Multiscale fractal descriptors applied to nanoscale images

This work proposes the application of fractal descriptors to the analysis of nanoscale materials under different experimental conditions. We obtain descriptors for images from the sample applying a multiscale transform to the calculation of fractal dimension of a surface map of such image. Particularly, we have used the Bouligand-Minkowski fractal dimension. We applied these descriptors to discriminate between two titanium oxide films prepared under different experimental conditions. Results demonstrate the discrimination power of proposed descriptors in such kind of application.

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 variability in the North Atlantic Ocean

Programa de doctorado, Oceanografía ; 2004-2006

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.

Ionic liquids in a multiscale study

Trotz des hohen Interesse an Ionischen Flüssigkeiten wird das zielgerichtete Design und die Anwendung Ionischer Flüssigkeiten durch fehlendes grundlegendes Verständnis erschwert. Deshalb wurde die Balance der molekularen Wechselwirkungen in Ionischen Flüssigkeiten studiert, um die Eigenschaften dieser zu verstehen und die Kraftfeldentwicklung im Rahmen des Multiskalenansatzes zu systematisieren. Es wurden reine Imidazolium-basierte Ionische Flüssigkeiten, Mischungen mit kleinen Molekülen und eine protische Ionische Flüssigkeit mit ab-initio-Methoden, hauptsächlich Car-Parrinello-Molekulardynamik, untersucht. Weiterhin wurden Eigenschaften der Flüssigphase mit denen von Ionenpaaren verglichen.rnIm Fokus standen die molekularen elektrostatischen Eigenschaften und es wurde gezeigt, dass Coulomb-Wechselwirkungen zu einzigartigen Charakteristika führten. So waren die Ionen-Nettoladungen stets reduziert, die molekularen Dipolmomentverteilungen sehr breit, elektronische Polarisation war entscheidend. Die elektrostatischen Eigenschaften waren allgemein lokal auf molekularen Größen- und Zeitskalen und hingen stark von Phasenzustand und Zusammensetzung ab. Für andere molekulare Eigenschaften, wie der Neigung zu dispersiven Kontakten oder Wasserstoffbrücken, wurde gezeigt, dass sie einen entscheidenden Einfluss auf die Feinstruktur Ionischer Flüssigkeiten hatten. Das Gleichgewicht der Wechselwirkungen zeigte sich auch in Leistungsspektren, die sich aus den ab-initio-Molekulardynamiksimulationen ergaben. Diese boten einen neuen Weg für den Vergleich zum Experiment und für einen Einblick in die schnelle Dynamik Ionischer Flüssigkeiten.

Elasticity in Cloud Computing: Tecnologia e applicazione aziendale presso Onit

Il Cloud Computing permette di utilizzare al meglio le risorse distribuite allo scopo di risolvere problemi di computazione su larga scala, e viene distribuito dai provider all'utente finale sotto forma di servizio. Presentati i diversi modelli di distribuzione dei servizi Cloud, si discutono le varie tipologie di servizi offerti. Efficaci meccanismi di elasticità e scalabilità hanno permesso al Cloud Computing di superare lo scoglio iniziale di utilizzo medio dei server al 10%. L'elasticità (rapid elasticity) è l’abilità di acquisire e rilasciare le risorse di un'infrastruttura Cloud su richiesta, l’abilità di un'applicazione di cambiare le sue dimensione durante il suo tempo di esecuzione; la scalabilità è un prerequisito per ottenere una buona elasticità per il sistema, ed è l'abilità che ha un layer di sostenere carichi di lavoro variabili continuando ad adempiere agli obblighi imposti dallo SLA allocando o disallocando risorse computazionali. Le diverse modalità di scaling e il loro utilizzo determinano la scalabilità e di conseguenza l'elasticità del sistema, e sfruttano la virtualizzazione per poter funzionare. Ciò ha portato notevoli benefici perchè aumenta l'utilizzo dei server, migliora l'efficienza del sistema, e dona flessibilità in caso di errori massimizzando il tempo di funzionamento. Sono stati introdotti due esempi di sistemi elastici basati ovviamente sulla virtualizzazione come Amazon Web Services e Microsoft Azure, che dominano il mercato del Cloud Computing e fanno uso dei più efficenti meccanismi d'elasticità. Il cuore di questo elaborato è l'analisi dell'ampliamento dell'adozione del Cloud Computing in azienda Onit Group srl. L'obiettivo è trattare i punti fondamentali per il Cloud Computing, analizzarli e immagazzinare tutte queste conoscenze per analizzare lo stato attuale del Cloud nell'azienda focalizzando l'attenzione sui vantaggi e sugli svantaggi che un sostanziale ampliamento dell'adozione ai sistemi Cloud poteva apportare.

