Prediction of wastewater quality using amperometric bioelectronic tongues.

Wastewater samples from a Swedish chemi-thermo-mechanical pulp (CTMP) mill collected at different purification stages in a wastewater treatment plant (WWTP) were analyzed with an amperometric enzyme-based biosensor array in a flow-injection system. In order to resolve the complex composition of the wastewater, the array consists of several sensing elements which yield a multidimensional response. We used principal component analysis (PCA) to decompose the array's responses, and found that wastewater with different degrees of pollution can be differentiated. With the help of partial least squares regression (PLS-R), we could link the sensor responses to the Microtox® toxicity parameter, as well as to global organic pollution parameters (COD, BOD, and TOC). From investigating the influences of individual sensors in the array, it was found that the best models were in most cases obtained when all sensors in the array were included in the PLS-R model. We find that fast simultaneous determination of several global environmental parameters characterizing wastewaters is possible with this kind of biosensor array, in particular because of the link between the sensor responses and the biological effect onto the ecosystem into which the wastewater would be released. In conjunction with multivariate data analysis tools, there is strong potential to reduce the total time until a result is yielded from days to a few minutes.

Non-linear calibration models for near infrared spectroscopy.

Different calibration techniques are available for spectroscopic applications that show nonlinear behavior. This comprehensive comparative study presents a comparison of different nonlinear calibration techniques: kernel PLS (KPLS), support vector machines (SVM), least-squares SVM (LS-SVM), relevance vector machines (RVM), Gaussian process regression (GPR), artificial neural network (ANN), and Bayesian ANN (BANN). In this comparison, partial least squares (PLS) regression is used as a linear benchmark, while the relationship of the methods is considered in terms of traditional calibration by ridge regression (RR). The performance of the different methods is demonstrated by their practical applications using three real-life near infrared (NIR) data sets. Different aspects of the various approaches including computational time, model interpretability, potential over-fitting using the non-linear models on linear problems, robustness to small or medium sample sets, and robustness to pre-processing, are discussed. The results suggest that GPR and BANN are powerful and promising methods for handling linear as well as nonlinear systems, even when the data sets are moderately small. The LS-SVM is also attractive due to its good predictive performance for both linear and nonlinear calibrations.

Crossed responses found in human trapezius muscles are not H-reflexes.

INTRODUCTION: We sought to confirm the presence of crossed short-latency reflexes in trapezius. METHODS: Mmax and Hmax were measured in the ipsilateral trapezius in 10 subjects by percutaneous electrical stimulation of the accessory nerve and the cervical nerves of C3/4 respectively. Repeated stimulation of the C3/4 cervical nerves was performed during 3 different tasks (relaxation, contraction of ipsilateral side, contraction of contralateral side). RESULTS: Ipsilaterally, responses increased significantly with an increase in the prestimulus electromyogram (EMG) and decreased significantly with a decrease in prestimulus EMG. Contralateral potentials increased significantly with contraction of the trapezius ipsilateral to the stimulus compared with contraction of the muscle in which they were recorded and decreased significantly with increasing distance from the ipsilateral side. CONCLUSIONS: We found ipsilateral and contralateral responses consistent with previous findings. However, we conclude that the contralateral response in trapezius is not a crossed reflex.

Eccentric exercise inhibits the H reflex in the middle part of the trapezius muscle.

The objectives of this study were to (1) investigate the modulation of the H reflex immediately after and 24 h after eccentric exercise in the presence of delayed-onset muscle soreness (DOMS) and (2) test the reproducibility of the H reflex in trapezius across days. H reflexes were recorded from the dominant middle trapezius muscle by electrical stimulation of the C3/4 cervical nerve in ten healthy subjects. DOMS was induced by eccentric exercise of the dominant shoulder. H reflexes were obtained in four sessions: "24 h before", "Pre", "Post", and "24 h after" eccentric exercise. Ratios of maximal H reflex and M wave responses (H (max)/M (max)) were compared between sessions. In addition, a between session comparison was done for the ratios of H reflex amplitudes (H (i_75)/M (max), and H (i_50)/M (max)) obtained from the stimulus intensity needed to obtain 75 and 50 % of H (max) at "24 h before". No ratio changes were found when comparing "24 h before" and "Pre" recordings. A decrease in H (i_50)/M (max) was found at "Post" (P < 0.05) and decreases in both H (i_75)/M (max) and H (i_50)/M (max) were observed at "24 h after" (P < 0.05). This study presented evidence that an acceptable day-to-day reproducibility of the H reflex could be obtained with the applied experimental setup. Furthermore, immediately after and 24 h after exercise a stronger stimulus intensity was needed to reach the same magnitude of the H reflex reflecting that the recruitment curve was shifted to the right. This modulation of the stimulus-response relationship could be caused by presynaptic inhibition of Ia afferent fibres' input to the motoneuron by group III and IV afferents.

