NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

Development of the optimal estimation method for inversion of stratospheric emission spectra and validation of HNO3 profiles

This doctoral thesis focuses on ground-based measurements of stratospheric nitric acid (HNO3)concentrations obtained by means of the Ground-Based Millimeter-wave Spectrometer (GBMS). Pressure broadened HNO3 emission spectra are analyzed using a new inversion algorithm developed as part of this thesis work and the retrieved vertical profiles are extensively compared to satellite-based data. This comparison effort I carried out has a key role in establishing a long-term (1991-2010), global data record of stratospheric HNO3, with an expected impact on studies concerning ozone decline and recovery. The first part of this work is focused on the development of an ad hoc version of the Optimal Estimation Method (Rodgers, 2000) in order to retrieve HNO3 spectra observed by means of GBMS. I also performed a comparison between HNO3 vertical profiles retrieved with the OEM and those obtained with the old iterative Matrix Inversion method. Results show no significant differences in retrieved profiles and error estimates, with the OEM providing however additional information needed to better characterize the retrievals. A final section of this first part of the work is dedicated to a brief review on the application of the OEM to other trace gases observed by GBMS, namely O3 and N2O. The second part of this study deals with the validation of HNO3 profiles obtained with the new inversion method. The first step has been the validation of GBMS measurements of tropospheric opacity, which is a necessary tool in the calibration of any GBMS spectra. This was achieved by means of comparisons among correlative measurements of water vapor column content (or Precipitable Water Vapor, PWV) since, in the spectral region observed by GBMS, the tropospheric opacity is almost entirely due to water vapor absorption. In particular, I compared GBMS PWV measurements collected during the primary field campaign of the ECOWAR project (Bhawar et al., 2008) with simultaneous PWV observations obtained with Vaisala RS92k radiosondes, a Raman lidar, and an IR Fourier transform spectrometer. I found that GBMS PWV measurements are in good agreement with the other three data sets exhibiting a mean difference between observations of ~9%. After this initial validation, GBMS HNO3 retrievals have been compared to two sets of satellite data produced by the two NASA/JPL Microwave Limb Sounder (MLS) experiments (aboard the Upper Atmosphere Research Satellite (UARS) from 1991 to 1999, and on the Earth Observing System (EOS) Aura mission from 2004 to date). This part of my thesis is inserted in GOZCARDS (Global Ozone Chemistry and Related Trace gas Data Records for the Stratosphere), a multi-year project, aimed at developing a long-term data record of stratospheric constituents relevant to the issues of ozone decline and expected recovery. This data record will be based mainly on satellite-derived measurements but ground-based observations will be pivotal for assessing offsets between satellite data sets. Since the GBMS has been operated for more than 15 years, its nitric acid data record offers a unique opportunity for cross-calibrating HNO3 measurements from the two MLS experiments. I compare GBMS HNO3 measurements obtained from the Italian Alpine station of Testa Grigia (45.9° N, 7.7° E, elev. 3500 m), during the period February 2004 - March 2007, and from Thule Air Base, Greenland (76.5°N 68.8°W), during polar winter 2008/09, and Aura MLS observations. A similar intercomparison is made between UARS MLS HNO3 measurements with those carried out from the GBMS at South Pole, Antarctica (90°S), during the most part of 1993 and 1995. I assess systematic differences between GBMS and both UARS and Aura HNO3 data sets at seven potential temperature levels. Results show that, except for measurements carried out at Thule, ground based and satellite data sets are consistent within the errors, at all potential temperature levels.

A new method for the estimation of the reverberation time from measured room impulse responses with application to Italian opera houses

