Synthesis, multiscale-multiphase characterization and applications of thiophene-based biohybrids

Biohybrid derivatives of π-conjugated materials are emerging as powerful tools to study biological events through the (opto)electronic variations of the π-conjugated moieties, as well as to direct and govern the self-assembly properties of the organic materials through the organization principles of the bio component. So far, very few examples of thiophene-based biohybrids have been reported. The aim of this Ph. D thesis has been the development of oligothiophene-oligonucleotide hybrid derivatives as tools, on one side, to detect DNA hybridisation events and, on the other, as model compounds to investigate thiophene-nucleobase interactions in the solid state. To obtain oligothiophene bioconjugates with the required high level of purity, we first developed new synthetic ecofriendly protocols for the synthesis of thiophene oligomers. Our innovative heterogeneous Suzuki coupling methodology, carried out in EtOH/water or isopropanol under microwave irradiation, allowed us to obtain alkyl substituted oligothiophenes and thiophene based co-oligomers in high yields and very short reaction times, free from residual metals and with improved film forming properties. These methodologies were subsequently applied in the synthesis of oligothiophene-oligonucleotide conjugates. Oligothiophene-5-labeled deoxyuridines were synthesized and incorporated into 19-meric oligonucletide sequences. We showed that the oligothiophene-labeled oligonucletide sequences obtained can be used as probes to detect a single nucleotide polymorphism (SNP) in complementary DNA target sequences. In fact, all the probes showed marked variations in emission intensity upon hybridization with a complementary target sequence. The observed variations in emitted light were comparable or even superior to those reported in similar studies, showing that the biohybrids can potentially be useful to develop biosensors for the detection of DNA mismatches. Finally, water-soluble, photoluminescent and electroactive dinucleotide-hybrid derivatives of quaterthiophene and quinquethiophene were synthesized. By means of a combination of spectroscopy and microscopy techniques, electrical characterizations, microfluidic measurements and theoretical calculations, we were able to demonstrate that the self-assembly modalities of the biohybrids in thin films are driven by the interplay of intra and intermolecular interactions in which the π-stacking between the oligothiophene and nucleotide bases plays a major role.

Adaptive multiscale biological signal processing

Biological processes are very complex mechanisms, most of them being accompanied by or manifested as signals that reflect their essential characteristics and qualities. The development of diagnostic techniques based on signal and image acquisition from the human body is commonly retained as one of the propelling factors in the advancements in medicine and biosciences recorded in the recent past. It is a fact that the instruments used for biological signal and image recording, like any other acquisition system, are affected by non-idealities which, by different degrees, negatively impact on the accuracy of the recording. This work discusses how it is possible to attenuate, and ideally to remove, these effects, with a particular attention toward ultrasound imaging and extracellular recordings. Original algorithms developed during the Ph.D. research activity will be examined and compared to ones in literature tackling the same problems; results will be drawn on the base of comparative tests on both synthetic and in-vivo acquisitions, evaluating standard metrics in the respective field of application. All the developed algorithms share an adaptive approach to signal analysis, meaning that their behavior is not dependent only on designer choices, but driven by input signal characteristics too. Performance comparisons following the state of the art concerning image quality assessment, contrast gain estimation and resolution gain quantification as well as visual inspection highlighted very good results featured by the proposed ultrasound image deconvolution and restoring algorithms: axial resolution up to 5 times better than algorithms in literature are possible. Concerning extracellular recordings, the results of the proposed denoising technique compared to other signal processing algorithms pointed out an improvement of the state of the art of almost 4 dB.

