongest peaks in the data, compared to no normalization, normalization to total intensity (NTI) or normalization to an internal standard (NIS). Consequently, quotient normalization appears optimal for validating low concentration metabolites. NTI or NIS appear superior to QN for samples that have very small variation in total signal intensity. While the inverse relationship between CV and log10(SNR) did not strictly hold for all metabolites, weaker concentration metabolites will likely require more rigorous validation as potential biomarkers since they tend to have poorer reproducibility.
Key wavelengths selection from near infrared spectra using Monte Carlo sampling–recursive partial least squares
25 September 2013,
09:32:08
Publication date: 15 October
2013
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Mingjin Zhang , Shizhi Zhang , Jibran Iqbal
Variable selection is a critical step in data analysis for near infrared spectroscopy. Recently, many studies have been reported on variable selection and researchers have proposed a large number of methods to identify variables (wavelengths) that contribute useful information. In the present study, a key wavelengths selection method named Monte Carlo sampling–recursive partial least squares (MCS-RPLS) is proposed. The method mainly includes three steps: (1) Monte Carlo sampling; (2) feature selection for each subset; and (3) determination of the optimum feature set for the dataset. The method has been used for feature selection and multivariate calibration on four near infrared spectroscopic datasets: corn moisture, corn protein, HSA and γ-globulin of biological samples. And the 10-fold cross validation results are compared with those obtained by full spectra-PLS, Moving Window Partial Least Squares (MWPLS), Monte Carlo-based Uninformative Variable Elimination (MC-UVE) and CARS. The results showed that the data dimensionalities and the RMSECV values of the selected variables are greatly reduced, thus the MCS-RPLS is available for feature selection from NIR data.
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Mingjin Zhang , Shizhi Zhang , Jibran Iqbal
Variable selection is a critical step in data analysis for near infrared spectroscopy. Recently, many studies have been reported on variable selection and researchers have proposed a large number of methods to identify variables (wavelengths) that contribute useful information. In the present study, a key wavelengths selection method named Monte Carlo sampling–recursive partial least squares (MCS-RPLS) is proposed. The method mainly includes three steps: (1) Monte Carlo sampling; (2) feature selection for each subset; and (3) determination of the optimum feature set for the dataset. The method has been used for feature selection and multivariate calibration on four near infrared spectroscopic datasets: corn moisture, corn protein, HSA and γ-globulin of biological samples. And the 10-fold cross validation results are compared with those obtained by full spectra-PLS, Moving Window Partial Least Squares (MWPLS), Monte Carlo-based Uninformative Variable Elimination (MC-UVE) and CARS. The results showed that the data dimensionalities and the RMSECV values of the selected variables are greatly reduced, thus the MCS-RPLS is available for feature selection from NIR data.
A fault detection and diagnosis technique for multivariate processes using a PLS-decomposition of the measurement space
25 September 2013,
09:32:08
Publication date: 15 October
2013
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): José L. Godoy , Jorge R. Vega , Jacinto L. Marchetti
A new statistical monitoring technique based on partial least squares (PLS) is proposed for fault detection and diagnosis in multivariate processes that exhibit collinear measurements. A typical PLS regression (PLSR) modeling strategy is first extended by adding the projections of the model outputs to the latent space. Then, a PLS-decomposition of the measurements into four terms that belongs to four different subspaces is derived. In order to online monitor the PLS-projections in each subspace, new specific statistics with non-overlapped domains are combined into a single index able to detect process anomalies. To reach a complete diagnosis, a further decomposition of each statistic was defined as a sum of variable contributions. By adequately processing all this information, the technique is able to: i) detect an anomaly through a single combined index, ii) diagnose the anomaly class from the observed pattern of the four component statistics with respect to their respective confidence intervals, and iii) identify the disturbed variables based on the analysis of the main variable contributions to each of the four subspaces. The effectiveness observed in the simulated examples suggests the potential application of this technique to real production systems.
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): José L. Godoy , Jorge R. Vega , Jacinto L. Marchetti
A new statistical monitoring technique based on partial least squares (PLS) is proposed for fault detection and diagnosis in multivariate processes that exhibit collinear measurements. A typical PLS regression (PLSR) modeling strategy is first extended by adding the projections of the model outputs to the latent space. Then, a PLS-decomposition of the measurements into four terms that belongs to four different subspaces is derived. In order to online monitor the PLS-projections in each subspace, new specific statistics with non-overlapped domains are combined into a single index able to detect process anomalies. To reach a complete diagnosis, a further decomposition of each statistic was defined as a sum of variable contributions. By adequately processing all this information, the technique is able to: i) detect an anomaly through a single combined index, ii) diagnose the anomaly class from the observed pattern of the four component statistics with respect to their respective confidence intervals, and iii) identify the disturbed variables based on the analysis of the main variable contributions to each of the four subspaces. The effectiveness observed in the simulated examples suggests the potential application of this technique to real production systems.
Predicting the heats of combustion of polynitro arene, polynitro heteroarene, acyclic and cyclic nitramine, nitrate ester and nitroaliphatic compounds using bee algorithm and adaptive neuro-fuzzy inference system
25 September 2013,
09:32:08
Publication date: 15 October
2013
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): K. Zarei , M. Atabati , S. Moghaddary
A new method was developed for prediction of the heats of combustion of important classes of energetic compounds including polynitro arene, polynitro heteroarene, acyclic and cyclic nitramine, nitrate ester and nitroaliphatic compounds. A set of 1497 zero- to three-dimensional descriptors was generated for each molecule in the data set. A major problem of modeling is the high dimensionality of the descriptor space; therefore, descriptor selection is one of the most important steps. In this paper, bee algorithm (BA) was used to select the best descriptors. Bee algorithm is a new population-based optimization algorithm, which is derived from the observation of real bees and proposed to feature selection. Four descriptors were selected and used as inputs for adaptive neuro-fuzzy inference system (ANFIS). Squared correlations of coefficients were obtained as 0.9980, 0.9996 and 0.9988 for training, test and validation sets, respectively. In comparison with genetic algorithm (GA)-ANFIS and multiple linear regression (MLR)-ANFIS, the results showed that Bee-ANFIS can be used as a powerful model for prediction of heats of combustion of these compounds.
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): K. Zarei , M. Atabati , S. Moghaddary
A new method was developed for prediction of the heats of combustion of important classes of energetic compounds including polynitro arene, polynitro heteroarene, acyclic and cyclic nitramine, nitrate ester and nitroaliphatic compounds. A set of 1497 zero- to three-dimensional descriptors was generated for each molecule in the data set. A major problem of modeling is the high dimensionality of the descriptor space; therefore, descriptor selection is one of the most important steps. In this paper, bee algorithm (BA) was used to select the best descriptors. Bee algorithm is a new population-based optimization algorithm, which is derived from the observation of real bees and proposed to feature selection. Four descriptors were selected and used as inputs for adaptive neuro-fuzzy inference system (ANFIS). Squared correlations of coefficients were obtained as 0.9980, 0.9996 and 0.9988 for training, test and validation sets, respectively. In comparison with genetic algorithm (GA)-ANFIS and multiple linear regression (MLR)-ANFIS, the results showed that Bee-ANFIS can be used as a powerful model for prediction of heats of combustion of these compounds.
Fault diagnosis based on PCA for sensors of laboratorial wastewater treatment process
25 September 2013,
09:32:08
Publication date: 15 October
2013
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): E.P. Tao , W.H. Shen , T.L. Liu , X.Q. Chen
This paper presents a PCA (principal component analysis)-based diagnostic approach, combining the principal component scores with the principal component loadings, to determine the fault location of sensors in a pilot-scale SBR (sequencing batch reactor activated sludge process) wastewater treatment process. The PCA diagnostic model is firstly built with the historical normal data, and the determination of fault location of sensors in wastewater treatment process is further achieved through the combination of the scores with the loadings of principal components. The study results reveal that PCA model can be used to detect faults; the loadings of principal components can well represent the contributions of variables to the principal components; and the scores of principal components give a clear indication of the faulty samples. The feasibility and effectiveness of the application of the combination of score plots with loading plots for sensor fault diagnosis in the wastewater treatment process are well demonstrated in the study.
