Profiling of seized Cannabis sativa L. flowering tops by means of microwave-assisted hydro distillation and gas chromatography analyses.

This research aimed to support police forces in their battle against illicit drug trafficking by means of a multi-technique approach, based on gas chromatography. In detail, this study was focused on the profiling of volatile substances in narcotic Cannabis sativa L. flowering tops. For this purpose, the Scientific Investigation Department, RIS Carabinieri of Messina, provided 25 seized samples of Cannabis sativa L. The content of Δ9-tetrahydrocannabinol (THC), useful to classify cannabis plant as hemp (≤ 0.2 %) or as marijuana (> 0.2 %), was investigated. Essential oils of illicit drug samples were extracted using a microwave-assisted hydro-distillation (MAHD) system; GC-MS and GC-FID analytical techniques were used for the characterization of the terpenes and terpenoids fingerprint. Furthermore, the enantiomeric and carbon isotopic ratios of selected chiral compounds were investigated using a heart-cutting multidimensional GC (MDGC) approach. The latter exploited a combination of an apolar column in the first dimension, and a chiral cyclodextrin-based column in the second one, prior to parallel isotope-ratio mass spectrometry (C-IRMS) and MS detection. Finally, all the data were gathered into a statistical model, to demonstrate the existence of useful parameters to be used for the classification of seized samples.

Flow-modulation comprehensive two-dimensional enantio-gas chromatography: A valid and flexible alternative to heart-cutting multidimensional enantio-gas chromatography.

The present research is focused on the proposal of use of flow-modulation comprehensive two-dimensional enantio-gas chromatography (FM eGC × GC) as a valid, flexible, and possibly superior alternative to heart-cutting multidimensional enantio-GC (eMDGC). The latter, a technique of demonstrated utility, is used specifically for the targeted separation of chiral compounds, whereas FM eGC × GC can produce both targeted and high-resolution untargeted information in a single run. It is clearly possible to use eMDGC for untargeted analysis, often with a flame ionization detector (stand-by analysis), to monitor a first-dimension (1D) separation, of much lower peak capacity compared to FM eGC × GC. If eMDGC is used with mass spectrometry (MS), it is normally exploited to monitor the second-dimension (2D) separation. The analytical instrument consisted of automated solid-phase microextraction (SPME), and a low duty-cycle FM eGC × GC system (with time-of-flight MS), equipped with an enantioselective 1D column (2,3-di-O-methyl-6-t-butyl silyl ß-cyclodextrin derivative) and a 2D polyethylene glycol one. Ten Marsala wines were subjected to analysis, for the determination of chiral lactones (many at the low ppb level, due to the high concentration capacity of SPME) and for general analyte profiling. In many instances, highly complex chromatograms were attained, with statistical analysis (ANOVA-simultaneous component analysis and partial least squares discriminant analysis) used for sample differentiation.

The effect of SARS-CoV-2 variants on the plasma oxylipins and PUFAs of COVID-19 patients.

Oxylipins are important signalling compounds that are significantly involved in the regulation of the immune system and the resolution of inflammation. Lipid metabolism is strongly activated upon SARS-CoV-2 infection, however the modulating effects of oxylipins induced by different variants remain unexplored. Here, we compare the plasma profiles of thirty-seven oxylipins and four PUFAs in subjects infected with Wild-type, Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529) variants. The results suggest that oxidative stress and inflammation resulting from COVID-19 were highly dependent on the SARS-CoV-2 variant, and that the Wild-type elicited the strongest inflammatory storm. The Alpha and Delta variants induced a comparable lipid profile alteration upon infection, which differed significantly from Omicron. The latter variant increased the levels of pro-inflammatory mediators and decreased the levels of omega-3 PUFA in infected patients. We speculate that changes in therapeutics, vaccination, and prior infections may have a role in the alteration of the oxylipin profile besides viral mutations. The results shed new light on the evolution of the inflammatory response in COVID-19.

