Le pois chiche (Cicer arietinum L.) a l’avantage de pouvoir assimiler l'azote atmosphérique grâce à son association symbiotique avec des bactéries du genre Mesorhizobium. Malgré cet effet bénéfique sur les systèmes culturaux, le pois chiche réduit parfois la productivité du blé qui la suit. Cet effet négatif du pois chiche pourrait provenir d’une réaction allélopathique à ses exsudats racinaires ou résidus, ou de changements inopportuns dans la communauté microbienne du sol induits par la plante. L'amélioration des interactions symbiotiques du pois chiche pourrait améliorer la performance économique et environnementale des systèmes culturaux basés sur le blé. L’objectif à long terme de ce travail est d'améliorer l’influence du pois chiches sur son environnement biologique et sur la productivité du système cultural. À court terme, nous voulons 1) vérifier l'effet des champignons endophytes sur la performance de cultivars de pois chiche de type desi et kabuli, particulièrement en conditions de stress hydrique, ainsi que sur celle d’une culture subséquente de blé dur, 2) identifier des cultivars de pois chiche capables d’améliorer la qualité biologique de sols cultivés, 3) vérifier que des composés biologiquement actifs sont présents dans les racines des différents cultivars de pois chiches et 4) définir la nature de l’activité (stimulation ou inhibition) des ces composés sur les champignons endomycorhiziens à arbuscules (CMA), qui sont des microorganismes bénéfiques du sol reconnus. L’inoculation du pois chiche avec des champignons endophytes indigènes en serre a augmenté la tolérance à la sécheresse du cultivar de type kabuli à feuille simple CDC Xena et amélioré la nutrition azotée et phosphatée d’un cultivar de type desi, cv. CDC Nika, cultivé en conditions de stress hydrique. La germination des graines de blé dur fut meilleure lorsque celles-ci étaient semées dans les débris de pois chiche inoculé de type kabuli. Le sol dans lequel le génotype de pois chiche à feuille simple CDC Xena fut cultivé mais duquel tout le matériel végétal de pois chiche fut retiré a fortement inhibé la germination des semences de blé dur, ce qui suggère un effet des exsudats racinaires sur la communauté microbienne du sol associée à cette variété de pois chiche. En champ, les cultivars de pois chiche ont influencé différemment la composition des communautés de champignons de la rhizosphère. Les espèces de champignons pathogènes étaient infréquentes et les espèces saprotrophiques et de CMA étaient fréquentes dans la zone des racines du cultivar de type desi CDC Anna. L’effet des composés contenus dans les fractions séparées par HPLC et solubles en solution de méthanol à 25% et 50% de l’extrait racinaire de ce cultivar sur la germination de spores de CMA a été testé in vitro. Les deux espèces de CMA utilisées ont répondu différemment à l’exposition aux composés testés, révélant un mécanisme impliqué dans l’association préférentielle entre les plantes hôtes et les CMA qui leurs sont associés. Nous concluons que le génotype de pois chiche influence la composition de la communauté microbienne qui lui est associée et que cette influence est reliée au moins en partie aux molécules bioactives produites par les racines de la plante. D’autre part, la productivité du pois chiche et de la culture subséquente pourrait être favorisée par la manipulation de leurs champignons endophytes par inoculation. / Chickpea (Cicer arietinum L.) has the ability to bring free N into cropping systems, but is only a fair rotation crop, leading to lower yield in following wheat crops, as compared to medic, vetch or lentil. The negative effects of a chickpea plant on the following wheat crops could come from chickpea root exudates, their residues or their influence on the soil microbial community. The identification of chickpea cultivars best able to promote soil biological quality and the growth of a subsequent crop in rotation will help farmers in selecting better crop rotations and, thus, will improve crop management in soil zone growing chickpea. The global objective of this research is to improve the fitness of chickpea crops to their biological environment and to improve the ability of the plant to enhance soil biological quality. The specific objectives were (1) to verify that the productivity of chickpea and subsequent crops could be promoted through the inoculation by some indigenous endophytic fungi particularly under drought stress conditions (2) to verify the existence of variation in the rhizospheric associations of field-grown chickpea, as it is a necessary condition for the selection of genotypes with improved compatibility with beneficial microorganisms. (3) to identify the biologically active compounds present in the root extracts of chickpea cultivars with contrasting phenotypes, and assess their effect on beneficial and pathogenic soil microorganisms. The greenhouse experiments show that inoculation with indigenous endophytes increased drought tolerance of the unifoliate Kabuli chickpea CDC Xena and the N and P nutrition of the drought stressed Desi chickpea CDC Nika. Inoculation of both Kabuli chickpea varieties with indigenous endophytes improved wheat seeds germination in tissues amended soil. Residue-free soil previously growing the unifoliate Kabuli chickpea CDC Xena strongly inhibited durum seed germination suggesting an effect of root exudates on the soil microbial community, with this Kabuli chickpea variety. In a field experiment, the fungal diversity in cultivated Prairie dryland appeared to host a large array of fungal groups known to reduced plant nutrient, water and biotic stresses, and chickpea genotypes influenced differently the composition and biomass of the soil microbial community. The Desi chickpea CDC Anna was associated with high diversity of arbuscular mycorrhizal fungi (AMF) and culturable fungi, favored the proliferation of soil bacteria and fungal genus hosting biocontrol agents, and developed high AM root colonization level, as compared to the three Kabuli genotypes examined. The HPLC fractions of the roots of chickpea cultivar CDC Anna were recovered and the effects of these fractions on AM fungal spore germination were assayed in multi-well plates. Root extract fractions affect in a different ways the percentage of spores’ germination of Glomus etunicatum and Gigaspora Rosea. We concluded that the genotype of chickpea plants influences the composition of the associated microbial community, and this influence may be related to molecular signals produced by the plants. Furthermore, the productivity of chickpea and subsequent crops could be promoted through the inoculation with indigenous endophytic fungi. / réalisé en cotutelle avec la Faculté des Sciences de Tunis, Université Tunis El Manar.