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): E.P. Tao , W.H. Shen , T.L. Liu , X.Q. Chen
This paper presents a PCA (principal component analysis)-based diagnostic approach, combining the principal component scores with the principal component loadings, to determine the fault location of sensors in a pilot-scale SBR (sequencing batch reactor activated sludge process) wastewater treatment process. The PCA diagnostic model is firstly built with the historical normal data, and the determination of fault location of sensors in wastewater treatment process is further achieved through the combination of the scores with the loadings of principal components. The study results reveal that PCA model can be used to detect faults; the loadings of principal components can well represent the contributions of variables to the principal components; and the scores of principal components give a clear indication of the faulty samples. The feasibility and effectiveness of the application of the combination of score plots with loading plots for sensor fault diagnosis in the wastewater treatment process are well demonstrated in the study.
Uninformative variable elimination assisted by Gram–Schmidt Orthogonalization/successive projection algorithm for descriptor selection in QSAR
25 September 2013,
09:32:08
Publication date: 15 October
2013
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Nematollah Omidikia , Mohsen Kompany-Zareh
Employment of Uninformative Variable Elimination (UVE) as a robust variable selection method is reported in this study. Each regression coefficient represents the contribution of the corresponding variable in the established model, but in the presence of uninformative variables as well as collinearity reliability of the regression coefficient's magnitude is suspicious. Successive Projection Algorithm (SPA) and Gram–Schmidt Orthogonalization (GSO) were implemented as pre-selection technique for removing collinearity and redundancy among variables in the model. Uninformative variable elimination-partial least squares (UVE-PLS) was performed on the pre-selected data set and Cvalue's were calculated for each descriptor. In this case the Cvalue's of UVE assisted by SPA or GSO could be used in order to rank the variables according to their importance. Leave-many-out cross-validation (LMO-CV) was applied to ordered descriptors for selecting optimal number of descriptors. Selwood data including 31 molecules and 53 descriptors, and anti-HIV data including 107 molecules and 160 descriptors were utilized in this study. When GSO pre-selection method is used for the Selwood data and SPA for the anti-HIV data set, obtained results were desired not only in the prediction ability of the constructed model but also in the number of selected informative descriptors. By applying GSO-UVE-PLS to the Selwood data, in an optimized condition, seven descriptors out of 53 were selected with q2 =0.769 and R 2 =0.915. Also applying SPA-UVE-PLS on the anti-HIV data, nine descriptors were selected out of 160 with q2 =0.81, R 2 =0.84 and Q2 F3 =0.8.
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Nematollah Omidikia , Mohsen Kompany-Zareh
Employment of Uninformative Variable Elimination (UVE) as a robust variable selection method is reported in this study. Each regression coefficient represents the contribution of the corresponding variable in the established model, but in the presence of uninformative variables as well as collinearity reliability of the regression coefficient's magnitude is suspicious. Successive Projection Algorithm (SPA) and Gram–Schmidt Orthogonalization (GSO) were implemented as pre-selection technique for removing collinearity and redundancy among variables in the model. Uninformative variable elimination-partial least squares (UVE-PLS) was performed on the pre-selected data set and Cvalue's were calculated for each descriptor. In this case the Cvalue's of UVE assisted by SPA or GSO could be used in order to rank the variables according to their importance. Leave-many-out cross-validation (LMO-CV) was applied to ordered descriptors for selecting optimal number of descriptors. Selwood data including 31 molecules and 53 descriptors, and anti-HIV data including 107 molecules and 160 descriptors were utilized in this study. When GSO pre-selection method is used for the Selwood data and SPA for the anti-HIV data set, obtained results were desired not only in the prediction ability of the constructed model but also in the number of selected informative descriptors. By applying GSO-UVE-PLS to the Selwood data, in an optimized condition, seven descriptors out of 53 were selected with q2 =0.769 and R 2 =0.915. Also applying SPA-UVE-PLS on the anti-HIV data, nine descriptors were selected out of 160 with q2 =0.81, R 2 =0.84 and Q2 F3 =0.8.
Graphical abstract
An improved self-adaptive differential evolution algorithm and its application
25 September 2013,
09:32:08
Publication date: 15 October
2013
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Wu Deng , Xinhua Yang , Li Zou , Meng Wang , Yaqing Liu , Yuanyuan Li
Because of the deficiencies in the global searching ability and convergence speed of the differential evolution (DE) algorithm in solving high-dimensional problems, this paper proposes an improved self-adaptive differential evolution algorithm with multiple strategies (ISDEMS) algorithm using a different search strategy and a parallel evolution mechanism. In the ISDEMS algorithm, the population is dynamically divided into multiple populations according to the fitness value of the individuals. Multiple strategies are used to improve the diversity of the individuals, to avoid premature convergence and to ensure efficiency in exchanging information among sub-populations. In addition, a self-adaptive adjustment method is introduced to automatically adjust the scaling and crossover factors during the running time. It is helpful to improve the robustness of the ISDEMS algorithm. To prove the validity of the ISDEMS algorithm for solving complex problems, thirteen benchmark problems and one real-life problem are selected to validate the performance of the ISDEMS algorithm. The experiment results show that the ISDEMS algorithm is better in terms of search precision and convergence performance than the DE, ACDE and SACDE algorithms from the literature.
Source:Chemometrics and Intelligent Laboratory Systems, Volume 128
Author(s): Wu Deng , Xinhua Yang , Li Zou , Meng Wang , Yaqing Liu , Yuanyuan Li
Because of the deficiencies in the global searching ability and convergence speed of the differential evolution (DE) algorithm in solving high-dimensional problems, this paper proposes an improved self-adaptive differential evolution algorithm with multiple strategies (ISDEMS) algorithm using a different search strategy and a parallel evolution mechanism. In the ISDEMS algorithm, the population is dynamically divided into multiple populations according to the fitness value of the individuals. Multiple strategies are used to improve the diversity of the individuals, to avoid premature convergence and to ensure efficiency in exchanging information among sub-populations. In addition, a self-adaptive adjustment method is introduced to automatically adjust the scaling and crossover factors during the running time. It is helpful to improve the robustness of the ISDEMS algorithm. To prove the validity of the ISDEMS algorithm for solving complex problems, thirteen benchmark problems and one real-life problem are selected to validate the performance of the ISDEMS algorithm. The experiment results show that the ISDEMS algorithm is better in terms of search precision and convergence performance than the DE, ACDE and SACDE algorithms from the literature.
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Tuesday, 24 September 2013
Just Published: Biosensors & Bioelectronics
A new issue of this journal has just
been published. To see abstracts of the papers it contains (with links through
to the full papers) click here:
Selected
papers from the latest issue:
Preparation and characterization of three dimensional graphene foam supported platinum–ruthenium bimetallic nanocatalysts for hydrogen peroxide based electrochemical biosensors
24 September 2013,
00:50:18
Publication date: 15 February
2014
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Chih-Chien Kung , Po-Yuan Lin , Frederick John Buse , Yuhua Xue , Xiong Yu , Liming Dai , Chung-Chiun Liu
The large surface, the excellent dispersion and the high degrees of sensitivity of bimetallic nanocatalysts were the attractive features of this investigation. Graphene foam (GF) was a three dimensional (3D) porous architecture consisting of extremely large surface and high conductive pathways. In this study, 3D GF was used incorporating platinum–ruthenium (PtRu) bimetallic nanoparticles as an electrochemical nanocatalyst for the detection of hydrogen peroxide (H2O2). PtRu/3D GF nanocatalyst exhibited a remarkable performance toward electrochemical oxidation of H2O2 without any additional mediator showing a high sensitivity (1023.1µAmM−1 cm−2) and a low detection limit (0.04µM) for H2O2. Amperometric results demonstrated that GF provided a promising platform for the development of electrochemical sensors in biosensing and PtRu/3D GF nanocatalyst possessed the excellent catalytic activity toward the H2O2 detection. A small particle size and a high degree of the dispersion in obtaining of large active surface area were important for the nanocatalyst for the best H2O2 detection in biosensing. Moreover, potential interference by ascorbic acid and uric acid appeared to be negligible.
