A Preliminary Color Study of Different Basil-Based Semi-Finished Products during Their Storage

open6: Basil-based semi-finished products, which are mainly used as an intermediate to produce the typical pesto sauce, are prepared and exported all over the world. Color is a fundamental organoleptic requirement for the acceptability of these semi-finished products by the manufacturers of the pesto sauce. Some alternative formulations, which adjust the typical industrial recipe by both changing the preservative agent (ascorbic acid, citric acid, or a mixture of both) and introducing a preliminary thermic treatment (blast chilling), were evaluated. In this work, a fast and non-destructive spectrophotometric analysis, to monitor the color variations in these food products during their shelf-life, was proposed. The raw diffuse reflectance spectra (380–900 nm) obtained by a UV–visible spectrophotometer, endowed with an integrating sphere, together with the CIELab parameters (L*, a*, b*) automatically obtained from these, were considered, and elaborated using multivariate statistical analysis (principal component analysis). From this preliminary study, blast chilling, together with the use of ascorbic acid, proved to be the best solution to better preserve the color of these products during their shelf-life.openTurrini, Federica; Farinini, Emanuele; Leardi, Riccardo; Grasso, Federica; Orlandi, Valentina; Boggia, Raffaella;Turrini, Federica; Farinini, Emanuele; Leardi, Riccardo; Grasso, Federica; Orlandi, Valentina; Boggia, Raffaell

Intra-source provenance study on Monte Arci (Sardinia) obsidian by pXRF: Role of the data acquisition and analysis tools

In this work, a detailed study of Monte Arci obsidian sub-sources using the increasingly accessible technique of pXRF is presented based upon a large dataset of 68 geological samples, for the development of X-ray fluorescence-based analytical standardless procedure. In addition, a non-conventional (for obsidian provenance study) direct application of multivariate analysis on XRF spectra (continuous variables), rather than absolute concentrations or intensity ratios (discrete variables) is proposed. Results from different softwares and data analysis approaches (bi-/trivariate versus multivariate) were compared. In a blind test, the bi-/trivariate approach led to the correct assignment for the main SA, SB, and SC sub-sources, taking into account averaged values of intensity ratios with their standard deviation obtained from three independent measurements. A high intra-source variability for the SB subgroups was detected (almost 13% of error in the assignment, 9 samples out of 68). A non-conventional application of multivariate analysis was carried out directly on the XRF spectra and correct assignments were obtained for SA, SB1, SC groups, while 71% of the SB2 samples were correctly identified. The non-destructive analysis on 14 archaeological samples from Su Carroppu (Carbonia, southwestern Sardinia) rockshelter and from the Middle Neolithic (MN) 422 structure of the open-air dwelling site at Cuccuru is Arrius (Cabras, central-western Sardinia) permitted to test the method and hypothesise their provenance. The comparison with visual characterization or previous analyses by Particle Induced X-Ray Emission (PIXE) permitted to verify the correct provenance assignment of all artifacts for the bi-/trivariate method, and for 12/14 samples in the case of the multivariate one. The standardless analytical approach proposed in this work can represent a more general method exploitable for other obsidian sources, other glassy materials, besides other materials of archaeological interest

Use of Experimental Design and Multivariate Analysis for solving industrial problems

Over the past few decades, data analytics has gained significant importance for various professional roles within industries and academic research. In detail, in the field of chemistry takes place chemometrics, a branch of chemistry, which has multiple purposes, including enabling researchers to gain valuable insights and knowledge about systems and processes across a wide range of levels of complexity. By the use deep-rooted mathematical and statistical tools chemometrics allows to solve chemical problems. While many chemometric methods have been well-established in chemistry, often some scientists, both in academia and industry, either do not employ these methods or use them with a limited understanding of their underlying principles and recognized statistical properties, known as a black-box approach. The present thesis aims to fill this knowledge gap by demonstrating different approaches applied at different stages of the data analysis pipeline. It highlights the crucial aspect of selecting the suitable and interpretable method, regardless of the case study's complexity, with the primary focus on problems resolution. The studies presented in this thesis include a wide range of chemical cases, conducted in collaboration with international research groups and industries. To achieve this, an extensive exploitation of chemometric tools was employed in the field of Experimental Design or Design of Experiments (DoE) and Multivariate Analysis. DoE facilitated the systematic exploration of the experimental domain, allowing to extract high quality information by a series of planned experiments and therefore to build a mathematical model for quantifying the effect of various factors affecting the system and, when necessary, enabling to make predictions. On the other hand, Multivariate Analysis was employed to extract meaningful insights that enable pattern recognition within complex, high-dimensional data. These two domains of chemometrics are deeply interconnected over the manuscript. Chemometric tools are imperative for instrumental analytical techniques that generate a set of numbers instead of just a single value. This requirement applies to various techniques such as chromatographic or spectroscopic, for instance, vibrational spectroscopy (mid-infrared (MIR), near-infrared (NIR), and Raman), ultraviolet visible spectroscopy (UV-vis), nuclear magnetic resonance (NMR), X-ray spectroscopy, etc. In these cases, the analytical approach is not always focused on identifying or quantifying specific chemicals in a sample. Instead, it aims to provide an overall characterization of the sample, like a unique fingerprint. These a-specific techniques have several advantages compared to traditional methods. They are usually faster, cheaper, require minimal or no sample preparation, do not destroy the sample, do not necessarily require highly high-skilled personnel, can be implemented for real-time or online analysis, and are easy to automate and transport. Being a-specific techniques, the use of chemometrics is well established with methods such as multivariate calibration, classification or multivariate class-modeling. However, there are many other characterization techniques such as granulometry (PSD), rheology, calorimetry, etc., which generate an "analytical profile" and multivariate analysis in these cases is often overlooked. From this profile, so-called descriptors are regularly used. However, these descriptors offer only very limited information without providing global and unequivocal information. A further aim of this thesis is to exploit multivariate analysis to effectively interpret all the techniques and therefore to develop rapid and effective methods for their interpretation. Another important aspect of this thesis is the exploitation of multi-block analysis in production processes. Thanks to the technological progress and the growing availability of powerful tools, it is now possible to gather a vast amount of data, ranging from process variables (temperatures, flow rates, etc.) to determinations made through various analytical techniques mentioned earlier. The aim is to analyze this extensive data using data-fusion approaches and uncover the relationships between different blocks of data, eventually constructing predictive models. Techniques such as Principal Properties or innovative multi-block analysis methods like SO-PLS are employed for this purpose

