Quantitative Chemical Composition, Anti-Oxidant Activity, and Inhibition of TNF Release by THP-1 Cells Induced by Extracts of and .

This study investigated the similarities between and , plant species that are traditionally used in Brazil to treat rheumatism and arthritis, whose anti-inflammatory effects are supported by scientific evidence. The contents of - and -aconitic acid, homoorientin, chicoric acid, swertisin, caffeoyl-feruloyl-tartaric acid, and di-feruloyl-tartaric acid were quantified by UPLC-DAD in various hydroethanolic extracts from the leaves, whereas their anti-oxidant activity and their effect on TNF release by LPS-stimulated THP-1 cells were assessed to evaluate potential anti-inflammatory effects. The 50% and 70% ethanol extracts showed higher concentrations of the analyzed markers in two commercial samples and a cultivated specimen of , as well as in a commercial lot of .

Authenticity study of commercial samples of St. John's wort by paper spray ionization mass spectrometry and chemometric tools.

Hypericum perforatum L. (St. John's wort) is one of the world's most consumed medicinal plants for treating depression and psychiatric disorders.

Screening method for the characterization of anabolic steroids seized in Brazil using paper spray mass spectrometry and chemometric tools.

This paper reports the use of paper spray mass spectrometry (PS-MS) combined with chemometric models to analyze seized samples of anabolic steroids. Because many forensic laboratories typically demand high-throughput analysis for this type of sample, we developed a quicker and simpler alternative analytical method for routine analysis with minimal sample preparation. Oily samples (n = 39) resulting from seizures carried out by Brazilian Federal and State Police units were selected for this study.

One-class model with two decision thresholds for the rapid detection of cashew nuts adulteration by other nuts.

A green screening method to determine cashew nut adulteration with Brazilian nut, pecan nut, macadamia nut and peanut was proposed. The method was based on the development of a one-class soft independent modelling of class analogy (SIMCA) model for non-adulterated cashew nuts using near-infrared (NIR) spectra obtained with portable equipment. Once the model is established, the assignment of unknown samples depends on the threshold established for the authentic class, which is a key aspect in any screening approach.

Definition of chemical markers for Hancornia speciosa Gomes by chemometric analysis based on the chemical composition of extracts, their vasorelaxant effect and α-glucosidase inhibition.

Ethnopharmacological Relevance: Hancornia speciosa Gomes (Apocynaceae) is a tree found in the Brazilian savannah, traditionally used to treat several diseases, including diabetes and hypertension. The anti-hypertensive activity of H. speciosa leaves (HSL) has been demonstrated in different models and is credited to the vasodilator effect and ACE (angiotensin-converting enzyme) inhibition.

A t-test ranking-based discriminant analysis for classification of free-range and barn-raised broiler chickens by H NMR spectroscopy.

Intensive systems of raising chickens in barns prevail worldwide for financial reasons. In contrast, free-range chickens are raised in better welfare conditions, and preferred by consumers due to their distinctive taste/flavor, having higher market prices. Thus, free-range chickens have been the target of frauds.

Screening method for the rapid detection of diethylene glycol in beer based on chemometrics and portable near-infrared spectroscopy.

A recent case of contamination of some batches of a Brazilian beer brand with diethylene glycol (DEG) had great repercussion, resulting in at least seven deaths. In this article, a direct method was developed for the rapid detection of DEG in beer samples based on portable near-infrared spectroscopy combined with partial least squares discriminant analysis (PLS-DA). The discriminant model was built with 100 uncontaminated beer samples and 100 samples containing DEG in a concentration range between 10 and 1000 mg L, totalizing 200 samples of different brands and styles.

Detection of adulterations in a valuable Brazilian honey by using spectrofluorimetry and multiway classification.

Spectrofluorimetry combined with multiway chemometric tools were applied to discriminate pure Aroeira honey samples from samples adulterated with corn syrup, sugar cane molasses and polyfloral honey. Excitation emission spectra were acquired for 232 honey samples by recording excitation from 250 to 500 nm and emission from 270 to 640 nm. Parallel factor analysis (PARAFAC), partial least squares discriminant analysis (PLS-DA), unfolded PLS-DA (UPLS-DA) and multilinear PLS-DA (NPLS-DA) methods were used to decompose the spectral data and build classification models.