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Chih-Chien Kung , Po-Yuan Lin , Frederick John Buse , Yuhua Xue , Xiong Yu , Liming Dai , Chung-Chiun Liu
The large surface, the excellent dispersion and the high degrees of sensitivity of bimetallic nanocatalysts were the attractive features of this investigation. Graphene foam (GF) was a three dimensional (3D) porous architecture consisting of extremely large surface and high conductive pathways. In this study, 3D GF was used incorporating platinum–ruthenium (PtRu) bimetallic nanoparticles as an electrochemical nanocatalyst for the detection of hydrogen peroxide (H2O2). PtRu/3D GF nanocatalyst exhibited a remarkable performance toward electrochemical oxidation of H2O2 without any additional mediator showing a high sensitivity (1023.1µAmM−1 cm−2) and a low detection limit (0.04µM) for H2O2. Amperometric results demonstrated that GF provided a promising platform for the development of electrochemical sensors in biosensing and PtRu/3D GF nanocatalyst possessed the excellent catalytic activity toward the H2O2 detection. A small particle size and a high degree of the dispersion in obtaining of large active surface area were important for the nanocatalyst for the best H2O2 detection in biosensing. Moreover, potential interference by ascorbic acid and uric acid appeared to be negligible.
Novel paper-based cholesterol biosensor using graphene/polyvinylpyrrolidone/polyaniline nanocomposite
24 September 2013,
00:50:18
Publication date: 15 February
2014
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Nipapan Ruecha , Ratthapol Rangkupan , Nadnudda Rodthongkum , Orawon Chailapakul
A novel nanocomposite of graphene (G), polyvinylpyrrolidone (PVP) and polyaniline (PANI) has been successfully prepared and used for the modification of paper-based biosensors via electrospraying. The droplet-like nanostructures of G/PVP/PANI-modified electrodes are obtained with an average size of 160±1.02nm. Interestingly, the presence of small amount of PVP (2mgmL−1) in the nanocomposites can substantially improve the dispersibility of G and increase the electrochemical conductivity of electrodes, leading to enhanced sensitivity of the biosensor. The well-defined cyclic voltammogram of standard ferri/ferrocyanide is achieved on a G/PVP/PANI-modified electrode with a 3-fold increase in the current signal compared to an unmodified electrode. This modified electrode also exhibits excellent electrocatalytic activity towards the oxidation of hydrogen peroxide (H2O2). Furthermore, cholesterol oxidase (ChOx) is attached to G/PVP/PANI-modified electrode for the amperometric determination of cholesterol. Under optimum conditions, a linear range of 50μM to 10mM is achieved and the limit of detection is found to be 1 μM for cholesterol. Finally, the proposed system can be applied for the determination of cholesterol in a complex biological fluid (i.e. human serum).
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Nipapan Ruecha , Ratthapol Rangkupan , Nadnudda Rodthongkum , Orawon Chailapakul
A novel nanocomposite of graphene (G), polyvinylpyrrolidone (PVP) and polyaniline (PANI) has been successfully prepared and used for the modification of paper-based biosensors via electrospraying. The droplet-like nanostructures of G/PVP/PANI-modified electrodes are obtained with an average size of 160±1.02nm. Interestingly, the presence of small amount of PVP (2mgmL−1) in the nanocomposites can substantially improve the dispersibility of G and increase the electrochemical conductivity of electrodes, leading to enhanced sensitivity of the biosensor. The well-defined cyclic voltammogram of standard ferri/ferrocyanide is achieved on a G/PVP/PANI-modified electrode with a 3-fold increase in the current signal compared to an unmodified electrode. This modified electrode also exhibits excellent electrocatalytic activity towards the oxidation of hydrogen peroxide (H2O2). Furthermore, cholesterol oxidase (ChOx) is attached to G/PVP/PANI-modified electrode for the amperometric determination of cholesterol. Under optimum conditions, a linear range of 50μM to 10mM is achieved and the limit of detection is found to be 1 μM for cholesterol. Finally, the proposed system can be applied for the determination of cholesterol in a complex biological fluid (i.e. human serum).
Graphical abstract
A highly sensitive prostate-specific antigen immunosensor based on gold nanoparticles/PAMAM dendrimer loaded on MWCNTS/chitosan/ionic liquid nanocomposite
24 September 2013,
00:50:18
Publication date: 15 February
2014
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Begard Kavosi , Abdollah Salimi , Rahman Hallaj , Kamal Amani
We have developed a sensitive electrochemical immunosensor for the detection of prostate-specific antigen (PSA), based on covalently immobilizing of anti-PSA and redox mediator (thionine) onto gold nanoparticles–incorporated polyamidoamine dendrimer (AuNPs–PAMAM) and multiwalled carbon nanotubes/ionic liquid/chitosan nanocomposite (MWCNTs/IL/Chit) as the support platform. The MWCNTs/IL/Chit nanocomposite and synthesized AuNPs were characterized using SEM and TEM microscopy techniques. Greatly amplified immunoassay was established by sandwiching the antigen between anti-PSA immobilized on the MWCNTs/IL/Chit/AuNPs–PAMAM interface and anti-PSA labeled with horseradish peroxidase (HRP-labeled anti-PSA) as secondary antibody. Phtaloyl chloride (Ph) was used as linking agent for the subsequent immobilization of AuNPs–PAMAM onto platform and anti-PSA antibody and thionine onto AuNPs–PAMAM dendrimer. The increased electrocatalytic reduction of H2O2 by HRP was monitored by differential pulse voltammetry technique. Under optimized condition the calibration curve for PSA concentration was linear up to 80ngml−1 with detection limit (signal-to-noise ratio of 3) of 1pgml−1. AuNPs–PAMAM dendrimer as platform not only increased the amount of thionine and PSA antibody but also the electron transfer process accelerated by encapsulated AuNPs. Moreover, the proposed PSA immunosensor exhibited excellent stability and reproducibility. Accurate detection of PSA in human serum samples was demonstrated by comparison to standard ELISA assays. In addition, impedance technique was used as simple, rapid, low cost label free analytical method for PSA measurement with detection limit of 0.5ngml−1 at concentration range up to 25ngml−1. The results indicate that the present protocol is quite promising in developing other electrochemical immunosensors.
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Begard Kavosi , Abdollah Salimi , Rahman Hallaj , Kamal Amani
We have developed a sensitive electrochemical immunosensor for the detection of prostate-specific antigen (PSA), based on covalently immobilizing of anti-PSA and redox mediator (thionine) onto gold nanoparticles–incorporated polyamidoamine dendrimer (AuNPs–PAMAM) and multiwalled carbon nanotubes/ionic liquid/chitosan nanocomposite (MWCNTs/IL/Chit) as the support platform. The MWCNTs/IL/Chit nanocomposite and synthesized AuNPs were characterized using SEM and TEM microscopy techniques. Greatly amplified immunoassay was established by sandwiching the antigen between anti-PSA immobilized on the MWCNTs/IL/Chit/AuNPs–PAMAM interface and anti-PSA labeled with horseradish peroxidase (HRP-labeled anti-PSA) as secondary antibody. Phtaloyl chloride (Ph) was used as linking agent for the subsequent immobilization of AuNPs–PAMAM onto platform and anti-PSA antibody and thionine onto AuNPs–PAMAM dendrimer. The increased electrocatalytic reduction of H2O2 by HRP was monitored by differential pulse voltammetry technique. Under optimized condition the calibration curve for PSA concentration was linear up to 80ngml−1 with detection limit (signal-to-noise ratio of 3) of 1pgml−1. AuNPs–PAMAM dendrimer as platform not only increased the amount of thionine and PSA antibody but also the electron transfer process accelerated by encapsulated AuNPs. Moreover, the proposed PSA immunosensor exhibited excellent stability and reproducibility. Accurate detection of PSA in human serum samples was demonstrated by comparison to standard ELISA assays. In addition, impedance technique was used as simple, rapid, low cost label free analytical method for PSA measurement with detection limit of 0.5ngml−1 at concentration range up to 25ngml−1. The results indicate that the present protocol is quite promising in developing other electrochemical immunosensors.
