The dataset includes the annotated features from the peak table generated using XCMS software and UPLC-TOFMS data acquired from the analysis of plasma samples from 47 quiescent UC and CD patients (23 fatigued, 24 non-fatigued), for the... more
The dataset includes the annotated features from the peak table generated using XCMS software and UPLC-TOFMS data acquired from the analysis of plasma samples from 47 quiescent UC and CD patients (23 fatigued, 24 non-fatigued), for the identification of a metabolic phenotype associated to fatigue (<strong>SM_peak_table.csv</strong>). It also includes the network of protein-protein and protein-metabolite interactions inferred by PIUMet (<strong>SM_output_network.html</strong>) using a set of 180 annotated features selected as discriminant between fatigue and non-fatigued by univariate (t-test) or multivariate (PLSDA) analysis. UC: ulcerative colitis CD: Crohn disease PIUMet: L. Pirhaji, P. Milani, M. Leidl, T. Curran, J. Avila-Pacheco, C.B. Clish, F.M. White, A. Saghatelian, E. Fraenkel, Revealing disease-associated pathways by network integration of untargeted metabolomics, Nat. Methods, 13 (2016) 770–776.
<strong>Matlab scripts for the simulation and treatment of Raman datasets obtained from time dependent experiments Using MCR-ALS.</strong> <strong>- SIMULATED DATA: </strong>Simulated data is obtained by adding... more
<strong>Matlab scripts for the simulation and treatment of Raman datasets obtained from time dependent experiments Using MCR-ALS.</strong> <strong>- SIMULATED DATA: </strong>Simulated data is obtained by adding spectra of artificially generated responses (weighted considering artificially generated time profiles) to an experimental cell spectrum (Initial component) Three Different Scenarios are generated. Spectral and time profiles are obtained from here: <strong>- EXPERIMENTAL DATA: </strong>DOX dataset obtained from here https://doi.org/10.1002/jbio.201800328 <strong>- DATA ANALYSIS INSTRUCTIONS</strong> Just run <em>datatreatment.m</em>
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A multivariate analysis of data from urine with an electronic voltammetric tongue to detect patients with prostate cancer.
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An multivariate approach based on1H NMR spectra profiles of urine samples to detect patients with prostate cancer.
Research Interests: Chemistry, Analytical Chemistry, Metabolomics, Performance, Prostate Cancer, and 15 moreMagnetic Resonance Spectroscopy, Medicine, Multivariate Analysis, Validation, Humans, Male, Prostate, Urine, Urinalysis, Analyst, Proyectos De Ingenieria, Quimica Inorganica, Tissues, Urine samples, and Prostatic neoplasms
This work exploits the possibilities offered by the recently developed multivariate method named Science-Based Calibration (SBC), for the extraction of... more
This work exploits the possibilities offered by the recently developed multivariate method named Science-Based Calibration (SBC), for the extraction of &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;analyte-specific&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; chromatograms in on-line gradient reversed phase LC-infrared spectrometry (IR) in the presence of a high spectral and chromatographic overlapping between the analyte of interest, co-eluting sample matrix constituents and the mobile phase components. The SBC method uses an experimentally measured single response spectrum of the analyte of interest and representative noise to calculate an optimum regression vector (b(opt(1))). Then, the b(opt(1)) vector is used to predict the concentration of the analyte of interest in the spectra of the LC-IR sample chromatograms. To evaluate the advantages and pitfalls of the proposed approach, two different situations were analysed on real LC-IR data sets obtained from the injection of a series of standard solutions of four nitrophenols (p-nitrophenol, 3-methyl-4-nitrophenol, 2,4-dinitrophenol and 4-nitrophenol) in a reversed phase system under gradient conditions. In the first situation, the extraction of the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;analyte-specific&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; chromatogram was carried out without previous knowledge of the spectral features of other interferents present in the sample matrix. In a second situation evaluated, data obtained from the LC injection of a sample blank is available. Results show the potential applicability of this technique in a variety of situations and evidenced that the proposed chemometric approach improves the selectivity and sensitivity of the LC-IR hyphenation.