During face-to-face meetings, humans use multimodal information, including verbal information, visual information, body language, facial expressions, and other non-verbal gestures. In contrast, during computer-mediated-communication (CMC), humans rely either on mono-modal information such as text-only, voice-only, or video-only or on bi-modal information by using audiovisual modalities such as video teleconferencing. Psychologically, the difference between the two lies in the level of the subjective experience of presence, where people perceive a reduced feeling of presence in the case of CMC. Despite the current advancements in CMC, it is still far from face-to-face communication, especially in terms of the experience of presence. This thesis aims to introduce new concepts, theories, and technologies for presence design where the core is actions for creating presence. Thus, the contribution of the thesis can be divided into a technical contribution and a knowledge contribution. Technically, this thesis details novel technologies for improving presence experience during mediated communication (video teleconferencing). The proposed technologies include action robots (including a telepresence mechatronic robot (TEBoT) and a face robot), embodied control techniques (head orientation modeling and virtual reality headset based collaboration), and face reconstruction/retrieval algorithms. The introduced technologies enable action possibilities and embodied interactions that improve the presence experience between the distantly located participants. The novel setups were put into real experimental scenarios, and the well-known social, spatial, and gaze related problems were analyzed. The developed technologies and the results of the experiments led to the knowledge contribution of this thesis. In terms of knowledge contribution, this thesis presents a more general theoretical conceptual framework for mediated communication technologies. This conceptual framework can guide telepresence researchers toward the development of appropriate technologies for mediated communication applications. Furthermore, this thesis also presents a novel strong concept – presence through actions - that brings in philosophical understandings for developing presence- related technologies. The strong concept - presence through actions is an intermediate-level knowledge that proposes a new way of creating and developing future 'presence artifacts'. Presence- through actions is an action-oriented phenomenological approach to presence that differs from traditional immersive presence approaches that are based (implicitly) on rationalist, internalist views.

