Molecular phylogenetics and temporal diversification in the genus Aeromonas based on the sequences of five housekeeping genes

Several approaches have been developed to estimate both the relative and absolute rates of speciation and extinction within clades based on molecular phylogenetic reconstructions of evolutionary relationships, according to an underlying model of diversification. However, the macroevolutionary models established for eukaryotes have scarcely been used with prokaryotes. We have investigated the rate and pattern of cladogenesis in the genus Aeromonas (γ-Proteobacteria, Proteobacteria, Bacteria) using the sequences of five housekeeping genes and an uncorrelated relaxed-clock approach. To our knowledge, until now this analysis has never been applied to all the species described in a bacterial genus and thus opens up the possibility of establishing models of speciation from sequence data commonly used in phylogenetic studies of prokaryotes. Our results suggest that the genus Aeromonas began to diverge between 248 and 266 million years ago, exhibiting a constant divergence rate through the Phanerozoic, which could be described as a pure birth process.

Generative models of the human connectome.

The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan.

Adjusting for the environment in DEA: a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of Data Envelopment Analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run their own efficiency analysis. Within DEA, several alternative models allow for an environmental adjustment. Four alternative models, each user-friendly and easily accessible to practitioners and decision makers, are performed using empirical data of 90 primary schools in the State of Geneva, Switzerland. Results show that the majority of alternative models deliver divergent results. From a political and a managerial standpoint, these diverging results could lead to potentially ineffective decisions. As no consensus emerges on the best model to use, practitioners and decision makers may be tempted to select the model that is right for them, in other words, the model that best reflects their own preferences. Further studies should investigate how an appropriate multi-criteria decision analysis method could help decision makers to select the right model.

Structure-Based, Rational Design of T Cell Receptors.

Adoptive cell transfer using engineered T cells is emerging as a promising treatment for metastatic melanoma. Such an approach allows one to introduce T cell receptor (TCR) modifications that, while maintaining the specificity for the targeted antigen, can enhance the binding and kinetic parameters for the interaction with peptides (p) bound to major histocompatibility complexes (MHC). Using the well-characterized 2C TCR/SIYR/H-2K(b) structure as a model system, we demonstrated that a binding free energy decomposition based on the MM-GBSA approach provides a detailed and reliable description of the TCR/pMHC interactions at the structural and thermodynamic levels. Starting from this result, we developed a new structure-based approach, to rationally design new TCR sequences, and applied it to the BC1 TCR targeting the HLA-A2 restricted NY-ESO-1157-165 cancer-testis epitope. Fifty-four percent of the designed sequence replacements exhibited improved pMHC binding as compared to the native TCR, with up to 150-fold increase in affinity, while preserving specificity. Genetically engineered CD8(+) T cells expressing these modified TCRs showed an improved functional activity compared to those expressing BC1 TCR. We measured maximum levels of activities for TCRs within the upper limit of natural affinity, K D = ∼1 - 5 μM. Beyond the affinity threshold at K D < 1 μM we observed an attenuation in cellular function, in line with the "half-life" model of T cell activation. Our computer-aided protein-engineering approach requires the 3D-structure of the TCR-pMHC complex of interest, which can be obtained from X-ray crystallography. We have also developed a homology modeling-based approach, TCRep 3D, to obtain accurate structural models of any TCR-pMHC complexes when experimental data is not available. Since the accuracy of the models depends on the prediction of the TCR orientation over pMHC, we have complemented the approach with a simplified rigid method to predict this orientation and successfully assessed it using all non-redundant TCR-pMHC crystal structures available. These methods potentially extend the use of our TCR engineering method to entire TCR repertoires for which no X-ray structure is available. We have also performed a steered molecular dynamics study of the unbinding of the TCR-pMHC complex to get a better understanding of how TCRs interact with pMHCs. This entire rational TCR design pipeline is now being used to produce rationally optimized TCRs for adoptive cell therapies of stage IV melanoma.

