MicroNIR/chemometrics assessement of occupational exposure to hydroxyurea

Portable Near Infrared spectroscopy (NIRs) coupled to chemometrics was investigated for the first time as a novel entirely on-site approach for occupational exposure monitoring in pharmaceutical field. Due to a significant increase in the number of patients receiving chemotherapy, the development of reliable, fast, and on-site analytical methods to assess the occupational exposure of workers in the manufacture of pharmaceutical products, has become more and more required. In this work, a fast, accurate, and sensitive detection of hydroxyurea, a cytotoxic antineoplastic agent commonly used in chemotherapy, was developed. Occupational exposure to antineoplastic agents was evaluated by collecting hydroxyurea on a membrane filter during routine drug manufacturing process. Spectra were acquired in the NIR region in reflectance mode by the means of a miniaturized NIR spectrometer coupled with chemometrics. This MicroNIR instrument is a very ultra-compact portable device with a particular geometry and optical resolution designed in such a manner that the reduction in size does not compromise the performances of the spectrometer. The developed method could detect up to 50 ng of hydroxyurea directly measured on the sampling filter membrane, irrespective of complexity and variability of the matrix; thus extending the applicability of miniaturized NIR instruments in pharmaceutical and biomedical analysis

Assessment of Virgin Olive Oil Adulteration by a Rapid Luminescent Method

The adulteration of virgin olive oil with hazelnut oil is a common fraud in the food industry, which makes mandatory the development of accurate methods to guarantee the authenticity and traceability of virgin olive oil. In this work, we demonstrate the potential of a rapid luminescent method to characterize edible oils and to detect adulterations among them. A regression model based on five luminescent frequencies related to minor oil components was designed and validated, providing excellent performance for the detection of virgin olive oil adulteration

Evaluation of quality parameters of apple juices using near-infrared spectroscopy and chemometrics

Near-infrared (NIR) spectra were recorded for commercial apple juices. Analysis of these spectra using partial least squares (PLS) regression revealed quantitative relations between the spectra and quality- and taste-related properties of juices: soluble solids content (SSC), titratable acidity (TA), and the ratio of soluble solids content to titratable acidity (SSC/TA). Various spectral preprocessing methods were used for model optimization. The optimal spectral variables were chosen using the jack-knife-based method and different variants of the interval PLS (iPLS) method. The models were cross-validated and evaluated based on the determination coefficients (R-2), root-mean-square error of cross-validation (RMSECV), and relative error (RE). The best model for the prediction of SSC (R-2 = 0.881, RMSECV = 0.277 degrees Brix, and RE = 2.37%) was obtained for the first-derivative preprocessed spectra and jack-knife variable selection. The optimal model for TA (R-2 = 0.761, RMSECV = 0.239 g/L, and RE = 4.55%) was obtained for smoothed spectra in the range of 6224-5350 cm(-1). The best model for the SSC/TA (R-2 = 0.843, RMSECV = 0.113, and RE = 5.04%) was obtained for the spectra without preprocessing in the range of 6224-5350 cm(-1). The present results show the potential of the NIR spectroscopy for screening the important quality parameters of apple juices.National Science Centre, Poland [2016/23/B/NZ9/03591

Standardized maximim D-optimal designs for enzyme kineticinhibition models

Locally optimal designs for nonlinear models require a single set of nominal values for the unknown parameters.An alternative is the maximin approach that allows the user to specify a range of values for each parameter ofinterest. However, the maximin approach is difficult because we first have to determine the locally optimal designfor each set of nominal values before maximin types of optimal designs can be found via a nested optimizationprocess. We show that particle swarm optimization (PSO) techniques can solve such complex optimizationproblems effectively. We demonstrate numerical results from PSO can help find, for the first time, formulae forstandardized maximin D-optimal designs for nonlinear model with 3 or 4 parameters on the compact andnonnegative design space. Additionally, we show locally and standardized maximin D-optimal designs for inhibitionmodels are not necessarily supported at a minimum number of points. To facilitate use of such designs, wecreate a web-based tool for practitioners to find tailor-made locally and standardized maximin optimal designs

Modeling solid state stability for speciation: a ten-year long study

Speciation studies are based on fundamental models that relate the properties of biomimetic coordination compounds to the stability of the complexes. In addition to the classic approach based on solution studies, solid state properties have been recently proposed as supporting tools to understand the bioavailability of the involved metal. A ten-year long systematic study of several different complexes of imidazole substituted ligands with transition metal ions led our group to the definition of a model based on experimental evidences. This model revealed to be a useful tool to predict the stability of such coordination complexes and is based on the induced behavior under thermal stress. Several different solid state complexes were characterized by Thermally Induced Evolved Gas Analysis by Mass Spectrometry (TI-EGA-MS). This hyphenated technique provides fundamental information to determine the solid state properties and to create a model that relates stability to coordination. In this research, the model resulting from our ten-year long systematic study of complexes of transition metal ions with imidazole substituted ligands is described. In view of a systematic addition of information, new complexes of Cu(II), Zn(II), or Cd(II) with 2-propyl-4,5-imidazoledicarboxylic acid were precipitated, characterized, and studied by means of Thermally Induced Evolved Gas Analysis performed by mass spectrometry (TI-EGA-MS). The hyphenated approach was applied to enrich the information related to thermally induced steps, to confirm the supposed decomposition mechanism, and to determine the thermal stability of the studied complexes. Results, again, allowed supporting the theory that only two main characteristic and common thermally induced decomposition behaviors join the imidazole substituted complexes studied by our group. These two behaviors could be considered as typical trends and the model allowed to predict coordination behavior and to provide speciation information

Effect of agro-climatic conditions on near infrared spectra of extra virgin olive oils

Authentication of extra virgin olive oil requires fast and cost-effective analytical procedures, such as near infrared spectroscopy. Multivariate analysis and chemometrics have been successfully applied in several papers to gather qualitative and quantitative information of extra virgin olive oils from near infrared spectra. Moreover, there are many examples in the literature analysing the effect of agro-climatic conditions on food content, in general, and in olive oil components, in particular. But the majority of these studies considered a factor, a non-numerical variable, containing this meteorological information. The present work uses all the agro-climatic data with the aim of highlighting the linear relationships between them and the near infrared spectra. The study begins with a graphical motivation, continues with a bivariate analysis and, finally, applies redundancy analysis to extend and confirm the previous conclusions.Peer Reviewe

A novel R-package graphic user interface for the analysis of metabonomic profiles

Background Analysis of the plethora of metabolites found in the NMR spectra of biological fluids or tissues requires data complexity to be simplified. We present a graphical user interface (GUI) for NMR-based metabonomic analysis. The "Metabonomic Package" has been developed for metabonomics research as open-source software and uses the R statistical libraries. /Results The package offers the following options: Raw 1-dimensional spectra processing: phase, baseline correction and normalization. Importing processed spectra. Including/excluding spectral ranges, optional binning and bucketing, detection and alignment of peaks. Sorting of metabolites based on their ability to discriminate, metabolite selection, and outlier identification. Multivariate unsupervised analysis: principal components analysis (PCA). Multivariate supervised analysis: partial least squares (PLS), linear discriminant analysis (LDA), k-nearest neighbor classification. Neural networks. Visualization and overlapping of spectra. Plot values of the chemical shift position for different samples. Furthermore, the "Metabonomic" GUI includes a console to enable other kinds of analyses and to take advantage of all R statistical tools. /Conclusion We made complex multivariate analysis user-friendly for both experienced and novice users, which could help to expand the use of NMR-based metabonomics