Ghanaian cocoa bean fermentation characterized by spectroscopic and chromatographic methods and chemometrics.

Export of cocoa beans is of great economic importance in Ghana and several other tropical countries. Raw cocoa has an astringent, unpleasant taste, and flavor, and has to be fermented, dried, and roasted to obtain the characteristic cocoa flavor and taste. In an attempt to obtain a deeper understanding of the changes in the cocoa beans during fermentation and investigate the possibility of future development of objective methods for assessing the degree of fermentation, a novel combination of methods including cut test, colorimetry, fluorescence spectroscopy, NIR spectroscopy, and GC-MS evaluated by chemometric methods was used to examine cocoa beans sampled at different durations of fermentation and samples representing fully fermented and dried beans from all cocoa growing regions of Ghana. Using colorimetry it was found that samples moved towards higher a* and b* values as fermentation progressed. Furthermore, the degree of fermentation could, in general, be well described by the spectroscopic methods used. In addition, it was possible to link analysis of volatile compounds with predictions of fermentation time. Fermented and dried cocoa beans from the Volta and the Western regions clustered separately in the score plots based on colorimetric, fluorescence, NIR, and GC-MS indicating regional differences in the composition of Ghanaian cocoa beans. The study demonstrates the potential of colorimetry and spectroscopic methods as valuable tools for determining the fermentation degree of cocoa beans. Using GC-MS it was possible to demonstrate the formation of several important aroma compounds such 2-phenylethyl acetate, propionic acid, and acetoin and the breakdown of others like diacetyl during fermentation. Practical Application: The present study demonstrates the potential of using colorimetry and spectroscopic methods as objective methods for determining cocoa bean quality along the processing chain. Development of objective methods for determining cocoa bean quality will be of great importance for quality insurance within the fields of cocoa processing and raw material control in chocolate producing companies.

A chemometric analysis of ligand-induced changes in intrinsic fluorescence of folate binding protein indicates a link between altered conformational structure and physico-chemical characteristics.

Ligand binding alters the conformational structure and physico-chemical characteristics of bovine folate binding protein (FBP). For the purpose of achieving further information we analyzed ligand (folate and methotrexate)-induced changes in the fluorescence landscape of FBP. Fluorescence excitation and emission two-dimensional (2D) spectra were recorded over a wide range of wavelengths on a Perkin-Elmer LS 55 spectrofluorometer at varying pH in different buffers, and the resulting three-dimensional data were subjected to a chemometric analysis, parallel factor analysis (PARAFAC). The most important finding was the occurrence of two maximum intensity emission wavelengths of tryptophan, 350 nm (component one) and 330 nm (component two). In contrast to the first component, the score of the short wavelength component increased with increasing ligation of FBP. Since the emission wavelengths of indole groups in tryptophan shorten with increasing distance from the solvent surface of proteins, an increasing number of the 11 tryptophan residues seem to reorientate from the solvent surface to the interior of FBP with increasing ligation. The sharp decrease in hydrophobicity at pI=7-8 following binding of folate accords fairly well with the disappearance of strongly hydrophobic tryptophan residues from the solvent-exposed surface of FBP. The PARAFAC has thus proven useful to establish a hitherto unexplained link between parallel changes in conformational structure and physico-chemical characteristics of FBP induced by folate binding. Parameters for ligand binding derived from PARAFAC analysis of the fluorescence data were qualitatively and quantitatively similar to those obtained from binding of radiofolate to FBP. Herein, methotrexate exhibited a higher affinity for FBP than in competition with radiofolate. This could suggest a rapid and firm complexation of folate to FBP, blocking access of competing ligands.

A novel photodiode for reflectance pulse oximetry in low-power applications.

The amount of light collected is crucial for low-power applications of pulse oximetry. In this work a novel ring-shaped backside photodiode has been developed for a wearable reflectance pulse oximeter. The photodiode is proven to work with a dual LED with wavelengths of 660 nm and 940 nm. For the purpose of continuously monitoring vital signs of a human, a temperature sensor is integrated onto the chip containing the photodiode. This biomedical multisensor chip is made for integration into "the Electronic Patch", an autonomous monitoring system for humans.

