Qualitative and quantitative control of pediatric syrups using Nuclear Magnetic Resonance and chemometrics

NMR and multivariate methods: Identification of chemical markers in extracts of pedra-ume-caá and their antiglycation, antioxidant, and enzymatic inhibition activities

INTRODUCTION

In Brazil, the plant group popularly known as "pedra-ume-caá" is used in folk medicine for the treatment of diabetes, and its raw material is commonly sold.

OBJECTIVE

The aim of the study was to apply a method for chemical identification of extracts of dry pedra-ume-caá leaves using HPLC-high-resolution mass spectrometry (HRMS) and NMR and develop a multivariate model with NMR data to authenticate commercial samples. In addition, to evaluate the biological activities of the extracts.

MATERIALS AND METHODS

Dry extracts of Myrcia multiflora, Myrcia amazonica, Myrcia guianensis, Myrcia sylvatica, Eugenia punicifolia leaves, and 15 commercial samples (sold in Manaus and Belém, Brazil) were prepared by infusion. All the extracts were analysed using HPLC-high-resolution mass spectrometry (HRMS), NMR, principal component analysis (PCA), and hierarchical cluster analysis (HCA). The antidiabetic effect of extracts was evaluated according to enzymatic inhibition. Their content of total phenols, cell viability, and antioxidant and antiglycation activities were also determined.

RESULTS

HPLC-HRMS and NMR analysis of these extracts permitted the identification of 17 compounds. 1H NMR data combined with multivariate analyses allowed us to conclude that catechin, myricitrin, quercitrin, and gallic and quinic acids are the main chemical markers of pedra-ume-caá species. These markers were identified in 15 commercial samples of pedra-ume-caá. Additionally, only the extracts of M. multiflora and E. punicifolia inhibited α-glucosidase. All the extracts inhibited the formation of advanced glycation end products (AGEs) and showed free-radical-scavenging activity. These extracts did not present cytotoxicity.

CONCLUSION

This study revealed the chemical markers of matrices, and it was possible to differentiate the materials marketed as pedra-ume-caá. Moreover, this study corroborates the potential of these species for treating diabetes.

High-performance liquid chromatography-based fingerprint analysis with chemical pattern recognition for evaluation of Mahonia bealei (Fort.) Carr

A simple and efficient high-performance liquid chromatography method combined with chemical pattern recognition was established for quality evaluation of Mahonia bealei (Fort.) Carr. A common pattern of 30 characteristic peaks was applied for similarity analysis, hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis in the 37 batches of M. bealei (Fort.) Carr. to discriminate wild M. bealei (Fort.) Carr., cultivated M. bealei (Fort.) Carr., and its substitutes. The results showed that partial least squares discriminant analysis was the most effective method for discrimination. Eight characteristics peaks with higher variable importance in projection values were selected for pattern recognition model. A permutation test and 26 batches of testing set samples were performed to validate the model that was successfully established. All of the training and testing set samples were correctly classified into three clusters (wild M. bealei (Fort.) Carr., cultivated M. bealei (Fort.) Carr., and its substitutes) based on the selected chemical markers. Moreover, 26 batches of unknown samples were used to predict the accuracy of the established model with a discrimination accuracy of 100%. The obtained results indicated that the method showed great potential application for accurate evaluation and prediction of the quality of M. bealei (Fort.) Carr.

High-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) as a tool in the determination of biomarkers of Passiflora-based herbal medicines

High-resolution magic-angle spinning nuclear magnetic resonance spectroscopy (HR-MAS NMR) for the identification of the metabolic profile of plants under conditions very close to that in which the compounds are present in the matrix, the herbal medicines in this case. This enables selectivity in the determination of the active principle and other biomarkers present in the complex matrix, avoiding degradation products, which may occur in the extractive processes required in several analytical methods. In this study, HR-MAS analysis was applied in the quality control of seven Passiflora-based herbal medicines, using metabolic fingerprinting to confirm plant species and identify biomarkers. Vitexin and isovitexin were identified as major compounds in three of these herbal medicines (0.17 to 0.55%), while salicin was the majority in two others. On the other hand, no significant flavonoid contents were observed in the remaining two. In addition, it was possible to detect ethanol, a non-target compound, in all herbal medicines in concentrations varying between 0.009 and 0.342%. In this way, combined with chemometrics ¹H HR-MAS NMR proved to be suitable for the qualitative and quantitative study of Passiflora biomarkers, using a minimal pre-treatment of the sample.

