Modelling and simulating in systems biology: an approach based on multi-agent systems

Systems Biology is an innovative way of doing biology recently raised in bio-informatics contexts, characterised by the study of biological systems as complex systems with a strong focus on the system level and on the interaction dimension. In other words, the objective is to understand biological systems as a whole, putting on the foreground not only the study of the individual parts as standalone parts, but also of their interaction and of the global properties that emerge at the system level by means of the interaction among the parts. This thesis focuses on the adoption of multi-agent systems (MAS) as a suitable paradigm for Systems Biology, for developing models and simulation of complex biological systems. Multi-agent system have been recently introduced in informatics context as a suitabe paradigm for modelling and engineering complex systems. Roughly speaking, a MAS can be conceived as a set of autonomous and interacting entities, called agents, situated in some kind of nvironment, where they fruitfully interact and coordinate so as to obtain a coherent global system behaviour. The claim of this work is that the general properties of MAS make them an effective approach for modelling and building simulations of complex biological systems, following the methodological principles identified by Systems Biology. In particular, the thesis focuses on cell populations as biological systems. In order to support the claim, the thesis introduces and describes (i) a MAS-based model conceived for modelling the dynamics of systems of cells interacting inside cell environment called niches. (ii) a computational tool, developed for implementing the models and executing the simulations. The tool is meant to work as a kind of virtual laboratory, on top of which kinds of virtual experiments can be performed, characterised by the definition and execution of specific models implemented as MASs, so as to support the validation, falsification and improvement of the models through the observation and analysis of the simulations. A hematopoietic stem cell system is taken as reference case study for formulating a specific model and executing virtual experiments.

Development, characterization, and application of flowing atmospheric-pressure afterglow ionization for mass spectrometric analysis of ambient organic aerosols

Addressing current limitations of state-of-the-art instrumentation in aerosol research, the aim of this work was to explore and assess the applicability of a novel soft ionization technique, namely flowing atmospheric-pressure afterglow (FAPA), for the mass spectrometric analysis of airborne particulate organic matter. Among other soft ionization methods, the FAPA ionization technique was developed in the last decade during the advent of ambient desorption/ionization mass spectrometry (ADI–MS). Based on a helium glow discharge plasma at atmospheric-pressure, excited helium species and primary reagent ions are generated which exit the discharge region through a capillary electrode, forming the so-called afterglow region where desorption and ionization of the analytes occurs. Commonly, fragmentation of the analytes during ionization is reported to occur only to a minimum extent, predominantly resulting in the formation of quasimolecular ions, i.e. [M+H]+ and [M–H]– in the positive and the negative ion mode, respectively. Thus, identification and detection of signals and their corresponding compounds is facilitated in the acquired mass spectra. The focus of the first part of this study lies on the application, characterization and assessment of FAPA–MS in the offline mode, i.e. desorption and ionization of the analytes from surfaces. Experiments in both positive and negative ion mode revealed ionization patterns for a variety of compound classes comprising alkanes, alcohols, aldehydes, ketones, carboxylic acids, organic peroxides, and alkaloids. Besides the always emphasized detection of quasimolecular ions, a broad range of signals for adducts and losses was found. Additionally, the capabilities and limitations of the technique were studied in three proof-of-principle applications. In general, the method showed to be best suited for polar analytes with high volatilities and low molecular weights, ideally containing nitrogen- and/or oxygen functionalities. However, for compounds with low vapor pressures, containing long carbon chains and/or high molecular weights, desorption and ionization is in direct competition with oxidation of the analytes, leading to the formation of adducts and oxidation products which impede a clear signal assignment in the acquired mass spectra. Nonetheless, FAPA–MS showed to be capable of detecting and identifying common limonene oxidation products in secondary OA (SOA) particles on a filter sample and, thus, is considered a suitable method for offline analysis of OA particles. In the second as well as the subsequent parts, FAPA–MS was applied online, i.e. for real time analysis of OA particles suspended in air. Therefore, the acronym AeroFAPA–MS (i.e. Aerosol FAPA–MS) was chosen to refer to this method. After optimization and characterization, the method was used to measure a range of model compounds and to evaluate typical ionization patterns in the positive and the negative ion mode. In addition, results from laboratory studies as well as from a field campaign in Central Europe (F–BEACh 2014) are presented and discussed. During the F–BEACh campaign AeroFAPA–MS was used in combination with complementary MS techniques, giving a comprehensive characterization of the sampled OA particles. For example, several common SOA marker compounds were identified in real time by MSn experiments, indicating that photochemically aged SOA particles were present during the campaign period. Moreover, AeroFAPA–MS was capable of detecting highly oxidized sulfur-containing compounds in the particle phase, presenting the first real-time measurements of this compound class. Further comparisons with data from other aerosol and gas-phase measurements suggest that both particulate sulfate as well as highly oxidized peroxyradicals in the gas phase might play a role during formation of these species. Besides applying AeroFAPA–MS for the analysis of aerosol particles, desorption processes of particles in the afterglow region were investigated in order to gain a more detailed understanding of the method. While during the previous measurements aerosol particles were pre-evaporated prior to AeroFAPA–MS analysis, in this part no external heat source was applied. Particle size distribution measurements before and after the AeroFAPA source revealed that only an interfacial layer of OA particles is desorbed and, thus, chemically characterized. For particles with initial diameters of 112 nm, desorption radii of 2.5–36.6 nm were found at discharge currents of 15–55 mA from these measurements. In addition, the method was applied for the analysis of laboratory-generated core-shell particles in a proof-of-principle study. As expected, predominantly compounds residing in the shell of the particles were desorbed and ionized with increasing probing depths, suggesting that AeroFAPA–MS might represent a promising technique for depth profiling of OA particles in future studies.