Multiscale fabrication of functional materials for life sciences

Regenerative medicine claims for a better understanding of the cause-effect relation between cell behaviour and environment signals. The latter encompasses topographical, chemical and mechanical stimuli, electromagnetic fields, gradients of chemo-attractants and haptotaxis. In this perspective, a spatial control of the structures composing the environment is required. In this thesis I describe a novel approach for the multiscale patterning of biocompatible functional materials in order to provide systems able to accurately control cell adhesion and proliferation. The behaviour of different neural cell lines in response to several stimuli, specifically chemical, topographical and electrical gradients is presented. For each of the three kind of signals, I chose properly tailored materials and fabrication and characterization techniques. After a brief introduction on the state of art of nanotechnology, nanofabrication techniques and regenerative medicine in Chapter 1 and a detailed description of the main fabrication and characterization techniques employed in this work in Chapter 2, in Chapter 3 an easy route to obtain accurate control over cell proliferation close to 100% is described (chemical control). In Chapter 4 (topographical control) it is shown how the multiscale patterning of a well-established biocompatible material as titanium dioxide provides a versatile and robust method to study the effect of local topography on cell adhesion and growth. The third signal, viz. electric field, is investigated in Chapter 5 (electrical control), where the very early stages of neural cell adhesion are studied in the presence of modest steady electric fields. In Chapter 6 (appendix) a new patterning technique, called Lithographically Controlled Etching (LCE), is proposed. It is shown how LCE can provide at the same time the micro/nanostructuring and functionalization of a surface with nanosized objects, thus being suitable for applications both in regenerative medicine in biosensing.

Homogenization of nonlinear composites for multiscale analysis

A composite is a material made out of two or more constituents (phases) combined together in order to achieve desirable mechanical or thermal properties. Such innovative materials have been widely used in a large variety of engineering fields in the past decades. The design of a composite structure requires the resolution of a multiscale problem that involves a macroscale (i.e. the structural scale) and a microscale. The latter plays a crucial role in the determination of the material behavior at the macroscale, especially when dealing with constituents characterized by nonlinearities. For this reason, numerical tools are required in order to design composite structures by taking into account of their microstructure. These tools need to provide an accurate yet efficient solution in terms of time and memory requirements, due to the large number of internal variables of the problem. This issue is addressed by different methods that overcome this problem by reducing the number of internal variables. Within this framework, this thesis focuses on the development of a new homogenization technique named Mixed TFA (MxTFA) in order to solve the homogenization problem for nonlinear composites. This technique is based on a mixed-stress variational approach involving self-equilibrated stresses and plastic multiplier as independent variables on the Reference Volume Element (RVE). The MxTFA is developed for the case of elastoplasticity and viscoplasticity, and it is implemented into a multiscale analysis for nonlinear composites. Numerical results show the efficiency of the presented techniques, both at microscale and at macroscale level.

Fractal descriptors for quantifying brain complexity in MRI

Magnetic Resonance Imaging (MRI) is the in vivo technique most commonly employed to characterize changes in brain structures. The conventional MRI-derived morphological indices are able to capture only partial aspects of brain structural complexity. Fractal geometry and its most popular index, the fractal dimension (FD), can characterize self-similar structures including grey matter (GM) and white matter (WM). Previous literature shows the need for a definition of the so-called fractal scaling window, within which each structure manifests self-similarity. This justifies the existence of fractal properties and confirms Mandelbrot’s assertion that "fractals are not a panacea; they are not everywhere". In this work, we propose a new approach to automatically determine the fractal scaling window, computing two new fractal descriptors, i.e., the minimal and maximal fractal scales (mfs and Mfs). Our method was implemented in a software package, validated on phantoms and applied on large datasets of structural MR images. We demonstrated that the FD is a useful marker of morphological complexity changes that occurred during brain development and aging and, using ultra-high magnetic field (7T) examinations, we showed that the cerebral GM has fractal properties also below the spatial scale of 1 mm. We applied our methodology in two neurological diseases. We observed the reduction of the brain structural complexity in SCA2 patients and, using a machine learning approach, proved that the cerebral WM FD is a consistent feature in predicting cognitive decline in patients with small vessel disease and mild cognitive impairment. Finally, we showed that the FD of the WM skeletons derived from diffusion MRI provides complementary information to those obtained from the FD of the WM general structure in T1-weighted images. In conclusion, the fractal descriptors of structural brain complexity are candidate biomarkers to detect subtle morphological changes during development, aging and in neurological diseases.