The Schroeder's backward integration method is the most used method to extract the decay curve of an acoustic impulse response and to calculate the reverberation time from this curve. In the literature the limits and the possible improvements of this method are widely discussed. In this work a new method is proposed for the evaluation of the energy decay curve. The new method has been implemented in a Matlab toolbox. Its performance has been tested versus the most accredited literature method. The values of EDT and reverberation time extracted from the energy decay curves calculated with both methods have been compared in terms of the values themselves and in terms of their statistical representativeness. The main case study consists of nine Italian historical theatres in which acoustical measurements were performed. The comparison of the two extraction methods has also been applied to a critical case, i.e. the structural impulse responses of some building elements. The comparison underlines that both methods return a comparable value of the T30. Decreasing the range of evaluation, they reveal increasing differences; in particular, the main differences are in the first part of the decay, where the EDT is evaluated. This is a consequence of the fact that the new method returns a “locally" defined energy decay curve, whereas the Schroeder's method accumulates energy from the tail to the beginning of the impulse response. Another characteristic of the new method for the energy decay extraction curve is its independence on the background noise estimation. Finally, a statistical analysis is performed on the T30 and EDT values calculated from the impulse responses measurements in the Italian historical theatres. The aim of this evaluation is to know whether a subset of measurements could be considered representative for a complete characterization of these opera houses.

Matrix Designs and Methods for Secure and Efficient Compressed Sensing

The idea of balancing the resources spent in the acquisition and encoding of natural signals strictly to their intrinsic information content has interested nearly a decade of research under the name of compressed sensing. In this doctoral dissertation we develop some extensions and improvements upon this technique's foundations, by modifying the random sensing matrices on which the signals of interest are projected to achieve different objectives. Firstly, we propose two methods for the adaptation of sensing matrix ensembles to the second-order moments of natural signals. These techniques leverage the maximisation of different proxies for the quantity of information acquired by compressed sensing, and are efficiently applied in the encoding of electrocardiographic tracks with minimum-complexity digital hardware. Secondly, we focus on the possibility of using compressed sensing as a method to provide a partial, yet cryptanalysis-resistant form of encryption; in this context, we show how a random matrix generation strategy with a controlled amount of perturbations can be used to distinguish between multiple user classes with different quality of access to the encrypted information content. Finally, we explore the application of compressed sensing in the design of a multispectral imager, by implementing an optical scheme that entails a coded aperture array and Fabry-Pérot spectral filters. The signal recoveries obtained by processing real-world measurements show promising results, that leave room for an improvement of the sensing matrix calibration problem in the devised imager.

Electric techniques for the assessment of quality parameters of foodstuffs

In food industry, quality assurance requires low cost methods for the rapid assessment of the parameters that affect product stability. Foodstuffs are complex in their structure, mainly composed by gaseous, liquid and solid phases which often coexist in the same product. Special attention is given to water, concerned as natural component of the major food product or as added ingredient of a production process. Particularly water is structurally present in the matrix and not completely available. In this way, water can be present in foodstuff in many different states: as water of crystallization, bound to protein or starch molecules, entrapped in biopolymer networks or adsorbed on solid surfaces of porous food particles. The traditional technique for the assessment of food quality give reliable information but are destructive, time consuming and unsuitable for on line application. The techniques proposed answer to the limited disposition of time and could be able to characterize the main compositional parameters. Dielectric interaction response is mainly related to water and could be useful not only to provide information on the total content but also on the degree of mobility of this ubiquitous molecule in different complex food matrix. In this way the proposal of this thesis is to answer at this need. Dielectric and electric tool can be used for the scope and led us to describe the complex food matrix and predict food characteristic. The thesis is structured in three main part, in the first one some theoretical tools are recalled to well assess the food parameter involved in the quality definition and the techniques able to reply at the problem emerged. The second part explains the research conducted and the experimental plans are illustrated in detail. Finally the last section is left for rapid method easily implementable in an industrial process.

The foodomics approach to investigate the impact of the matrix structure on food quality: applications of magnetic resonance spectroscopy, relaxometry and imaging