Chestnut Episperm as a Promising Natural Source of Phenolics from Agri-Food Processing by-Products: Optimisation of a Sustainable Extraction Protocol by Ultrasounds

Chestnut processing has increasingly grown in recent years. All the processes involved in the chestnut supply chain are characterized by the production of high levels of by-products that cause several environmental and disposal issues. The Castanea spp. fruit production is related to a high number of chestnut episperm. This underutilized agricultural by-product may be evaluated as a good resource for the extraction of health-promoting natural molecules, such as phenolics. This preliminary study aimed to develop and optimize, using a multivariate statistical approach, a sustainable protocol for the ultrasound-assisted extraction (UAE) of the main phenolics from chestnut episperm (cv Marsol, C. sativa × C. crenata). A design of experiment (DoE) approach was employed. This approach focused on the two quantitative UAE process factors: the extraction time (X1), within a timeframe ranging from 10 to 30 min, and the sample-to-solvent (w/v) ratio (X2), ranging from 1/30 to 1/10. These variables were investigated to determine their impact on phenol extraction yield. Exploratory analysis, in particular principal component analysis (PCA) and multiple linear regression (MLR), were carried out on the studied responses. The phenolic characterization of ten different extracts was also performed using high-performance liquid chromatography (HPLC), both to define the levels of specific phenolics selected for their health-promoting properties and to evaluate some important features, such as the total antioxidant capacity. The values of total polyphenolic content (TPC) obtained in the different experiments ranged between 97 (extract 4) and 142 (extract 6) mg GAE/g of dried weight (DW). Moreover, results from the ferric reducing antioxidant power (FRAP) test confirmed the high TPC values, highlighting that all the ultrasound extracts contained excellent levels of molecules with good antioxidant properties. In particular, extracts 2 and 3 showed the highest AOC values (about 490–505 mmol Fe2+/Kg of dried weight). The proposed optimized protocol allowed for obtaining formulations characterized by high levels of tannins, phenolic acids, and catechins. Indeed, episperm extracts contained high levels of chlorogenic acid (15–25 mg/100 g DW), ferulic acid (80–120 mg/100 g DW), castalagin (20–80 mg/100 g DW), and vescalagin (40–75 mg/100 g). Finally, in this research study, the potential of chestnut episperm as a source of polyphenolic molecules to be extracted by green technologies and used in several food and/or pharmaceutical applications was evaluated to valorize a sustainable reuse strategy of agri-food processing by-products, also reducing the environmental impact of this waste derived from chestnut processing

Multi-Elemental Analysis as a Tool to Ascertain the Safety and the Origin of Beehive Products: Development, Validation, and Application of an ICP-MS Method on Four Unifloral Honeys Produced in Sardinia, Italy

Despite unifloral honeys from Sardinia, Italy, being appreciated worldwide for their peculiar organoleptic features, their elemental signature has only partly been investigated. Hence, the principal aim of this study was to measure the concentration of trace and toxic elements (i.e., Ag, As, Ba, Be, Bi, Cd, Co, Cr, Cu, Fe, Hg, Li, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Te, Tl, V, and Zn) in four unifloral honeys produced in Sardinia. For this purpose, an original ICP-MS method was developed, fully validated, and applied on unifloral honeys from asphodel, eucalyptus, strawberry tree, and thistle. Particular attention was paid to the method’s development: factorial design was applied for the optimization of the acid microwave digestion, whereas the instrumental parameters were tuned to minimize the polyatomic interferences. Most of the analytes’ concentration ranged between the relevant LoDs and few mg kg−1, while toxic elements were present in negligible amounts. The elemental signatures of asphodel and thistle honeys were measured for the first time, whereas those of eucalyptus and strawberry tree honeys suggested a geographical differentiation if compared with the literature. Chemometric analysis allowed for the botanical discrimination of honeys through their elemental signature, whereas linear discriminant analysis provided an accuracy level of 87.1%

Potential Role of miRNAs in the Acquisition of Chemoresistance in Neuroblastoma

Neuroblastoma (NB) accounts for about 8–10% of pediatric cancers, and the main causes of death are the presence of metastases and the acquisition of chemoresistance. Metastatic NB is characterized by MYCN amplification that correlates with changes in the expression of miRNAs, which are small non-coding RNA sequences, playing a crucial role in NB development and chemoresistance. In the present study, miRNA expression was analyzed in two human MYCN-amplified NB cell lines, one sensitive (HTLA-230) and one resistant to Etoposide (ER-HTLA), by microarray and RT-qPCR techniques. These analyses showed that miRNA-15a, -16-1, -19b, -218, and -338 were down-regulated in ER-HTLA cells. In order to validate the presence of this down-regulation in vivo, the expression of these miRNAs was analyzed in primary tumors, metastases, and bone marrow of therapy responder and non-responder pediatric patients. Principal component analysis data showed that the expression of miRNA-19b, -218, and -338 influenced metastases, and that the expression levels of all miRNAs analyzed were higher in therapy responders in respect to non-responders. Collectively, these findings suggest that these miRNAs might be involved in the regulation of the drug response, and could be employed for therapeutic purposes

PKCα Inhibition as a Strategy to Sensitize Neuroblastoma Stem Cells to Etoposide by Stimulating Ferroptosis

Cancer stem cells (CSCs) are a limited cell population inside a tumor bulk characterized by high levels of glutathione (GSH), the most important antioxidant thiol of which cysteine is the limiting amino acid for GSH biosynthesis. In fact, CSCs over-express xCT, a cystine transporter stabilized on cell membrane through interaction with CD44, a stemness marker whose expression is modulated by protein kinase Cα (PKCα). Since many chemotherapeutic drugs, such as Etoposide, exert their cytotoxic action by increasing reactive oxygen species (ROS) production, the presence of high antioxidant defenses confers to CSCs a crucial role in chemoresistance. In this study, Etoposide-sensitive and -resistant neuroblastoma CSCs were chronically treated with Etoposide, given alone or in combination with Sulfasalazine (SSZ) or with an inhibitor of PKCα (C2-4), which target xCT directly or indirectly, respectively. Both combined approaches are able to sensitize CSCs to Etoposide by decreasing intracellular GSH levels, inducing a metabolic switch from OXPHOS to aerobic glycolysis, down-regulating glutathione-peroxidase-4 activity and stimulating lipid peroxidation, thus leading to ferroptosis. Our results suggest, for the first time, that PKCα inhibition inducing ferroptosis might be a useful strategy with which to fight CSC chemoresistance

Table_1_PLX4032 resistance of patient-derived melanoma cells: crucial role of oxidative metabolism.docx

BackgroundMalignant melanoma is the most lethal form of skin cancer which shows BRAF mutation in 50% of patients. In this context, the identification of BRAFV600E mutation led to the development of specific inhibitors like PLX4032. Nevertheless, although its initial success, its clinical efficacy is reduced after six-months of therapy leading to cancer relapse due to the onset of drug resistance. Therefore, investigating the mechanisms underlying PLX4032 resistance is fundamental to improve therapy efficacy. In this context, several models of PLX4032 resistance have been developed, but the discrepancy between in vitro and in vivo results often limits their clinical translation.MethodsThe herein reported model has been realized by treating with PLX4032, for six months, patient-derived BRAF-mutated melanoma cells in order to obtain a reliable model of acquired PLX4032 resistance that could be predictive of patient’s treatment responses. Metabolic analyses were performed by evaluating glucose consumption, ATP synthesis, oxygen consumption rate, P/O ratio, ATP/AMP ratio, lactate release, lactate dehydrogenase activity, NAD+/NADH ratio and pyruvate dehydrogenase activity in parental and drug resistant melanoma cells. The intracellular oxidative state was analyzed in terms of reactive oxygen species production, glutathione levels and NADPH/NADP+ ratio. In addition, a principal component analysis was conducted in order to identify the variables responsible for the acquisition of targeted therapy resistance.ResultsCollectively, our results demonstrate, for the first time in patient-derived melanoma cells, that the rewiring of oxidative phosphorylation and the maintenance of pyruvate dehydrogenase activity and of high glutathione levels contribute to trigger the onset of PLX4032 resistance.ConclusionTherefore, it is possible to hypothesize that inhibitors of glutathione biosynthesis and/or pyruvate dehydrogenase activity could be used in combination with PLX4032 to overcome drug resistance of BRAF-mutated melanoma patients. However, the identification of new adjuvant targets related to drug-induced metabolic reprogramming could be crucial to counteract the failure of targeted therapy in metastatic melanoma.</p