Shellfish sanitation monitoring in La Spezia gulf: Chemometric evaluation of data from 2015 to 2021.

Shellfish sanitary controls are very important to guarantee consumer health because bivalve molluscs (BVM) are filter-feeders so they can accumulate pathogens, environmental contaminants and biotoxins produced by some algae, causing infections and food poisoning in humans after ingestion. The purpose of this work was to analyse with chemometric methods the historical data relating to routine analyses carried out by the competent authority (Liguria Local Health Unit, National Health Service) on the BVM reared in a shellfish farm located in the Gulf of La Spezia (Italy). Chemometric analysis was aimed at identifying any correlations between the variables, as well as any seasonal trends and similarities between the stations, in order to be able to provide further material for a more accurate risk assessment and to improve the monitoring organization for example by reducing sampling stations and/or sampling frequency. The dataset used included 31 variables classified as biotoxicological, microbiological and chemical variables, measured twice a week, monthly or half yearly respectively, for a total of 6 years (from 2015 to 2021), on samples of Mytilus galloprovincialis coming from 7 monitoring stations. The results obtained by the application of principal component analysis have shown positive alga-biotoxin correlations, as well as seasonal trends linked to algae growth, with a greater algal biomass and their toxins during the spring months. In addition, periods characterised by low rainfall were found to affect algal development, promoting especially species such as Dinophysis spp. Considering the microbiological and biotoxicological variables, significant differences between the monitoring stations were not found. However, stations could be distinguished on the basis of the nature of the predominant chemical pollutants.

Near-infrared hyperspectral imaging to map collagen content in prehistoric bones for radiocarbon dating.

Many of the rarest prehistoric bones found by archaeologists are enormously precious and are considered to be part of our cultural and historical patrimony. Radiocarbon dating is a well-established technique that estimates the ages of bones by analysing the collagen still present. However, this method is destructive, and its use must be limited. In this study, we used imaging technology to quantify the presence of collagen in bone samples in a non-destructive way to select the most suitable samples (or sample regions) to be submitted to radiocarbon dating analysis. Near-infrared spectroscopy (NIR) that was connected to a camera with hyperspectral imaging (HSI) was used along with a chemometric model to create chemical images of the distribution of collagen in ancient bones. This model quantifies the collagen at every pixel and thus provides a chemical mapping of collagen content. Our results will offer significant advances for the study of human evolution as we will be able to minimise the destruction of valuable bone material, which is under the protection and enhancement of European cultural heritage and thus allow us to contextualise the valuable object by providing an accurate calendar age.

Towards the non-destructive analysis of multilayered samples: A novel XRF-VNIR-SWIR hyperspectral imaging system combined with multiblock data processing.

The new challenge in the investigation of cultural heritage is the possibility to obtain stratigraphical information about the distribution of the different organic and inorganic components without sampling. In this paper recently commercialized analytical set-up, which is able to co-register VNIR, SWIR, and XRF spectral data simultaneously, is exploited in combination with an innovative multivariate and multiblock high-throughput data processing for the analysis of multilayered paintings. The instrument allows to obtain elemental and molecular information from superficial to subsurface layers across the investigated area. The chemometric strategy proved to be highly efficient in data reduction and for the extraction and integration of the most useful information coming from the three different spectroscopies, also filling the gap between data acquisition and data understanding through the combination of principal component analysis (PCA), brushing, correlation diagrams and maps (within and between spectral blocks) on the low-level fused. In particular, correlation diagrams and maps provide useful information for the reconstruction of a stratigraphic structure without the need to take any sample, thanks to the effective account for inter-correlation among data (variables), which is able to effectively characterize the possible combinations of components located in the same depth level. The highly innovative technology and the data processing strategy are applied for the multi-level characterization of a complex painting reproduction as an illustrative pilot study.

Identification of mechanically separated meat using multivariate analysis of 43 trace elements detected by inductively coupled mass spectrometry: A validated approach.