Advances in unsupervised learning and deep neural networks have led to increased performance in a number of domains, and to the ability to draw strong comparisons between the biological method of self-organization conducted by the brain and computational mechanisms. This thesis aims to use real-world data to tackle two areas in the domain of computer vision which have biological equivalents: feature detection and motion tracking. The aforementioned advances have allowed efficient learning of feature representations directly from large sets of unlabeled data instead of using traditional handcrafted features. The first part of this thesis evaluates such representations by comparing regularization and preprocessing methods which incorporate local neighbouring information during training on a single-layer neural network. The networks are trained and tested on the Hollywood2 video dataset, as well as the static CIFAR-10, STL-10, COIL-100, and MNIST image datasets. The induction of topography or simple image blurring via Gaussian filters during training produces better discriminative features as evidenced by the consistent and notable increase in classification results that they produce. In the visual domain, invariant features are desirable such that objects can be classified despite transformations. It is found that most of the compared methods produce more invariant features, however, classification accuracy does not correlate to invariance. The second, and paramount, contribution of this thesis is a biologically-inspired model to explain the emergence of motion tracking behaviour in early development using unsupervised learning. The model’s self-organization is biased by an original concept called retinal constancy, which measures how similar visual contents are between successive frames. In the proposed two-layer deep network, when exposed to real-world video, the first layer learns to encode visual motion, and the second layer learns to relate that motion to gaze movements, which it perceives and creates through bi-directional nodes. This is unique because it uses general machine learning algorithms, and their inherent generative properties, to learn from real-world data. It also implements a biological theory and learns in a fully unsupervised manner. An analysis of its parameters and limitations is conducted, and its tracking performance is evaluated. Results show that this model is able to successfully follow targets in real-world video, despite being trained without supervision on real-world video.

Diploma thesis will be dealt with the utilization of ozone wastewater treatment. Experimental part will be focused on study of ozone utilization in two different reactors (bubble column, jet loop reactor). Reactors will be compared by overall mass transfer coefficient and saturation concentration. Ozonization will be applied because of biological resistent and toxic compound 2-mercaptobenzothiazole disposal. Changes of biological decomposition will be measured and assessed by respirometric measurements.

Present Ph.D. Thesis is focused on the development of electrochemical methods for determination of anticancer drugs using various types of membranes for their preliminary separation. Furthermore, this Thesis reports the study of transport mechanisms of heavy metals in the presence of phytochelatins across biological membranes. Sodium anthraquinone-2-sulphonate (AQS) was used as a model compound for its similar structure with anthraquinone-based (AQ-based) anticancer drugs (doxo/daunorubicin) and also due to its better availability. All these compounds can be easily electrochemically oxidized and/or reduced. Redox behaviour of AQS was investigated by cyclic voltammetry (CV) and differential pulse voltammetry (DPV) in a cathodic region on mercury meniscus modified (m-AgSAE) and polished silver solid amalgam (p-AgSAE) electrodes, Obtained results were used for the development of a micro-volume voltammetric cell (MVVC). Its applicability for voltammetric determination of anticancer drugs was verified by using doxorubicin (DX) as a model substance. The second part of this Thesis deals with therapeutic monitoring of anticancer drugs in the blood circulation of the patients. For pilot experiments, a liquid-flow system with dialysis catheter and amperometric detection was used. The flow rate of carrier...

<p>Microglia are a population of specialized, tissue-resident immune cells that make up around 10% of total cells in our brain. They actively prune neuronal synapses, engulf cellular debris, and misfolded protein aggregates such as the Alzheimer’s Disease (AD)-associated amyloid-beta (Aβ) by the process of phagocytosis. During AD, microglia are unable to phagocytose Aβ, perhaps due to the several disease-associated changes affecting their normal function. Functional molecules such as lipids and metabolites also influence microglial behavior but have primarily remained uncharacterized to date. The overarching question of this work is, <i>How do microglia become dysfunctional in chronic inflammation</i>? To this end, we developed new chemical tools to better understand and investigate the microglial response to Aβ <i>in vitro</i> and <i>in vivo</i>. Specifically, we introduce three new tools. (1) Recombinant human Aβ was developed via a rapid, refined, and robust method for expressing, purifying, and characterizing the protein. (2) A pH-sensitive fluorophore conjugate of Aβ (called Aβ^pH) was developed to identify and separate Aβ-specific phagocytic and non-phagocytic glial cells <i>ex vivo</i> and <i>in vivo</i>. (3) New lysosomal, mitochondrial, and nuclei-targeting pH-activable fluorescent probes (called LysoShine, MitoShine, and NucShine, respectively) to visualize subcellular organelles in live microglia. Next, we asked, <i>What changes occur to the global lipid and metabolite profiles of microglia in the presence of Aβ in vitro and in vivo</i>? We screened 1500 lipids comprising 10 lipid classes and 700 metabolites in microglia exposed to Aβ. We found significant changes in specific lipid classes with acute and prolonged Aβ exposure. We also identified a lipid-related protein that was differentially regulated due to Aβ <i>in vivo</i>. This new lipid reprogramming mechanism “turned on” in the presence of cellular stress was also present in microglia in the brains of the 5xFAD mouse model, suggesting a generic response to inflammation and toxicity. It is well known that activated microglia induce reactive astrocytes during inflammation. Therefore, we asked, <i>What changes in proteins, lipids, and metabolites occur in astrocytes due to their reactive state? </i>We provide a comprehensive characterization of reactive astrocytes comprising 3660 proteins, 1500 lipids, and 700 metabolites. These microglia and astrocytes datasets will be available to the scientific community as a web application. We propose a final model wherein the molecules secreted by reactive astrocytes may also induce lipid-related changes to the microglial cell state in inflammation. In conclusion, this thesis highlights chemical neuroimmunology as the new frontier of neuroscience propelled by the development of new chemical tools and techniques to characterize glial cell states and function in neurodegeneration.</p>

