Molecular approach to Neurodegenerative Disorders: Role of Nociceptin/Orphanin FQ - NOP System in Parkinson and Epigenetic Mechanism in Alzheimer's Disease

With life expectancies increasing around the world, populations are getting age and neurodegenerative diseases have become a global issue. For this reason we have focused our attention on the two most important neurodegenerative diseases: Parkinson’s and Alzheimer’s. Parkinson’s disease is a chronic progressive neurodegenerative movement disorder of multi-factorial origin. Environmental toxins as well as agricultural chemicals have been associated with PD. Has been observed that N/OFQ contributes to both neurotoxicity and symptoms associated with PD and that pronociceptin gene expression is up-regulated in rat SN of 6-OHDA and MPP induced experimental parkinsonism. First, we investigated the role of N/OFQ-NOP system in the pathogenesis of PD in an animal model developed using PQ and/or MB. Then we studied Alzheimer's disease. This disorder is defined as a progressive neurologic disease of the brain leading to the irreversible loss of neurons and the loss of intellectual abilities, including memory and reasoning, which become severe enough to impede social or occupational functioning. Effective biomarker tests could prevent such devastating damage occurring. We utilized the peripheral blood cells of AD discordant monozygotic twin in the search of peripheral markers which could reflect the pathology within the brain, and also support the hypothesis that PBMC might be a useful model of epigenetic gene regulation in the brain. We investigated the mRNA levels in several genes involve in AD pathogenesis, as well DNA methylation by MSP Real-Time PCR. Finally by Western Blotting we assess the immunoreactivity levels for histone modifications. Our results support the idea that epigenetic changes assessed in PBMCs can also be useful in neurodegenerative disorders, like AD and PD, enabling identification of new biomarkers in order to develop early diagnostic programs.

Numerical optimization,modeling and system evaluation of a thermophotovoltaic hybrid panel

Photovoltaic (PV) solar panels generally produce electricity in the 6% to 16% efficiency range, the rest being dissipated in thermal losses. To recover this amount, hybrid photovoltaic thermal systems (PVT) have been devised. These are devices that simultaneously convert solar energy into electricity and heat. It is thus interesting to study the PVT system globally from different point of views in order to evaluate advantages and disadvantages of this technology and its possible uses. In particular in Chapter II, the development of the PVT absorber numerical optimization by a genetic algorithm has been carried out analyzing different internal channel profiles in order to find a right compromise between performance and technical and economical feasibility. Therefore in Chapter III ,thanks to a mobile structure built into the university lab, it has been compared experimentally electrical and thermal output power from PVT panels with separated photovoltaic and solar thermal productions. Collecting a lot of experimental data based on different seasonal conditions (ambient temperature,irradiation, wind...),the aim of this mobile structure has been to evaluate average both thermal and electrical increasing and decreasing efficiency values obtained respect to separate productions through the year. In Chapter IV , new PVT and solar thermal equation based models in steady state conditions have been developed by software Dymola that uses Modelica language. This permits ,in a simplified way respect to previous system modelling softwares, to model and evaluate different concepts about PVT panel regarding its structure before prototyping and measuring it. Chapter V concerns instead the definition of PVT boundary conditions into a HVAC system . This was made trough year simulations by software Polysun in order to finally assess the best solar assisted integrated structure thanks to F_save(solar saving energy)factor. Finally, Chapter VI presents the conclusion and the perspectives of this PhD work.

