1,720,997 research outputs found
Quantifying API polymorphs in formulations using X-ray powder diffraction and multivariate standard addition method combined with net analyte signal analysis
Full text linkThe direct quantification of Active Pharmaceutical Ingredients in solid formulations is a challenging open issue. A consolidated analytical technique based on X-ray Powder Diffraction is available, being the definitive test for the identification of polymorphs and crystal phases. However, its application for quantitative analysis is hindered by matrix effects: refinement methods (e.g. Rietveld method) require a complete knowledge of samples’ composition, while univariate calibration methods require the matrix effect to be studied and severely suffer from the co-presence of crystalline and amorphous phases in the sample. Multivariate analysis is the only way to bypass problems affecting refinements procedures and univariate calibration. In particular, the multivariate standard addition method (SAM) is promising; however, it is straightforward only when the analytical blank (matrix devoid of analyte) is available: in that case SAM is applied by simply extrapolating the SAM model to the matrix experimental signal. In this work, the quantitative analysis of polymorphic forms of Active Pharmaceutical Ingredients based on X-ray Powder Diffraction is performed for the first time by a method based on multivariate standard addition method combined with net analyte signal procedure; it allows for reliable quantification of polymorphs of active principles in solid formulations, which are rapidly analyzed without any sample pre-treatment. Two test cases are presented: quantification of two polymorphs of piracetam in binary mixtures (forms II and III), and quantification of paracetamol (form I) in Tachifludec®
Floristic diversity in different urban ecological niches of a southern European city
Full text linkThe present paper aimed at studying the vertical and horizontal spatial distribution, species richness
and diversity of vascular plants in different urban ecological niches (urban habitats) by means of the
case study of Bologna (Italy), a typical densely populated southern European city. A total of 477 species
were found in the study area of the historical city centre, 30% of which were alien species. Alien plant
species were mainly present among phanerophytes, while native plants were mainly therophytes
and hemicryptophytes. The habitats that mostly contributed to the species total richness were seminatural
soils, followed by paved areas, walls, rooftops and manholes. The number of exclusive species
decreased according to the selectiveness of the habitat, with manholes and rooftops being the most
selective. The presence of hemicryptophytes constant decreased going from 27% of more humid
habitats to 5% of more arid habitats, so that they can be considered a water availability biomarker.
Urban habitat quality, measured by the number of native species, was directly proportional to the
strength of selective factors and inversely proportional to the rate of disturbance, with roofs and seminatural
soils having, respectively, the highest and lowest quality. Finally, a relation between species
richness and street characteristics, like width, orientation and type of flooring, was demonstrated
How to use efficiently airborne criteria pollutants and radon-222 in source apportionment: A self-organizing maps approach
Full text linkPollutant source apportionment represents one of the fundamental activities in environmental science. Several efficient chemometric tools are available to the scope, mostly based on multivariate techniques and usually applied to aerosol chemical speciation data. In the present work, an alternative source profiling method is proposed, based on the self-organizing maps (SOM) algorithm. Moreover, the dataset used includes typical criteria pollutants and physical parameters related to airborne particulate matter widely used as a complement of aerosol source apportionment and largely available at a higher time resolution than bulk aerosol samplings, allowing the information on the dynamic behavior of the local airshed to be extended. In this work, data was collected at a coastal location in NW Italy, between January and July 2012. Hourly concentrations of typical gaseous pollutants (SO2, NO, NO2, benzene, toluene, (m-p)-xylene, o-xylene), black-carbon and particle number concentrations by an optical particle sizer (OPS) were collected. The dataset was integrated with radon-222 activity concentration and meteorological parameters to enrich and refine the information obtained by SOM computation as well as to improve the air pollution source localization. Despite the lower specificity of criteria pollutants, the approach developed was capable of revealing distinct pollution sources such as the urban background traffic, the coal-fired power plant active at the time of the study, and the harbor, in agreement with previous PM-based source apportionment studies carried out locally, while enlightening peculiar dynamical conditions detectable at the sub-daily time scale. The application of the SOM algorithm, with the integration of meteorological parameters and atmospheric radon, proved to be very efficient in unveiling the air pollution sources
Rapid discrimination of Italian Prosecco wines by head-space gas-chromatography basing on the volatile profile as a chemometric fingerprint
No full textProsecco wine is one of the most important products of the Italian oenological landscape. Its production is strictly regulated by several disciplinary. Thus, it is important to verify the quality of the final product, to defend the uniqueness of this wine. This work describes a rapid method to discriminate among varieties of Italian Prosecco wine using the volatile-fraction distribution as an untargeted fingerprint. The volatile profile corresponds to gas-chromatograms obtained in head-space mode. Principal components analysis of chromatograms allows discriminating the Prosecco samples depending on geographical origin, cultivation practices, and wine-making technologies. In particular, conventional vs. biological agriculture and manual vs. mechanical harvesting give well-separated clusters when projected on a scores plot. Influence plots allow evaluating which variables are the most effective to describe the differences between oenological classes, which are declared in the label and coded in the disciplinary of origin denomination. The identification of discriminating molecules in the volatile profile is also performed by Kovats indexes. Thus, possible chemical markers for the classification of Italian Prosecco wines are appointed
