Chemometrics applied to direct multivariate analysis

The present Ph.D. Thesis is focused on applications and developments of chemometrics. After a short introduction about chemometrics (Chapter 1), the present work is divided in three Chapters, reflecting the research activities addressed during the three-year PhD work: • Chapter 2 concerns the application of classification tools to food traceability (Chapter 2.1), plant metabolomics (Chapter 2.2), and food-frauds detection (Chapter 2.3) problems. • Chapter 3 concerns the application of design of experiments for a bio-remediation research (Chapter 3.1) and for machine optimization (Chapter 3.2). • Chapter 4 concerns the development of the net analyte signal (NAS) procedure and its application to several analytical problems. The main aim of this research is to face the matrix-effect problem using a multivariate approach. Chemometrics is the science that extracts useful information from chemical data. The development of instruments and computers is bringing to analytical methodologies ever more sophisticated, and the consequence is that huge amounts of data are collected. In parallel with this rapid evolution, it is, therefore, important to develop chemometric methods able to handle and process the data. Moreover, the attention is also focusing on analytical techniques that do not destroy the analyzed samples. Chemometrics and its application to non-destructive analytical methods are the main topics of this research project. Several analytical techniques have been used during this project: gas-chromatography (GC), bioluminescence, atomic absorption spectroscopy (AAS), liquid chromatography (HPLC), near-infrared spectroscopy, UV-Vis spectroscopy, Raman spectroscopy, X-ray powder diffraction (XRPD), attenuated total reflectance (ATR) spectroscopy. Moreover, this research activity was carried out in collaboration with several external research groups and companie

Floristic diversity in different urban ecological niches of a southern European city

The 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

An Authentication Study on Grappa Spirit: The Use of Chemometrics to Detect a Food Fraud

An 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

Extraction Improvement and Chemometric Study

Funding Information: This work was supported by the NoAW project (‘‘Innovative approaches to turn agricultural waste into ecological and economic assets”), founded by the European Union Horizon 2020 research and innovation program under the grant agreement No 688338. This research was carried out within the Agritech National Research Center and received funding from the European Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR)–MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4–D.D. 1032 17/06/2022, CN00000022), Italy. This study was also funded by national funding by FCT, Foundation for Science and Technology, MCTES, and by ESF (European Social Fund) through NORTE 2020 (Programa Operacional Região Norte), Portugal, through the individual PhD research grant (SFRH/BD/146080/2019) of V.L. This work was also supported by the MEtRICs unit which is funded by national funds from FCT/MCTES (UIDB/04077/2020 and UIDP/04077/2020) and by the Associate Laboratory for Green Chemistry–LAQV which is financed by national funds from FCT/MCTES (UIDB/50006/2020 and UIDP/50006/2020). Publisher Copyright: © 2023 by the authors.In the last 20 years, an increased interest has been shown in the application of different types and combinations of enzymes to obtain phenolic extracts from grape pomace in order to maximize its valorization. Within this framework, the present study aims at improving the recovery of phenolic compounds from Merlot and Garganega pomace and at contributing to the scientific background of enzyme-assisted extraction. Five commercial cellulolytic enzymes were tested in different conditions. Phenolic compound extraction yields were analyzed via a Design of Experiments (DoE) methodology and a second extraction step with acetone was sequentially added. According to DoE, 2% w/w enzyme/substrate ratio was more effective than 1%, allowing a higher total phenol recovery, while the effect of incubation time (2 or 4 h) variation was more enzyme-dependent. Extracts were characterized via spectrophotometric and HPLC-DAD analyses. The results proved that enzymatic and acetone Merlot and Garganega pomace extracts were complex mixtures of compounds. The use of different cellulolytic enzymes led to different extract compositions, as demonstrated using PCA models. The enzyme effects were observed both in water enzymatic and in the subsequent acetone extracts, probably due to their specific grape cell wall degradation and leading to the recovery of different molecule arrays.publishersversionpublishe

Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics

At present, the geographical origin of extra virgin olive oils can be ensured by documented traceability, although chemical analysis may add information that is useful for possible confirmation. This preliminary study investigated the effectiveness of flash gas chromatography electronic nose and multivariate data analysis to perform rapid screening of commercial extra virgin olive oils characterized by a different geographical origin declared in the label. A comparison with solid phase micro extraction coupled to gas chromatography mass spectrometry was also performed. The new method is suitable to verify the geographic origin of extra virgin olive oils based on principal components analysis and discriminant analysis applied to the volatile profile of the headspace as a fingerprint. The selected variables were suitable in discriminating between ''100% Italian" and ''non-100% Italian" oils. Partial least squares discriminant analysis also allowed prediction of the degree of membership of unknown samples to the classes examined

Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics

At present, the geographical origin of extra virgin olive oils can be ensured by documented traceability, although chemical analysis may add information that is useful for possible confirmation. This preliminary study investigated the effectiveness of flash gas chromatography electronic nose and multivariate data analysis to perform rapid screening of commercial extra virgin olive oils characterized by a different geographical origin declared in the label. A comparison with solid phase micro extraction coupled to gas chromatography mass spectrometry was also performed. The new method is suitable to verify the geographic origin of extra virgin olive oils based on principal components analysis and discriminant analysis applied to the volatile profile of the headspace as a fingerprint. The selected variables were suitable in discriminating between '100% Italian' and 'non-100% Italian' oils. Partial least squares discriminant analysis also allowed prediction of the degree of membership of unknown samples to the classes examined

The Palliative Prognostic (PaP) Score without Clinical Evaluation Predicts Early Mortality among Advanced NSCLC Patients Treated with Immunotherapy

Background: An acceptable risk-benefit ratio may encourage the prescription of immune checkpoint inhibitors (ICI) near the late stage of life. The lung immune prognostic index (LIPI) was validated in advanced non-small cell lung cancer (NSCLC) patients treated with ICIs. The palliative prognostic (PaP) score without clinical prediction of survival (PaPwCPS) predicts early mortality probability in terminal cancer patients. Methods: We performed a retrospective study including 182 deceased advanced NSCLC patients, treated with single-agent ICI at our Institution. Two prognostic categories of high and low mortality risk were identified through ROC curve analysis for PaPwCPS and LIPI scores. Results: Most were >65 years of age (68.3%) and received second-line ICI (61.2%). A total of 29 (15.9%) and 131 (72.0%) patients died within 30 and 90 days from treatment start, respectively. A total of 81 patients (44.5%) received ICI during the last month of life. Baseline PaPwCPS and LIPI scores were assessable for 78 patients. The AUC of ROC curves was significantly increased for PaPwCPS as compared with LIPI score for both 30-day and 90-day mortality. A high PaPwCPS score was associated in multivariate analysis with increased 30-day (HR 2.69, p = 0.037) and 90-day (HR 4.01, p < 0.001) mortality risk. A high LIPI score was associated with increased 90-day mortality risk (p < 0.001). Conclusion: We found a tendency towards ICI prescription near the late stage of life. The PaPwCPS score was a reliable predictor of 30- and 90-day mortality

Characteristics, comorbidities and laboratory measures associated with disease severity and poor prognosis in young and elderly patients with COVID-19 admitted to medical wards in Emilia-Romagna region, Italy: a multicentre retrospective study

Background and Objectives. A relatively small number of studies have investigated the characteristics, comorbidities and laboratory measures associated with prognosis in patients with COVID-19, admitted to Internal Medicine Units (IMU) in Italy. Therefore, we performed a retrospective multicentre study to identify baseline features, predisposing to severe disease and poor outcomes, in adult individuals with SARS-CoV2 infection, hospitalized in 5 IMUs in the Emilia-Romagna region (Italy). Materials and Methods. We included 129 consecutive patients (male 75, median age 68 years) from 1st March 2020 to 31st October 2021. Patients' baseline characteristics, comorbidities, laboratory measures, and outcomes were collected. Results. At admission, the factors significantly associated with a higher risk of in-hospital mortality included: age (median 68 vs. 83 years in survived vs. dead patients, P=0.000), diabetes [Odds Ratio (OR) 4.00, P=0.016], chronic obstructive pulmonary disease (OR 4.60, P=0.022), cancer (OR 5.81, P=0.021), acute- (OR 9.88, P=0.000) and chronicrenal failure (OR 6.76, P=0.004). During the study period, 16 individuals died (12.4%), all over 70 years old. In deceased vs. non-deceased patients were detected: i) more elevated white blood cells and neutrophils-counts and lower lymphocytes count; ii) higher levels of total/direct bilirubin, creatinine, C-reactive-protein, lactate-dehydrogenase, ferritin, but only a slight Interleukin-6 increase; iii) a trend of lower vitamin D values. Conclusions. We proposed a new I index, a modified form of the Age-Adjusted Charlson Comorbidity Index, by considering pO(2)/FiO(2) ratio, to better characterize the severity of COVID-19. Furthermore, we critically discuss our results with the current assumption which considers COVID-19 as a pathological condition associated with cytokine storm

Extracting Information and Enhancing the Quality of Separation Data: A Review on Chemometrics-Assisted Analysis of Volatile, Soluble and Colloidal Samples

Instrument automation, technological advancements and improved computational power made separation science an extremely data-rich approach, requiring the use of statistical and data analysis tools that are able to optimize processes and combine multiple outputs. The use of chemometrics is growing, greatly improving the ability to extract meaningful information. Separation–multidetection generates multidimensional data, whose elaboration should not be left to the discretion of the operator. However, some applications or techniques still suffer from the lack of method optimization through DoE and downstream multivariate analysis, limiting their potential. This review aims at summarizing how chemometrics can assist analytical chemists in terms of data elaboration and method design, focusing on what can be achieved by applying chemometric approaches to separation science. Recent applications of chemometrics in separation analyses, in particular in gas, liquid and size-exclusion chromatography, together with field flow fractionation, will be detailed to visualize the state of the art of separation chemometrics, encompassing volatile, soluble and solid (colloidal) analytes. The samples considered will range from food chemistry and environmental chemistry to bio/pharmaceutical science