The aim of this thesis is to explore the possible influence of the food matrix on food quality attributes. Using nuclear magnetic resonance techniques, the matrix-dependent properties of different foods were studied and some useful indices were defined to classify food products based on the matrix behaviour when responding to processing phenomena. Correlations were found between fish freshness indices, assessed by certain geometric parameters linked to the morphology of the animal, i.e. a macroscopic structure, and the degradation of the product structure. The same foodomics approach was also applied to explore the protective effect of modified atmospheres on the stability of fish fillets, which are typically susceptible to oxidation of the polyunsaturated fatty acids incorporated in the meat matrix. Here, freshness is assessed by evaluating the time-dependent change in the fish metabolome, providing an established freshness index, and its relationship to lipid oxidation. In vitro digestion studies, focusing on food products with different matrixes, alone and in combination with other meal components (e.g. seasoning), were conducted to investigate possible interactions between enzymes and food, modulated by matrix structure, which influence digestibility. The interaction between water and the gelatinous matrix of the food, consisting of a network of protein gels incorporating fat droplets, was also studied by means of nuclear magnetic relaxometry, in order to create a prediction tool for the correct classification of authentic and counterfeit food products protected by a quality label. This is one of the first applications of an NMR method focusing on the supramolecular structure of the matrix, rather than the chemical composition, to assess food authenticity. The effect of innovative processing technologies, such as PEF applied to fruit products, has been assessed by magnetic resonance imaging, exploiting information associated with the rehydration kinetics exerted by a modified food structure.

Circadian rhythms, sleep and autonomic function in progressive supranuclear palsy: characteristic features and reciprocal interactions

Background: Progressive supranuclear palsy (PSP) is a rare neurodegenerative condition. The aims of this study were to evaluate the association between sleep, the circadian system and autonomic function in a cohort of PSP patients. Methods: Patients with PSP diagnosed according to consensus criteria were recruited prospectively and retrospectively and performed the following tests: body core temperature (BcT), sleep-wake cycle, systolic and diastolic blood pressure (SBP, DBP) continuous monitoring for 48 h under controlled environmental conditions; cardiovascular reflex tests (CRTs). The analysis of circadian rhythmicity was performed with the single cosinor method. For state-dependent analysis, the mean value of variables in each sleep stage was calculated as well as the difference to the value in wake. Results: PSP patients presented a reduced total duration of night sleep, with frequent and prolonged awakenings. During daytime, patients had very short naps, suggesting a state of profound sleep deprivation across the 24-h. REM sleep behaviour disorder was found in 15%, restless legs syndrome in 46%, periodic limb movements in 52% and obstructive sleep apnea in 54%. BcT presented the expected fall during night-time, however, compared to controls, mean values during day and night were higher. However BcT state-dependent modulation was maintained. Increased BcT could be attributed to an inability to properly reduce sympathetic activity favoured by the sleep deprivation. At CRTs, PSP presented mild cardiovascular adrenergic impairment and preserved cardiovagal function. 14% had non-neurogenic orthostatic hypotension. Only 2 PSP presented the expected BP dipping pattern, possibly as a consequence of sleep disruption. State-dependent analysis showed a partial loss of the state-dependent modulation for SBP. Discussion: This study showed that PSP presented abnormalities of sleep, circadian rhythms and cardiovascular autonomic function that are likely to be closely linked one to another.

Enhancing predictive capability of models for solubility and permeability in polymers and composites

The interpretation of phase equilibrium and mass transport phenomena in gas/solvent - polymer system at molten or glassy state is relevant in many industrial applications. Among tools available for the prediction of thermodynamics properties in these systems, at molten/rubbery state, is the group contribution lattice-fluid equation of state (GCLF-EoS), developed by Lee and Danner and ultimately based on Panayiotou and Vera LF theory. On the other side, a thermodynamic approach namely non-equilibrium lattice-fluid (NELF) was proposed by Doghieri and Sarti to consistently extend the description of thermodynamic properties of solute polymer systems obtained through a suitable equilibrium model to the case of non-equilibrium conditions below the glass transition temperature. The first objective of this work is to investigate the phase behaviour in solvent/polymer at glassy state by using NELF model and to develop a predictive tool for gas or vapor solubility that could be applied in several different applications: membrane gas separation, barrier materials for food packaging, polymer-based gas sensors and drug delivery devices. Within the efforts to develop a predictive tool of this kind, a revision of the group contribution method developed by High and Danner for the application of LF model by Panayiotou and Vera is considered, with reference to possible alternatives for the mixing rule for characteristic interaction energy between segments. The work also devotes efforts to the analysis of gas permeability in polymer composite materials as formed by a polymer matrix in which domains are dispersed of a second phase and attention is focused on relation for deviation from Maxwell law as function of arrangement, shape of dispersed domains and loading.