Classification models for neurocognitive impairment in HIV infection based on demographic and clinical variables

Objective: We used demographic and clinical data to design practical classification models for prediction of neurocognitive impairment (NCI) in people with HIV infection. Methods: The study population comprised 331 HIV-infected patients with available demographic, clinical, and neurocognitive data collected using a comprehensive battery of neuropsychological tests. Classification and regression trees (CART) were developed to btain detailed and reliable models to predict NCI. Following a practical clinical approach, NCI was considered the main variable for study outcomes, and analyses were performed separately in treatment-naïve and treatment-experienced patients. Results: The study sample comprised 52 treatment-naïve and 279 experienced patients. In the first group, the variables identified as better predictors of NCI were CD4 cell count and age (correct classification [CC]: 79.6%, 3 final nodes). In treatment-experienced patients, the variables most closely related to NCI were years of education, nadir CD4 cell count, central nervous system penetration-effectiveness score, age, employment status, and confounding comorbidities (CC: 82.1%, 7 final nodes). In patients with an undetectable viral load and no comorbidities, we obtained a fairly accurate model in which the main variables were nadir CD4 cell count, current CD4 cell count, time on current treatment, and past highest viral load (CC: 88%, 6 final nodes). Conclusion: Practical classification models to predict NCI in HIV infection can be obtained using demographic and clinical variables. An approach based on CART analyses may facilitate screening for HIV-associated neurocognitive disorders and complement clinical information about risk and protective factors for NCI in HIV-infected patients.

Evaluation of drug-induced neurotoxicity based on metabolomics, proteomics and electrical activity measurements in complementary CNS in vitro models.

The present study was performed in an attempt to develop an in vitro integrated testing strategy (ITS) to evaluate drug-induced neurotoxicity. A number of endpoints were analyzed using two complementary brain cell culture models and an in vitro blood-brain barrier (BBB) model after single and repeated exposure treatments with selected drugs that covered the major biological, pharmacological and neuro-toxicological responses. Furthermore, four drugs (diazepam, cyclosporine A, chlorpromazine and amiodarone) were tested more in depth as representatives of different classes of neurotoxicants, inducing toxicity through different pathways of toxicity. The developed in vitro BBB model allowed detection of toxic effects at the level of BBB and evaluation of drug transport through the barrier for predicting free brain concentrations of the studied drugs. The measurement of neuronal electrical activity was found to be a sensitive tool to predict the neuroactivity and neurotoxicity of drugs after acute exposure. The histotypic 3D re-aggregating brain cell cultures, containing all brain cell types, were found to be well suited for OMICs analyses after both acute and long term treatment. The obtained data suggest that an in vitro ITS based on the information obtained from BBB studies and combined with metabolomics, proteomics and neuronal electrical activity measurements performed in stable in vitro neuronal cell culture systems, has high potential to improve current in vitro drug-induced neurotoxicity evaluation.

Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.

Membrane interaction of a new synthetic antimicrobial lipopetide sp-85 with broad spectrum activity

Antimicrobial peptides offer a new class of therapeutic agents to which bacteria may not be able todevelop genetic resistance, since their main activity is in the lipid component of the bacterial cell mem-brane. We have developed a series of synthetic cationic cyclic lipopeptides based on natural polymyxin,and in this work we explore the interaction of sp-85, an analog that contains a C12 fatty acid at theN-terminus and two residues of arginine. This analog has been selected from its broad spectrum antibac-terial activity in the micromolar range, and it has a disruptive action on the cytoplasmic membrane ofbacteria, as demonstrated by TEM. In order to obtain information on the interaction of this analog withmembrane lipids, we have obtained thermodynamic parameters from mixed monolayers prepared withPOPG and POPE/POPG (molar ratio 6:4), as models of Gram positive and Gram negative bacteria, respec-tively. LangmuirBlodgett films have been extracted on glass plates and observed by confocal microscopy,and images are consistent with a strong destabilizing effect on the membrane organization induced bysp-85. The effect of sp-85 on the membrane is confirmed with unilamelar lipid vesicles of the same com-position, where biophysical experiments based on fluorescence are indicative of membrane fusion andpermeabilization starting at very low concentrations of peptide and only if anionic lipids are present.Overall, results described here provide strong evidence that the mode of action of sp-85 is the alterationof the bacterial membrane permeability barrier.

Studies on the Multifaceted Interaction of Atoms and an Electromagnetic Field

In this Thesis the interaction of an electromagnetic field and matter is studied from various aspects in the general framework of cold atoms. Our subjects cover a wide spectrum of phenomena ranging from semiclassical few-level models to fully quantum mechanical interaction with structured reservoirs leading to non-Markovian open quantum system dynamics. Within closed quantum systems, we propose a selective method to manipulate the motional state of atoms in a time-dependent double-well potential and interpret the method in terms of adiabatic processes. Also, we derive a simple wave-packet model, based on distributions of generalized eigenstates, explaining the finite visibility of interference in overlapping continuous-wave atom lasers. In the context of open quantum systems, we develop an unraveling of non-Markovian dynamics in terms of piecewise deterministic quantum jump processes confined in the Hilbert space of the reduced system - the non-Markovian quantum jump method. As examples, we apply it for simple 2- and 3-level systems interacting with a structured reservoir. Also, in the context of ion-cavity QED we study the entanglement generation based on collective Dicke modes in experimentally realistic conditions including photonic losses and an atomic spontaneous decay.

Viral and cellular modulation of virus-induced apoptosis in experimental infection models

The aim of this study was to investigate herpes simplex virus type 1 (HSV-1)- and measles virus (MV)-induced cell death. HSV-1 with deletion in genes encoding infected cell protein (ICP)4 and protein kinase Us3 (d120) induced apoptosis and cathepsin activation in epithelial (HEp-2) and monocytic (U937) cells. Inhibition of cathepsin activity decreased the amount of d120-induced apoptosis indicating that d120-induced apoptosis could be cathepsin-mediated. Also, HSV-1 infection increased caspase activation suggesting that d120-induced apoptosis is probably caspase-mediated. Cystatin treatment decreased the activity of cathepsins and the replication of HSV-1 indicating that cathepsins contribute to HSV-1 infection. Interestingly, d120 induced also necroptosis in monocytic cells. This is the first report on necroptosis in HSV-1- infected cells. MV induced apoptosis in uninfected bystander T lymphocytes, probably via interaction of MV-infected monocytes with uninfected lymphocytes. The expression of death receptor Fas was clearly increased on the surface of lymphocytes. The number of apoptotic cells and the activation of cathepsins and caspases were increased in MVinfected U937 cells suggesting that MV-induced apoptosis could be cathepsin- and caspase-mediated. Cystatin treatment inhibited cathepsin activities but not MV-induced apoptosis. Besides HSV-1-induced apoptosis, innate immune responses were studied in HSV-1-infection. HSV-1 viruses with either ICP4 and Us3, or Us3 deletion only, increased the expression of Toll-like receptor (TLR)3 and stimulated its downstream pathways leading to increased expression of type I interferon gene and to functional interferons. These findings suggest that besides controlling apoptosis, HSV-1 ICP4 and Us3 genes are involved in the control of TLR3 response in infected cell.

Management zones using fuzzy clustering based on spatial-temporal variability of soil and corn yield

Clustering soil and crop data can be used as a basis for the definition of management zones because the data are grouped into clusters based on the similar interaction of these variables. Therefore, the objective of this study was to identify management zones using fuzzy c-means clustering analysis based on the spatial and temporal variability of soil attributes and corn yield. The study site (18 by 250-m in size) was located in Jaboticabal, São Paulo/Brazil. Corn yield was measured in one hundred 4.5 by 10-m cells along four parallel transects (25 observations per transect) over five growing seasons between 2001 and 2010. Soil chemical and physical attributes were measured. SAS procedure MIXED was used to identify which variable(s) most influenced the spatial variability of corn yield over the five study years. Basis saturation (BS) was the variable that better related to corn yield, thus, semivariograms models were fitted for BS and corn yield and then, data values were krigged. Management Zone Analyst software was used to carry out the fuzzy c-means clustering algorithm. The optimum number of management zones can change over time, as well as the degree of agreement between the BS and corn yield management zone maps. Thus, it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately.

Scheduling of guarded command based models

Formal methods provide a means of reasoning about computer programs in order to prove correctness criteria. One subtype of formal methods is based on the weakest precondition predicate transformer semantics and uses guarded commands as the basic modelling construct. Examples of such formalisms are Action Systems and Event-B. Guarded commands can intuitively be understood as actions that may be triggered when an associated guard condition holds. Guarded commands whose guards hold are nondeterministically chosen for execution, but no further control flow is present by default. Such a modelling approach is convenient for proving correctness, and the Refinement Calculus allows for a stepwise development method. It also has a parallel interpretation facilitating development of concurrent software, and it is suitable for describing event-driven scenarios. However, for many application areas, the execution paradigm traditionally used comprises more explicit control flow, which constitutes an obstacle for using the above mentioned formal methods. In this thesis, we study how guarded command based modelling approaches can be conveniently and efficiently scheduled in different scenarios. We first focus on the modelling of trust for transactions in a social networking setting. Due to the event-based nature of the scenario, the use of guarded commands turns out to be relatively straightforward. We continue by studying modelling of concurrent software, with particular focus on compute-intensive scenarios. We go from theoretical considerations to the feasibility of implementation by evaluating the performance and scalability of executing a case study model in parallel using automatic scheduling performed by a dedicated scheduler. Finally, we propose a more explicit and non-centralised approach in which the flow of each task is controlled by a schedule of its own. The schedules are expressed in a dedicated scheduling language, and patterns assist the developer in proving correctness of the scheduled model with respect to the original one.

Roles of leadership in complex environments : Enhancing Knowledge Flows in Organisational Constellations through Practice-Based Innovation Processes

Global challenges, complexity and continuous uncertainty demand development of leadership approaches, employees and multi-organisation constellations. Current leadership theories do not sufficiently address the needs of complex business environments. First of all, before successful leadership models can be applied in practice, leadership needs to shift from the industrial age to the knowledge era. Many leadership models still view leadership solely through the perspective of linear process thinking. In addition, there is not enough knowledge or experience in applying these newer models in practice. Leadership theories continue to be based on the assumption that leaders possess or have access to all the relevant knowledge and capabilities to decide future directions without external advice. In many companies, however, the workforce consists of skilled professionals whose work and related interfaces are so challenging that the leaders cannot grasp all the linked viewpoints and cross-impacts alone. One of the main objectives of this study is to understand how to support participants in organisations and their stakeholders to, through practice-based innovation processes, confront various environments. Another aim is to find effective ways of recognising and reacting to diverse contexts, so companies and other stakeholders are better able to link to knowledge flows and shared value creation processes in advancing joint value to their customers. The main research question of this dissertation is, then, to seek understanding of how to enhance leadership in complex environments. The dissertation can, on the whole, be characterised as a qualitative multiple-case study. The research questions and objectives were investigated through six studies published in international scientific journals. The main methods applied were interviews, action research and a survey. The empirical focus was on Finnish companies, and the research questions were examined in various organisations at the top levels (leaders and managers) and bottom levels (employees) in the context of collaboration between organisations and cooperation between case companies and their client organisations. However, the emphasis of the analysis is the internal and external aspects of organisations, which are conducted in practice-based innovation processes. The results of this study suggest that the Cynefin framework, complexity leadership theory and transformational leadership represent theoretical models applicable to developing leadership through practice-based innovation. In and of themselves, they all support confronting contemporary challenges, but an implementable method for organisations may be constructed by assimilating them into practice-based innovation processes. Recognition of diverse environments, their various contexts and roles in the activities and collaboration of organisations and their interest groups is ever-more important to achieving better interaction in which a strategic or formal status may be bypassed. In innovation processes, it is not necessarily the leader who is in possession of the essential knowledge; thus, it is the role of leadership to offer methods and arenas where different actors may generate advances. Enabling and supporting continuous interaction and integrated knowledge flows is of crucial importance, to achieve emergence of innovations in the activities of organisations and various forms of collaboration. The main contribution of this dissertation relates to applying these new conceptual models in practice. Empirical evidence on the relevance of different leadership roles in practice-based innovation processes in Finnish companies is another valuable contribution. Finally, the dissertation sheds light on the significance of combining complexity science with leadership and innovation theories in research.

Task-based information interaction

Esitys KDK-käytettävyystyöryhmän järjestämässä seminaarissa: Miten käyttäjien toiveet haastavat metatietokäytäntöjämme? / How users' expectations challenge our metadata practices? 30.9.2014.

Numerical Studies of Dark Energy Models and Observations

The cosmological standard view is based on the assumptions of homogeneity, isotropy and general relativistic gravitational interaction. These alone are not sufficient for describing the current cosmological observations of accelerated expansion of space. Although general relativity is extremely accurately tested to describe the local gravitational phenomena, there is a strong demand for modifying either the energy content of the universe or the gravitational interaction itself to account for the accelerated expansion. By adding a non-luminous matter component and a constant energy component with negative pressure, the observations can be explained with general relativity. Gravitation, cosmological models and their observational phenomenology are discussed in this thesis. Several classes of dark energy models that are motivated by theories outside the standard formulation of physics were studied with emphasis on the observational interpretation. All the cosmological models that seek to explain the cosmological observations, must also conform to the local phenomena. This poses stringent conditions for the physically viable cosmological models. Predictions from a supergravity quintessence model was compared to Supernova 1a data and several metric gravity models were studied with local experimental results. Polytropic stellar configurations of solar, white dwarf and neutron stars were numerically studied with modified gravity models. The main interest was to study the spacetime around the stars. The results shed light on the viability of the studied cosmological models.