Graphical abstract
“Turn off–on” fluorescent sensor for platinum drugs-DNA interactions based on quantum dots
24 September 2013,
00:50:18
Publication date: 15 February
2014
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Dan Zhao , Jiaotian Li , Tianming Yang , Zhike He
A “turn off–on” mode has been established by using the interaction between platinum anticancer drugs and DNA as input signal and the fluorescence reversible change of quantum dots (QDs) as output signal. The QDs fluorescence can be quenched by platinum anticancer drugs via photo-induced electron transfer process, rendering the system into “turn off” status, and the system can then be “turned on” when fluorescence is restored due to covalent conjugation between DNA and platinum anticancer drugs. This dual-directional fluorescence change realized the detection of cisplatin and DNA, overcoming the selectivity problem commonly existed in the traditional mono-directional fluorescence detection mode. The reversible fluorescent “turn off-on” mode has been further employed to study the interactions between DNA and different platinum anticancer drugs (cisplatin, oxaliplatin and carboplatin). Furthermore, the impacts of different types of DNAs (different in base sequence, chain length and ssDNA/dsDNA) on the mode are also explored. This simple, fast and convenient spectroscopic method owns promising applications in the study on interaction between medical molecules and DNA, and in biochemical detections.
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Dan Zhao , Jiaotian Li , Tianming Yang , Zhike He
A “turn off–on” mode has been established by using the interaction between platinum anticancer drugs and DNA as input signal and the fluorescence reversible change of quantum dots (QDs) as output signal. The QDs fluorescence can be quenched by platinum anticancer drugs via photo-induced electron transfer process, rendering the system into “turn off” status, and the system can then be “turned on” when fluorescence is restored due to covalent conjugation between DNA and platinum anticancer drugs. This dual-directional fluorescence change realized the detection of cisplatin and DNA, overcoming the selectivity problem commonly existed in the traditional mono-directional fluorescence detection mode. The reversible fluorescent “turn off-on” mode has been further employed to study the interactions between DNA and different platinum anticancer drugs (cisplatin, oxaliplatin and carboplatin). Furthermore, the impacts of different types of DNAs (different in base sequence, chain length and ssDNA/dsDNA) on the mode are also explored. This simple, fast and convenient spectroscopic method owns promising applications in the study on interaction between medical molecules and DNA, and in biochemical detections.
Analysis of cell surface antigens by Surface Plasmon Resonance imaging
24 September 2013,
00:50:18
Publication date: 15 February
2014
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Ivan Stojanović , Richard B.M. Schasfoort , Leon W.M.M. Terstappen
Surface Plasmon Resonance (SPR) is most commonly used to measure bio-molecular interactions. SPR is used significantly less frequent for measuring whole cell interactions. Here we introduce a method to measure whole cells label free using the specific binding of cell surface antigens expressed on the surface of cancer cells and specific ligands deposited on sensor chips using an IBIS MX96 SPR imager (SPRi). As a model system, cells from the breast cancer cell line HS578T, SKBR3 and MCF7 were used. SPRi responses to Epithelial Cell Adhesion Molecule (EpCAM) antibody and other ligands coated on the sensor chips were measured. SPR curves show a response attributable to the sedimentation of the cells and a specific binding response on top of the initial response, the magnitude of which is dependent on the ligand density and the cell type used. Comparison of SPRi with flow cytometry showed similar EpCAM expression on MCF7, SKBR3 and HS578T cells.
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Ivan Stojanović , Richard B.M. Schasfoort , Leon W.M.M. Terstappen
Surface Plasmon Resonance (SPR) is most commonly used to measure bio-molecular interactions. SPR is used significantly less frequent for measuring whole cell interactions. Here we introduce a method to measure whole cells label free using the specific binding of cell surface antigens expressed on the surface of cancer cells and specific ligands deposited on sensor chips using an IBIS MX96 SPR imager (SPRi). As a model system, cells from the breast cancer cell line HS578T, SKBR3 and MCF7 were used. SPRi responses to Epithelial Cell Adhesion Molecule (EpCAM) antibody and other ligands coated on the sensor chips were measured. SPR curves show a response attributable to the sedimentation of the cells and a specific binding response on top of the initial response, the magnitude of which is dependent on the ligand density and the cell type used. Comparison of SPRi with flow cytometry showed similar EpCAM expression on MCF7, SKBR3 and HS578T cells.
Graphene oxide as nanogold carrier for ultrasensitive electrochemical immunoassay of Shewanella oneidensis with silver enhancement strategy
24 September 2013,
00:50:18
Publication date: 15 February
2014
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Junlin Wen , Shungui Zhou , Yong Yuan
The genus Shewanella is ubiquitous in environment and has been extensively studied for their applications in bioremediation. A novel immunoassay for ultrasensitive detection of Shewanella oneidensis was presented based on graphene oxide (GO) as nanogold carrier with silver enhancement strategy. The enhanced sensitivity was achieved by employing conjugate-featuring gold nanoparticles (AuNPs) and antibodies (Ab) assembled on bovine serum albumin (BSA)-modified GO (Ab/AuNPs/BSA/GO). After a sandwich-type antigen–antibody reaction, Ab/AuNPs/BSA/GO conjugate binding on the target analyte produced an enhanced immune-recognition response by the reduction of silver ion in the present of hydroquinone. The deposited silver metal was dissolved with nitric acid and subsequently quantified by anodic stripping voltammetry. The high AuNPs loading capacity of GO and the obvious signal amplification by gold-catalyzed silver deposition offer an excellent detection method with a wide range of linear relationship between 7.0×101 and 7.0×107 cfu/mL. Furthermore, the immunoassay developed in this work exhibited high sensitivity, acceptable stability and reproducibility. This simple and sensitive assay method has promising application in various fields for rapid detection of bacteria, protein and DNA.
Source:Biosensors and Bioelectronics, Volume 52
Author(s): Junlin Wen , Shungui Zhou , Yong Yuan
The genus Shewanella is ubiquitous in environment and has been extensively studied for their applications in bioremediation. A novel immunoassay for ultrasensitive detection of Shewanella oneidensis was presented based on graphene oxide (GO) as nanogold carrier with silver enhancement strategy. The enhanced sensitivity was achieved by employing conjugate-featuring gold nanoparticles (AuNPs) and antibodies (Ab) assembled on bovine serum albumin (BSA)-modified GO (Ab/AuNPs/BSA/GO). After a sandwich-type antigen–antibody reaction, Ab/AuNPs/BSA/GO conjugate binding on the target analyte produced an enhanced immune-recognition response by the reduction of silver ion in the present of hydroquinone. The deposited silver metal was dissolved with nitric acid and subsequently quantified by anodic stripping voltammetry. The high AuNPs loading capacity of GO and the obvious signal amplification by gold-catalyzed silver deposition offer an excellent detection method with a wide range of linear relationship between 7.0×101 and 7.0×107 cfu/mL. Furthermore, the immunoassay developed in this work exhibited high sensitivity, acceptable stability and reproducibility. This simple and sensitive assay method has promising application in various fields for rapid detection of bacteria, protein and DNA.
Exeter Analytical Launches New Website
Exeter Analytical has launched a new website to provide visitors with in-depth
information relating to the company's performance leading range of
elemental (CHN) analysers, top quality microanalysis consumables and
analytical services provided by subsidiary company - Warwick Analytical Service
(WAS).
Designed to enable visitors to effortlessly navigate through Exeter Analytical products, the portfolio of ISO 17025 accredited analytical services from WAS and growing applications note bibliography, the new site at www.exeter-analytical.co.uk is a site worth bookmarking. Reflecting rapidly growing use of Exeter Analytical CHN analysers in environmental applications a series of new pages have been added describing the considerable benefits of the technique including soil and sediment analysis, waste material fuel value determination and filter analysis of air and water samples.
Exeter Analytical manufacture and sell the Model 440 CHN Elemental Analyser - which is based on a unique horizontal furnace design. In many independent evaluations the system has been shown the most accurate and precise available on the market today, capable of performing the widest range of sample applications.
In addition to the manufacturing of analytical instrumentation Exeter Analytical also maintain an analytical facility through subsidiary – Warwick Analytical service that specialises in providing elemental analysis (metals, CHN, Halogen determination etc.) as an analytical service. This enables Exeter analytical to offer unsurpassed application support as well as a free CHN analysis service to all its customers. Over the last 25+ years - Exeter Analytical have built-up extensive knowledge across a broad cross section of elemental analysis applications and are always happy to offer free applications advice. Exeter Analytical holds full ISO 9001 and ISO 17025 accreditation and can provide analytical service work that is GMP compliant.
For further information please visit www.exeteranalytical.co.uk or contact Exeter Analytical on tel. +44 (0)2476 323 223 or email info@exeteranalytical.co.uk
Designed to enable visitors to effortlessly navigate through Exeter Analytical products, the portfolio of ISO 17025 accredited analytical services from WAS and growing applications note bibliography, the new site at www.exeter-analytical.co.uk is a site worth bookmarking. Reflecting rapidly growing use of Exeter Analytical CHN analysers in environmental applications a series of new pages have been added describing the considerable benefits of the technique including soil and sediment analysis, waste material fuel value determination and filter analysis of air and water samples.
Exeter Analytical manufacture and sell the Model 440 CHN Elemental Analyser - which is based on a unique horizontal furnace design. In many independent evaluations the system has been shown the most accurate and precise available on the market today, capable of performing the widest range of sample applications.
In addition to the manufacturing of analytical instrumentation Exeter Analytical also maintain an analytical facility through subsidiary – Warwick Analytical service that specialises in providing elemental analysis (metals, CHN, Halogen determination etc.) as an analytical service. This enables Exeter analytical to offer unsurpassed application support as well as a free CHN analysis service to all its customers. Over the last 25+ years - Exeter Analytical have built-up extensive knowledge across a broad cross section of elemental analysis applications and are always happy to offer free applications advice. Exeter Analytical holds full ISO 9001 and ISO 17025 accreditation and can provide analytical service work that is GMP compliant.
For further information please visit www.exeteranalytical.co.uk or contact Exeter Analytical on tel. +44 (0)2476 323 223 or email info@exeteranalytical.co.uk
Monday, 23 September 2013
Just Published: Analytica Chimica Acta
A new issue of this journal has just
been published. To see abstracts of the papers it contains (with links through
to the full papers) click here:
Selected
papers from the latest issue:
Utilization of nanoparticle labels for signal amplification in ultrasensitive electrochemical affinity biosensors: A review
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Liang Ding , Alan M. Bond , Jianping Zhai , Jie Zhang
Nanoparticles with desirable properties not exhibited by the bulk material can be readily synthesized because of rapid technological developments in the fields of materials science and nanotechnology. In particular their highly attractive electrochemical properties and electrocatalytic activity have facilitated achievement of the high level of signal amplification needed for the development of ultrasensitive electrochemical affinity biosensors for the detection of proteins and DNA. This review article explains the basic principles of nanoparticle based electrochemical biosensors, highlights the recent advances in the development of nanoparticle based signal amplification strategies, and provides a critical assessment of the likely drawbacks associated with each strategy. Finally, future perspectives for achieving advanced signal simplification in nanoparticles based biosensors are considered.
Source:Analytica Chimica Acta, Volume 797
Author(s): Liang Ding , Alan M. Bond , Jianping Zhai , Jie Zhang
Nanoparticles with desirable properties not exhibited by the bulk material can be readily synthesized because of rapid technological developments in the fields of materials science and nanotechnology. In particular their highly attractive electrochemical properties and electrocatalytic activity have facilitated achievement of the high level of signal amplification needed for the development of ultrasensitive electrochemical affinity biosensors for the detection of proteins and DNA. This review article explains the basic principles of nanoparticle based electrochemical biosensors, highlights the recent advances in the development of nanoparticle based signal amplification strategies, and provides a critical assessment of the likely drawbacks associated with each strategy. Finally, future perspectives for achieving advanced signal simplification in nanoparticles based biosensors are considered.
Graphical abstract
Quantitative structure–retention relationships models for prediction of high performance liquid chromatography retention time of small molecules: Endogenous metabolites and banned compounds
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Krzysztof Goryński , Barbara Bojko , Alicja Nowaczyk , Adam Buciński , Janusz Pawliszyn , Roman Kaliszan
Quantitative structure–retention relationship (QSRR) is a technique capable of improving the identification of analytes by predicting their retention time on a liquid chromatography column (LC) and/or their properties. This approach is particularly useful when LC is coupled with a high-resolution mass spectrometry (HRMS) platform. The main aim of the present study was to develop and describe appropriate QSRR models that provide usable predictive capability, allowing false positive identification to be removed during the interpretation of metabolomics data, while additionally increasing confidence of experimental results in doping control area. For this purpose, a dataset consisting of 146 drugs, metabolites and banned compounds from World Anti-Doping Agency (WADA) lists, was used. A QSRR study was carried out separately on high quality retention data determined by reversed-phase (RP-LC–HRMS) and hydrophilic interaction chromatography (HILIC-LC–HRMS) systems, employing a single protocol for each system. Multiple linear regression (MLR) was applied to construct the linear QSRR models based on a variety of theoretical molecular descriptors. The regression equations included a set of three descriptors for each model: ALogP, BELe6, R2p and ALogP2, FDI, BLTA96, were used in the analysis of reversed-phase and HILIC column models, respectively. Statistically significant QSRR models (squared correlation coefficient for model fitting, R 2 =0.95 for RP and R 2 =0.84 for HILIC) indicate a strong correlation between retention time and the molecular descriptors. An evaluation of the best correlation models, performed by validation of each model using three tests (leave-one-out, leave-many-out, external tests), demonstrated the reliability of the models. This paper provides a practical and effective method for analytical chemists working with LC/HRMS platforms to improve predictive confidence of studies that seek to identify small molecules.
Source:Analytica Chimica Acta, Volume 797
Author(s): Krzysztof Goryński , Barbara Bojko , Alicja Nowaczyk , Adam Buciński , Janusz Pawliszyn , Roman Kaliszan
Quantitative structure–retention relationship (QSRR) is a technique capable of improving the identification of analytes by predicting their retention time on a liquid chromatography column (LC) and/or their properties. This approach is particularly useful when LC is coupled with a high-resolution mass spectrometry (HRMS) platform. The main aim of the present study was to develop and describe appropriate QSRR models that provide usable predictive capability, allowing false positive identification to be removed during the interpretation of metabolomics data, while additionally increasing confidence of experimental results in doping control area. For this purpose, a dataset consisting of 146 drugs, metabolites and banned compounds from World Anti-Doping Agency (WADA) lists, was used. A QSRR study was carried out separately on high quality retention data determined by reversed-phase (RP-LC–HRMS) and hydrophilic interaction chromatography (HILIC-LC–HRMS) systems, employing a single protocol for each system. Multiple linear regression (MLR) was applied to construct the linear QSRR models based on a variety of theoretical molecular descriptors. The regression equations included a set of three descriptors for each model: ALogP, BELe6, R2p and ALogP2, FDI, BLTA96, were used in the analysis of reversed-phase and HILIC column models, respectively. Statistically significant QSRR models (squared correlation coefficient for model fitting, R 2 =0.95 for RP and R 2 =0.84 for HILIC) indicate a strong correlation between retention time and the molecular descriptors. An evaluation of the best correlation models, performed by validation of each model using three tests (leave-one-out, leave-many-out, external tests), demonstrated the reliability of the models. This paper provides a practical and effective method for analytical chemists working with LC/HRMS platforms to improve predictive confidence of studies that seek to identify small molecules.