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Extraction of meaningful biological information from the vast array of data that metabolomics analyses generate is a major challenge in the field. A variety of computational and visual tools that help to identify changes in metabolic... more
Extraction of meaningful biological information from the vast array of data that metabolomics analyses generate is a major challenge in the field. A variety of computational and visual tools that help to identify changes in metabolic pathways have been proposed including functional analysis and pathway analysis. Meta-analysis of metabolomic data has emerged as a powerful source of information. In this work, the applicability of the Mantel's test for the correlation of functional results from metabolic pathway analysis is shown using experimental and simulated data sets as evaluation examples. The statistical significance of the correlation coefficient can be assessed by permutation testing requiring practically no computation time. The use of the Mantel's test can assist the critical comparison of different phenotypes, studies, methods, platforms, or data preprocessing strategies, as well as help to identify inconsistencies between metabolomic study outcomes, making this algorithm attractive for data interpretation and meta-analysis on a routine basis.
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Inflammatory bowel disease (IBD) is a chronic, relapsing non-infectious inflammatory condition of the intestinal tract with two main phenotypes -ulcerative colitis (UC) and Crohn's disease (CD)- and a globally increasing incidence and... more
Inflammatory bowel disease (IBD) is a chronic, relapsing non-infectious inflammatory condition of the intestinal tract with two main phenotypes -ulcerative colitis (UC) and Crohn's disease (CD)- and a globally increasing incidence and prevalence. Nearly 80% of the IBD patients with active disease and 50% of those with inactive disease suffer fatigue with significant impairment of their quality of life. Fatigue has been associated with multiple factors in IBD patients but, in most cases, no direct cause can be identified and risk factors in clinically quiescent IBD are contradictory. Furthermore, as the assessment of fatigue is subjective, there is an unmet clinical need for fatigue biomarkers. In this explorative study, we analyzed the plasma lipidomic profile of 47 quiescent UC and CD patients (23 fatigued, 24 non-fatigued) by UPLC-TOFMS. Results showed changes in lipids associated with fatigue and IBD. Significantly decreased levels of phosphatidylcholines, plasmanyls, sphingomyelins, lysophosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, phosphatidylserines, and eicosanoids were observed in patients with fatigue. Network and metabolic pathway analysis indicated a dysregulation of the arachidonic acid and glycerophospholipid metabolisms, and the sphingolipid pathway. The protein-metabolite interaction network showed interactions between functionally related metabolites and proteins, displaying 40 disease-associated hidden proteins including ABDH4, GLTP, and LCAT.
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Analysis of proteins in bovine milk is usually tackled by time-consuming analytical approaches involving wet-chemical, multi-step sample clean-up procedures. The use of external cavity-quantum cascade laser (EC-QCL) based IR spectroscopy... more
Analysis of proteins in bovine milk is usually tackled by time-consuming analytical approaches involving wet-chemical, multi-step sample clean-up procedures. The use of external cavity-quantum cascade laser (EC-QCL) based IR spectroscopy was evaluated as an alternative screening tool for direct and simultaneous quantification of individual proteins (i.e. casein and β-lactoglobulin) and total protein content in commercial bovine milk samples. Mid-IR spectra of protein standard mixtures were used for building partial least squares (PLS) regression models. A sample set comprising different milk types (pasteurized; differently processed extended shelf life, ESL; ultra-high temperature, UHT) was analysed and results were compared to reference methods. Concentration values of the QCL-IR spectroscopy approach obtained within several minutes are in good agreement with reference methods involving multiple sample preparation steps. The potential application as a fast screening method for esti...
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Oxidative stress derived from perinatal asphyxia appears to be closely linked to neonatal brain damage and lipid peroxidation biomarkers have shown to provide predictive power of oxidative stress related pathologies in situations of... more
Oxidative stress derived from perinatal asphyxia appears to be closely linked to neonatal brain damage and lipid peroxidation biomarkers have shown to provide predictive power of oxidative stress related pathologies in situations of hypoxia and reoxygenation in the newborn. The objective of this work was to develop and validate of a comprehensive liquid chromatography tandem mass spectrometry approach for the quantitative profiling of 28 isoprostanoids in newborn plasma samples covering a broad range of lipid peroxidation product classes. The method was developed taking into account the specific requirements for its use in neonatology (i.e. limited sample volumes, straightforward sample processing and high analytical throughput). The method was validated following stringent FDA guidelines and was then applied to the analysis of 150 plasma samples collected from newborns. Information obtained from the quantitative analysis of isoprostanoids was critically compared to that provided by...