Synthesis, characterization and catalytic performances of ruthenium-based catalysts for the acceptorless dehydrogenative coupling of butanol

A growing interest towards new sources of energy has led in recent years to the development of a new generation of catalysts for alcohol dehydrogenative coupling (ADC). This green, atom-efficient reaction is capable of turning alcohol derivatives into higher value and chemically more attractive ester molecules, and it finds interesting applications in the transformation of the large variety of products deriving from biomass. In the present work, a new series of ruthenium-PNP pincer complexes are investigated for the transformation of 1-butanol, one of the most challenging substrates for this type of reactions, into butyl butyrate, a short-chain symmetrical ester widely used in flavor industries. Since the reaction kinetics depends on hydrogen diffusion, the study aimed at identifying proper reactor type and right catalyst concentration to avoid mass transfer interferences and to get dependable data. A comparison between catalytic activities and productivities has been made to establish the role of the different ligands bonded both to the PNP binder and to the ruthenium metal center, and hence to find the best catalyst for this type of reaction.

The contribution of the Finite Volume Point Dilution Method to the determination of solute mass flux in an alluvial aquifer.

Groundwater represents one of the most important resources of the world and it is essential to prevent its pollution and to consider remediation intervention in case of contamination. According to the scientific community the characterization and the management of the contaminated sites have to be performed in terms of contaminant fluxes and considering their spatial and temporal evolution. One of the most suitable approach to determine the spatial distribution of pollutant and to quantify contaminant fluxes in groundwater is using control panels. The determination of contaminant mass flux, requires measurement of contaminant concentration in the moving phase (water) and velocity/flux of the groundwater. In this Master Thesis a new solute flux mass measurement approach, based on an integrated control panel type methodology combined with the Finite Volume Point Dilution Method (FVPDM), for the monitoring of transient groundwater fluxes, is proposed. Moreover a new adsorption passive sampler, which allow to capture the variation of solute concentration with time, is designed. The present work contributes to the development of this approach on three key points. First, the ability of the FVPDM to monitor transient groundwater fluxes was verified during a step drawdown test at the experimental site of Hermalle Sous Argentau (Belgium). The results showed that this method can be used, with optimal results, to follow transient groundwater fluxes. Moreover, it resulted that performing FVPDM, in several piezometers, during a pumping test allows to determine the different flow rates and flow regimes that can occurs in the various parts of an aquifer. The second field test aiming to determine the representativity of a control panel for measuring mass flus in groundwater underlined that wrong evaluations of Darcy fluxes and discharge surfaces can determine an incorrect estimation of mass fluxes and that this technique has to be used with precaution. Thus, a detailed geological and hydrogeological characterization must be conducted, before applying this technique. Finally, the third outcome of this work concerned laboratory experiments. The test conducted on several type of adsorption material (Oasis HLB cartridge, TDS-ORGANOSORB 10 and TDS-ORGANOSORB 10-AA), in order to determine the optimum medium to dimension the passive sampler, highlighted the necessity to find a material with a reversible adsorption tendency to completely satisfy the request of the new passive sampling technique.