Spectroscopic properties from hybrid QM, MM molecular dynamics simulation

The central aim of this thesis work is the application and further development of a hybrid quantum mechanical/molecular mechanics (QM/MM) based approach to compute spectroscopic properties of molecules in complex chemical environments from electronic structure theory. In the framework of this thesis, an existing density functional theory implementation of the QM/MM approach is first used to calculate the nuclear magnetic resonance (NMR) solvent shifts of an adenine molecule in aqueous solution. The findings show that the aqueous solvation with its strongly fluctuating hydrogen bond network leads to specific changes in the NMR resonance lines. Besides the absolute values, also the ordering of the NMR lines changes under the influence of the solvating water molecules. Without the QM/MM scheme, a quantum chemical calculation could have led to an incorrect assignment of these lines. The second part of this thesis describes a methodological improvement of the QM/MM method that is designed for cases in which a covalent chemical bond crosses the QM/MM boundary. The development consists in an automatized protocol to optimize a so-called capping potential that saturates the electronic subsystem in the QM region. The optimization scheme is capable of tuning the parameters in such a way that the deviations of the electronic orbitals between the regular and the truncated (and "capped") molecule are minimized. This in turn results in a considerable improvement of the structural and spectroscopic parameters when computed with the new optimized capping potential within the QM/MM technique. This optimization scheme is applied and benchmarked on the example of truncated carbon-carbon bonds in a set of small test molecules. It turns out that the optimized capping potentials yield an excellent agreement of NMR chemical shifts and protonation energies with respect to the corresponding full molecules. These results are very promising, so that the application to larger biological complexes will significantly improve the reliability of the prediction of the related spectroscopic properties.

Monitoring Complex Processes to Verify System Conformance: A Declarative Rule-Based Framework

Over the last 60 years, computers and software have favoured incredible advancements in every field. Nowadays, however, these systems are so complicated that it is difficult – if not challenging – to understand whether they meet some requirement or are able to show some desired behaviour or property. This dissertation introduces a Just-In-Time (JIT) a posteriori approach to perform the conformance check to identify any deviation from the desired behaviour as soon as possible, and possibly apply some corrections. The declarative framework that implements our approach – entirely developed on the promising open source forward-chaining Production Rule System (PRS) named Drools – consists of three components: 1. a monitoring module based on a novel, efficient implementation of Event Calculus (EC), 2. a general purpose hybrid reasoning module (the first of its genre) merging temporal, semantic, fuzzy and rule-based reasoning, 3. a logic formalism based on the concept of expectations introducing Event-Condition-Expectation rules (ECE-rules) to assess the global conformance of a system. The framework is also accompanied by an optional module that provides Probabilistic Inductive Logic Programming (PILP). By shifting the conformance check from after execution to just in time, this approach combines the advantages of many a posteriori and a priori methods proposed in literature. Quite remarkably, if the corrective actions are explicitly given, the reactive nature of this methodology allows to reconcile any deviations from the desired behaviour as soon as it is detected. In conclusion, the proposed methodology brings some advancements to solve the problem of the conformance checking, helping to fill the gap between humans and the increasingly complex technology.

Optimal Supervisory Control of Hybrid Vehicles

Hybrid vehicles (HV), comprising a conventional ICE-based powertrain and a secondary energy source, to be converted into mechanical power as well, represent a well-established alternative to substantially reduce both fuel consumption and tailpipe emissions of passenger cars. Several HV architectures are either being studied or already available on market, e.g. Mechanical, Electric, Hydraulic and Pneumatic Hybrid Vehicles. Among the others, Electric (HEV) and Mechanical (HSF-HV) parallel Hybrid configurations are examined throughout this Thesis. To fully exploit the HVs potential, an optimal choice of the hybrid components to be installed must be properly designed, while an effective Supervisory Control must be adopted to coordinate the way the different power sources are managed and how they interact. Real-time controllers can be derived starting from the obtained optimal benchmark results. However, the application of these powerful instruments require a simplified and yet reliable and accurate model of the hybrid vehicle system. This can be a complex task, especially when the complexity of the system grows, i.e. a HSF-HV system assessed in this Thesis. The first task of the following dissertation is to establish the optimal modeling approach for an innovative and promising mechanical hybrid vehicle architecture. It will be shown how the chosen modeling paradigm can affect the goodness and the amount of computational effort of the solution, using an optimization technique based on Dynamic Programming. The second goal concerns the control of pollutant emissions in a parallel Diesel-HEV. The emissions level obtained under real world driving conditions is substantially higher than the usual result obtained in a homologation cycle. For this reason, an on-line control strategy capable of guaranteeing the respect of the desired emissions level, while minimizing fuel consumption and avoiding excessive battery depletion is the target of the corresponding section of the Thesis.