The European Food Safety Authority asked for novel approaches for identifying mechanically separated meat (MSM) in meat products, due to food safety concern. In this study, a novel approach based on multivariate analysis of 43 trace elements in meat products is described. Overall, 27 trace elements and 16 rare earth elements were determined by using ICP-MS after sample mineralization of 100 meat samples, composed of different percentages of MSM, obtained at low and high pressure, and without MSM. After development and optimization, the multivariate approach was validated by analyzing and then classifying 10 "blind" meat samples, obtaining method accuracy equal to 90%. Thus, the applicability of this new analytical approach was demonstrated. The method represents a significant improvement for this type of determination, especially when MSM is obtained at low pressure, since this product is characterized by chemical characteristics very similar to fresh meat.

Non-destructive age estimation of biological fluid stains: An integrated analytical strategy based on near-infrared hyperspectral imaging and multivariate regression.

From a criminalistic point of view, the accurate dating of biological traces found at the crime scene, together with its compatibility with the estimated crime perpetration timeframe, enables to limit the number of suspects by assessing their alibis and clarifying the sequence of events. The present study delineates, for the first time, the possibility of dating biological fluids such as semen and urine, as well as blood traces, by using a novel non-destructive analytical strategy based on hyperspectral imaging in the near infared region (HSI-NIR), coupled with multivariate regression methods. Investigated aspects of the present study include not only the progressive degradation of the biological trace itself, but also the effects of its interactions with the support on which it is absorbed, in particular the hydrophilic vs. hydrophobic character of fabric tissues. Results are critically discussed, highlighting potential and limitations of the proposed approach for a practical implementation.

Effects of long-term vegan diet on breath composition.

The composition of exhaled breath derives from an intricate combination of normal and abnormal physiological processes that are modified by the consumption of food and beverages, circadian rhythms, bacterial infections, and genetics as well as exposure to xenobiotics. This complexity, which results wide intra- and inter-individual variability and is further influenced by sampling conditions, hinders the identification of specific biomarkers and makes it difficult to differentiate between pathological and nominally healthy subjects. The identification of a 'normal' breath composition and the relative influence of the aforementioned parameters would make breath analyses much faster for diagnostic applications. We thus compared, for the first time, the breath composition of age-matched volunteers following a vegan and a Mediterranean omnivorous diet in order to evaluate the impact of diet on breath composition. Mixed breath was collected from 38 nominally healthy volunteers who were asked to breathe into a 2 l handmade Nalophan bag. Exhalation flow rate and carbon dioxide values were monitored during breath sampling. An aliquot (100 ml) of breath was loaded into a sorbent tube (250 mg of Tenax GR, 60/80 mesh) before being analyzed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Breath profiling using TD-GC-MS analysis identified five compounds (methanol, 1-propanol, pentane, hexane, and hexanal), thus enabling differentiation between samples collected from the different group members. Principal component analysis showed a clear separation between groups, suggesting that breath analysis could be used to study the influence of dietary habits in the fields of nutrition and metabolism. Surprisingly, one Italian woman and her brother showed extremely low breath isoprene levels (about 5 pbv), despite their normal lipidic profile and respiratory data, such as flow rate and pCO2. Further investigations to reveal the reasons behind low isoprene levels in breath would help reveal the origin of isoprene in breath.

MS-based targeted profiling of oxylipins in COVID-19: A new insight into inflammation regulation.