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Hypoxic-ischemic encephalopathy (HIE) secondary to perinatal asphyxia is a leading cause of mortality and acquired long-term neurologic co-morbidities in the neonate. The most successful intervention for the treatment of moderate to... more
Hypoxic-ischemic encephalopathy (HIE) secondary to perinatal asphyxia is a leading cause of mortality and acquired long-term neurologic co-morbidities in the neonate. The most successful intervention for the treatment of moderate to severe HIE is moderate whole body hypothermia initiated within 6h from birth. The objective and prompt identification of infants who are at risk of developing moderate to severe HIE in the critical first hours still remains a challenge. This work proposes a metabolite score calculated based on the relative intensities of three metabolites (choline, 6,8-dihydroxypurine and hypoxanthine) that showed maximum correlation with hypoxia time in a consolidated piglet model for neonatal hypoxia-ischemia. The metabolite score's performance as a biomarker for perinatal hypoxia and its usefulness for clinical grading and decision making have been assessed and compared to the performance of lactate which is currently considered the gold standard. For plasma sampl...
Research Interests: Biomarkers, Humans, Female, Animals, Male, and 4 moreSwine, Choline, Asphyxia neonatorum, and Severity of Illness Index
The analytical determination of bovine milk proteins is important in food and non-food industrial applications and yet, rather labour-intensive wet-chemical, low-throughput methods have been employed since decades. This work proposes the... more
The analytical determination of bovine milk proteins is important in food and non-food industrial applications and yet, rather labour-intensive wet-chemical, low-throughput methods have been employed since decades. This work proposes the use of external cavity-quantum cascade laser (EC-QCL) spectroscopy for the simultaneous quantification of the most abundant bovine milk proteins and the total protein content based on the chemical information contained in mid-infrared (IR) spectral features of the amide I band. Mid-IR spectra of protein standard mixtures were used for building partial least squares (PLS) regression models. Protein concentrations in commercial bovine milk samples were calculated after chemometric compensation of the matrix contribution employing science-based calibration (SBC) without sample pre-processing. The use of EC-QCL spectroscopy together with advanced multivariate data analysis allowed the determination of casein, α-lactalbumin, β-lactoglobulin and total pro...
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Using high definition (HD) and ultra-high definition (UHD) of Fourier-transform infrared (FTIR) spectroscopic imaging, we characterized spectrally pulmonary metastases in a murine model of breast cancer comparing them with... more
Using high definition (HD) and ultra-high definition (UHD) of Fourier-transform infrared (FTIR) spectroscopic imaging, we characterized spectrally pulmonary metastases in a murine model of breast cancer comparing them with histopathological results (Hematoxylin and eosin [H&E] staining). This comparison showed excellent agreement between the methods in case of localization of metastases with size below 1 mm and revealed that label-free HD and UHD IR spectral histopathology distinguish the type of neoplastic cells. We primary focused on differentiation between metastatic foci in the pleural cavity from cancer cells present in lung parenchyma and inflamed cells present in extracellular matrix of lungs due to growing of advanced metastases. In addition, a combination of unsupervised clustering and IR imaging indicated the high sensitivity of FTIR spectroscopy to identify chemical features of small macrometastases located under the pleural cavity and during epithelial-mesenchymal transition. FTIR-based spectral histopathology was proved to detect not only phases of breast cancer metastasis to lungs but also to differentiate various origins of metastases seeded from breast cancer.
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Metabolomics based on liquid chromatography-mass spectrometry (LC-MS) is a powerful tool for studying dynamic responses of biological systems to different physiological or pathological conditions. Differences in the instrumental response... more
Metabolomics based on liquid chromatography-mass spectrometry (LC-MS) is a powerful tool for studying dynamic responses of biological systems to different physiological or pathological conditions. Differences in the instrumental response within and between batches introduce unwanted and uncontrolled data variation that should be removed to extract useful information. This work exploits a recently developed method for the identification of batch effects in high throughput genomic data based on the calculation of a δ statistic through principal component analysis (PCA) and guided PCA. Its applicability to LC-MS metabolomic data was tested on two real examples. The first example involved the repeated analysis of 42 plasma samples and 6 blanks in three independent batches, and the second data set involved the analysis of 101 plasma and 18 blank samples in a single batch with a total runtime of 50 h. The first and second data set were used to evaluate between and within-batch effects using the δ statistic, respectively. Results obtained showed the usefulness of using the δ statistic together with other approaches such as summary statistics of peak intensity distributions, PCA scores plots or the monitoring of IS peak intensities, to detect and identify instrumental instabilities in LC-MS.
