EPR spectroscopy as a tool for the elucidation of non-covalent structuring principles in complex soft matter

This thesis aims at connecting structural and functional changes of complex soft matter systems due to external stimuli with non-covalent molecular interaction profiles. It addresses the problem of elucidating non-covalent forces as structuring principle of mainly polymer-based systems in solution. The structuring principles of a wide variety of complex soft matter types are analyzed. In many cases this is done by exploring conformational changes upon the exertion of external stimuli. The central question throughout this thesis is how a certain non-covalent interaction profile leads to solution condition-dependent structuring of a polymeric system.rnTo answer this question, electron paramagnetic resonance (EPR) spectroscopy is chosen as the main experimental method for the investigation of the structure principles of polymers. With EPR one detects only the local surroundings or environments of molecules that carry an unpaired electron. Non-covalent forces are normally effective on length scales of a few nanometers and below. Thus, EPR is excellently suited for their investigations. It allows for detection of interactions on length scales ranging from approx. 0.1 nm up to 10 nm. However, restriction to only one experimental technique likely leads to only incomplete pictures of complex systems. Therefore, the presented studies are frequently augmented with further experimental and computational methods in order to yield more comprehensive descriptions of the systems chosen for investigation.rnElectrostatic correlation effects in non-covalent interaction profiles as structuring principles in colloid-like ionic clusters and DNA condensation are investigated first. Building on this it is shown how electrostatic structuring principles can be combined with hydrophobic ones, at the example of host-guest interactions in so-called dendronized polymers (denpols).rnSubsequently, the focus is shifted from electrostatics in dendronized polymers to thermoresponsive alkylene oxide-based materials, whose structuring principles are based on hydrogen bonds and counteracting hydrophobic interactions. The collapse mechanism in dependence of hydrophilic-hydrophobic balance and topology of these polymers is elucidated. Complementarily the temperature-dependent phase behavior of elastin-like polypeptides (ELPs) is investigated. ELPs are the first (and so far only) class of compounds that is shown to feature a first-order inverse phase transition on nanoscopic length scales.rnFinally, this thesis addresses complex biological systems, namely intrinsically disordered proteins (IDPs). It is shown that the conformational space of the IDPs Osteopontin (OPN), a cytokine involved in metastasis of several kinds of cancer, and BASP1 (brain acid soluble protein one), a protein associated with neurite outgrowth, is governed by a subtle interplay between electrostatic forces, hydrophobic interaction, system entropy and hydrogen bonds. Such, IDPs can even sample cooperatively folded structures, which have so far only been associated with globular proteins.

Hypersonic phonon propagation in mesoscopic systems by Brillouin spectroscopy

Phononic crystals, capable to block or direct the propagation of elastic/acoustic waves, have attracted increasing interdisciplinary interest across condensed matter physics and materials science. As of today, no generalized full description of elastic wave propagation in phononic structures is available, mainly due to the large number of variables determining the band diagram. Therefore, this thesis aims for a deeper understanding of the fundamental concepts governing wave propagation in mesoscopic structures by investigation of appropriate model systems. The phononic dispersion relation at hypersonic frequencies is directly investigated by the non-destructive technique of high-resolution spontaneous Brillouin light scattering (BLS) combined with computational methods. Due to the vector nature of the elastic wave propagation, we first studied the hypersonic band structure of hybrid superlattices. These 1D phononic crystals composed of alternating layers of hard and soft materials feature large Bragg gaps. BLS spectra are sensitive probes of the moduli, photo-elastic constants and structural parameters of the constituent components. Engineering of the band structure can be realized by introduction of defects. Here, cavity layers are employed to launch additional modes that modify the dispersion of the undisturbed superlattice, with extraordinary implications to the band gap region. Density of states calculations in conjunction with the associated deformation allow for unambiguous identication of surface and cavity modes, as well as their interaction with adjacent defects. Next, the role of local resonances in phononic systems is explored in 3D structures based on colloidal particles. In turbid media BLS records the particle vibration spectrum comprising resonant modes due to the spatial confinement of elastic energy. Here, the frequency and lineshapes of the particle eigenmodes are discussed as function of increased interaction and departure from spherical symmetry. The latter is realized by uniaxial stretching of polystyrene spheres, that can be aligned in an alternating electric field. The resulting spheroidal crystals clearly exhibit anisotropic phononic properties. Establishing reliable predictions of acoustic wave propagation, necessary to advance, e.g., optomechanics and phononic devices is the ultimate aim of this thesis.

