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In the past recent years, the expanding use of next-generation sequencing has led to the discovery of new cancer predisposition syndromes (CPSs), which are now known to be responsible for up to 10% of childhood cancers. As knowledge in the field is in constant evolution, except for a few “classic” CPSs, there is no consensus about when and how to perform germline genetic diagnostic studies in cancer-bearing children. Several clinical screening tools have been proposed to help identify the patients who carry higher risk, with heterogeneous strategies and results. After introducing the main clinical and molecular features of several CPSs predisposing to solid and hematological malignancies, we compare the available clinical evidence on CPS prevalence in pediatric cancer patients and on the most used decision-support tools in identifying the patients who could benefit from genetic counseling and/or direct genetic testing. This analysis highlighted that a personalized stepwise approach employing clinical screening tools followed by sequencing in high-risk patients might be a reasonable and cost-effective strategy in the care of children with cancer.

The scientific interest in Cannabis sativa L. analysis has been rapidly increasing in recent years, especially for what concerns cannabinoids, plant secondary metabolites which are well known for having many biological properties. High-performance liquid chromatography (HPLC) is frequently used for both the qualitative and quantitative analysis of cannabinoids in plant extracts from C. sativa and its derived products. Many studies have been focused on the main cannabinoids, such as ∆

Geographical origin and authenticity of food are topics of interest for both consumers and producers. Among the different indicators used for traceability studies, n(87Sr)/n(86Sr) isotopic ratio has provided excellent results. In this study, the production chains of the balsamic vinegars of the Modena province, the Aceto Balsamico Tradizionale di Modena (ABTM) and the industrially made Aceto Balsamico di Modena (ABM) were investigated by using the n(87Sr)/n(86Sr) indicator. The geographical origin of the starting raw materials for the ABM production was investigated, as well as the variability of ABM samples of different production years, namely 2009, 2010, 2011 and 2014. The results show no significant variability among ABM samples of different production years and highlight the possibility to distinguish this product from the ABTM. Furthermore, the investigated indicator also confirms an objective link of the food with its starting raw material and the territory of origin of the grapes, assessing the discriminating power of n(87Sr)/n(86Sr) ratio for geographical traceability studies.

The metal content in some samples of horse chestnut seeds (Aesculus hippocastanum) was monitored over time (years 2016&ndash, 2019) considering the two most common and representative Mediterranean varieties: the pure species (AHP, which gives white flowers) and a hybrid one (AHH, which gives pink flowers). The selected elemental composition of the samples was determined by applying the Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) technique. Several samples obtained from different preliminary treatments of the peeled seeds were examined, such as: (i) floury samples (wild-type) mineralized with the wet method, (ii) the ashes of both AHP and AHH varieties, (iii) the fraction of total inorganic soluble salts (TISS). Furthermore, the hydroalcoholic crude extracts (as a tincture) were obtained according to the official Pharmacopoeia methods, and the relevant results were compared with those of a commercial sample, an herbal product-food supplement of similar characteristics. The main characteristics of this research work underline that the two botanical varieties give different distinctive characters, due to the Fe content (80.05 vs. 1.42 mg/100 g d.s., for AHP and AHH wild-type flour samples, respectively), along with K, Ca, Mn, Ni and Cu, which are more abundant in the AHP samples. Furthermore, the Principal Component Analysis (PCA) was applied to the experimental dataset in order to classify and discriminate the samples, in relation to their similar botanical origin, but different for the color of the bloom. These results can be useful for the traceability of raw materials potentially intended for the production of auxiliary systems of pharmacological interest.

Wine identification is one of the most important aspects in the classification of wines and consumer protection. In particular, assuring wine authenticity is a crucial issue on which researchers are focusing on. This study aims to evaluate the feasibility of using chemical (B, Pb and Sr concentration) and isotopic compositions (δ11B, 20yPb/20xPb, 87Sr/86Sr and δ18O) of wine samples to trace their geographic origins. Different PDO Lambrusco wines coming from a confined area of northern Italy were analyzed and all the isotopic systematics were monitored by using a multi collector inductively coupled plasma mass spectrometer (MC-ICP/MS). The obtained results showed that boron isotope ratio measurements led to a satisfactory degree of accuracy and precision (measured value, n = 28, 11B/10B of NIST SRM 951a equal to 4.04343 ± 0.00178, (u = 2s) with a certified value of 4.04362 ± 0.00136 (u = 2s). Furthermore, in the present study, it has been possible to highlight significant differences among samples by means of one-way analysis of variance (ANOVA) and post hoc Tukey-Kramer test. Finally, Principal Component Analysis (PCA) was also carried out in order to evaluate to which extent the different PDOs can be distinguished from each other, taking into account the whole set of geographical origin descriptors. Although δ11B provided more sensitive information, the obtained results highlighted the important to consider the synergistic combination of all the investigated parameters to trace the different samples and the need to combine the obtained values with the same parameters evaluated in the soil, water and fertilizer as well., Graphical abstract Image 1, Highlights • Multi-parameter approach was used to assess wine geographical origin. • Validation of 11B/10B measurements was accomplished by multicollector ICP/MS. • 11B/10B, 87Sr/86Sr, 20yPb/20xPb, 18O/16O, and relative elemental content, were measured in Lambrusco PDO wines. • Anova, Tukey-Kramer and multivariate (PCA) analysis was employed to investigate differences and similarities among samples. • Geographic differentiation of PDO wines resulted to be based more on B and Sr variables than Pb and O ones.

This study summarizes the results obtained from a systematic and long-term project aimed at the development of tools to assess the provenance of food in the oenological sector. In particular, 87Sr/86Sr isotope ratios were measured on statistically representative set of soils, vine branches and wines sampled in the production district of Modena, worldwide known for the Lambrusco wines production. The obtained data were used to build strontium isotopic maps able to objectively support the Lambrusco PDO wines origin as well as other products of the Modena district. Finally, a strong relationship was found between the 87Sr/86Sr isotope ratios of soils and vine branches on a large scale, highlighting and confirming once more the idea that plants can also represent an optimal sampling device to support geographical traceability.

In the development of a geographical traceability model, it is necessary to understand if the value of the monitored indicators in a food is correlated to its origin or if it is also influenced by 'external factors' such as those coming from its production. In this study, a deeper investigation of the trend of direct geographical traceability indicators along the winemaking process of two traditional oenological products was carried out. Different processes were monitored, sampling each step of their production (grape juice, intermediate products and wine). The results related to the determinations of δ(18)O, (D/H)I, (D/H)II, δ(13)C, δ(15)N and (87)Sr/(86)Sr have been reported. Furthermore, correspondence with the isotopic values coming from the respective soil and vine-branch samples have been investigated as well, showing the optimal traceability power of the monitored geographical tracers.

The mercury (Hg) pollution of sediments is the main carrier of Hg for the biota and, subsequently, for the local fish consumers in Augusta Bay area (SE Sicily, Italy), a coastal marine system affected by relevant sewage from an important chlor-alkali factory. This relationship was revealed by the determination of Mass Dependent (MDF) and Mass Independent Fractionation (MIF) of Hg isotopes in sediment, fish and human hair samples. Sediments showed MDF but no MIF, while fish showed MIF, possibly due to photochemical reduction in the water column and depending on the feeding habitat of the species. Benthic and demersal fish exhibited MDF similar to that of sediments in which anthropogenic Hg was deposited, while pelagic organisms evidenced higher MDF and MIF due to photoreduction. Human hair showed high values of δ(202)Hg (offset of +2.2‰ with respect to the consumed fish) and Δ(199)Hg, both associated to fish consumption.

Semolina pasta represents one of the most important dishes in Italian cuisine worldwide. Italy is the leader in its production and, recently, the worldwide diffusion of its production has begun to grow tremendously. The perceived quality of a food product, such as pasta, is a key feature that allows a company to increase and maintain the competitive advantage of a specific brand. The overall flavor perception of the consumer, therefore, has become as important as other key quality factors such as texture and color; thus, the food industry needs to meet consumer expectations and needs the tools to objectively “measure” the quality of food products. Untargeted fingerprinting by means of coupling LC with high-resolution MS (HRMS) has been well received within the analytical community, and different studies exploiting this approach for the characterization of high-value food products have recently been reported in the literature. In the present work, a tentative application of the sensomics approach to cluster analysis of semolina pasta obtained using different production conditions was developed to objectively define target molecules that correlate with consumer overall liking of an industrial standard product. Principal component analysis of chemical and physical testing, GC-MS, LC-HRMS, and sensory data were performed with the aim of identifying the main parameters to discern similarities and differences among samples and clustering them according to these features. The correlation between analytical data and compounds related to sensory data was further investigated, and lastly, a partial least-squares regression model for the prediction of consumer overall liking was reported.

This study summarizes the results obtained from a systematic and long-term project aimed at the development of tools to assess the provenance of food in the oenological sector. In particular

The main goal of this study was to evaluate 87 Sr/ 86 Sr ratio in different matrices, namely soils, branches, and grape juices, of an oenological food chain in order to develop a robust analytical strategy able to link the investigated food to its territory of origin. The 87 Sr/ 86 Sr has been used as traceability marker and several aspects, affected its variability, i.e. geological features of the investigated area, the bio-available fraction of elements in the soils and the up-take of the plant, have been taken into account. Optimisation of an analytical procedure for the separation of Sr from its interferences and investigation of the analytical performances in terms of precision of used methodology have been carried out as well. This work highlighted a good match between the isotopic values monitored in the bio-available fraction of soils and their respective grape juices for almost all the investigated areas. The correlation with food satisfyingly improves when isotopic relative abundance values of branches vine are considered.

The present research is part of a project dealing with the development of analytical methodologies mainly based on primary indicators, such as isotopic ratios of stable and radiogenic elements, for the authenticity and geographical traceability of oenological food, typical of the Modena district. In particular, considering the objective of establishing a food-territory link by means of these analytical indicators, it is straightforward that the representativeness of sampling, for both food and soils, covers a primary role in the robustness of the traceability models. With this aim, the issue of selecting a set of representative, informative and different soil samples is tackled. In this case, the goal is not obtaining a set of soil samples uniformly spanning the territory, since the planning of a punctual sampling of the whole district of Modena is not feasible considering the total number of affordable samples, but rather choosing a representative set of vineyards where the soil samples can be located. Thus, all the vineyard-registered producers of the district of Modena were considered and different variables (geological features of the soils, winegrowing coverage, grape varieties, yearly production of the farms, etc.) were handled with Experimental Design (DoE) techniques, to simultaneously take into account the different information in order to achieve a sustainable and rational site sampling. In particular, D-optimal onion design was chosen since it is widely used for mapping and planning purposes, hence it permits to achieve the maximum coverage and uniformity of the selected samples in the whole domain. An efficient mapping of the geographical region has been obtained ensuring coverage of farms characterized by the main grape production and insisting on soils with different geological features.

The p38 mitogen-activated protein kinase is activated by environmental stress and cytokines and plays a role in transcriptional regulation and inflammatory responses. Factors influencing the activity and selectivity of the p38α mitogen-activated protein kinase inhibitors have been investigated in this paper by inspecting the binding orientation and the possible residue-inhibitor interactions in the binding site. The binding pattern of a set of 45 different inhibitors against p38α mitogen-activated protein kinase was studied through Molecular Dynamic Simulations of the protein-inhibitor complexes. Further, Partial Least Squares regression was used to develop a Quantitative Structure Activity Relationship model to predict the binding affinities of ligands. The selected model successfully predicted the test set with a Root Mean Square Error of Prediction of 1.36. The regression coefficients and the Variable Importance in Projection plots highlighted the residue-inhibitor interactions which exhibited the largest absolute effect on the ligand binding, such as the van der Waals interaction with LYS50, ILE81, ASP165; electrostatic interactions with SER29, LEU164; hydrogen bonds with MET106; and total energy interaction with SER29 and LEU83.

The results obtained by means of Molecular Dynamics simulations and Multiway Explorative Data Analysis on ADAMTS4, ADAMTS5 and MMP13 complexed with Marimastat and two cis-1(S)2(R)-amino-2-indanol ligands suggest that determinant characteristics for ligand binding and selectivity among the three enzymes are to be found in the different protein conformation flexibility. Moreover, the role of the TS-domain in the inhibitor binding to ADAMTS enzymes has been investigated for the first time in this work. The results obtained suggest that the influence of the TS-domain on the S1' loop fluctuations of ADAMTS4 and ADAMTS5 could be exploited for the design of therapeutics for chronic osteoarthritis diseases. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Thermoplastic polymers can be viewed as a dynamic framework in which additives allocation is strongly dependent on the system' chemistry. Considering the complexity of the distribution phenomena that may occur in plastics obtained by blending polymeric resins with different additives, this work constitutes an attempt to the description of the behavior of PVC heat stabilizers (calcium and zinc carboxylates), as regard temperature and time. Thanks to the Fourier Transform Infrared Spectroscopy, it is possible to observe a first decreasing trend of the additives related IR-bands as a function of the increasing temperature and the higher the temperature the faster the decrease of the heat stabilizers intensities bands is, with respect to time. Additives distribution in not sterilized, sterilized, aged not sterilized and aged sterilized materials have been investigated to determine their behavior with respect to temperature, from 30 to 120°C, and time. A simulated supplementary aging process equivalent to 9 months aging was carried out on aged not sterilized and aged sterilized materials to gain more data on the transport/reaction phenomena these additives in the plastic material. Experimental evidences allow hypothesizing that reaction and redistribution phenomena probably concur to determine the additives allocation in PVC as a function of temperature and time.

The use of a Dynamic Headspace System (DHS) device combined with a Thermal Desorption Unit (TDU) interfaced to a Gas Chromatography/Mass Spectrometry (GC/MS) system is proposed for the determination of furfurals in oenological products. An experimental design protocol has been employed for the optimization of the instrumental settings concerning DHS and TDU extraction and desorption steps. It has been possible to individuate the following optimized conditions: incubation temperature 40 °C, purge volume 800 mL, dry volume 1500 mL, TDU hold time 5 min and incubation time 10 min. The performance of two different SPE sorbents, namely Tenax TA and Tenax GR used for the furfurals trapping, was investigated too. The developed DHS sampling procedure showed good reproducibility values with a RSD% lower than 10% for all the monitored species. The optimized experimental settings have been used to determine furfurals in several vinegar samples obtained by traditional procedure starting from cooked grape musts, i.e. in Aceto Balsamico Tradizionale di Modena (ABTM). In fact, the control of these species is extremely important for quality and safety issues.

In the literature there are only few papers concerned with classification methods for multi-way arrays. The most common procedure, by far, is to unfold the multi-way data array into an ordinary matrix and then to apply the traditional multivariate tools for classification. As opposed to unfolding the data several possibilities exist for building classification models more directly based on the multi-way structure of the data. As an example, multi-way partial least squares discriminant analysis has been used as a supervised classification method, another alternative that has been investigated is to perform classification using Fisher's LDA or SIMCA on the score matrix from e.g. a PARAFAC or a Tucker model. Despite a few attempts of applying such multi-way classification approaches, no-one has looked into how such models are best built and implemented. In this work, the SIMCA method is extended to three-way arrays. Included in this work is also actual code that will work on general multi-way arrays rather than just three-way arrays. In analogy with two-way SIMCA, a decomposition model is separately built for the multi-way data for each class, using multi-way decomposition method such as PARAFAC or Tucker3. In the choice of the best class dimensionality, i.e. number of latent factors, both the results of cross-validation but mainly the sensitivity/specificity values are evaluated. In order to estimate the class limits for each class model, orthogonal and score distances are considered, and different statistics are implemented and tested to set confidence limits for these two parameters. Classification performance using different definitions of class boundaries and classification rules, including the use of cross-validated residuals and scores is compared. The proposed N-SIMCA methodology and code, besides simulated data sets of varying dimensionality, has been tested on two case studies, concerning food authentication tasks for typical food products.

This work can be seen as an attempt to develop an analytical procedure in the context of quality control and authenticity assessment of typical food. To this aim, head-space mass spectrometry (HS-MS) coupled with multivariate data analysis, is proposed as a fast technique for furnishing a clear visualization and a suitable interpretation of the ageing process of 'Aceto Balsamico Tradizionale di Modena' (ABTM) and, for classifying products of different age. Considering the complexity of this food matrix, due to its traditional making procedure, the obtained instrumental data have first been analysed by parallel factor analysis (PARAFAC), an extension of principal component analysis to higher order arrays, in order to visualise the 'natural' grouping of vinegar samples and to inspect producers similarity/dissimilarity. On the basis of the PARAFAC results a reasonable class partition with respect to ageing was accomplished and both linear discriminant analysis (LDA) and soft independent modelling of class analogy (SIMCA) were applied as classification tools. Furthermore, it has been shown that discrimination on age basis can be improved by using feature selection in the wavelet domain through WPTER algorithm.

Background: Polychromatic flow cytometry (PFC) allows the simultaneous determination of multiple antigens in the same cell, resulting in the generation of a high number of subsets. As a consequence, data analysis is the main difficulty with this technology. Here we show the use of cluster analysis (CA) and principal component analyses (PCA) to simplify multicolor data visualization and to allow subjects' classification. Methods: By eight-colour cytofluorimetric analysis, we investigated the T cell compartment in donors of different age (young, middle-aged, and centenarians). T cell subsets were identified by combining positive and negative expression of antigens. The resulting data set was organized into a matrix and subjected to CA and PCA. Results: CA clustered people of different ages on the basis of cytofluorimetric profile. PCA of the cellular subsets identified centenarians within a different cluster from young donors, while middle-aged donors were scattered between these groups. These approaches identified T cell phenotypes that changed with increasing age. In young donors, memory T cell subsets tended to be CD127+ and CD95− whereas CD127−, CD95+ phenotypes were found at higher frequencies in people with advanced age. Conclusions: Our data suggest the use of bioinformatic approaches to analyze large data-sets generated by PFC and to obtain the rapid identification of key populations that best characterize a group of subjects. © 2007 International Society for Analytical Cytology

Geographical origin and authenticity of food are topics of interest for both consumers and producers. Among the different indicators used for traceability studies, (87)Sr/(86)Sr isotopic ratio has provided excellent results. In this study, two analytical approaches for wine sample pre-treatment, microwave and low temperature mineralisation, were investigated to develop accurate and precise analytical method for (87)Sr/(86)Sr determination. The two procedures led to comparable results (paired t-test, with t

Aceto Balsamico Tradizionale of Modena (ABTM) is a typical product (PDO denomination) of the province of Modena produced by cooked grape must which undergoes a long ageing period (at least 12 years) in series of wooden casks (batterie). The study of the transformations of this product during ageing is extremely relevant in order to control the authenticity of ABTM towards succedaneous products and mislabelling of age. This paper presents the results of the investigation of sugars and fixed organic acids in ABTM samples of different ages, coming from different batterie. The analytes were simultaneously determined by a gas chromatographic method optimised for this peculiar matrix. The method shows good separation and resolution of the investigated chemical species and allows their determination in the concentration ranges reported in brackets: malic (7.6-15.5 g kg(-1)), tartaric (4.0-9.7 g kg(-1)), citric (0.6-1.5 g kg(-1)) and succinic (0.36-0.62 g kg(-1)) acid and glucose (153-294 g kg(-1)), fructose (131-279 g kg(-1)), xylose (011-0.39 g kg(-1)), ribose (0.078-0.429 g kg(-1)), rhamnose (0.061-0.195 g kg(-1)), galactose (0.136-0.388 g kg(-1)), mannose (0.41-1.46 g kg(-1)), arabinose (0.33-1.00 g kg(-1)) and sucrose (0.46-6.84 g kg(-1)), with mean associated errors ranging from 5 to 19% depending on the analytes. Moreover, the recovery values are always satisfactory, being close to one for most of the analytes. Furthermore, in order to assess the degree of variability of the different analytes content with vinegar ageing and the similarity/dissimilarity among series of casks a three-way data analysis method (Tucker3) is proposed. The chemometric technique applied on the data set shows differences between the samples on the bases of their different ageing period, and between the batterie, which traditionally have an own peculiar production procedure.

A novel feature selection and classification algorithm (WPTER) based on the wavelet packet transform has been applied to the discrimination of balsamic vinegars, namely the typical made “Aceto Balsamico Tradizionale di Modena”, which gained the PDO denomination on the year 2000, from the industrial made “Aceto Balsamico” of the Modena district. All the samples have been characterized on the basis of the gas chromatographic (GC) profiles of the headspace (HS) volatile fraction, sampled by solid phase microextraction (SPME). Good discrimination between the two categories has been obtained both for the calibration and for the test set samples. GC-MS analysis allowed the identification of the peaks lying in the chromatographic regions selected by the algorithm, giving useful suggestions about the compounds which may be worth of further investigation in order to rationalize the chemical transformation occurring during the traditional making procedure. The proposed methodology seems very promising in authentication tasks, coupling some of the advantages of blind analysis with the possibility of acquiring chemical information, and giving, at the same time, very parsimonious multivariate classification models, which can be particularly suitable for data storage and handling.

Nowadays the necessity to reveal the hidden information from complex data sets is increasing due to the development of high-throughput instrumentation. The possibility to jointly analyze data sets arising from different sources (e.g. different analytical determinations/platforms) allows capturing the latent information that would not be extracted by the individual analysis of each block of data. Several approaches are proposed in the literature and are generally referred to as data fusion approaches. In this work a mid level data fusion is proposed for the characterization of three varieties ( Salamino di Santa Croce , Grasparossa di Castelvetro , Sorbara ) of Lambrusco wine, a typical PDO wine of the district of Modena (Italy). Wine samples of the three different varieties were analyzed by means of 1 H-NMR spectroscopy, Emission-Excitation Fluorescence Spectroscopy and HPLC-DAD of the phenolic compounds. Since the analytical outputs are characterized by different dimensionalities (matrix and tensor), several multivariate analyses were applied (PCA, PARAFAC, MCR-ALS) in order to extract and merge, in a hierarchical way, the information present in each data set. The results showed that this approach was able to well characterize Lambrusco samples giving also the possibility to understand the correlation between the sources of information arising from the three analytical techniques.

Multilinear PLS (NPLS) and its discriminant version (NPLS-DA) are very diffuse tools to model multi-way data arrays. Analysis of NPLS weights and NPLS regression coefficients allows data patterns, feature correlation and covariance structure to be depicted. In this study we propose an extension of the Variable Importance in Projection (VIP) parameter to multi-way arrays in order to highlight the most relevant features to predict the studied dependent properties either for interpretative purposes or to operate feature selection. The VIPs are implemented for each mode of the data array and in the case of multivariate dependent responses considering both the cases of expressing VIP with respect to each single y-variable and of taking into account all y-variables altogether. Three different applications to real data are presented: i) NPLS has been used to model the properties of bread loaves from near infrared spectra of dough, acquired at different leavening times, and corresponding to different flour formulations. VIP values were used to assess the spectral regions mainly involved in determining flour performance; ii) assessing the authenticity of extra virgin olive oils by NPLS-DA elaboration of gas chromatography/mass spectrometry data (GC–MS). VIP values were used to assess both GC and MS discriminant features; iii) NPLS analysis of a fMRI-BOLD experiment based on a pain paradigm of acute prolonged pain in healthy volunteers, in order to reproduce efficiently the corresponding psychophysical pain profiles. VIP values were used to identify the brain regions mainly involved in determining the pain intensity profile.

In the last decades, mankind has become totally aware about the importance of food quality: nowadays authentication and traceability are words of general use. Food authentication verifies how much a food is in accordance with its label description and law and it could be considered a further guarantee for the quality and safety of a foodstuff. The traceability of food could be considered an essential element in ensuring safety and high quality of food. The synergistic use of instrumental analytical techniques and chemometrics represents a promising way to obtain trustworthy results in the development of authenticity and traceability models. This chapter deals with the potentialities of chemometrics tools in resolving some real issues related to food traceability and authenticity. Particular attention will be paid to the use of some exploratory, classification, and discrimination techniques. In the first part of this chapter, a briefly description of European regulations ( Authenticity and Traceability: the European Union point of view ), and traceability and authenticity markers ( Authenticity and Traceability: a scientific point of view ) is reported. The second part is split into two sections: namely Food Authenticity and Food Traceability applications , where the main features and advantages of some chemometrics approaches are presented.

In the food research and production field, system complexity is increasing and several new challenges are emerging every day. This implies an urgent necessity to extract information and obtain models capable of inferring the underlying relationships that link all the variability sources which characterize food or its production process (e.g. compositional profile, processing conditions) to very general end properties of foodstuff, such as the healthiness, the consumer perception, the link to a territory and the effect of the production chain itself on food. This makes a ‘deductive’ theory-driven research approach inefficient, as it is often difficult to formulate hypotheses. Explorative multivariate data analysis methods, together with the most recent analytical instrumentation, offer the possibility to come back to an ‘inductive’ data-driven attitude with a minimum of a priori hypotheses, instead helping in formulating new ones from the direct observation of data. The aim of this chapter is to offer the reader an overview of the most significant tools that can be used in a preliminary, exploratory phase, ranging from the most classical descriptive statistics methods, to multivariate analysis methods, with particular attention to projection methods. For all techniques, examples are given so that the main advantage of these techniques, which is a direct, graphical representation of data and their characteristics, can be immediately experienced by the reader.

Lambrusco is a Protected Designation of Origin (PDO) red wine of Modena (Italy) produced according to the production regulation (Decreto Ministeriale (DM) July 27, 2009; GU no. 184-187-188, 13/08/2009). Here the use of (1)H NMR spectroscopy as molecular fingerprints of several PDO Lambrusco wines was proposed to serve as indicators of authenticity and quality control. Application of partial least squares discriminant analysis (PLS-DA) revealed a good varietal discrimination by analyzing the low-frequency spectral region. This model explains 68.8% of the variance for the Y vector (classification factor: varietal source). In particular, the signals of 2,3-butanediol, lactic, succinic and malic acids, and threonine were found to be the most statistically significant variables in the model. These findings seem to be very promising in the attempt to extend the study to geographical discrimination.

Aim of this work is to assess the potentialities of the X-ray powder diffraction technique as fingerprinting technique, i.e. as a preliminary tool to assess soil samples variability, in terms of geochemical features, in the context of food geographical traceability. A correct approach to sampling procedure is always a critical issue in scientific investigation. In particular, in food geographical traceability studies, where the cause-effect relations between the soil of origin and the final foodstuff is sought, a representative sampling of the territory under investigation is certainly an imperative. This research concerns a pilot study to investigate the field homogeneity with respect to both field extension and sampling depth, taking also into account the seasonal variability. Four Lambrusco production sites of the Modena district were considered. The X-Ray diffraction spectra, collected on the powder of each soil sample, were treated as fingerprint profiles to be deciphered by multivariate and multi-way data analysis, namely PCA and PARAFAC. The differentiation pattern observed in soil samples, as obtained by this fast and non-destructive analytical approach, well matches with the results obtained by characterization with other costly analytical techniques, such as ICP/MS, GFAAS, FAAS, etc. Thus, the proposed approach furnishes a rational basis to reduce the number of soil samples to be collected for further analytical characterization, i.e. metals content, isotopic ratio of radiogenic element, etc., while maintaining an exhaustive description of the investigated production areas.

Publisher Summary This chapter appraises the seeds of horse chestnuts (Aesculus hippocastanum [AH]) and their derived products. Escin, the major bioactive principle in AH seeds, has shown satisfactory evidence of clinically significant activity in the treatment of chronic venous insufficiency, hemorrhoids, postoperative edema, and mammary induration. There is some evidence that various escin molecules, such as saponins and sapogenins, show beneficial effects when administered at the right concentration, exhibiting an ethanol absorption inhibitory effect and hypoglycemic activity in the oral glucose tolerance test in vivo. Horse chestnut extract has a higher antioxidant activity than vitamin E, showing one of the highest “active-oxygen” scavenging abilities compared to other natural products. β-Escin from AH extracts was also tested to evaluate the chemopreventive efficacy of its dietary intake on azoxymethane-induced colonic aberrant crypt foci. The main adverse effects of escins in humans are due to their hemolytic activity. Research efforts in this field are devoted to improving the selectivity for aberrant red corpuscles, promoting the β-escin fraction as a useful candidate agent for exploring new potential antileukemic drugs. Fresh or naturally desiccated seeds are usually treated by long leaching with water or wooden ashes to remove harshness and bitterness. These treatments cause a variation in the molecular structures of escin fractions, reducing the toxicity but maintaining their nutraceutical potential and anti-obesity effects. Alternatively, the slow roasting of nuts makes the escins harmless and the seeds edible. The claimed toxicity of these extracts makes them natural antibacterials, antimicrobials, antivirals, and antifungals, to some extent, that also act as environmentally biocompatible phytotherapeutics.