A simple method based on the multivariate analysis of data from urine using an electronic voltammetric tongue is used to detect patients with prostate cancer. A sensitivity of 91% and a specificity of 73% were obtained to distinguish the... more
A simple method based on the multivariate analysis of data from urine using an electronic voltammetric tongue is used to detect patients with prostate cancer. A sensitivity of 91% and a specificity of 73% were obtained to distinguish the urine from cancer patients and the urine from non-cancer patients.
Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint... more
Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint analysis of data from multiple sources) has the potential to circumvent this issue facilitating knowledge discovery and reliable biomarker identification. Another field of application of data fusion is the simultaneous analysis of metabolomic changes through several biofluids or tissues. However, meta-bolomics typically deals with large datasets, with hundreds to thousands of variables and the identification of shared and individual factors or structures across multiple sources is challenging due to the high variable to sample ratios and differences in intensity and noise range. In this work we apply a recent method, Joint and Individual Variation Explained (JIVE), for the integrated unsupervised analysis of metabolomic profiles from multiple data sources. This method separates the shared patterns among data sources (i.e. the joint structure) from the individual structure of each data source that is unrelated to the joint structure. Two examples are described to show the applicability of JIVE for the simultaneous analysis of multi-source data using: (i) plasma samples subjected to different analytical techniques, sample treatment and measurement conditions; and (ii) plasma and urine samples subjected to liquid chromatography-mass spectrometry measured using two ionization conditions.
Gastric cancer (GC) is among the most common cancers worldwide. Gastric carcinogenesis is a multistep and multifactorial process beginning with chronic gastritis induced by Helicobacter pylori (H. pylori) infection. This process is often... more
Gastric cancer (GC) is among the most common cancers worldwide. Gastric carcinogenesis is a multistep and multifactorial process beginning with chronic gastritis induced by Helicobacter pylori (H. pylori) infection. This process is often described via a sequence of events known as Correas&#39;s cascade, a stepwise progression from nonactive gastritis, chronic active gastritis, precursor lesions of gastric cancer (atrophy, intestinal metaplasia, and dysplasia), and finally adenocarcinoma. Our aim was to identify a plasma metabolic pattern characteristic of GC through disease progression within the Correa&#39;s cascade. This study involved the analysis of plasma samples collected from 143 patients classified in four groups: patients with nonactive gastritis and no H. pylori infection, H. pylori infected patients with chronic active gastritis, infected or noninfected patients with precursor lesions of gastric cancer, and GC. Independent partial least-squares-discriminant binary models of UPLC-ESI(+)-TOFMS metabolic profiles, implemented in a decision-directed acyclic graph, allowed the identification of tryptophan and kynurenine as discriminant metabolites that could be attributed to indoleamine-2,3-dioxygenase upregulation in cancer patients leading to tryptophan depletion and kynurenine metabolites generation. Furthermore, phenylacetylglutamine was also classified as a discriminant metabolite. Our data suggest the use of tryptophan, kynurenine, and phenylacetylglutamine as potential GC biomarkers.