Chemometric exploration of an amperometric biosensor array for fast determination of wastewater quality.

Four wastewater samples of different treatment qualities; untreated, alarm, alert and normal, from a Swedish chemi-thermo-mechanical pulp mill and pure water were investigated using an amperometric bio-electronic tongue in a batch cell. The aim was to explore enzymatically modified screen-printed amperometric sensors for the discrimination of wastewater quality and to counteract the inherent drift. Seven out of eight platinum electrodes on the array were modified with four different enzymes; tyrosinase, horseradish peroxidase, acetyl cholinesterase and butyryl cholinesterase. At a constant potential the current intensity on each sensor was measured for 200s, 100s before injection and 100s after injection of the sample. The dynamic biosensor response curves from the eight sensors were used for principal component analysis (PCA). A simple baseline and sensitivity correction equivalent to multiplicative drift correction (MDC), using steady state intensities of reference sample (catechol) recordings, was employed. A clear pattern emerged in perfect agreement with prior knowledge of the samples explaining 97% of the variation in the data by two principal components (PCs). The first PC described the treatment quality of the samples and the second PC described the difference between treated and untreated samples. Horseradish peroxidase and pure platinum sensors were found to be the determinant sensors, while the rest did not contribute much to the discrimination. The wastewater samples were characterized by the chemical oxygen demand (COD), biological oxygen demand (BOD), total organic carbon (TOC), inhibition of nitrification, inhibition of respiration and toxicity towards Vibrio fischeri using Microtox, the freshwater alga Pseudokirchneriella subcapita and the freshwater crustacean Daphnia magna.

Quantification of lipoprotein subclasses by proton nuclear magnetic resonance-based partial least-squares regression models.

BACKGROUND: Cardiovascular disease risk can be estimated in part on the basis of the plasma lipoprotein profile. Analysis of lipoprotein subclasses improves the risk evaluation, but the traditional methods are very time-consuming. Novel, rapid, and productive methods are therefore needed. METHODS: We obtained plasma samples from 103 fasting people and determined the plasma lipoprotein subclass profiles by an established ultracentrifugation-based method. Proton nuclear magnetic resonance (NMR) spectra were obtained from replicate samples on a 600 MHz NMR spectrometer. From the ultracentrifugation-based reference data and the NMR spectra, we developed partial least-squares (PLS) regression models to predict cholesterol and triglyceride (TG) concentrations in plasma as well as in VLDL, intermediate-density lipoprotein (IDL), LDL, 3 LDL fractions, HDL, and 3 HDL subclasses. RESULTS: The correlation coefficients (r) between the plasma TG and cholesterol concentrations measured by the 2 methods were 0.98 and 0.91, respectively. For LDL- and HDL-cholesterol concentrations, r = 0.90 and 0.94, respectively. For cholesterol concentrations in the LDL-1, LDL-2, and LDL-3 fractions, r = 0.74, 0.78, and 0.69, respectively, and for HDL subclasses HDL(2b), HDL(2a), and HDL(3), cholesterol concentrations were predicted with r = 0.92, 0.94, and 0.75, respectively. TG concentrations in VLDL, IDL, LDL, and HDL were predicted with correlations of 0.98, 0.85, 0.77, and 0.74, respectively. The cholesterol and TG concentrations in the main lipoprotein fractions and in LDL fractions and HDL subclasses predicted by the PLS models were 94%-100% of the concentrations obtained by ultracentrifugation. CONCLUSION: NMR-based PLS regression models are appropriate for use in research in which analyses of the plasma lipoprotein profile, including LDL and HDL subclasses, are required in large numbers of samples.

Multivariate analysis to separate the signal given by cross-reactants in immunoassay with sample matrix dilution.

This paper describes a new approach to achieve selectivity in an immunoassay by separating the signals given by two cross-reactive compounds present simultaneously in a complex sample matrix. The method is based on the sequential dilution of the sample containing a mixture of the two analytes, spiking each diluted sample with a reference compound, and the detection by enzyme-linked immunosorbent assay (ELISA). The obtained multivariate response was used for the individual calibrations of the assay for each of the two cross-reactants simultaneously by using principal component analysis (PCA) and partial least squares regression (PLSR) data modeling. The calibration models showed that the signal separation due the analytes 2,4-dinitrophenol (2,4-DNP) and 4-nitrophenol (4-NP) was possible with a prediction concentration error of 1.4 microM and 72 microM, respectively.