The key role of inflammation in COVID-19 induced many authors to study the cytokine storm, whereas the role of other inflammatory mediators such as oxylipins is still poorly understood. IMPRECOVID was a monocentric retrospective observational pilot study with COVID-19 related pneumonia patients (n = 52) admitted to Pisa University Hospital between March and April 2020. Our MS-based analytical platform permitted the simultaneous determination of sixty plasma oxylipins in a single run at ppt levels for a comprehensive characterisation of the inflammatory cascade in COVID-19 patients. The datasets containing oxylipin and cytokine plasma levels were analysed by principal component analysis (PCA), computation of Fisher's canonical variable, and a multivariate receiver operating characteristic (ROC) curve. Differently from cytokines, the panel of oxylipins clearly differentiated samples collected in COVID-19 wards (n = 43) and Intensive Care Units (ICUs) (n = 27), as shown by the PCA and the multivariate ROC curve with a resulting AUC equal to 0.92. ICU patients showed lower (down to two orders of magnitude) plasma concentrations of anti-inflammatory and pro-resolving lipid mediators, suggesting an impaired inflammation response as part of a prolonged and unsolvable pro-inflammatory status. In conclusion, our targeted oxylipidomics platform helped shedding new light in this field. Targeting the lipid mediator class switching is extremely important for a timely picture of a patient's ability to respond to the viral attack. A prediction model exploiting selected lipid mediators as biomarkers seems to have good chances to classify patients at risk of severe COVID-19.

Analysing the water spectral pattern by near-infrared spectroscopy and chemometrics as a dynamic multidimensional biomarker in preservation: rice germ storage monitoring.

Water activity is an important phenomenon not yet explained in terms of water molecular structure. This paper aims to find the relationship between the water activity and water molecular structure of the rice germ, based on its spectral pattern which can be measured using non-destructive technology. Aquaphotomics near-infrared spectroscopy was used to study rice germ stored at different levels of water activity and atmosphere. The findings show that state of the rice germ is governed by the water activity upon storage, which is defined by the structure of water within germ matrix. The structure of water can be described solely by the absorbance spectral pattern at the following absorbance bands: proton hydrates, hydration shells and water vapor (1364, 1375 and 1382 nm), trapped water (1392 nm), free water (1410 nm), hydration water (1425 nm), adsorbed water (1455 nm), non-bonded hydroxyl (1436 nm) and bound water (1520 nm).

An effective strategy for the monitoring of microplastics in complex aquatic matrices: Exploiting the potential of near infrared hyperspectral imaging (NIR-HSI).

Contamination by microplastics (MP) represents a critical environmental challenge with potential consequences at ecosystem, economic and societal levels. As the marine system is the final sink for MP, there is an urgent need to develop methods for the monitoring of synthetic particles in different marine compartments and sample matrices. Extensive evaluations are hindered by time and costs associated with to conventional MP spectroscopic analyses. The potential of near infrared hyperspectral imaging (NIR-HSI) has been recently evaluated. However, NIR-HSI has been poorly studied so far, limitedly to the detection of large particles (>300 µm), and its capability for direct characterization of MP in real marine matrices has not been considered yet. In the present study, a rapid near infrared hyperspectral imaging (NIR-HSI) method, coupled with a customised normalised difference image (NDI) strategy for data processing, is presented and used to detect MP down to 50 µm in environmental matrices. The proposed method is largely automated, without the need for extensive data processing, and enabled a successful identification of different polymers, both in surface water and mussel soft tissue samples, as well as on real field samples with environmentally occurring MP. NIR-HSI is applied directly on filters, without the need for particles pre-sorting or multiple sample purifications, avoiding time consuming procedures, airborne contaminations, particle degradation and loss. Thanks to the time and cost effectiveness, a large-scale implementation of this method would enable to extensively monitor the MP presence in natural environments for assessing the ecological risk related to MP contamination.

An in-depth study of cheese ripening by means of NIR hyperspectral imaging: Spatial mapping of dehydration, proteolysis and lipolysis.

Cheese represents one of the most complex food matrices, for the high number of factors contributing to the chemical composition, and so its evaluation represents an important analytical challenge. The present study describes an innovative and non-destructive analytical approach, based on hyperspectral imaging in the near-infrared region (HSI-NIR) and multivariate pattern recognition, to study and monitor the extent - spatial and temporal - of biochemical phenomena responsible for cheese ripening. NIR spectral bands characterising dehydration, proteolysis and lipolysis were individuated and studied by exploiting a representative sample set of characteristic cheeses. The information obtained was employed to develop score maps based on principal component analysis (PCA), which permitted to monitor and visualise the ripening of Formaggetta, a commercial semi-hard cheese typical of Liguria, an Italian region, providing a deep understanding of the evolution of dehydration, proteolysis and lipolysis during the maturation period that precedes the placing on the market.