The role of the interplay between polymer architecture and bacterial surface properties on the microbial adhesion to polyoxazoline-based ultrathin films

Surface platforms were engineered from poly(L-lysine)-graft-poly(2-methyl-2-oxazoline) (PLL-g-PMOXA) copolymers to study the mechanisms involved in the non-specific adhesion of Escherichia coli (E. coli) bacteria. Copolymers with three different grafting densities (PMOXA chains/Lysine residue of 0.09, 0.33 and 0.56) were synthesized and assembled on niobia (Nb O ) surfaces. PLL-modified and bare niobia surfaces served as controls. To evaluate the impact of fimbriae expression on the bacterial adhesion, the surfaces were exposed to genetically engineered E. coli strains either lacking, or constitutively expressing type 1 fimbriae. The bacterial adhesion was strongly influenced by the presence of bacterial fimbriae. Non-fimbriated bacteria behaved like hard, charged particles whose adhesion was dependent on surface charge and ionic strength of the media. In contrast, bacteria expressing type 1 fimbriae adhered to the substrates independent of surface charge and ionic strength, and adhesion was mediated by non-specific van der Waals and hydrophobic interactions of the proteins at the fimbrial tip. Adsorbed polymer mass, average surface density of the PMOXA chains, and thickness of the copolymer films were quantified by optical waveguide lightmode spectroscopy (OWLS) and variable-angle spectroscopic ellipsometry (VASE), whereas the lateral homogeneity was probed by time-of-flight secondary ion mass spectrometry (ToF-SIMS). Streaming current measurements provided information on the charge formation of the polymer-coated and the bare niobia surfaces. The adhesion of both bacterial strains could be efficiently inhibited by the copolymer film only with a grafting density of 0.33 characterized by the highest PMOXA chain surface density and a surface potential close to zero.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Primer extension based quantitative polymerase chain reaction reveals consistent differences in the methylation status of the MGMT promoter in diffusely infiltrating gliomas (WHO grade II-IV) of adults

Diffusely infiltrating gliomas (WHO grade II-IV) are the most common primary brain tumours in adults. These tumours are not amenable to cure by surgery alone, so suitable biomarkers for adjuvant modalities are required to guide therapeutic decision-making. Epigenetic silencing of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene by promoter methylation has been associated with longer survival of patients with high-grade gliomas who receive alkylating chemotherapy; and molecular testing for the methylation status of the MGMT promoter sequence is regarded as among the most relevant of such markers. We have developed a primer extension-based assay adapted to formalin-fixed paraffin-embedded tissues that enables quantitative assessment of the methylation status of the MGMT promoter. The assay is very sensitive, highly reproducible, and provides valid test results in nearly 100% of cases. Our results indicate that oligodendrogliomas, empirically known to have a relatively favourable prognosis, are also the most homogeneous entities in terms of MGMT promoter methylation. Conversely, astrocytomas, which are more prone to spontaneous progression to higher grade malignancy, are significantly more heterogeneous. In addition, we show that the degree of promoter methylation correlates with the prevalence of loss of heterozygosity on chromosome arm 1p in the oligodendroglioma group, but not the astrocytoma group. Our results may have potentially important implications for clinical molecular diagnosis.

Learning Spike-Based Population Codes by Reward and Population Feedback

We investigate a recently proposed model for decision learning in a population of spiking neurons where synaptic plasticity is modulated by a population signal in addition to reward feedback. For the basic model, binary population decision making based on spike/no-spike coding, a detailed computational analysis is given about how learning performance depends on population size and task complexity. Next, we extend the basic model to n-ary decision making and show that it can also be used in conjunction with other population codes such as rate or even latency coding.