Determination of emerging metal pollutants and toxic metals in mussels and bivalve mollusks, very important food and environmental bio-monitoring species
No full textA quick and widespread diffusion of heavy metals as contaminants in all the environmental systems has called the attention to their determination. Indeed, heavy metals, together with pesticides, are very dangerous pollutants owing to their bioaccumulation and toxicity. It is, therefore, necessary to determine these metals at trace and ultra-trace level especially in aquatic ecosystems to establish reasonable water quality criteria. Certain marine species, in particular mussels, clams, but also oysters accumulate toxic metals, being filtering organisms. It was verified that an adult organism is able to filter several liters per hours (also up to 4-5 L h-1), depending on its weight. This prerogative involves two important facts and consequences: 1. The ability to accumulate all harmful substances for humans, toxic metals, in particular, requires particular attention and inspections before being sold on the market. 2. In addition to this important and fundamental aspect of public health, the determination of toxic metals in mussels, clams and also oysters, that are not only filtering organisms but also sessile species, can be usefully employed for bio-monitoring campaigns, that evaluate the long-term trend of the pollution load of an aquatic ecosystem, information that evidently cannot be provided by punctual determinations. For completely mapping environmental pollution, the sampling duration and cadence are very important. However, it should be emphasized that the use of bio-monitors, just proposed by several authors, but certainly not scientifically supported, is possible only in the case of a long sampling plan. In any case, the metal determination in mussels and bivalve mollusks evidently must be accurate, reproducible and especially it must show very low limits of detection. The present work reports and discusses the different analytical methodologies for the determination of emerging metals pollutants, together with all toxic metals, in mussels, clams, and oysters
Analysis of Solid Formulates Using UV-Visible Diffused Reflectance Spectroscopy with Multivariate Data Processing Based on Net Analyte Signal and Standard Additions Method
No full textQuality control in pharmaceutical manufacturing necessitates rigorous testing and approval, adhering to Current Good Manufacturing Practices before commercialization. The production of solid drugs presents significant industrial challenges regarding uniformity, homogeneity, and consistency. Traditional quality guidelines rely on classical analytical methods such as liquid chromatography coupled with mass spectrometry. However, the emergence of Process Analytical Technology introduced non-destructive, rapid, and cost-effective methods like UV-Visible Diffuse Reflectance Spectroscopy. The present study aimed to develop a chemometric method for quantifying Active Pharmaceutical Ingredients (APIs) in Neo Nisidine®, a solid mixture drug, using spectrophotometric data. The Net Analyte Signal (NAS) method, combined with standard additions, allowed the creation of a pseudo-univariate standard addition model, overcoming some challenges in solid-phase analysis. Successful quantifications of APIs in ideal laboratory samples and real pharmaceutical tablets were obtained. NAS-based chemometric models showed high precision and reliability, whose results were validated by comparisons with HPLC ones. The study revealed that solid-phase spectrophotometric analyses can be considered a valid alternative to API analyses. Solid-phase analysis offers non-destructive, cost-effective, and environmentally friendly benefits, enabling its integration into pharmaceutical production to improve quality control
An Authentication Study on Grappa Spirit: The Use of Chemometrics to Detect a Food Fraud
Full text linkAn authenticity study on Italian grape marc spirit was carried out by gas chromatography (GC) and chemometrics. A grape marc spirit produced in Italy takes the particular name of “grappa”, a product which has peculiar tradition and production in its country of origin. Therefore, the evaluation of its authenticity plays an important role for its consumption in Italy, as well as for its exportation all around the world. For the present work, 123 samples of grappa and several kinds of spirits were analyzed in their alcohol content by electronic densimetry, and in their volatile fraction by gas-chromatography with a flame-ionization detector. Part of these samples (94) was employed as a training set to compute a chemometric model (by linear discriminant analysis, LDA) and the other part (29 samples) was used as a test set to validate it. Finally, two grappa samples seized from the market by the Italian Customs and Monopolies Agency and considered suspicious due to their aroma reported as non-compliant were projected onto the LDA model to evaluate the compliance with the “grappa” class. A further one-class classification method by principal component analysis (PCA) was carried out to evaluate the compliance with other classes. Results showed that the suspicious samples were not recognized as belonging to any of the analyzed spirit classes, confirming the starting hypothesis that they could be grappa samples adulterated in some way
PM10 source apportionment in two sites of southern Spain by Positive Matrix Factorization. Evaluation of the relevance of sampling site altitude to the PM10 fingerprint
No full textThe evaluation of the sources of particulate matter (PM) is one of the most important topics in environmental science. Both natural and anthropogenic sources are involved in the overall PM pollution in both urban and rural areas. Mathematical methods, as Positive Matrix Factorization (PMF), applied to chemical data are the most powerful tools for the discrimination of PM sources.