Geometry-Aware Multiscale Image Registration via OBBTree-Based Polyaffine Log-Demons

Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.

Simultaneous Multiscale Polyaffine Registration by Incorporating Deformation Statistics

Locally affine (polyaffine) image registration methods capture intersubject non-linear deformations with a low number of parameters, while providing an intuitive interpretation for clinicians. Considering the mandible bone, anatomical shape differences can be found at different scales, e.g. left or right side, teeth, etc. Classically, sequential coarse to fine registration are used to handle multiscale deformations, instead we propose a simultaneous optimization of all scales. To avoid local minima we incorporate a prior on the polyaffine transformations. This kind of groupwise registration approach is natural in a polyaffine context, if we assume one configuration of regions that describes an entire group of images, with varying transformations for each region. In this paper, we reformulate polyaffine deformations in a generative statistical model, which enables us to incorporate deformation statistics as a prior in a Bayesian setting. We find optimal transformations by optimizing the maximum a posteriori probability. We assume that the polyaffine transformations follow a normal distribution with mean and concentration matrix. Parameters of the prior are estimated from an initial coarse to fine registration. Knowing the region structure, we develop a blockwise pseudoinverse to obtain the concentration matrix. To our knowledge, we are the first to introduce simultaneous multiscale optimization through groupwise polyaffine registration. We show results on 42 mandible CT images.

Multiscale Characterization of Acrylic Bone Cement Modified with Functionalized Mesoporous Silica Nanoparticles

Acrylic bone cement is widely used to anchor orthopedic implants to bone and mechanical failure of the cement mantle surrounding an implant can contribute to aseptic loosening. In an effort to enhance the mechanical properties of bone cement, a variety of nanoparticles and fibers can be incorporated into the cement matrix. Mesoporous silica nanoparticles (MSNs) are a class of particles that display high potential for use as reinforcement within bone cement. Therefore, the purpose of this study was to quantify the impact of modifying an acrylic cement with various low-loadings of mesoporous silica. Three types of MSNs (one plain variety and two modified with functional groups) at two loading ratios (0.1 and 0.2 wt/wt) were incorporated into a commercially available bone cement. The mechanical properties were characterized using four-point bending, microindentation and nanoindentation (static, stress relaxation, and creep) while material properties were assessed through dynamic mechanical analysis, differential scanning calorimetry, thermogravimetric analysis, FTIR spectroscopy, and scanning electron microscopy. Four-point flexural testing and nanoindentation revealed minimal impact on the properties of the cements, except for several changes in the nano-level static mechanical properties. Conversely, microindentation testing demonstrated that the addition of MSNs significantly increased the microhardness. The stress relaxation and creep properties of the cements measured with nanoindentation displayed no effect resulting from the addition of MSNs. The measured material properties were consistent among all cements. Analysis of scanning electron micrographs images revealed that surface functionalization enhanced particle dispersion within the cement matrix and resulted in fewer particle agglomerates. These results suggest that the loading ratios of mesoporous silica used in this study were not an effective reinforcement material. Future work should be conducted to determine the impact of higher MSN loading ratios and alternative functional groups. (C) 2014 Elsevier Ltd. All rights reserved.

A novel computer simulation method for simulating the multiscale transduction dynamics of signal proteins

Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional molecular-dynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo- and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.