Specific enzymatic cleavage and payload release from peptide-based hybrid nanocapsules

Within this thesis, new approaches for the concepts of peptide-polymer conjugates and peptide-based hybrid nanomaterials are investigated. In the first part, the synthesis of a triblock polymer-peptide-polymer is carried out following a typical peptide coupling reaction, both in solution and on solid-phase. The peptide sequence is chosen, so that it is cleaved by an enzyme preparation of trypsin. End-functionalized polystyrene is used as a model hydrophobic polymer and coupled to the peptide sequence. The results show successful coupling reactions in both methods, while the solid phase method produced a more defined product. Suspensions, consisting of peptide-polymer conjugates particles, are prepared in water by ultrasonication. In contact with the enzyme, the peptide constituting the conjugated particles is cleaved. This demonstrates the enzymatic cleavage in heterophase of enzymatic sequence bond to hydrophobic polymers, and is of great interest for the encapsulation and delivery of hydrophobic molecules.rnA second approach is the preparation of peptide-based hybrid nanocapsules. This is achieved by interfacial polyaddition in inverse miniemulsion with the peptide sequence functionalized with additional amino acids. A method suitable to the use of a peptide sequence for interfacial polyaddition was developed. It is shown that, the polarity of the dispersed phase influences the structures prepared, from particle-like to polymeric shell with a liquid core.rnThe peptide sequence is equipped with a FRET pair (more exactly, an internally-quenched fluorescent system) which allows the real-time monitoring of the enzymatic cleavage of the recognition site. This system shows the successful cleavage of the peptide-based nanocapsules when trypsin preparation is added to the suspensions. A water-soluble fluorescent polymer is efficiently entrapped and its possible use as marker for the capsules is highlighted. Furthermore, a small water-soluble fluorescent dye (SR-101) is successfully encapsulated and the encapsulation efficiency as a function of the functionality of the peptide and the amount of comonomer equivalent (toluene diisocyanate) is studied. The dye is encapsulated at such a high concentration, that self-quenching occurs. Thus, the release of the encapsulated dye triggered by the enzymatic cleavage of the peptide results in a fluorescence recovery of the dye. The fluorescence recovery of the FRET pair in the peptide and of the encapsulated dye correlate well.rnFinally, nanocapsules based on a hepsin-cleavable peptide sequence are prepared. Hepsin is an enzyme, which is highly upregulated in prostate cancer cells. The cleavage of the nanocapsules is investigated with healthy and “cancerous” (hepsin-expressing) cell cultures. The degradation, followed via fluorescence recovery of the FRET system, is faster for the suspensions introduced in the hepsin expressing cell cultures.rnIn summary, this work tackles the domain of responsive nanomaterials for drug delivery from a new perspective. It presents the adaptation of the miniemulsion process for hybrid peptide-based materials, and their successful use in preparing specific enzyme-responsive nanoparticles, with hydrophilic payload release properties.rn

Cannabinoid system combined to classic targets for a new MTDL strategy: design and synthesis of natural inspired molecules for Alzheimer's disease

In this thesis is described the design and synthesis of potential agents for the treatment of the multifactorial Alzheimer’s disease (AD). Our multi-target approach was to consider cannabinoid system involved in AD, together with classic targets. In the first project, designed modifications were performed on lead molecule in order to increase potency and obtain balanced activities on fatty acid amide hydrolase and cholinesterases. A small library of compounds was synthesized and biological results showed increased inhibitory activity (nanomolar range) related to selected target. The second project was focused on the benzofuran framework, a privileged structure being a common moiety found in many biologically active natural products and therapeutics. Hybrid molecules were designed and synthesized, focusing on the inhibition of cholinesterases, Aβ aggregation, FAAH and on the interaction with CB receptors. Preliminary results showed that several compounds are potent CB ligands, in particular the high affinity for CB2 receptors, could open new opportunities to modulate neuroinflammation. The third and the fourth project were carried out at the IMS, Aberdeen, under the supervision of Prof. Matteo Zanda. The role of the cannabinoid system in the brain is still largely unexplored and the relationship between the CB1 receptors functional modification, density and distribution and the onset of a pathological state is not well understood. For this reasons, Rimonabant analogues suitable as radioligands were synthesized. The latter, through PET, could provide reliable measurements of density and distribution of CB1 receptors in the brain. In the fifth project, in collaboration with CHyM of York, the goal was to develop arginine analogues that are target specific due to their exclusively location into NOS enzymes and could work as MRI contrasting agents. Synthesized analogues could be suitable substrate for the transfer of polarization by p-H2 molecules through SABRE technique transforming MRI a more sensitive and faster technique.