Combining mid infrared spectroscopy and paper spray mass spectrometry in a data fusion model to predict the composition of coffee blends.

This paper describes a robust multivariate model for quantifying and characterizing blends of Robusta and Arabica coffees. At different degrees of roasting, 120 ground coffee blends (0.0-33.

Detection of adulterants in grape nectars by attenuated total reflectance Fourier-transform mid-infrared spectroscopy and multivariate classification strategies.

There is no any doubt about the importance of food fraud control, as it has implications in food safety and in consumer health. Focusing on fruit beverages, some types of adulterations have been detected more frequently, such as substitution with less expensive fruits. A methodology based on attenuated total reflectance Fourier-transform mid-infrared spectroscopy (ATR-FTIR) and multivariate classification was applied to detect whether grape nectars were adulterated by substitution with apple juice or cashew juice.

Discrimination between conventional and omega-3 fatty acids enriched eggs by FT-Raman spectroscopy and chemometric tools.

This work developed an analytical method to differentiate conventional and omega-3 fat acids enriched eggs by Raman spectroscopy and multivariate supervised classification with Partial Least Squares Discriminant Analysis (PLS-DA). Forty samples of enriched eggs and forty samples of different types of common eggs from different batches were used to build the model. Firstly, gas chromatography was employed to analyze fatty acid profiles in egg samples.

Variable selection for multivariate classification aiming to detect individual adulterants and their blends in grape nectars.

During the quality inspection control of fruit beverages, some types of adulterations can be detected, such as the addition or substitution with less expensive fruits. To determine whether grape nectars were adulterated by substitution with apple or cashew juice or by a mixture of both, a methodology based on attenuated total reflectance Fourier transform mid infrared spectroscopy (ATR-FTIR) and multivariate classification methods was proposed. Partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) models were developed as multi-class methods (classes unadulterated, adulterated with cashew and adulterated with apple) with the full-spectra.

Determination of main fruits in adulterated nectars by ATR-FTIR spectroscopy combined with multivariate calibration and variable selection methods.

Grape, orange, peach and passion fruit nectars were formulated and adulterated by dilution with syrup, apple and cashew juices at 10 levels for each adulterant. Attenuated total reflectance Fourier transform mid infrared (ATR-FTIR) spectra were obtained. Partial least squares (PLS) multivariate calibration models allied to different variable selection methods, such as interval partial least squares (iPLS), ordered predictors selection (OPS) and genetic algorithm (GA), were used to quantify the main fruits.

Paper spray mass spectrometry and chemometric tools for a fast and reliable identification of counterfeit blended Scottish whiskies.

A direct method based on the application of paper spray mass spectrometry (PS-MS) combined with a chemometric supervised method (partial least square discriminant analysis, PLS-DA) was developed and applied to the discrimination of authentic and counterfeit samples of blended Scottish whiskies. The developed methodology employed the negative ion mode MS, included 44 authentic whiskies from diverse brands and batches and 44 counterfeit samples of the same brands seized during operations of the Brazilian Federal Police, totalizing 88 samples. An exploratory principal component analysis (PCA) model showed a reasonable discrimination of the counterfeit whiskies in PC2.

Paper Spray Mass Spectrometry for the Forensic Analysis of Black Ballpoint Pen Inks.

This article describes the use of paper spray mass spectrometry (PS-MS) for the direct analysis of black ink writings made with ballpoint pens. The novel approach was developed in a forensic context by first performing the classification of commercially available ballpoint pens according to their brands. Six of the most commonly worldwide utilized brands (Bic, Paper Mate, Faber Castell, Pentel, Compactor, and Pilot) were differentiated according to their characteristic chemical patterns obtained by PS-MS.

Paper spray mass spectrometry and PLS-DA improved by variable selection for the forensic discrimination of beers.

Paper spray mass spectrometry (PS-MS) combined with partial least squares discriminant analysis (PLS-DA) was applied for the first time in a forensic context to a fast and effective differentiation of beers. Eight different brands of American standard lager beers produced by four different breweries (141 samples from 55 batches) were studied with the aim at performing a differentiation according to their market prices. The three leader brands in the Brazilian beer market, which have been subject to fraud, were modeled as the higher-price class, while the five brands most used for counterfeiting were modeled as the lower-price class.