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Research Interests: Analytical Chemistry, FTIR spectroscopy, Sampling, Pesticide, Standard Deviation, and 11 moreFlow Injection Analysis, Pesticides, Standard, Spectrum, Fourier Transform spectroscopy, Fourier transform infrared spectroscopy, Sensitivity, Infrared Spectrometry, Etalon, Standard Curve, and Sampling Frequency
A new method is proposed for the elimination of the spectral contribution of two atmospheric gases (CO2 and H2O) in Fourier transform infrared (FT-IR) spectra of clinical samples. The algorithm is based on the measurement of reference... more
A new method is proposed for the elimination of the spectral contribution of two atmospheric gases (CO2 and H2O) in Fourier transform infrared (FT-IR) spectra of clinical samples. The algorithm is based on the measurement of reference spectra of H2O followed by an automatic calculation of the spectral contribution of the above-mentioned gases to the sample spectra. Then this contribution is compensated by spectral subtraction. Attenuated total reflectance FT-IR spectra of serum and urine samples in the presence of atmospheric gases were corrected and compared with spectra obtained with an N2 purge. Visual inspection of the spectra as well as calculated noise levels confirmed that the method compensated for the contribution of CO2 and H2O to serum and urine spectra to a great extent. As compared with the correction performed by a commercial software package, the proposed method clearly improved the correction of CO2 and provided similar results for H2O compensation. Correlation values between corrected spectra and those obtained under N2-purged conditions in the fingerprint region were higher than 0.995, and noise values in regions where samples did not absorb confirmed the suitability of the correction. The proposed method is fast, easy, and extensible to other gaseous interferences, devices, and acquisition conditions.
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BackgroundPerinatal hypoxic-ischemic brain damage is a major cause of mortality and morbidity in the neonatal period. Currently, limited ranges of biochemical tests assessing the intensity and duration of hypoxia are ready for clinical... more
BackgroundPerinatal hypoxic-ischemic brain damage is a major cause of mortality and morbidity in the neonatal period. Currently, limited ranges of biochemical tests assessing the intensity and duration of hypoxia are ready for clinical use. However, the need to initiate hypothermia therapy early after the clinical suspicion of hypoxic-ischemic encephalopathy requires the availability of early and reliable hypoxia markers. We have sought these biomarkers in an experimental model of hypoxia reoxygenation. Hypoxia and hypotension were induced in newborn piglets following a standardized model and reoxygenation was carried out using room air (RA). An untargeted Liquid Chromatography - Time of Flight Mass Spectrometry (LC-TOFMS) approach was used to assess changes in the metabolomic profile of plasma samples after intense hypoxia and upon reoxygenation. At the end of hypoxia, the plasma metabolome showed an increased plasma concentration of analytes reflecting a metabolic adaptation to pr...
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Biothiols play an essential role in a number of biological processes in living organisms including detoxification and metabolism. Fetal to neonatal transition poses a pro-oxidant threat for newborn infants, especially those born... more
Biothiols play an essential role in a number of biological processes in living organisms including detoxification and metabolism. Fetal to neonatal transition poses a pro-oxidant threat for newborn infants, especially those born prematurely. A reliable and rapid tool for the direct determination of thiols in small volume whole blood (WB) samples would be desirable for its application in clinical practice. This study shows the feasibility of Surface Enhanced Raman Spectroscopy (SERS) using a silver colloid prepared by reduction of silver nitrate using hydroxylamine, as the SERS substrate for the quantification of thiols in WB samples after a simple precipitation step for protein removal. Bands originating from biothiols (790, 714 and 642 cm(-1)) were enhanced by the employed SERS substrate and the specificity of the detected SERS signal was tested for molecules presenting -SH functional groups. A statistically significant correlation between the obtained SERS signals and the thiol concentration measured using a chromatographic reference method in umbilical cord WB samples could be demonstrated. Using WB GSH concentrations obtained from the chromatographic reference procedure, a Partial Least Squares (PLS) regression model covering GSH concentrations from 13 to 2200 μM was calculated obtaining a root mean square error of prediction (RMSEP) of 381 μM when applied to an external test set. The developed approach uses small blood sample volumes (50 μL), which is important for clinical applications, especially in the field of neonatology. This feasibility study shows that the present approach combines all the necessary characteristics for its potential application in clinical practice.
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A routine method based on Fourier transform infrared spectrometry was developed for the simultaneous determination of pirimicarb and endosulfan in commercially available pesticide formulations. The method is based on peak area absorbance... more
A routine method based on Fourier transform infrared spectrometry was developed for the simultaneous determination of pirimicarb and endosulfan in commercially available pesticide formulations. The method is based on peak area absorbance measurements between 1362 and 1352 cm(-1), corrected with a baseline fixed at 1338 cm(-1), for pirimicarb and peak area absorbance measurements between 919 and 909 cm(-1) with a baseline fixed at 931 cm(-1) for endosulfan; chloroform solutions for analysis were obtained by direct dilution of emulsifiable concentrates or by solvent extraction from solid samples. Various extraction conditions and appropriate band selection were investigated, and interference studies were performed. Under the experimental conditions selected, limits of detection of 13 microg/g for pirimicarb and 150 microg/g for endosulfan were obtained that correspond to 0.13 and 1.6% (w/w), respectively, in commercial samples. Results from analyses of commercial samples by the developed method compared well with those obtained by a liquid chromatography reference method.
