New analytical LC-mass spectrometry methodologies for the quali-quantitative determination of natural substances and drugs in complex matrices

This thesis reports an integrated analytical and physicochemical approach for the study of natural substances and new drugs based on mass spectrometry techniques combined with liquid chromatography. In particular, Chapter 1 concerns the study of Berberine a natural substance with pharmacological activity for the treatment of hepatobiliary and intestinal diseases. The first part focused on the relationships between physicochemical properties, pharmacokinetics and metabolism of Berberine and its metabolites. For this purpose a sensitive HPLC-ES-MS/MS method have been developed, validated and used to determine these compounds during their physicochemical properties studies and plasma levels of berberine and its metabolites including berberrubine(M1), demethylenberberine(M3), and jatrorrhizine(M4) in humans. Data show that M1, could have an efficient intestinal absorption by passive diffusion due to a keto-enol tautomerism confirmed by NMR studies and its higher plasma concentration. In the second part of Chapter 1, a comparison between M1 and BBR in vivo biodistribution in rat has been studied. In Chapter 2 a new HPLC-ES-MS/MS method for the simultaneous determination and quantification of glucosinolates, as glucoraphanin, glucoerucin and sinigrin, and isothiocyanates, as sulforaphane and erucin, has developed and validated. This method has been used for the analysis of functional foods enriched with vegetable extracts. Chapter 3 focused on a physicochemical study of the interaction between the bile acid sequestrants used in the treatment of hypercholesterolemia including colesevelam and cholestyramine with obeticolic acid (OCA), potent agonist of nuclear receptor farnesoid X (FXR). In particular, a new experimental model for the determination of equilibrium binding isotherm was developed. Chapter 4 focused on methodological aspects of new hard ionization coupled with liquid chromatography (Direct-EI-UHPLC-MS) not yet commercially available and potentially useful for qualitative analysis and for “transparent” molecules to soft ionization techniques. This method was applied to the analysis of several steroid derivatives.

Novel techniques for the remote sensing of photosynthetic processes

Remote sensing (RS) techniques have evolved into an important instrument to investigate forest function. New methods based on the remote detection of leaf biochemistry and photosynthesis are being developed and applied in pilot studies from airborne and satellite platforms (PRI, solar-induced fluorescence; N and chlorophyll content). Non-destructive monitoring methods, a direct application of RS studies, are also proving increasingly attractive for the determination of stress conditions or nutrient deficiencies not only in research but also in agronomy, horticulture and urban forestry (proximal RS). In this work I will focus on some novel techniques recently developed for the estimation of photochemistry and photosynthetic rates based (i) on the proximal measurement of steady-state chlorophyll fluorescence yield, or (ii) the remote sensing of changes in hyperspectral leaf reflectance, associated to xanthophyll de-epoxydation and energy partitioning, which is closely coupled to leaf photochemistry and photosynthesis. I will also present and describe a mathematical model of leaf steady-state fluorescence and photosynthesis recently developed in our group. Two different species were used in the experiments: Arbutus unedo, a schlerophyllous Mediterranean species, and Populus euroamericana, a broad leaf deciduous tree widely used in plantation forestry. Results show that ambient fluorescence could provide a useful tool for testing photosynthetic processes from a distance. These results confirm also the photosynthetic reflectance index (PRI) as an efficient remote sensing reflectance index estimating short-term changes in photochemical efficiency as well as long-term changes in leaf biochemistry. The study also demonstrated that RS techniques could provide a fast and reliable method to estimate photosynthetic pigment content and total nitrogen, beside assessing the state of photochemical process in our plants’ leaves in the field. This could have important practical applications for the management of plant cultivation systems, for the estimation of the nutrient requirements of our plants for optimal growth.

Technologies for Ambient intelligence: from Smart Objects to Sensor Networks

n the last few years, the vision of our connected and intelligent information society has evolved to embrace novel technological and research trends. The diffusion of ubiquitous mobile connectivity and advanced handheld portable devices, amplified the importance of the Internet as the communication backbone for the fruition of services and data. The diffusion of mobile and pervasive computing devices, featuring advanced sensing technologies and processing capabilities, triggered the adoption of innovative interaction paradigms: touch responsive surfaces, tangible interfaces and gesture or voice recognition are finally entering our homes and workplaces. We are experiencing the proliferation of smart objects and sensor networks, embedded in our daily living and interconnected through the Internet. This ubiquitous network of always available interconnected devices is enabling new applications and services, ranging from enhancements to home and office environments, to remote healthcare assistance and the birth of a smart environment. This work will present some evolutions in the hardware and software development of embedded systems and sensor networks. Different hardware solutions will be introduced, ranging from smart objects for interaction to advanced inertial sensor nodes for motion tracking, focusing on system-level design. They will be accompanied by the study of innovative data processing algorithms developed and optimized to run on-board of the embedded devices. Gesture recognition, orientation estimation and data reconstruction techniques for sensor networks will be introduced and implemented, with the goal to maximize the tradeoff between performance and energy efficiency. Experimental results will provide an evaluation of the accuracy of the presented methods and validate the efficiency of the proposed embedded systems.