1 H-NMR and GC for detection of adulteration in commercial essential oils of Cymbopogon ssp

INTRODUCTION

Essential oils of Cymbopogon nardus and C. winterianus have fungicidal, bactericidal, and insect repellent activities. In addition, they are components of fragrances, cosmetics, and household products. The growing demand for essential oils has intensified adulteration practices of such products.

OBJECTIVES

To evaluate the authenticity and quality of citronella commercial essential oils based on chemical composition [by gas chromatography mass spectrometry (GC-MS)] and the contents of its major constituents [by ¹ H-NMR, and gas chromatography with a flame ionisation detector using internal standardisation (GC-IS)].

MATERIALS AND METHODS

The chemical composition of essential oil was determined by GC-MS. Major components were quantified by ¹ H-NMR and the results compared to those obtained by GC-IS.

RESULTS

The adulteration of oils was verified by GC and ¹ H-NMR. In the pure oils, the results obtained by ¹ H-NMR were similar to those obtained by GC-IS for most of the oils. However, in adulterated oils, signal overlap prevented the quantification of citronellol and geraniol by NMR. Importantly, due to dilution with dipropylene glycol it was not possible to quantify citronellal using ¹ H-NMR. However, for both pure and adulterated oils, GC-IS method proved successful in quantifying notable constituents.

CONCLUSION

All the methods used proved efficient in detecting adulteration. However, whilst GC-IS provided quantification of constituents of interest, both in pure and adulterated oils, their quantification by NMR was only possible in non-adulterated samples. None of the oils evaluated presented a composition within the threshold established by British Pharmacopoeia quality standards.

Quantitative analysis of PET microplastics in environmental model samples using quantitative 1H-NMR spectroscopy: validation of an optimized and consistent sample clean-up method

Identification and quantification of microplastics (MP) in environmental samples is crucial for understanding the risk and distribution of MP in the environment. Currently, quantification of MP particles in environmental samples and the comparability of different matrices is a major research topic. Research also focusses on sample preparation, since environmental samples must be free of inorganic and organic matrix components for the MP analysis. Therefore, we would like to propose a new method that allows the comparison of the results of MP analysis from different environmental matrices and gives a MP concentration in mass of MP particles per gram of environmental sample. This is possible by developing and validating an optimized and consistent sample preparation scheme for quantitative analysis of MP particles in environmental model samples in conjunction with quantitative ¹H-NMR spectroscopy (qNMR). We evaluated for the first time the effects of different environmental matrices on identification and quantification of polyethylene terephthalate (PET) fibers using the qNMR method. Furthermore, high recovery rates were obtained from spiked environmental model samples (without matrix ~ 90%, sediment ~ 97%, freshwater ~ 94%, aquatic biofilm ~ 95%, and invertebrate matrix ~ 72%), demonstrating the high analytical potential of the method. Graphical abstract.

Quo Vadis qNMR?

The quantification of a drug, its impurities, and e.g. components of a mixture has become routine in NMR laboratories and many applications have been described in the literature. However, besides simply using 1D ¹H or ¹³C NMR, a number of more advanced methods has been developed and used in the past. Here, we want to describe the applicability of nuclei beyond the classical ones ¹H and ¹³C. Mixtures can be characterized much better by applying various chemometric methods and separating the signals of mixture components can be achieved by DOSY experiments. All these methods contribute to the platform of qNMR methods and extend the possibilities of NMR for quantification and quality evaluation of drugs, excipients, polymers, and plant extracts. However, for quantification purposes, validation is always an issue and it is necessary to think about taking NMR related measures which might be different from the ones considered for chromatographic methods.

Physiological changes for drought resistance in different species of Phyllanthus

The Phyllanthus genus is widely distributed in tropical and subtropical areas of the world and present several pharmacological applications. Drought is a restrictive factor for crop development and production, and is becoming a severe problem in many regions of the world. The species Phyllanthus amarus and Phyllanthus niruri were subjected to drought stress for varying periods of time (0, 3, 5, 7, and 10 days), and afterwards, leaves were collected and evaluated for physiological and biochemical responses, such as oxidative stress markers and drought-associated defense mechanisms. Results show that P. amarus has an endogenously higher level of variables of the oxidative/antioxidant metabolism, and P. niruri presents the most significant changes in those variables when compared to control and stressed plants. For both Phyllanthus species, drought stress induces higher levels of organic acids such as malic, succinic, and citric acids, and amino acids such as proline, GABA, alanine, and valine. Moreover, P. niruri plants respond with greater glucose and corilagin contents. Therefore, considering the evaluated metabolic changes, P. amarus is better adapted to drought-stress, while P. niruri presents an acclimation strategy that increases the corilagin levels induced by short-term drought stress.