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High-throughput proteomic experiments have raised the importance and complexity of bioinformatic analysis to extract useful information from raw data. Discriminant analysis is frequently used to identify differences among test groups of... more
High-throughput proteomic experiments have raised the importance and complexity of bioinformatic analysis to extract useful information from raw data. Discriminant analysis is frequently used to identify differences among test groups of individuals or to describe combinations of discriminant variables. However, even in relatively large studies, the number of detected variables typically largely exceeds the number of samples and the classifiers should be thoroughly validated to assess their performance for new samples. Cross-validation is a widely approach when an external validation set is not available. In this chapter, different approaches for cross-validation are presented including relevant aspects that should be taken into account to avoid overly optimistic results and the assessment of the statistical significance of cross-validated figures of merit.
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Instrumental developments in sensitivity and selectivity boost the application of liquid chromatography-mass spectrometry (LC-MS) in metabolomics. Gradual changes in the LC-MS instrumental response (i.e. intra-batch effect) are often... more
Instrumental developments in sensitivity and selectivity boost the application of liquid chromatography-mass spectrometry (LC-MS) in metabolomics. Gradual changes in the LC-MS instrumental response (i.e. intra-batch effect) are often unavoidable and they reduce the repeatability and reproducibility of the analysis, decrease the power to detect biological responses and hinder the interpretation of the information provided. Because of that, there is interest in the development of chemometric techniques for the post-acquisition correction of batch effects. In this work, the use of quality control (QC) samples and support vector regression (QC-SVRC) and a radial basis function kernel is proposed to correct intra-batch effects. The repeated analysis of a single sample is used for the assessment of both the correction accuracy and the effect of the distribution of QC samples throughout the batch. The QC-SVRC method is evaluated and compared with a recently developed method based on QC samples and robust cubic smoothing splines (QC-RSC). The results show that QC-SVRC slightly outperformed QC-RSC and allows a straightforward fitting of the SVRC parameters to the instrument performance by using the ε-insensitive loss parameter.
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RESUMEN "Se ha desarrollado un método rápido y medioambientalmente sostenible para la determinación de Fenoxicarb mediante espectrometría FTIR. El procedimiento general está basado en la extracción off-line del pesticida con... more
RESUMEN "Se ha desarrollado un método rápido y medioambientalmente sostenible para la determinación de Fenoxicarb mediante espectrometría FTIR. El procedimiento general está basado en la extracción off-line del pesticida con cloroformo y obtención del espectro infrarrojo de transmisión entre 4000 y 850 cm -1. en modo stopped - flow con una resolución nominal de 4 cm -1 y acumulando 25 barridos por espectro. El Fenoxicarb se determina a partir de la medida del área de la banda de absorción entre 1509 y 1499 cm -1 con una corrección de línea base entre 1570 y 1403 cm -1. Los resultados obtenidos por el procedimiento propuesto se han comparado con el método de referencia HPLC, resultando ser estadísticamente equivalentes. El procedimiento FTIR proporciona un límite de detección de 14 pg gl , que equivale a un 0.2 % (p/p) de Fenoxicarb en la muestra original y con una frecuencia de medida de 60 h-1 y generando únicamente 3mL de residuos de cloroformo por muestra. Esto supone una im...
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Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint... more
Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint analysis of data from multiple sources) has the potential to circumvent this issue facilitating knowledge discovery and reliable biomarker identification. Another field of application of data fusion is the simultaneous analysis of metabolomic changes through several biofluids or tissues. However, metabolomics typically deals with large datasets, with hundreds to thousands of variables and the identification of shared and individual factors or structures across multiple sources is challenging due to the high variable to sample ratios and differences in intensity and noise range. In this work we apply a recent method, Joint and Individual Variation Explained (JIVE), for the integrated unsupervised analysis of metabolomic profiles from multiple data sources. This method separates the shared patterns among data sources (i.e. the joint structure) from the individual structure of each data source that is unrelated to the joint structure. Two examples are described to show the applicability of JIVE for the simultaneous analysis of multi-source data using: (i) plasma samples subjected to different analytical techniques, sample treatment and measurement conditions; and (ii) plasma and urine samples subjected to liquid chromatography-mass spectrometry measured using two ionization conditions.