Motor control system in Parkinson’s disease: a modeling approach

Parkinson’s disease is a neurodegenerative disorder due to the death of the dopaminergic neurons of the substantia nigra of the basal ganglia. The process that leads to these neural alterations is still unknown. Parkinson’s disease affects most of all the motor sphere, with a wide array of impairment such as bradykinesia, akinesia, tremor, postural instability and singular phenomena such as freezing of gait. Moreover, in the last few years the fact that the degeneration in the basal ganglia circuitry induces not only motor but also cognitive alterations, not necessarily implicating dementia, and that dopamine loss induces also further implications due to dopamine-driven synaptic plasticity got more attention. At the present moment, no neuroprotective treatment is available, and even if dopamine-replacement therapies as well as electrical deep brain stimulation are able to improve the life conditions of the patients, they often present side effects on the long term, and cannot recover the neural loss, which instead continues to advance. In the present thesis both motor and cognitive aspects of Parkinson’s disease and basal ganglia circuitry were investigated, at first focusing on Parkinson’s disease sensory and balance issues by means of a new instrumented method based on inertial sensor to provide further information about postural control and postural strategies used to attain balance, then applying this newly developed approach to assess balance control in mild and severe patients, both ON and OFF levodopa replacement. Given the inability of levodopa to recover balance issues and the new physiological findings than underline the importance in Parkinson’s disease of non-dopaminergic neurotransmitters, it was therefore developed an original computational model focusing on acetylcholine, the most promising neurotransmitter according to physiology, and its role in synaptic plasticity. The rationale of this thesis is that a multidisciplinary approach could gain insight into Parkinson’s disease features still unresolved.

Morphological and biochemical T2 evaluation of cartilage repair tissue based on a hybrid double echo at steady state (DESS-T2d) approach

To use a new approach which provides, based on the widely used three-dimensional double-echo steady-state (DESS) sequence, in addition to the morphological information, the generation of biochemical T2 maps in one hybrid sequence.

Io volcano observer (IVO) integrated approach to optimizing system design for radiation challenges

One of the major challenges for a mission to the Jovian system is the radiation tolerance of the spacecraft (S/C) and the payload. Moreover, being able to achieve science observations with high signal to noise ratios (SNR), while passing through the high flux radiation zones, requires additional ingenuity on the part of the instrument provider. Consequently, the radiation mitigation is closely intertwined with the payload, spacecraft and trajectory design, and requires a systems-level approach. This paper presents a design for the Io Volcano Observer (IVO), a Discovery mission concept that makes multiple close encounters with Io while orbiting Jupiter. The mission aims to answer key outstanding questions about Io, especially the nature of its intense active volcanism and the internal processes that drive it. The payload includes narrow-angle and wide-angle cameras (NAC and WAC), dual fluxgate magnetometers (FGM), a thermal mapper (ThM), dual ion and neutral mass spectrometers (INMS), and dual plasma ion analyzers (PIA). The radiation mitigation is implemented by drawing upon experiences from designs and studies for missions such as the Radiation Belt Storm Probes (RBSP) and Jupiter Europa Orbiter (JEO). At the core of the radiation mitigation is IVO's inclined and highly elliptical orbit, which leads to rapid passes through the most intense radiation near Io, minimizing the total ionizing dose (177 krads behind 100 mils of Aluminum with radiation design margin (RDM) of 2 after 7 encounters). The payload and the spacecraft are designed specifically to accommodate the fast flyby velocities (e.g. the spacecraft is radioisotope powered, remaining small and agile without any flexible appendages). The science instruments, which collect the majority of the high-priority data when close to Io and thus near the peak flux, also have to mitigate transient noise in their detectors. The cameras use a combination of shielding and CMOS detectors with extremely fast readout to mi- imize noise. INMS microchannel plate detectors and PIA channel electron multipliers require additional shielding. The FGM is not sensitive to noise induced by energetic particles and the ThM microbolometer detector is nearly insensitive. Detailed SNR calculations are presented. To facilitate targeting agility, all of the spacecraft components are shielded separately since this approach is more mass efficient than using a radiation vault. IVO uses proven radiation-hardened parts (rated at 100 krad behind equivalent shielding of 280 mils of Aluminum with RDM of 2) and is expected to have ample mass margin to increase shielding if needed.