Federico Marini

Learn More
Artificial neural networks are a family of non-linear computational methods, loosely inspired by the human brain, that have found application in an increasing number of fields of analytical chemistry and specifically of food control. In this review, the main neural network architectures are described and examples of their application to solve food(More)
An NMR and chemometric analytical approach to classify extra virgin olive oils according to their geographical origin was developed within the European TRACE project (FP6-2003-FOOD-2-A, contract number: 0060942). Olive oils (896 samples) of three consecutive harvesting years (2005, 2006, and 2007) coming from Mediterranean areas were analyzed by (1)H NMR(More)
BACKGROUND Aging is characterized by derangements in multiple metabolic pathways that progressively constrict the homeostatic reserve (homeostenosis). The signature of metabolic alterations that accompany aging can be retrieved through the metabolomic profiling of biological fluids. OBJECTIVE To characterize the age-related changes in urinary and fecal(More)
A computational approach for the identification and investigation of correlations between a chemical structure and a selected biological property is described. It is based on a set of 132 compounds of known chemical structures, which were tested for their binding affinities to the estrogen receptor. Different multivariate modeling methods, i.e., partial(More)
OBJECTIVE The aim of this study is to evaluate the systemic effects of an isotonic sports drink on the metabolic status of athletes of the Italian Olympic rowing team during recovery after strenuous and prolonged physical exercise by means of nuclear magnetic resonance (NMR)-based metabolomics analysis on plasma and urine. METHODS Forty-four male athletes(More)
The problem of authenticating extra virgin olive oil varieties is particularly important from the standpoint of quality control. After having shown in our previous works the possibility of discriminating oils from a single variety using chemometrics, in this study a combination of two different neural networks architectures was employed for the resolution(More)
An innovative procedure to classify oat and groat kernels based on coupling hyperspectral imaging (HSI) in the near infrared (NIR) range (1006-1650 nm) and chemometrics was designed, developed and validated. According to market requirements, the amount of groat, that is the hull-less oat kernels, is one of the most important quality characteristics of oats.(More)
In this paper, the potential of coupling mid- and near-infrared spectroscopic fingerprinting techniques and chemometric classification methods for the traceability of extra virgin olive oil samples from the PDO Sabina was investigated. To this purpose, two different pattern recognition algorithm representative of the discriminant (PLS-DA) and modeling(More)
BACKGROUND Nowadays, non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases in children. Our recent clinical trial demonstrated that dietary and VSL#3-based interventions may improve fatty liver by ultrasound and body mass index (BMI) after 4 months. OBJECTIVES As in this short-term trial, as in others, it is(More)
In this paper, we propose an analytical methodology for attributing provenance to natural lapis lazuli pigments employed in works of art, and for distinguishing whether they are of natural or synthetic origin. A multitechnique characterization of lazurite and accessory phases in lapis lazuli stones from Afghan, Siberian and Chilean quarries, on the pigments(More)