Multiscale comparative analysis of marine biominerals and their ecological implications

Marine biomineralizing organisms provide a fundamental link between biology and environment. Calcified structure are important archives that can provide us main means of understanding organism adaptation, habits, environmental characteristics, and to look back in time and explore the past climate and their evolutionary history. In fact, biomineralized structures retain an unparalleled record of current and past ocean conditions through the investigation of their microchemistry and isotopes. This thesis considers aspects of two different biomineralization systems: fish otolith and coral skeletons at macro-, micro- and nanoscale, with the aim to understand how their morphology, structural characteristics and compositions can provide information of their functionality, and the environmental, behavioural, and evolutionary context in which organisms are framed. To this end, I applied a multidisciplinary approach in the scope to investigate calcified structures as “information recorders” and as models to study the phenotypic plasticity.

Orchestration of multiscale model for computational oncology

Cancer is a challenging disease that involves multiple types of biological interactions in different time and space scales. Often computational modelling has been facing problems that, in the current technology level, is impracticable to represent in a single space-time continuum. To handle this sort of problems, complex orchestrations of multiscale models is frequently done. PRIMAGE is a large EU project that aims to support personalized childhood cancer diagnosis and prognosis. The goal is to do so predicting the growth of the solid tumour using multiscale in-silico technologies. The project proposes an open cloud-based platform to support decision making in the clinical management of paediatric cancers. The orchestration of predictive models is in general complex and would require a software framework that support and facilitate such task. The present work, proposes the development of an updated framework, referred herein as the VPH-HFv3, as a part of the PRIMAGE project. This framework, a complete re-writing with respect to the previous versions, aims to orchestrate several models, which are in concurrent development, using an architecture as simple as possible, easy to maintain and with high reusability. This sort of problem generally requires unfeasible execution times. To overcome this problem was developed a strategy of particularisation, which maps the upper-scale model results into a smaller number and homogenisation which does the inverse way and analysed the accuracy of this approach.

Multiscale modeling of light-harvesting systems based on rhodamine B aggregates

Rhodamine B (RB) has been successfully exploited in the synthesis of light harvesting systems, but since RB is prone to form dimers acting as quenchers for the fluorescence, high energy transfer efficiencies can be reached only when using bulky and hydrophobic counterions acting as spacers between RBs. In this PhD thesis, a multiscale theoretical study aimed at providing insights into the structural, photophysical and optical properties of RB and its aggregates is presented. At the macroscopic level (no atomistic details) a phenomenological model describing the fluorescence decay of RB networks in presence of both quenching from dimers and exciton-exciton annihiliation is presented and analysed, showing that the quenching from dimers affects the decay only at long times, a feature that can be exploited in global fitting analysis to determine relevant chemical and photophysical information. At the mesoscopic level (atomistic details but no electronic structure) the RB aggregation in water in presence of different counterions is studied with molecular dynamics (MD) simulations. A new force field has been parametrized for describing the RB flexibility and the RB-RB interaction driving the dimerization. Simulations correctly predict the RB/counterion aggregation only in presence of bulky and hydrophobic counterion and its ability to prevent the dimerization. Finally, at the microscopic level, DFT calculations are performed to demonstrate the spacing action of bulky counterions, but standard TDDFT calculations are showed to fail in correctly describing the excited states of RB and its dimers. Moreover, also standard procedures proposed in literature for obtaining ad hoc functionals are showed to not work properly. A detailed analysis on the effect of the exact exchange shows that its short-range contribution is the crucial quantity for ameliorating results, and a new functional containing a proper amount of such an exchange is proposed and successfully tested.

