Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.     

Definition and detection of data-based uniqueness in evaluating bilinear (two-way) chemical measurements

Multivariate curve resolution methods, frequently used in analyzing bilinear data sets, result in ambiguous decomposition in general. Implementing the adequate constraints may lead to reduce the so-called rotational ambiguity drastically, and in the most favorable cases to the unique solution. However, in some special cases, non-negativity constraint as minimal information of the system is a sufficient condition to resolve profiles uniquely. Although, several studies on exploring the uniqueness of the bilinear non-negatively constrained multivariate curve resolution methods have been made in the literature, it has still remained a mysterious question. In 1995, Manne published his profile-based theorems giving the necessary and sufficient conditions of the unique resolution. In this study, a new term, i.e., data-based uniqueness is defined and investigated in details, and a general procedure is suggested for detection of uniquely recovered profile(s) on the basis of data set structure in the abstract space. Close inspection of Borgen plots of these data sets leads to realize the comprehensive information of local rank, and these argumentations furnish a basis for data-based uniqueness theorem. The reported phenomenon and its exploration is a new stage (it can be said fundament) in understanding and describing the bilinear (matrix-type) chemical data in general.     

Fundamental solution of the time‐fractional telegraph Dirac operator

In this work, we obtain the fundamental solution (FS) of the multidimensional time‐fractional telegraph Dirac operator where the 2 time‐fractional derivatives of orders α∈]0,1] and β∈]1,2] are in the Caputo sense. Explicit integral and series representation of the FS are obtained for any dimension. We present and discuss some plots of the FS for some particular values of the dimension and of the fractional parameters α and β. Finally, using the FS, we study some Poisson and Cauchy problems.     

Evaluation of the quality consistency of powdered poppy capsule extractive by an averagely linear‐quantified fingerprint method in combination with antioxidant activities and two compounds analyses

A novel averagely linear‐quantified fingerprint method was proposed and successfully applied to monitor the quality consistency of alkaloids in powdered poppy capsule extractive. Averagely linear‐quantified fingerprint method provided accurate qualitative and quantitative similarities for chromatographic fingerprints of Chinese herbal medicines. The stability and operability of the averagely linear‐quantified fingerprint method were verified by the parameter r . The average linear qualitative similarity (improved based on conventional qualitative “Similarity”) was used as a qualitative criterion in the averagely linear‐quantified fingerprint method, and the average linear quantitative similarity was introduced as a quantitative one. was able to identify the difference in the content of all the chemical components. In addition, was found to be highly correlated to the contents of two alkaloid compounds (morphine and codeine). A simple flow injection analysis was developed for the determination of antioxidant capacity in Chinese Herbal Medicines, which was based on the scavenging of 2,2‐diphenyl‐1‐picrylhydrazyl radical by antioxidants. The fingerprint–efficacy relationship linking chromatographic fingerprints and antioxidant activities was investigated utilizing orthogonal projection to latent structures method, which provided important pharmacodynamic information for Chinese herbal medicines quality control. In summary, quantitative fingerprinting based on averagely linear‐quantified fingerprint method can be applied for monitoring the quality consistency of Chinese herbal medicines, and the constructed orthogonal projection to latent structures model is particularly suitable for investigating the fingerprint–efficacy relationship.     

Phase II monitoring of changes in mean from high‐dimensional data

The generalized T² chart (GT‐chart), which is composed of the T² statistic based on a small number of principal components and the remaining components, is a popular alternative to the traditional Hotelling's T² control chart. However, the application of the GT‐chart to high‐dimensional data, which are now ubiquitous, encounters difficulties from high dimensionality similar to other multivariate procedures. The sample principal components and their eigenvalues do not consistently estimate the population values, and the GT‐chart relying on them is also inconsistent in estimating the control limits. In this paper, we investigate the effects of high dimensionality on the GT‐chart and then propose a corrected GT‐chart using the recent results of random matrix theory for the spiked covariance model. We numerically show that the corrected GT‐chart exhibits superior performance compared to the existing methods, including the GT‐chart and Hotelling's T² control chart, under various high‐dimensional cases. Finally, we apply the proposed corrected GT‐chart to monitor chemical processes introduced in the literature.     

An integrated strategy for the geographical origin traceability of Goji berries by antioxidants characteristic fingerprint based online ultra-performance liquid chromatography-2,2-diphenyl-1-picrylhydrazyl- photodiode array detector-mass spectrometry combined with multivariate statistics analysis

Goji berries are now becoming increasingly popular in the human diet due to their potential health benefits. Unscrupulous traders deliberately mislabel with certain origins to gain illegal profits, which seriously affected the consumers’ benefits. In this study, an online ultra-performance liquid chromatography-2,2-diphenyl-1 -picrylhydrazyl-photodiode array detector-electrospray ionization-quadrupole time of flight mass was developed for rapid screening and identification of the antioxidants from Goji berry; then, the antioxidants characteristic fingerprint was established and explored in the origins discrimination of Goji berries from China combined with multivariate statistics analysis. As a result, twenty-eight compounds were screened from Goji berry extract, 19 of which were identified by accurate molecular and ultraviolet information according to references. Principal components analysis and partial least squares discrimination analysis achieved the accurate classification from the four regions, eight compounds were selected as origin-related antioxidant markers with variable importance in projection >1 and one-way analysis of variance (P<0.05), including rutin, rutin di-hexose, P-coumaric acid tri-hexose, dicaffeoylquinic acid isomer, Quercetin-rhamno-di-hexoside, peak14, peak16, and peak27. This study provides a feasible strategy for the geographical origins discrimination of Goji berries based on antioxidant ingredients difference and will be helpful for improving the quality control level of Goji berries.     

1H-NMR Profiling Shows as Specific Constituents Strongly Affect the International EVOO Blends Characteristics: The Case of the Italian Oil

Considering the growing number of extra virgin olive oil (EVOO) producers in the world, knowing the influence of olive oils with different geographical origins on the characteristics of the final blend becomes an interesting goal. The present work is focused on commercial organic EVOO blends obtained by mixing multiple oils from different geographical origins. These blends have been studied by ¹H-NMR spectroscopy supported by multivariate statistical analysis. Specific characteristics of commercial organic EVOO blends originated by mixing oils from Italy, Tunisia, Portugal, Spain, and Greece were found to be associated with the increasing content of the Italian component. A linear progression of the metabolic profile defined characteristics for the analysed samples—up to a plateau level—was found in relation to the content of the main constituent of the Italian oil, the monocultivar Coratina. The Italian constituent percentage appears to be correlated with the fatty acids (oleic) and the polyphenols (tyrosol, hydroxytyrosol, and derivatives) content as major and minor components respectively. These results, which highlight important economic aspects, also show the utility of ¹H-NMR associated with chemometric analysis as a powerful tool in this field. Mixing oils of different national origins, to obtain blends with specific characteristics, could be profitably controlled by this methodology.