Esperienza di creazione di entrate lessicografiche combinatorie: metodi e dati dal progetto CombiNet

The present dissertation aims at simulating the construction of lexicographic layouts for an Italian combinatory dictionary based on real linguistic data, extracted from corpora by using computational methods. This work is based on the assumption that the intuition of the native speaker, or the lexicographer, who manually extracts and classifies all the relevant data, are not adequate to provide sufficient information on the meaning and use of words. Therefore, a study of the real use of language is required and this is particularly true for dictionaries that collect the combinatory behaviour of words, where the task of the lexicographer is to identify typical combinations where a word occurs. This study is conducted in the framework of the CombiNet project aimed at studying Italian Word Combinationsand and at building an online, corpus-based combinatory lexicographic resource for the Italian language. This work is divided into three chapters. Chapter 1 describes the criteria considered for the classification of word combinations according to the work of Ježek (2011). Chapter 1 also contains a brief comparison between the most important Italian combinatory dictionaries and the BBI Dictionary of Word Combinations in order to describe how word combinations are considered in these lexicographic resources. Chapter 2 describes the main computational methods used for the extraction of word combinations from corpora, taking into account the advantages and disadvantages of the two methods. Chapter 3 mainly focuses on the practical word carried out in the framework of the CombiNet project, with reference to the tools and resources used (EXTra, LexIt and "La Repubblica" corpus). Finally, the data extracted and the lexicographic layout of the lemmas to be included in the combinatory dictionary are commented, namely the words "acqua" (water), "braccio" (arm) and "colpo" (blow, shot, stroke).

The binding mode of side chain- and C3-modified epothilones to tubulin

The tubulin-binding mode of C3- and C15-modified analogues of epothilone A (Epo A) was determined by NMR spectroscopy and computational methods and compared with the existing structural models of tubulin-bound natural Epo A. Only minor differences were observed in the conformation of the macrocycle between Epo A and the C3-modified analogues investigated. In particular, 3-deoxy- (compound 2) and 3-deoxy-2,3-didehydro-Epo A (3) were found to adopt similar conformations in the tubulin-binding cleft as Epo A, thus indicating that the 3-OH group is not essential for epothilones to assume their bioactive conformation. None of the available models of the tubulin-epothilone complex is able to fully recapitulate the differences in tubulin-polymerizing activity and microtubule-binding affinity between C20-modified epothilones 6 (C20-propyl), 7 (C20-butyl), and 8 (C20-hydroxypropyl). Based on the results of transferred NOE experiments in the presence of tubulin, the isomeric C15 quinoline-based Epo B analogues 4 and 5 show very similar orientations of the side chain, irrespective of the position of the nitrogen atom in the quinoline ring. The quinoline side chain stacks on the imidazole moiety of beta-His227 with equal efficiency in both cases, thus suggesting that the aromatic side chain moiety in epothilones contributes to tubulin binding through strong van der Waals interactions with the protein rather than hydrogen bonding involving the heteroaromatic nitrogen atom. These conclusions are in line with existing tubulin polymerization and microtubule-binding data for 4, 5, and Epo B.

The Search for Low Energy Conformational Families of Small Peptides: Searching for Active Conformations of Small Peptides in the Absence of a Known Receptor

Breast cancer is the most common cancer among women. Tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment, yet many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Therefore, scientists are searching for breast cancer drugs that have different molecular targets. Previous work revealed that 8-mer and cyclic 9-mer peptides inhibit breast cancer in mouse and rat model systems, interacting with an unknown receptor, while peptides smaller than eight amino acids did not inhibit breast cancer. We have shown that the use of replica exchange molecular dynamics predicts structure and dynamics of active peptides, leading to the discovery of smaller peptides with full biological activity. These simulations identified smaller peptide analogs with a conserved turn, a β-turn formed in the larger peptides. These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition. We outline the computational methods that were tried and used with the experimental information that led to the successful completion of this research.

Evidence for Long-lived Excited States of CnH22+ Carbodications

The energetics, structures, stabilities and reactivities of[CnH2]2+ ions have been investigated using computational methods and experimental mass spectrometric techniques. Spontaneous decompositions of [CnH2]2+ into [CnH]+ + H+ products, observed for ions with odd-n values, have been explained by invoking the formation of excited triplet states. Even-n [CnH]+ ions possess triplet ground states with low-lying excited states, whereas odd-n ions have triplet states with energies several eV above ground singlet states. Radiationless transitions of vibrationally excited long-lived triplet state ions into singlet state continua are suggested as possible mechanisms for spontaneous deprotonation processes of odd-n [CnH2]2+ ions. Evidence for these long-lived excited states has been obtained in bimolecular single electron transfer reactions.

DISSECTION OF STRESS RESPONSE NETWORKS REGULATING MULTIPLE STRESSES IN RICE

Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.