Aspetti innovativi per la valutazione e la misura della porosità nei materiali dell'edilizia antica e moderna. La geometria frattale della porosità

New concepts on porosity appraisal in ancient and modern construction materials. The role of Fractal Geometry on porosity characterization and transport phenomena. This work studied the potential of Fractal Geometry to the characterization of porous materials. Besides the descriptive aspects of the pore size distribution, the fractal dimensions have led to the development of rational relations for the prediction of permeability coefficients to fluid and heat transfer. The research considered natural materials used in historical buildings (rock and earth) as well as currently employed materials as hydraulic cement and technologically advanced materials such as silicon carbide or YSZ ceramics. The experimental results of porosity derived from the techniques of mercury intrusion and from the image analysis. Data elaboration was carried out according to established procedures of Fractal Geometry. It was found that certain classes of materials are clearly fractal and respond to simple patterns such as Sierpinski and Menger models. In several cases, however, the fractal character is not recognised because the microstructure of the material is based on different phases at different dimensional scales, and in consequence the “fractal dimensions” calculated from porosimetric data do not come within the standard range (less than 3). Using different type and numbers of fractal units is possible, however, to obtain “virtual” microstructures that have the fraction of voids and pore size distribution equivalent with the experimental ones for almost any material. Thus it was possible to take the expressions for the permeability and the thermal conduction which does not require empirical “constants”, these expressions have also provided values that are generally in agreement with the experimental available data. More problematic has been the fractal discussion of the geometry of the rupture of the material subjected to mechanical stress both external and internal applied. The results achieved on these issues are qualitative and prone to future studies. Keywords: Materials, Microstructure, Porosity, Fractal Geometry, Permeability, Thermal conduction, Mechanical strength.

Theoretical studies of microfluidics: "walking" drops and "melting" snowflakes.

The present PhD thesis summarizes two examples of research in microfluidics. Both times water was the subject of interest, once in the liquid state (droplets adsorbed on chemically functionalized surfaces), the other time in the solid state (ice snowflakes and their fractal behaviour). The first problem deals with a slipping nano-droplet of water adsorbed on a surface with photo-switchable wettability characteristics. Main focus was on identifying the underlying driving forces and mechanical principles at the molecular level of detail. Molecular Dynamics simulation was employed as investigative tool owing to its record of successfully describing the microscopic behaviour of liquids at interfaces. To reproduce the specialized surface on which a water droplet can effectively “walk”, a new implicit surface potential was developed. Applying this new method the experimentally observed droplet slippage could be reproduced successfully. Next the movement of the droplet was analyzed at various conditions emphasizing on the behaviour of the water molecules in contact with the surface. The main objective was to identify driving forces and molecular mechanisms underlying the slippage process. The second part of this thesis is concerned with theoretical studies of snowflake melting. In the present work snowflakes are represented by filled von Koch-like fractals of mesoscopic beads. A new algorithm has been developed from scratch to simulate the thermal collapse of fractal structures based on Monte Carlo and Random Walk Simulations (MCRWS). The developed method was applied and compared to Molecular Dynamics simulations regarding the melting of ice snowflake crystals and new parameters were derived from this comparison. Bigger snow-fractals were then studied looking at the time evolution at different temperatures again making use of the developed MCRWS method. This was accompanied by an in-depth analysis of fractal properties (border length and gyration radius) in order to shed light on the dynamics of the melting process.

Three dimensional seismic imaging and earthquake locations in a complex, segmented fault region in Southern Apennines (Italy)