Rapid and direct detection of small microplastics in aquatic samples by a new near infrared hyperspectral imaging (NIR-HSI) method.

Microplastic (MP) contamination is a critical environmental challenge with a strong impact on the ecosystems, economy and potentially for human health. The smaller the MP size, the greater is the environmental risks as well as the analytical difficulties in detecting and characterising the particles. .We propose a rapid near infrared hyperspectral imaging (NIR-HSI) method that enables the chemical identification and characterisation of small MP (down to 80 µm) in aquatic samples, directly on filters, with no pre-sorting step needed. By considerably reducing the procedural steps, the time of analysis and costs our method addresses the urgent need of cost-effective and robust tools for extensive monitoring of MP in natural systems.

Identification of invisible biological traces in forensic evidences by hyperspectral NIR imaging combined with chemometrics.

The importance of detecting minute biological traces in forensic evidences feeds the continuous interest towards the development of new dedicated technologies both sensitive and reliable. The present study describes the opportunity to combine chemical properties derived from NIR signals with spatial features typical of RGB images by means of hyperspectral imaging (HSI). An analytical procedure based on HSI data collection and their multivariate processing followed by normalized difference images (NDI) is proposed as a screening method to highlight otherwise invisible traces of biological fluids on different supports in view of their collection for DNA analysis. The pattern features identified inside the NDI provided insight into the nature of the biological trace, on the basis of the wavelength at which the stain is highlighted and irrespective of the support on which the stain is deposited. In particular, the procedure allowed to detect and distinguish traces (i.e., 10 and 20 µL volumes) of dehydrated blood, urine, and semen on glass, paper, cotton, denim and polyblend fabric. Beside the simulated specimens used to develop and test the protocol, its robustness was demonstrated also on real and unknown validation samples, confirming its feasibility in some real case studies. An interesting evolution of the proposed strategy is to lay the scientific foundations for the development of a handheld device directly applicable in field.

Trace elements in the estuarine systems of the Gulf of Trieste (northern Adriatic Sea): A chemometric approach to depict partitioning and behaviour of particulate, colloidal and truly dissolved fractions.

Estuaries are transitional water systems where the hydrodynamic processes governing water circulation actively influence suspended particle transport and deposition. In the estuarine mixing zone, the strong physico-chemical gradients resulting from the interaction between river freshwater and seawater may affect the distribution, mobility and fate of several potentially toxic compounds, among which trace elements are of major concern. Knowledge regarding the partitioning behaviour of trace elements would provide essential scientific support for the environmental management of estuaries. In this study, trace element occurrence and phase partitioning among suspended particulate matter, colloidal material and the truly dissolved fraction were investigated in the main Italian and Slovenian estuarine environments of the Gulf of Trieste (northern Adriatic Sea). Further information about the water quality at the river mouths was provided and, in addition to the traditional evaluation of single chemical parameters, a multi-way principal component analysis was employed in order to depict disparities among sampling sites, water layers and seasonal conditions with the final aim of evaluating trace element phase partitioning. Results indicated that the suspended particulate matter acts as the main effective vehicle for Cu, Cr, Fe, Ni and Pb, and enhanced adsorption processes resulted in elevated partitioning coefficients, especially for Fe and Pb. Although disparities occurred between sampling sites and seasons, trace elements showing affinity for the solid phase appeared to be partially bound to the colloidal material. Conversely, As and Cs prevailed in the truly dissolved fraction, especially in seawater and showed scarce affinity for both the suspended particles and colloids.

Chemometric challenges in development of paper-based analytical devices: Optimization and image processing.