NEW TOOLS FOR MONITORING GAMMA CAMERA UNIFORMITY

Detector uniformity is a fundamental performance characteristic of all modern gamma camera systems, and ensuring a stable, uniform detector response is critical for maintaining clinical images that are free of artifact. For these reasons, the assessment of detector uniformity is one of the most common activities associated with a successful clinical quality assurance program in gamma camera imaging. The evaluation of this parameter, however, is often unclear because it is highly dependent upon acquisition conditions, reviewer expertise, and the application of somewhat arbitrary limits that do not characterize the spatial location of the non-uniformities. Furthermore, as the goal of any robust quality control program is the determination of significant deviations from standard or baseline conditions, clinicians and vendors often neglect the temporal nature of detector degradation (1). This thesis describes the development and testing of new methods for monitoring detector uniformity. These techniques provide more quantitative, sensitive, and specific feedback to the reviewer so that he or she may be better equipped to identify performance degradation prior to its manifestation in clinical images. The methods exploit the temporal nature of detector degradation and spatially segment distinct regions-of-non-uniformity using multi-resolution decomposition. These techniques were tested on synthetic phantom data using different degradation functions, as well as on experimentally acquired time series floods with induced, progressively worsening defects present within the field-of-view. The sensitivity of conventional, global figures-of-merit for detecting changes in uniformity was evaluated and compared to these new image-space techniques. The image-space algorithms provide a reproducible means of detecting regions-of-non-uniformity prior to any single flood image’s having a NEMA uniformity value in excess of 5%. The sensitivity of these image-space algorithms was found to depend on the size and magnitude of the non-uniformities, as well as on the nature of the cause of the non-uniform region. A trend analysis of the conventional figures-of-merit demonstrated their sensitivity to shifts in detector uniformity. The image-space algorithms are computationally efficient. Therefore, the image-space algorithms should be used concomitantly with the trending of the global figures-of-merit in order to provide the reviewer with a richer assessment of gamma camera detector uniformity characteristics.

Automated 3D Lumbar Intervertebral Disc Segmentation from MRI Data Sets

This paper proposed an automated 3D lumbar intervertebral disc (IVD) segmentation strategy from MRI data. Starting from two user supplied landmarks, the geometrical parameters of all lumbar vertebral bodies and intervertebral discs are automatically extracted from a mid-sagittal slice using a graphical model based approach. After that, a three-dimensional (3D) variable-radius soft tube model of the lumbar spine column is built to guide the 3D disc segmentation. The disc segmentation is achieved as a multi-kernel diffeomorphic registration between a 3D template of the disc and the observed MRI data. Experiments on 15 patient data sets showed the robustness and the accuracy of the proposed algorithm.

Structure–mechanics relationships in mineralized tendons

In this paper, we review the hierarchical structure and the resulting elastic properties of mineralized tendons as obtained by various multiscale experimental and computational methods spanning from nano- to macroscale. The mechanical properties of mineralized collagen fibres are important to understand the mechanics of hard tissues constituted by complex arrangements of these fibres, like in human lamellar bone. The uniaxial mineralized collagen fibre array naturally occurring in avian tendons is a well studied model tissue for investigating various stages of tissue mineralization and the corresponding elastic properties. Some avian tendons mineralize with maturation, which results in a graded structure containing two zones of distinct morphology, circumferential and interstitial. These zones exhibit different amounts of mineral, collagen, pores and a different mineral distribution between collagen fibrillar and extrafibrillar space that lead to distinct elastic properties. Mineralized tendon cells have two phenotypes: elongated tenocytes placed between fibres in the circumferential zone and cuboidal cells with lower aspect ratios in the interstitial zone. Interestingly some regions of avian tendons seem to be predestined to mineralization, which is exhibited as specific collagen cross-linking patterns as well as distribution of minor tendon constituents (like proteoglycans) and loss of collagen crimp. Results of investigations in naturally mineralizing avian tendons may be useful in understanding the pathological mineralization occurring in some human tendons.