Graphical abstract
Information fusion via constrained principal component regression for robust quantification with incomplete calibrations
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Frank Vogt
Incomplete calibrations are encountered in many applications and hamper chemometric data analyses. Such situations arise when target analytes are embedded in a chemically complex matrix from which calibration concentrations cannot be determined with reasonable efforts. In other cases, the samples’ chemical composition may fluctuate in an unpredictable way and thus cannot be comprehensively covered by calibration samples. The reason for calibration model to fail is the regression principle itself which seeks to explain measured data optimally in terms of the (potentially incomplete) calibration model but does not consider chemical meaningfulness. This study presents a novel chemometric approach which is based on experimentally feasible calibrations, i.e. concentration series of the target analytes outside the chemical matrix (‘ex situ calibration’). The inherent lack-of-information is then compensated by incorporating additional knowledge in form of regression constraints. Any outside knowledge can be utilized such as literature values of concentration ranges, concentration ratios implied e.g. by stoichiometry, sum parameters to which multiple analytes need to amount to, and/or reasonable signal reconstructions. The core idea is to mitigate the regression principle's strive for the best possible explanation of measured signals toward the best possible explanation under the condition of chemical meaningfulness. As proof-of-principle application, quantitative analyses of selected compounds in microalgae cells have been chosen. After acquiring FTIR calibration spectra from concentration series of 28 analytes, an ex situ calibration model has been built via principal component regression (PCR). Since microalgae biomass is a very complex matrix, the prediction step based on such an incomplete calibration fails. However, after incorporating several regression constraints into PCR predictions, chemically impossible results are avoided as depicted in the graphical abstract. Equally important are enhancements in concentration reproducibility. For most samples in the chosen application, the errorbars were reduced by one order of magnitude. By means of this novel chemometric method, quantitative analyses have been improved so much that cell responses to chemical shifts in their culturing environment can be studied.
Source:Analytica Chimica Acta, Volume 797
Author(s): Frank Vogt
Incomplete calibrations are encountered in many applications and hamper chemometric data analyses. Such situations arise when target analytes are embedded in a chemically complex matrix from which calibration concentrations cannot be determined with reasonable efforts. In other cases, the samples’ chemical composition may fluctuate in an unpredictable way and thus cannot be comprehensively covered by calibration samples. The reason for calibration model to fail is the regression principle itself which seeks to explain measured data optimally in terms of the (potentially incomplete) calibration model but does not consider chemical meaningfulness. This study presents a novel chemometric approach which is based on experimentally feasible calibrations, i.e. concentration series of the target analytes outside the chemical matrix (‘ex situ calibration’). The inherent lack-of-information is then compensated by incorporating additional knowledge in form of regression constraints. Any outside knowledge can be utilized such as literature values of concentration ranges, concentration ratios implied e.g. by stoichiometry, sum parameters to which multiple analytes need to amount to, and/or reasonable signal reconstructions. The core idea is to mitigate the regression principle's strive for the best possible explanation of measured signals toward the best possible explanation under the condition of chemical meaningfulness. As proof-of-principle application, quantitative analyses of selected compounds in microalgae cells have been chosen. After acquiring FTIR calibration spectra from concentration series of 28 analytes, an ex situ calibration model has been built via principal component regression (PCR). Since microalgae biomass is a very complex matrix, the prediction step based on such an incomplete calibration fails. However, after incorporating several regression constraints into PCR predictions, chemically impossible results are avoided as depicted in the graphical abstract. Equally important are enhancements in concentration reproducibility. For most samples in the chosen application, the errorbars were reduced by one order of magnitude. By means of this novel chemometric method, quantitative analyses have been improved so much that cell responses to chemical shifts in their culturing environment can be studied.
Graphical abstract
Amorphous carbon nitride as an alternative electrode material in electroanalysis: Simultaneous determination of dopamine and ascorbic acid
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Roberta A. Medeiros , Roberto Matos , Abdelkader Benchikh , Boualem Saidani , Catherine Debiemme-Chouvy , Claude Deslouis , Romeu C. Rocha-Filho , Orlando Fatibello-Filho
Boron-doped diamond (BDD) films are excellent electrode materials, whose electrochemical activity for some analytes can be tuned by controlling their surface termination, most commonly either to predominantly hydrogen or oxygen. This tuning can be accomplished by e.g. suitable cathodic or anodic electrochemical pretreatments. Recently, it has been shown that amorphous carbon nitride (a-CN x ) films may present electrochemical characteristics similar to those of BDD, including the influence of surface termination on their electrochemical activity toward some analytes. In this work, we report for the first time a complete electroanalytical method using an a-CN x electrode. Thus, an a-CN x film deposited on a stainless steel foil by DC magnetron sputtering is proposed as an alternative electrode for the simultaneous determination of dopamine (DA) and ascorbic acid (AA) in synthetic biological samples by square-wave voltammetry. The obtained results are compared with those attained using a BDD electrode. For both electrodes, a same anodic pretreatment in 0.1molL−1 KOH was necessary to attain an adequate and equivalent separation of the DA and AA oxidation potential peaks of about 330mV. The detection limits obtained for the simultaneous determination of these analytes using the a-CN x electrode were 0.0656μmolL−1 for DA and 1.05μmolL−1 for AA, whereas with the BDD electrode these values were 0.283μmolL−1 and 0.968μmolL−1, respectively. Furthermore, the results obtained in the analysis of the analytes in synthetic biological samples were satisfactory, attesting the potential application of the a-CN x electrode in electroanalysis.
Source:Analytica Chimica Acta, Volume 797
Author(s): Roberta A. Medeiros , Roberto Matos , Abdelkader Benchikh , Boualem Saidani , Catherine Debiemme-Chouvy , Claude Deslouis , Romeu C. Rocha-Filho , Orlando Fatibello-Filho
Boron-doped diamond (BDD) films are excellent electrode materials, whose electrochemical activity for some analytes can be tuned by controlling their surface termination, most commonly either to predominantly hydrogen or oxygen. This tuning can be accomplished by e.g. suitable cathodic or anodic electrochemical pretreatments. Recently, it has been shown that amorphous carbon nitride (a-CN x ) films may present electrochemical characteristics similar to those of BDD, including the influence of surface termination on their electrochemical activity toward some analytes. In this work, we report for the first time a complete electroanalytical method using an a-CN x electrode. Thus, an a-CN x film deposited on a stainless steel foil by DC magnetron sputtering is proposed as an alternative electrode for the simultaneous determination of dopamine (DA) and ascorbic acid (AA) in synthetic biological samples by square-wave voltammetry. The obtained results are compared with those attained using a BDD electrode. For both electrodes, a same anodic pretreatment in 0.1molL−1 KOH was necessary to attain an adequate and equivalent separation of the DA and AA oxidation potential peaks of about 330mV. The detection limits obtained for the simultaneous determination of these analytes using the a-CN x electrode were 0.0656μmolL−1 for DA and 1.05μmolL−1 for AA, whereas with the BDD electrode these values were 0.283μmolL−1 and 0.968μmolL−1, respectively. Furthermore, the results obtained in the analysis of the analytes in synthetic biological samples were satisfactory, attesting the potential application of the a-CN x electrode in electroanalysis.
Graphical abstract
Development of hyperbranched polymers with non-covalent interactions for extraction and determination of aflatoxins in cereal samples
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Xiaoyan Liu , Huihui Li , Zhigang Xu , Jialin Peng , Shuqiang Zhu , Haixia Zhang
A novel approach for assembling homogeneous hyperbranched polymers based on non-covalent interactions with aflatoxins was developed; the polymers were used to evaluate the extraction of aflatoxins B1, B2, G1 and G2 (AFB1, AFB2, AFG1 and AFG2) in simulant solutions. The results showed that the extraction efficiencies of three kinds of synthesized polymers for the investigated analytes were not statistically different; as a consequence, one of the representative polymers (polymer I) was used as the solid-phase extraction (SPE) sorbent to evaluate the influences of various parameters, such as desorption conditions, pH, ionic strength, concentration of methanol in sample solutions, and the mass of the sorbent on the extraction efficiency. In addition, the extraction efficiencies for these aflatoxins were compared between the investigated polymer and the traditional sorbent C18. The results showed that the investigated polymer had superior extraction efficiencies. Subsequently, the proposed polymer for the SPE packing material was employed to enrich and analyze four aflatoxins in the cereal powder samples. The limits of detection (LODs) at a signal-to-noise (S/N) ratio of 3 were in the range of 0.012–0.120ngg−1 for four aflatoxins, and the limits of quantification (LOQs) calculated at S/N=10 were from 0.04 to 0.40ngg−1 for four aflatoxins. The recoveries of four aflatoxins from cereal powder samples were in the range of 82.7–103% with relative standard deviations (RSDs) lower than 10%. The results demonstrate the suitability of the SPE approach for the analysis of trace aflatoxins in cereal powder samples.
Source:Analytica Chimica Acta, Volume 797
Author(s): Xiaoyan Liu , Huihui Li , Zhigang Xu , Jialin Peng , Shuqiang Zhu , Haixia Zhang
A novel approach for assembling homogeneous hyperbranched polymers based on non-covalent interactions with aflatoxins was developed; the polymers were used to evaluate the extraction of aflatoxins B1, B2, G1 and G2 (AFB1, AFB2, AFG1 and AFG2) in simulant solutions. The results showed that the extraction efficiencies of three kinds of synthesized polymers for the investigated analytes were not statistically different; as a consequence, one of the representative polymers (polymer I) was used as the solid-phase extraction (SPE) sorbent to evaluate the influences of various parameters, such as desorption conditions, pH, ionic strength, concentration of methanol in sample solutions, and the mass of the sorbent on the extraction efficiency. In addition, the extraction efficiencies for these aflatoxins were compared between the investigated polymer and the traditional sorbent C18. The results showed that the investigated polymer had superior extraction efficiencies. Subsequently, the proposed polymer for the SPE packing material was employed to enrich and analyze four aflatoxins in the cereal powder samples. The limits of detection (LODs) at a signal-to-noise (S/N) ratio of 3 were in the range of 0.012–0.120ngg−1 for four aflatoxins, and the limits of quantification (LOQs) calculated at S/N=10 were from 0.04 to 0.40ngg−1 for four aflatoxins. The recoveries of four aflatoxins from cereal powder samples were in the range of 82.7–103% with relative standard deviations (RSDs) lower than 10%. The results demonstrate the suitability of the SPE approach for the analysis of trace aflatoxins in cereal powder samples.
Graphical abstract
Hyphenation of optimized microfluidic sample preparation with nano liquid chromatography for faster and greener alkaloid analysis
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Yao Shen , Teris A. van Beek , Han Zuilhof , Bo Chen
A glass liquid–liquid extraction (LLE) microchip with three parallel 3.5cm long and 100μm wide interconnecting channels was optimized in terms of more environmentally friendly (greener) solvents and extraction efficiency. In addition, the optimized chip was successfully hyphenated with nano-liquid chromatography with ultraviolet and mass spectrometric detection (nanoLC–UV–MS) for on-line analysis. In this system, sample pretreatment, separation and detection are integrated, which significantly shortens the analysis time, saves labor and drastically reduces solvent consumption. Strychnine was used as model analyte to determine the extraction efficiency of the optimized 3-phase chip. Influence of organic solvent, pH of feed phase, type of alkaloid, and flow rates were investigated. The results demonstrated that the 3-phase chip nanoLC–UV/MS hyphenation combines rapid (∼25s) and efficient (extraction efficiency >90%) sample prep, with automated alkaloid analyses. The method was applied to real samples including Strychnos nux-vomica seeds, Cephaelis ipecacuanha roots, Atropa belladonna leaves, and Vinca minor leaves.
Source:Analytica Chimica Acta, Volume 797
Author(s): Yao Shen , Teris A. van Beek , Han Zuilhof , Bo Chen
A glass liquid–liquid extraction (LLE) microchip with three parallel 3.5cm long and 100μm wide interconnecting channels was optimized in terms of more environmentally friendly (greener) solvents and extraction efficiency. In addition, the optimized chip was successfully hyphenated with nano-liquid chromatography with ultraviolet and mass spectrometric detection (nanoLC–UV–MS) for on-line analysis. In this system, sample pretreatment, separation and detection are integrated, which significantly shortens the analysis time, saves labor and drastically reduces solvent consumption. Strychnine was used as model analyte to determine the extraction efficiency of the optimized 3-phase chip. Influence of organic solvent, pH of feed phase, type of alkaloid, and flow rates were investigated. The results demonstrated that the 3-phase chip nanoLC–UV/MS hyphenation combines rapid (∼25s) and efficient (extraction efficiency >90%) sample prep, with automated alkaloid analyses. The method was applied to real samples including Strychnos nux-vomica seeds, Cephaelis ipecacuanha roots, Atropa belladonna leaves, and Vinca minor leaves.
Graphical abstract
Biparametric multicommutated flow analysis system for determination of human serum phosphoesterase activity
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Łukasz Tymecki , Kamil Strzelak , Robert Koncki
A multicommutated flow analysis (MCFA) system constructed of microsolenoid valves and pumps offering simultaneous determination of activity of acid phosphatase (ACP) and alkaline phosphatase (ALP) in human serum samples has been developed. The MCFA system is based on optoelectronic flow-through detector made of two light emitting diodes and operating according to paired emitter detector diode (PEDD) principle. This photometric PEDD device has been dedicated for detection of p-nitrophenol (NP) generated in the course of enzymatic hydrolysis of p-nitrophenyl phosphate and optimized for the determination of NP in human serum samples. The developed PEDD-based MCFA system allows independent optimization of conditions for reaction and detection steps of photometric ACP and ALP bioassays. Moreover, it allows elimination of photometric interferences from serum matrix components according to two-points kinetic mode of measurement. The single measurement cycle takes 12min, consists of four measurements (two for each phosphoesterase) and enables determination of serum ACP and ALP activities at physiological and pathological levels. The real analytical utility of the developed MCFA system has been confirmed by analysis of control sera as well as real human serum samples from healthy persons and oncological patients.
Source:Analytica Chimica Acta, Volume 797
Author(s): Łukasz Tymecki , Kamil Strzelak , Robert Koncki
A multicommutated flow analysis (MCFA) system constructed of microsolenoid valves and pumps offering simultaneous determination of activity of acid phosphatase (ACP) and alkaline phosphatase (ALP) in human serum samples has been developed. The MCFA system is based on optoelectronic flow-through detector made of two light emitting diodes and operating according to paired emitter detector diode (PEDD) principle. This photometric PEDD device has been dedicated for detection of p-nitrophenol (NP) generated in the course of enzymatic hydrolysis of p-nitrophenyl phosphate and optimized for the determination of NP in human serum samples. The developed PEDD-based MCFA system allows independent optimization of conditions for reaction and detection steps of photometric ACP and ALP bioassays. Moreover, it allows elimination of photometric interferences from serum matrix components according to two-points kinetic mode of measurement. The single measurement cycle takes 12min, consists of four measurements (two for each phosphoesterase) and enables determination of serum ACP and ALP activities at physiological and pathological levels. The real analytical utility of the developed MCFA system has been confirmed by analysis of control sera as well as real human serum samples from healthy persons and oncological patients.
Graphical abstract
Alkyd paints in art: Characterization using integrated mass spectrometry
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Jacopo La Nasa , Ilaria Degano , Francesca Modugno , Maria Perla Colombini
Alkyd resins have been commonly used as binders in artist paints since the 1940s. The characterization of alkyds in samples from artworks can help to solve attribution and dating issues, investigate decay processes, and contribute to the planning of conservation strategies. Being able to assess the components of industrially formulated paint materials and to differentiate between different trademarks and producers is extremely interesting and requires multi-analytical approaches. In this paper we describe the characterization of commercial alkyd paint materials using a multi-analytical approach based on the integration of three different mass spectrometric techniques: gas chromatography–mass spectrometry (GC/MS), high performance liquid chromatography coupled with electrospray ionization mass spectrometry with a tandem quadrupole-time of flight mass spectrometer (HPLC–ESI-Q-ToF), and flow injection analysis (FIA) in the ESI-Q-ToF mass spectrometer. GC/MS was successful in determining the fatty acid and aromatic fractions of the resins after hydrolysis; HPLC–ESI-Q-ToF analysis enabled us to identify the triglycerides (TAGs) and diglycerides (DAGs) profile of each resin, and FIA analysis was used as a rapid method to evaluate the presence of possible additives such as synthetic polymers.