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A routine method based on Fourier transform infrared spectrometry was developed for the simultaneous determination of pirimicarb and endosulfan in commercially available pesticide formulations. The method is based on peak area absorbance... more
A routine method based on Fourier transform infrared spectrometry was developed for the simultaneous determination of pirimicarb and endosulfan in commercially available pesticide formulations. The method is based on peak area absorbance measurements between 1362 and 1352 cm(-1), corrected with a baseline fixed at 1338 cm(-1), for pirimicarb and peak area absorbance measurements between 919 and 909 cm(-1) with a baseline fixed at 931 cm(-1) for endosulfan; chloroform solutions for analysis were obtained by direct dilution of emulsifiable concentrates or by solvent extraction from solid samples. Various extraction conditions and appropriate band selection were investigated, and interference studies were performed. Under the experimental conditions selected, limits of detection of 13 microg/g for pirimicarb and 150 microg/g for endosulfan were obtained that correspond to 0.13 and 1.6% (w/w), respectively, in commercial samples. Results from analyses of commercial samples by the develo...
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A new method is proposed for the elimination of the spectral contribution of two atmospheric gases (CO2 and H2O) in Fourier transform infrared (FT-IR) spectra of clinical samples. The algorithm is based on the measurement of reference... more
A new method is proposed for the elimination of the spectral contribution of two atmospheric gases (CO2 and H2O) in Fourier transform infrared (FT-IR) spectra of clinical samples. The algorithm is based on the measurement of reference spectra of H2O followed by an automatic calculation of the spectral contribution of the above-mentioned gases to the sample spectra. Then this contribution is compensated by spectral subtraction. Attenuated total reflectance FT-IR spectra of serum and urine samples in the presence of atmospheric gases were corrected and compared with spectra obtained with an N2 purge. Visual inspection of the spectra as well as calculated noise levels confirmed that the method compensated for the contribution of CO2 and H2O to serum and urine spectra to a great extent. As compared with the correction performed by a commercial software package, the proposed method clearly improved the correction of CO2 and provided similar results for H2O compensation. Correlation values between corrected spectra and those obtained under N2-purged conditions in the fingerprint region were higher than 0.995, and noise values in regions where samples did not absorb confirmed the suitability of the correction. The proposed method is fast, easy, and extensible to other gaseous interferences, devices, and acquisition conditions.
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Research Interests: Engineering, Biological Sciences, Humans, Female, Male, and 11 moreTandem Mass Spectrometry, Lipid peroxidation, High Pressure Liquid Chromatography, Newborn Infant, CHEMICAL SCIENCES, Reproducibility of Results, Biological markers, Analytical and Bioanalytical Chemistry, Prostaglandins, Reference Values, and Randomized Controlled Trials as Topic
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Nuclear magnetic resonance spectroscopy (NMR) provides a rich source of structural information which when combined with other spectroscopic data allows structural elucidation of complex compounds as well as a universal detection method... more
Nuclear magnetic resonance spectroscopy (NMR) provides a rich source of structural information which when combined with other spectroscopic data allows structural elucidation of complex compounds as well as a universal detection method for compounds of interest in complex mixtures. NMR is a nondestructive technique that facilitates its coupling with other spectroscopic methods such as mass spectrometry. The key to on-line NMR detection is the design of the flow probe. Suitable probes for continuous flow, stop flow, loop collection, solid-phase extraction, and microflow probes are described emphasizing their general applications and limitations. Sensitivity and probe volume are major limitations of NMR coupling to liquid chromatography. Solvent selection for separations needs to consider the unique characteristics of NMR, for example the use of deuterated solvents for proton detection, and methods available for solvent suppression. Practical applications of LC-NMR are presented to illustrate the use of this technique in different areas of analytical chemistry.