Exploratory multivariate spectroscopic study on human skin.

BACKGROUND/AIMS: Spectroscopy on human skin is a field that is being adopted increasingly because of its rapidity and high reproducibility. Infrared reflectance (IR), near-infrared reflectance (NIR), and fluorescence spectroscopy have previously been applied to human skin in vivo to compare healthy and sick skin, including skin cancer, atopy, and leprosy. Exploratory data analysis/chemometrics is a tool for evaluating multivariate data such as spectroscopic measurements. The objective of this study was to explore the spectral variance spanned by people with normal integument, and to demonstrate the advantages of multivariate analysis to skin research. METHODS: IR, NIR and fluorescence spectroscopy have been carried out in vivo on 216 volunteers' forearms before and after four tape strippings. The subjects were asked to fill in a questionnaire regarding factors suspected to influence the measurement results. Principal Component Analysis (PCA) was used to investigate whether the population can be divided into groups on the basis of their skin chemistry. Unless otherwise stated, the results are from the measurements prior to stripping. RESULTS: In contrast to IR and fluorescence spectra, NIR spectra proved able to detect gender differences. By use of PCA, classifications on male and female subjects were observed from the IR and NIR measurements, and as an indication from the fluorescence measurements. The NIR and fluorescence measurements varied between elderly and young subjects. The largest variance in the fluorescence landscapes was seen between pigmented and non-pigmented skin. No connection was found between the spectroscopic measurements and smoking or drinking habits. CONCLUSIONS: Future spectroscopic skin investigations should be balanced as regards to gender and age, as these can possibly affect the measurement results. Chemometrics proved to be superior to traditional attempts of interpreting the spectra.

Prediction of technological quality (cooking loss and Napole Yield) of pork based on fresh meat characteristics.

In order to investigate if cooking loss and Napole Yield can be predicted from various fresh meat characteristics, pH (1, 15, 30, 60, 120 min and 24 h post mortem), temperature (1, 15, 30, 60, 120 min and 24 h post mortem), water-holding capacity (Honikel's drip loss method and centrifugation loss), and NMR T2 relaxation 24 h post mortem were measured in fresh porcine M. longissimus dorsi from 102 Hampshire crossbreeds of known RN(-) genotype. Subsequently, cooking loss and Napole Yield were determined on cooked and cured, cooked samples, respectively, and partial least squares regression (PLS) was carried out to investigate possible intercorrelations between the physico-chemical measurements performed on the fresh meat and cooking loss/Napole Yield. Significant correlations were found between NMR T2 relaxation measured in fresh pork 24 h post mortem and the cooking loss (R=0.64) and Napole Yield (R=0.58), whereas no correlations were found between traditionally applied methods such as pH measurements, Honikel's method and centrifugation, and the cooking loss/Napole Yield. Consequently, it is concluded that NMR T2 relaxation characteristics of fresh pork in contrast to traditional fresh meat characteristics contain information about factors of importance for cooking loss/Napole Yield from cooked uncured/cured pork. The result implies that low-field (LF) NMR data from fresh meat reflects information about water compartmentalisation and mobility that is partly decisive for subsequent heat-induced changes of importance for the distribution of water within the cooked meat. In addition, the obtained results show that LF NMR data measured on fresh meat also seems to contain information about the inherent water of importance for the technological characteristics of the meat even when the meat is cured before cooking.

Prediction of in vitro metabolic stability of calcitriol analogs by QSAR.

The metabolic stability of a drug is an important property for potential drug candidates. Measuring this property, however, can be costly and time-consuming. The use of quantitative structure-activity relationships (QSAR) to estimate the in vitro stability is an attractive alternative to experimental measurements. A data set of 130 calcitriol analogs with known values of in vitro metabolic stability was used to develop QSAR models. The analogs were encoded with molecular structure descriptors computed mainly with the commercial software QikProp and DiverseSolutions. Variable selection was carried out by five different variable selection techniques and Partial Least Squares Regression (PLS) models were generated from the 130 analogs. The models were used for prediction of the metabolic stability of 244 virtual calcitriol analogs. Twenty of the 244 analogs were selected and the in vitro metabolic stability was determined experimentally. The PLS models were able to predict the correct metabolic stability for 17 of the 20 selected analogs, corresponding to a prediction performance of 85%. The results clearly demonstrate the utility of QSAR models in predicting the in vitro metabolic stability of calcitriol analogs.