Although microfluidic paper-based analytical devices (µPADs) get a lot of attention in the scientific literature, they rarely reach the level of commercialization. One possible reason for this is a lack of application of machine learning techniques supporting the design, optimization and fabrication of such devices. This work demonstrates the potential of two chemometric techniques including design of experiments (DoE) and digital image processing to support the production of µPADs. On the example of a simple colorimetric assay for isoniazid relying on the protonation equilibrium of methyl orange, the experimental conditions were optimized using a D-optimal design (DO) and the impact of multiple factors on the µPAD response was investigated. In addition, this work demonstrates the impact of automatic image processing on accelerating color value analysis and on minimizing errors caused by manual detection area selection. The employed algorithm is based on morphological recognition and allows the analysis of RGB (red, green, and blue) values in a repeatable way. In our belief, DoE and digital image processing methodologies are keys to overcome some of the remaining weaknesses in µPAD development to facilitate their future market entry.

Electrochemical preconcentration coupled with spectroscopic techniques for trace lead analysis in olive oils.

In this paper we present a novel combined electrochemical-spectroscopic approach suitable to monitor trace levels of heavy metals directly in edible oils. The method is based on the electrochemical preconcentration/extraction of the analyte from the tested real matrix by cathodic deposition onto a Pt working electrode, then transfer and anodic re-oxidation of the metallic deposit to a "clean" aqueous solution, suitable for the subsequent spectroscopic analysis. The procedure has been here focused to the determination of lead in extra virgin olive oil (EVOO), performed by applying ICP-QMS or GFAAS techniques. To this aim, the EVOO samples were mixed with proper amounts of the room temperature ionic liquid (RTIL) [P14,6,6,6]+[NTf2]-, in order to obtain a non-aqueous supporting electrolyte suitable for the electrodeposition process. The feasibility and performance of the analytical strategy were at first tested in standard solutions of Pb(II) in RTIL, produced by anodic dissolution of lead in the RTIL, as well as in olive oil samples mixed with 0.5 M RTIL and spiked with known amounts of Pb(II). The optimisation of the electrochemical parameters was achieved by applying a D-Optimal Design, properly set up to optimise the efficiency of the deposition and re-oxidation steps, quantitative recovery and measurement time. Finally, the analytical procedure was applied to the determination of Pb content in some Italian EVOOs, without any need of performing mineralization pretreatments. Data obtained with the proposed procedure satisfactorily agree with those achieved by ICP-QMS analysis after microwave digestion, being differences between the two approaches within 10%, with the advantage of reducing to half the pretreatment time, operating at room temperature and avoiding the use of aggressive solvents.

Macroscopic mid-FTIR mapping and clustering-based automated data-reduction: An advanced diagnostic tool for in situ investigations of artworks.

The present study describes a multivariate strategy that can be used for automatic on-site processing of reflection mode macro FTIR mapping (MA-rFTIR) data obtained during investigation of artworks. The chemometric strategy is based on the integration of principal component analysis (PCA) with a clustering approach in the space subtended by the three lowest-order principal components and allows to automatically identify the regions of interest (ROIs) of the area scanned and to extract the average FTIR spectra related to each ROI. Thanks to the automatic data management, in-field HSI (hyperspectral imaging)-based analyses may be performed even by staff lacking specific advanced chemometric expertise, as it is sometimes the case for conservation scientists or conservators with a scientific background. MA-rFTIR was only recently introduced in the conservation field and, in this work the technique was employed to characterize the surface of metallic artefacts. The analytical protocol was employed as part of a rapid procedure to evaluate the conservation state and the performance of cleaning methods on bronze objects. Both activities are commonly part of restoration campaigns of bronzes and require an on-site analytical procedure for efficient and effective diagnosis. The performance of the method was first evaluated on aged standard samples (bronzes with a layer of green basic copper hydroxysulphate, treated with different organic coatings) and then scrutinized in situ on areas of the 16th century Neptune fountain statue (Piazza del Nettuno, Bologna, Italy) by Gianbologna.