Solvation-Driven Charge Transfer and Localization in Metal Complexes

In any physicochemical process in liquids, the dynamical response of the solvent to the solutes out of equilibrium plays a crucial role in the rates and products: the solvent molecules react to the changes in volume and electron density of the solutes to minimize the free energy of the solution, thus modulating the activation barriers and stabilizing (or destabilizing) intermediate states. In charge transfer (CT) processes in polar solvents, the response of the solvent always assists the formation of charge separation states by stabilizing the energy of the localized charges. A deep understanding of the solvation mechanisms and time scales is therefore essential for a correct description of any photochemical process in dense phase and for designing molecular devices based on photosensitizers with CT excited states. In the last two decades, with the advent of ultrafast time-resolved spectroscopies, microscopic models describing the relevant case of polar solvation (where both the solvent and the solute molecules have a permanent electric dipole and the mutual interaction is mainly dipole−dipole) have dramatically progressed. Regardless of the details of each model, they all assume that the effect of the electrostatic fields of the solvent molecules on the internal electronic dynamics of the solute are perturbative and that the solvent−solute coupling is mainly an electrostatic interaction between the constant permanent dipoles of the solute and the solvent molecules. This well-established picture has proven to quantitatively rationalize spectroscopic effects of environmental and electric dynamics (time-resolved Stokes shifts, inhomogeneous broadening, etc.). However, recent computational and experimental studies, including ours, have shown that further improvement is required. Indeed, in the last years we investigated several molecular complexes exhibiting photoexcited CT states, and we found that the current description of the formation and stabilization of CT states in an important group of molecules such as transition metal complexes is inaccurate. In particular, we proved that the solvent molecules are not just spectators of intramolecular electron density redistribution but significantly modulate it. Our results solicit further development of quantum mechanics computational methods to treat the solute and (at least) the closest solvent molecules including the nonperturbative treatment of the effects of local electrostatics and direct solvent−solute interactions to describe the dynamical changes of the solute excited states during the solvent response.

DETERMINING THE GENOTYPE-PHENOTYPE CONNECTION IN SYNTHETIC INDUCIBLE GENE EXPRESSION SYSTEMS

Introduction Gene expression is an important process whereby the genotype controls an individual cell’s phenotype. However, even genetically identical cells display a variety of phenotypes, which may be attributed to differences in their environment. Yet, even after controlling for these two factors, individual phenotypes still diverge due to noisy gene expression. Synthetic gene expression systems allow investigators to isolate, control, and measure the effects of noise on cell phenotypes. I used mathematical and computational methods to design, study, and predict the behavior of synthetic gene expression systems in S. cerevisiae, which were affected by noise. Methods I created probabilistic biochemical reaction models from known behaviors of the tetR and rtTA genes, gene products, and their gene architectures. I then simplified these models to account for essential behaviors of gene expression systems. Finally, I used these models to predict behaviors of modified gene expression systems, which were experimentally verified. Results Cell growth, which is often ignored when formulating chemical kinetics models, was essential for understanding gene expression behavior. Models incorporating growth effects were used to explain unexpected reductions in gene expression noise, design a set of gene expression systems with “linear” dose-responses, and quantify the speed with which cells explored their fitness landscapes due to noisy gene expression. Conclusions Models incorporating noisy gene expression and cell division were necessary to design, understand, and predict the behaviors of synthetic gene expression systems. The methods and models developed here will allow investigators to more efficiently design new gene expression systems, and infer gene expression properties of TetR based systems.

Pathway Semantics: An Algebraic Data Driven Algorithm to Generate Hypotheses about Molecular Patterns Underlying Disease Progression

The overarching goal of the Pathway Semantics Algorithm (PSA) is to improve the in silico identification of clinically useful hypotheses about molecular patterns in disease progression. By framing biomedical questions within a variety of matrix representations, PSA has the flexibility to analyze combined quantitative and qualitative data over a wide range of stratifications. The resulting hypothetical answers can then move to in vitro and in vivo verification, research assay optimization, clinical validation, and commercialization. Herein PSA is shown to generate novel hypotheses about the significant biological pathways in two disease domains: shock / trauma and hemophilia A, and validated experimentally in the latter. The PSA matrix algebra approach identified differential molecular patterns in biological networks over time and outcome that would not be easily found through direct assays, literature or database searches. In this dissertation, Chapter 1 provides a broad overview of the background and motivation for the study, followed by Chapter 2 with a literature review of relevant computational methods. Chapters 3 and 4 describe PSA for node and edge analysis respectively, and apply the method to disease progression in shock / trauma. Chapter 5 demonstrates the application of PSA to hemophilia A and the validation with experimental results. The work is summarized in Chapter 6, followed by extensive references and an Appendix with additional material.

Non-tariff barriers, integration and the transatlantic economy

We examine the potential impact of TTIP through trade-cost reductions, applying a mix of econometric and computational methods to develop estimates of the benefits (and costs) for the EU, United States, and third countries. Econometric results point to an approximate 80% growth in bilateral trade with an ambitious trade agreement. However, at the same time, computable general equilibrium (CGE) estimates highlight distributional impacts across countries and factors not evident from econometrics alone. Translated through our CGE framework, while bilateral trade increases roughly 80%, there is a fall of about 2.5% in trade with the rest of the world in our central case. The estimated gains in annual consumption range between 1% and 2.25% for the United States and EU, respectively. A purely discriminatory agreement would harm most countries outside the agreement, while the direction of third-country effects hinges critically on whether NTB reductions end up being discriminatory or not. Within the United States and EU, while labour gains across skill categories, the impact on farmers is mixed.