The southern Apennines of Italy have been experienced several destructive earthquakes both in historic and recent times. The present day seismicity, characterized by small-to-moderate magnitude earthquakes, was used like a probe to obatin a deeper knowledge of the fault structures where the largest earthquakes occurred in the past. With the aim to infer a three dimensional seismic image both the problem of data quality and the selection of a reliable and robust tomographic inversion strategy have been faced. The data quality has been obtained to develop optimized procedures for the measurements of P- and S-wave arrival times, through the use of polarization filtering and to the application of a refined re-picking technique based on cross-correlation of waveforms. A technique of iterative tomographic inversion, linearized, damped combined with a strategy of multiscale inversion type has been adopted. The retrieved P-wave velocity model indicates the presence of a strong velocity variation along a direction orthogonal to the Apenninic chain. This variation defines two domains which are characterized by a relatively low and high velocity values. From the comparison between the inferred P-wave velocity model with a portion of a structural section available in literature, the high velocity body was correlated with the Apulia carbonatic platforms whereas the low velocity bodies was associated to the basinal deposits. The deduced Vp/Vs ratio shows that the ratio is lower than 1.8 in the shallower part of the model, while for depths ranging between 5 km and 12 km the ratio increases up to 2.1 in correspondence to the area of higher seismicity. This confirms that areas characterized by higher values are more prone to generate earthquakes as a response to the presence of fluids and higher pore-pressures.

Automated Segmentation and Non-Rigid Registration for the Quantitative Evaluation of Myocardial Perfusion from Magnetic Resonance Images

Myocardial perfusion quantification by means of Contrast-Enhanced Cardiac Magnetic Resonance images relies on time consuming frame-by-frame manual tracing of regions of interest. In this Thesis, a novel automated technique for myocardial segmentation and non-rigid registration as a basis for perfusion quantification is presented. The proposed technique is based on three steps: reference frame selection, myocardial segmentation and non-rigid registration. In the first step, the reference frame in which both endo- and epicardial segmentation will be performed is chosen. Endocardial segmentation is achieved by means of a statistical region-based level-set technique followed by a curvature-based regularization motion. Epicardial segmentation is achieved by means of an edge-based level-set technique followed again by a regularization motion. To take into account the changes in position, size and shape of myocardium throughout the sequence due to out of plane respiratory motion, a non-rigid registration algorithm is required. The proposed non-rigid registration scheme consists in a novel multiscale extension of the normalized cross-correlation algorithm in combination with level-set methods. The myocardium is then divided into standard segments. Contrast enhancement curves are computed measuring the mean pixel intensity of each segment over time, and perfusion indices are extracted from each curve. The overall approach has been tested on synthetic and real datasets. For validation purposes, the sequences have been manually traced by an experienced interpreter, and contrast enhancement curves as well as perfusion indices have been computed. Comparisons between automatically extracted and manually obtained contours and enhancement curves showed high inter-technique agreement. Comparisons of perfusion indices computed using both approaches against quantitative coronary angiography and visual interpretation demonstrated that the two technique have similar diagnostic accuracy. In conclusion, the proposed technique allows fast, automated and accurate measurement of intra-myocardial contrast dynamics, and may thus address the strong clinical need for quantitative evaluation of myocardial perfusion.

Methods for the Quantification of Motor Stability for the Assessment of Fall Risk

The research field of the Thesis is the evaluation of motor variability and the analysis of motor stability for the assessment of fall risk. Since many falls occur during walking, a better understanding of motor stability could lead to the definition of a reliable fall risk index aiming at measuring and assessing the risk of fall in the elderly, in the attempt to prevent traumatic events. Several motor variability and stability measures are proposed in the literature, but still a proper methodological characterization is lacking. Moreover, the relationship between many of these measures and fall history or fall risk is still unknown, or not completely clear. The aim of this thesis is hence to: i) analyze the influence of experimental implementation parameters on variability/stability measures and understand how variations in these parameters affect the outputs; ii) assess the relationship between variability/stability measures and long- short-term fall history. Several implementation issues have been addressed. Following the need for a methodological standardization of gait variability/stability measures, highlighted in particular for orbital stability analysis through a systematic review, general indications about implementation of orbital stability analysis have been showed, together with an analysis of the number of strides and the test-retest reliability of several variability/stability numbers. Indications about the influence of directional changes on measures have been provided. The association between measures and long/short-term fall history has also been assessed. Of all the analyzed variability/stability measures, Multiscale entropy and Recurrence quantification analysis demonstrated particularly good results in terms of reliability, applicability and association with fall history. Therefore, these measures should be taken in consideration for the definition of a fall risk index.

Analisi d'immagine, patologia quantitativa e dimensione frattale in patologia veterinaria: Densita' e forme

Fino dagli albori della metodica scientifica, l’osservazione e la vista hanno giocato un ruolo fondamentale. La patologia è una scienza visiva, dove le forme, i colori, le interfacce e le architetture di organi, tessuti, cellule e componenti cellulari guidano l’occhio del patologo e ne indirizzano la scelta diagnostico-classificativa. L’osservazione del preparato istologico in microscopia ottica si attua mediante l’esame e la caratterizzazione di anomalie ad ingrandimenti progressivamente crescenti, a diverse scale spaziali, che partono dalla valutazione dell’assetto architettonico sovracellulare, per poi spostarsi ad investigare e descrivere le cellule e le peculiarità citomorfologiche delle stesse. A differenza di altri esami di laboratorio che sono pienamente quantificabili, l’analisi istologica è intrinsecamente soggettiva, e quindi incline ad un alto grado di variabilità nei risultati prodotti da differenti patologi. L’analisi d’immagine, l’estrazione da un’immagine digitale di contenuti utili, rappresenta una metodica oggettiva, valida e robusta ormai largamente impiegata a completamento del lavoro del patologo. Si sottolinea come l’analisi d’immagine possa essere vista come fase descrittiva quantitativa di preparati macroscopici e microscopici che poi viene seguita da una interpretazione. Nuovamente si sottolinea come questi descrittori siano oggettivi, ripetibili e riproducibili, e non soggetti a bassa concordanza inter operatore. La presente tesi si snoda attraverso un percorso concettuale orientato ad applicazioni di analisi d’immagine e patologia quantitativa che parte dalle applicazioni più elementari (densità, misure lineari), per arrivare a nozioni più avanzate, quali lo studio di complessità delle forme mediante l’analisi frattale e la quantificazione del pattern spaziale di strutture sovracellulari.

Biomimetic Scaffolds for the Controlled Release of Bioactive Molecules for Tissue Engineering Applications

The temporospatial controlled delivery of growth factors is crucial to trigger the desired healing mechanisms in target tissues. The uncontrolled release of growth factors has been demonstrated to cause severe side effects in its surrounding tissues. Thus, the first working hypothesis was to tune and optimize a newly developed multiscale delivery platform based on a nanostructured silicon particle core (pSi) and a poly (dl-lactide-co-glycolide) acid (PLGA) outer shell. In a murine subcutaneous model, the platform was demonstrated to be fully tunable for the temporal and spatial control release of the payload. Secondly, a multiscale approach was followed in a multicompartment collagen scaffold, to selectively integrate different sets of PLGA-pSi loaded with different reporter proteins. The spatial confinement of the microspheres allowed the release of the reporter proteins in each of the layers of the scaffold. Finally, the staged and zero-order release kinetics enabled the temporal biochemical patterning of the scaffold. The last step of this PhD project was to test if by fully embedding PLGA microspheres in a highly structured and fibrous collagen-based scaffold (camouflaging), it was possible to prevent their early detection and clearance by macrophages. It was further studied whether such a camouflaging strategy was efficient in reducing the production of key inflammatory molecules, while preserving the release kinetics of the payload of the PLGA microspheres. Results demonstrated that the camouflaging allowed for a 10-fold decrease in the number of PLGA microspheres internalized by macrophages, suggesting that the 3D scaffold operated by cloaking the PLGA microspheres. When the production of key inflammatory cytokines induced by the scaffold was assessed, macrophages' response to the PLGA microspheres-integrated scaffolds resulted in a response similar to that observed in the control (not functionalized scaffold) and the release kinetic of a reporter protein was preserved.