Primary tumors of the submandibular glands: a retrospective study based on 41 cases

We report our experience on the diagnostic approach, treatment, and follow-up of primary submandibular gland tumors. Retrospective review. Tertiary referral center. Forty-one adult patients, 22 male and 19 female, with primary submandibular gland tumors, 20 benign and 21 malignant. Age, gender, clinical findings, cyto- and histopathology, treatment and outcome were analyzed. Most tumors presented as a painless submandibular mass. Thirty three patients underwent a fine needle aspiration, the sensitivity, specificity and accuracy of which--in detecting malignant tumors--were 79%, 100% and 88%, respectively. Preoperative radiological imaging was performed in 30 cases. Patients with benign tumors were treated with surgery. Most malignant tumors were treated with a combined modality, including neck dissection and radiation therapy. Five patients developed a postoperative complication. Recurrent disease was encountered in 5 malignant tumors. The 2, 5 and 10 year disease-specific survival of patients with malignancy were 84%, 75% and 41%, respectively. The preoperative assessment of the nature of submandibular gland tumors remains challenging. Aggressive treatment of patients with malignant disease may help to avoid poor prognosis.

Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

Comparative metabolism of cyclophosphamide and ifosfamide in the mouse using UPLC-ESI-QTOFMS-based metabolomics

Ifosfamide (IF) and cyclophosphamide (CP) are common chemotherapeutic agents. Interestingly, while the two drugs are isomers, only IF treatment is known to cause nephrotoxicity and neurotoxicity. Therefore, it was anticipated that a comparison of IF and CP drug metabolites in the mouse would reveal reasons for this selective toxicity. Drug metabolites were profiled by ultra-performance liquid chromatography-linked electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOFMS), and the results analyzed by multivariate data analysis. Of the total 23 drug metabolites identified by UPLC-ESI-QTOFMS for both IF and CP, five were found to be novel. Ifosfamide preferentially underwent N-dechloroethylation, the pathway yielding 2-chloroacetaldehyde, while cyclophosphamide preferentially underwent ring-opening, the pathway yielding acrolein (AC). Additionally, S-carboxymethylcysteine and thiodiglycolic acid, two downstream IF and CP metabolites, were produced similarly in both IF- and CP-treated mice. This may suggest that other metabolites, perhaps precursors of thiodiglycolic acid, may be responsible for IF encephalopathy and nephropathy.

MRI-based breast volumetry-evaluation of three different software solutions

As lipofilling of the female breast is becoming more popular in plastic surgery, the use of MRI to assess breast volume has been employed to control postoperative results. Therefore, we sought to evaluate the accuracy of magnetic resonance imaging (MRI)-based breast volumetry software tools by comparing the measurements of silicone implant augmented breasts with the actual implant volume specified by the manufacturer. MRI-based volume analysis was performed in eight bilaterally augmented patients (46 ± 9 years) with three different software programs (Brainlab© I plan 2.6 neuronavigation software; mass analysis, version 5.3, Medis©; and OsiriX© v.3.0.2. 32-bit). The implant volumes analysed by the BrainLab© software had a mean deviation of 2.2 ± 1.7% (r?=?0.99) relative to the implanted prosthesis. OsiriX© software analysis resulted in a mean deviation of 2.8 ± 3.0% (r?=?0.99) and the Medis© software had a mean deviation of 3.1 ± 3.0% (r?=?0.99). Overall, the volumes of all analysed breast implants correlated very well with the real implant volumes. Processing time was 10 min per breast with each system and 30 s (OsiriX©) to 5 min (BrainLab© and Medis©) per silicone implant. MRI-based volumetry is a powerful tool to calculate both native breast and silicone implant volume in situ. All software solutions performed well and the measurements were close to the actual implant sizes. The use of MRI breast volumetry may be helpful in: (1) planning reconstructive and aesthetic surgery of asymmetric breasts, (2) calculating implant size in patients with missing documentation of a previously implanted device and (3) assessing post-operative results objectively.

A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm.