Ricerc@Sapienza

GFD remains the only "therapy" currently available, resulting in a global improvement in symptoms. Antihistamines and/or corticosteroids can be used only for brief periods, in order to reduce the cutaneous symptomatology, together with emollient creams. Immunotherapy may be also as a valid therapeutic option.

Neural network compression has recently received much attention due to the computational requirements of modern deep models. In this work, our objective is to transfer knowledge from a deep and accurate model to a smaller one.

An HS-SPME/GC-MS procedure was optimised in order to characterize the aromatic fingerprint of 82 spirit drinks, belonging to Grappa GI samples and other distillates. “Grappa” is a geographical indication (GI) allowed by EC Regulation No 110/2008 only for Italian-made grape marc spirit. Multivariate chemometric techniques were applied to the collected chromatographic profiles in order to classify the samples on the basis of chemical information provided by their volatile composition data.

An authentication study based on two different instrumental techniques, headspace solid-phase microextraction/gas chromatography-mass spectrometry and mid-/near-infrared spectroscopies, was performed with a set of 75 samples representative of traditional Italian spirit “Grappa Geographical Indication (GI)” and other Italian spirits obtained by distillation of fruits or cereals. Chemometric classification methods were applied to the collected fingerprint profiles to build models which could allow differentiating GI Grappa from other distillates produced in the same geographical areas.

In this chapter, a survey of the chemometric (data analytical) methods most used for the characterization of plant varieties and cultivars based on spectroscopic measurements is presented. After an introductory section, illustrating the basics of data representation, the main tools for exploratory (descriptive) data analysis and predictive modeling are discussed. In particular, how to predict quantitative responses by multivariate calibration methods and how to assess qualitative attributes by means of classification techniques are addressed.

Classification methods, i.e., the chemometric strategies for predicting a qualitative response, find many applications in the omic sciences, where often data are collected in order to categorize individuals (e.g. according to whether they were treated or administered a placebo or, for instance, depending on if they were healthy or ill). After a brief discussion of the differences between discriminant and modelling approaches, some of the techniques most commonly used in the omic fields are illustrated in greater detail.

Spectroscopy is widely used to characterize pharmaceutical products or processes, especially due to its desirable characteristics of being rapid, cheap, non-invasive/non-destructive and applicable both off-line and in-/at-/on-line. Spectroscopic techniques produce profiles containing a high amount of information, which can profitably be exploited through the use of multivariate mathematic and statistic (chemometric) techniques.

A chromatographic procedure (HPLC-DAD) using a relatively rapid gradient has been combined with a chemometric curve deconvolution method, multivariate curve resolution-alternating least squares (MCR-ALS), in order to quantify caffeine and chlorogenic acid in green coffee beans.

Common hazelnuts are widely present in human diet all over the world, and their beneficial effects on the health have been extensively investigated and demonstrated. Different in-depth researches have highlighted that the harvesting area can define small variations in the chemical composition of the fruits, affecting their quality. As a consequence, it has become relevant to develop methodologies which would allow authenticating and tracing hazelnuts.

Alteration of glycosylation has been observed in several diseases, such as cancer and neurodegenerative disorders. The study of changes in glycosylation could lead to a better understanding of mechanisms underlying these diseases and to the identification of new biomarkers. In this work the N-linked glycosylation of five target proteins in cerebrospinal fluid (CSF) from Alzheimer's disease (AD) patients and healthy controls have been analyzed for the first time.