Source:Analytica Chimica Acta, Volume 797
Author(s): Jacopo La Nasa , Ilaria Degano , Francesca Modugno , Maria Perla Colombini
Alkyd resins have been commonly used as binders in artist paints since the 1940s. The characterization of alkyds in samples from artworks can help to solve attribution and dating issues, investigate decay processes, and contribute to the planning of conservation strategies. Being able to assess the components of industrially formulated paint materials and to differentiate between different trademarks and producers is extremely interesting and requires multi-analytical approaches. In this paper we describe the characterization of commercial alkyd paint materials using a multi-analytical approach based on the integration of three different mass spectrometric techniques: gas chromatography–mass spectrometry (GC/MS), high performance liquid chromatography coupled with electrospray ionization mass spectrometry with a tandem quadrupole-time of flight mass spectrometer (HPLC–ESI-Q-ToF), and flow injection analysis (FIA) in the ESI-Q-ToF mass spectrometer. GC/MS was successful in determining the fatty acid and aromatic fractions of the resins after hydrolysis; HPLC–ESI-Q-ToF analysis enabled us to identify the triglycerides (TAGs) and diglycerides (DAGs) profile of each resin, and FIA analysis was used as a rapid method to evaluate the presence of possible additives such as synthetic polymers.
Graphical abstract
Quantitative analysis of polypeptide antibiotic residues in a variety of food matrices by liquid chromatography coupled to tandem mass spectrometry
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): A. Kaufmann , M. Widmer
A quantitative LC–MS/MS method was developed for the determination of five polypeptide antibiotics (bacitracin, colistin A, colistin B, polymyxin B1 and polymyxin B2) in a variety of food matrices (muscle, liver, kidney, egg and milk). The described method is sufficiently sensitive, selective and provides acceptable recoveries for all compounds. The extraction is based on acidified methanolic solvent. This is followed by a reversed phase solid phase extraction step to clean-up and concentrate the extracts. The use of a modern core shell column in combination with an eluent consisting of trifluoroacetic acid, formic acid and acetonitrile provides chromatographically well resolved analyte peaks The single-step clean-up is fast and produces a sufficiently clean extract in order to control matrix-related signal suppression in the electrospray interface.
Source:Analytica Chimica Acta, Volume 797
Author(s): A. Kaufmann , M. Widmer
A quantitative LC–MS/MS method was developed for the determination of five polypeptide antibiotics (bacitracin, colistin A, colistin B, polymyxin B1 and polymyxin B2) in a variety of food matrices (muscle, liver, kidney, egg and milk). The described method is sufficiently sensitive, selective and provides acceptable recoveries for all compounds. The extraction is based on acidified methanolic solvent. This is followed by a reversed phase solid phase extraction step to clean-up and concentrate the extracts. The use of a modern core shell column in combination with an eluent consisting of trifluoroacetic acid, formic acid and acetonitrile provides chromatographically well resolved analyte peaks The single-step clean-up is fast and produces a sufficiently clean extract in order to control matrix-related signal suppression in the electrospray interface.
Graphical abstract
Sensing of a nucleic acid binding protein via a label-free perylene probe fluorescence recovery assay
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Dongli Liao , Wenying Li , Jian Chen , Huping Jiao , Huipeng Zhou , Bin Wang , Cong Yu
A novel label-free fluorescence recovery assay for the sensing of a DNA binding protein has been developed. A transcription factor c-Jun protein, and a 21 base pair duplex DNA containing the c-Jun protein binding site (J-DNA) were selected. J-DNA was mixed with a cationic fluorescent perylene probe (compound 1), and induced aggregation of the probe. Quenching of the probe's fluorescence was observed. However, when c-Jun protein was mixed with the J-DNA, c-Jun bound to the duplex DNA, which reduced the degree of the induced perylene probe aggregation, and a turn on fluorescence signal was observed. The recovered fluorescence intensity was directly related to the amount of c-Jun added. The method is highly selective, six non-DNA binding proteins and one randomly selected 21 base pair duplex DNA (con-1) were tested. No noticeable compound 1 fluorescence recovery was observed. Mutations were also introduced to the c-Jun recognition sequence and much reduced fluorescence recovery was observed. Our assay is label-free, convenient, inexpensive, and fast. It can be used in biomedical research such as high throughput screening of drugs targeted at DNA-binding proteins.
Source:Analytica Chimica Acta, Volume 797
Author(s): Dongli Liao , Wenying Li , Jian Chen , Huping Jiao , Huipeng Zhou , Bin Wang , Cong Yu
A novel label-free fluorescence recovery assay for the sensing of a DNA binding protein has been developed. A transcription factor c-Jun protein, and a 21 base pair duplex DNA containing the c-Jun protein binding site (J-DNA) were selected. J-DNA was mixed with a cationic fluorescent perylene probe (compound 1), and induced aggregation of the probe. Quenching of the probe's fluorescence was observed. However, when c-Jun protein was mixed with the J-DNA, c-Jun bound to the duplex DNA, which reduced the degree of the induced perylene probe aggregation, and a turn on fluorescence signal was observed. The recovered fluorescence intensity was directly related to the amount of c-Jun added. The method is highly selective, six non-DNA binding proteins and one randomly selected 21 base pair duplex DNA (con-1) were tested. No noticeable compound 1 fluorescence recovery was observed. Mutations were also introduced to the c-Jun recognition sequence and much reduced fluorescence recovery was observed. Our assay is label-free, convenient, inexpensive, and fast. It can be used in biomedical research such as high throughput screening of drugs targeted at DNA-binding proteins.
Graphical abstract
Cyclically amplified fluorescent detection of theophylline and thiamine pyrophosphate by coupling self-cleaving RNA ribozyme with endonuclease
23 September 2013,
08:39:12
Publication date: 3 October
2013
Source:Analytica Chimica Acta, Volume 797
Author(s): Xuemei Li , Jian Song , Yan Wang , Tao Cheng
A structure-switching-based approach for the design of fluorescent biosensors from known RNA aptazymes were demonstrated for the detection of theophylline and thiamine pyrophosphate (TPP). Taking advantages of the ability of graphene oxide (GO) to protect ssDNA from nuclease cleavage and the cyclic amplification induced by deoxyribonuclease I (DNase I), the amplified assay showed high sensitivity. In the presence of target, the target-dependent hammerhead aptazyme cleaves off. The released Shine–Dalgarno (SD) sequence was introduced into the detection system, in which a FAM labeled probe ssDNA was noncovalently assembled on GO, and the fluorescence of the dye was completely quenched. In the presence of the released sequence, the binding between the dye-labeled DNA and the SD sequence alter the conformation of dye-labeled DNA, and disturb the interaction between the dye-labeled DNA and GO, liberating dye-labeled DNA from GO. The fluorescent intensity was increased, whereupon the DNase I can cleave the free DNA in the DNA/RNA complex, thereby liberating the fluorophore and ultimately releasing the SD RNA sequence. The released SD RNA sequence then binds another DNA probe, and the cycle starts anew, which leads to significant amplification of the fluorescent signal. The strategy showed good sensitivity and the dynamic ranges were of 0.1–10μM and 0.5–100μM for theophylline and TPP, respectively. The approach opens up a wide range of possibilities for sensing of other small molecules in biological entities.
Source:Analytica Chimica Acta, Volume 797
Author(s): Xuemei Li , Jian Song , Yan Wang , Tao Cheng
A structure-switching-based approach for the design of fluorescent biosensors from known RNA aptazymes were demonstrated for the detection of theophylline and thiamine pyrophosphate (TPP). Taking advantages of the ability of graphene oxide (GO) to protect ssDNA from nuclease cleavage and the cyclic amplification induced by deoxyribonuclease I (DNase I), the amplified assay showed high sensitivity. In the presence of target, the target-dependent hammerhead aptazyme cleaves off. The released Shine–Dalgarno (SD) sequence was introduced into the detection system, in which a FAM labeled probe ssDNA was noncovalently assembled on GO, and the fluorescence of the dye was completely quenched. In the presence of the released sequence, the binding between the dye-labeled DNA and the SD sequence alter the conformation of dye-labeled DNA, and disturb the interaction between the dye-labeled DNA and GO, liberating dye-labeled DNA from GO. The fluorescent intensity was increased, whereupon the DNase I can cleave the free DNA in the DNA/RNA complex, thereby liberating the fluorophore and ultimately releasing the SD RNA sequence. The released SD RNA sequence then binds another DNA probe, and the cycle starts anew, which leads to significant amplification of the fluorescent signal. The strategy showed good sensitivity and the dynamic ranges were of 0.1–10μM and 0.5–100μM for theophylline and TPP, respectively. The approach opens up a wide range of possibilities for sensing of other small molecules in biological entities.
Graphical abstract
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