In the present work, the results obtained from a three-year sampling campaign (between 2017 and 2019) are presented. 700 PM10 filters were collected in the framework of FRESA Project (Impact of dust-laden African air masses and of stratospheric air masses in the Iberian Peninsula. Role of the Atlas Mountains) from two sites in Andalusia, southern Spain: the first one is in the city of Granada, while the second one is in Sierra Nevada. Filters were analyzed by ion chromatography and Particle-Induced X-ray Emission (PIXE) for elemental analysis.
The two stations are relatively close to each other (around 20 km). However, the Sierra Nevada station is located at an altitude of 2550 m a.s.l, while the Granada station is at 738 m a.s.l. This altitude difference of almost 2000 m makes the two sites very different from a PM-sources point of view, as highlighted by the two parallel PMF models applied to chemical data. Indeed, Sierra Nevada samples showed the impact of frequent mineral dust intrusions from Sahara Desert, that greatly affected the overall PM composition; in Granada site, instead, samples showed the typical urban fingerprint, with lower evidences of Saharan dust intrusions, due to the different circulation as a function of height
Seasonal changes in amino acids and phenolic compounds in fruits from hybrid cross populations of American grapes differing in disease resistance
No full textThe production of wine grapes in upstate New York (USA) is limited by diseases that are promoted by the cool and sometimes rainy climate. A breeding program has been introducing disease resistance from related species into the cultivated stock. Previous work has indicated that such resistance may be based on biochemical reactions rather than on a hypersensitive reaction. We therefore undertook metabolic profiling of amino acids and phenolic compounds in berries from collections of susceptible and resistant hybrids over the course of berry development to determine whether any of these compounds could be causal in disease resistance. The most abundant amino acids were GLN, ARG, PRO and THR. The amount of amino acids in ripe berries was from 3 to 4.7-fold higher compared to earlier stages. The concentrations of total phenolics were variable through the season with no consistent trend between susceptible and resistant fruits. Notable changes in phenolic compounds, especially anthocyanins, were recorded, especially during the ripening phase, when phenolics and anthocyanins increased following veraison. The most abundant phenolic compounds were catechin and epi-catechin; the most abundant anthocyanin was delphinidin-3-glucoside, which had a slightly greater concentration in resistant fruit at harvest, followed by malvidin-3-glucoside and petunidin-3-glucoside. The content of both amino acids and phenolic compounds in white-fruited parent cv. Horizon was equal to several-fold lower than the progeny plants, whether susceptible or resistant, depending on the harvest time. While no major differences between susceptible and resistant lines were found, multivariate analyses showed that it is possible to discriminate the susceptibility or resistance of grapes by analyzing their combined concentrations of amino acids, polyphenols and anthocyanins. Therefore, these compounds are influenced by the resistance capacity of grapes and could be used as a chemical fingerprint of this ability. However, it is likely that these are associations with disease resistance rather than their cause as no major consistent differences were noted
Botanical traceability of unifloral honeys by chemometrics based on head-space gas chromatography
No full textThe botanical origin of honey is subjected to severe controls by Food Control Institutions, both for health protection and for frauds prevention. The complexity of honey makes it very difficult to verify the botanical origin. Among the available validated methods, sensory analysis and melissopalynology are the most widely employed. These methods require a long time and deep consolidated expertise. To shorten analysis time while simplifying the analytical procedure, head-space flash gas chromatography was applied in the present study. Chromatographic peak areas were processed by chemometrics (in particular principal components analysis and linear discriminant analysis). Three hundred and thirty-nine honey samples from twelve categories of unifloral honey were analyzed: acacia, citrus, chestnut, thistle, tree heath, eucalyptus, sunflower, rhododendron, lime, French honeysuckle, fir honeydew, and wood honeydew. Each sample was a priori classified by sensory analysis. The multivariate models were validated by cross validation and test-set validation, with predictive abilities always higher than 80%: good results were obtained both in calibration and in prediction mode, showing a good agreement between this new approach and the traditional one for the determination of the botanical origin of honey
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