Indiana University-Purdue University Indianapolis (IUPUI) / Proteins are nano-machines that work inside every living organism. Functional disruption of one or several proteins is the cause for many diseases. However, the functions for most proteins are yet to be annotated because inexpensive sequencing techniques dramatically speed up discovery of new protein sequences (265 million and counting) and experimental examinations of every protein in all its possible functional categories are simply impractical. Thus, it is necessary to develop computational function-prediction tools that complement and guide experimental studies. In this study, we developed a series of predictors for highly accurate prediction of proteins with DNA-binding, RNA-binding and carbohydrate-binding capability. These predictors are a template-based technique that combines sequence and structural information with predicted binding affinity. Both sequence and structure-based approaches were developed. Results indicate the importance of binding affinity prediction for improving sensitivity and precision of function prediction. Application of these methods to the human genome and structure genome targets demonstrated its usefulness in annotating proteins of unknown functions and discovering moon-lighting proteins with DNA,RNA, or carbohydrate binding function. In addition, we also investigated disruption of protein functions by naturally occurring genetic variations due to insertions and deletions (INDELS). We found that protein structures are the most critical features in recognising disease-causing non-frame shifting INDELs. The predictors for function predictions are available at http://sparks-lab.org/spot, and the predictor for classification of non-frame shifting INDELs is available at http://sparks-lab.org/ddig.

Indiana University-Purdue University Indianapolis (IUPUI) / There have been many endeavors to design humanoid robots that have human characteristics such as dexterity, autonomy and intelligence. Humanoid robots are intended to cooperate with humans and perform useful work that humans can perform. The main advantage of humanoid robots over other machines is that they are flexible and multi-purpose. In this thesis, a human-like robotic arm is designed and used in a task which is typically performed by humans, namely, catching a ball. The robotic arm was designed to closely resemble a human arm, based on anthropometric studies. A rigid multibody dynamics software was used to create a virtual model of the robotic arm, perform experiments, and collect data. The inverse kinematics of the robotic arm was solved using a Newton-Raphson numerical method with a numerically calculated Jacobian. The system was validated by testing its ability to find a kinematic solution for the catch position and successfully catch the ball within the robot's workspace. The tests were conducted by throwing the ball such that its path intersects different target points within the robot's workspace. The method used for determining the catch location consists of finding the intersection of the ball's trajectory with a virtual catch plane. The hand orientation was set so that the normal vector to the palm of the hand is parallel to the trajectory of the ball at the intersection point and a vector perpendicular to this normal vector remains in a constant orientation during the catch. It was found that this catch orientation approach was reliable within a 0.35 x 0.4 meter window in the robot's workspace. For all tests within this window, the robotic arm successfully caught and dropped the ball in a bin. Also, for the tests within this window, the maximum position and orientation (Euler angle) tracking errors were 13.6 mm and 4.3 degrees, respectively. The average position and orientation tracking errors were 3.5 mm and 0.3 degrees, respectively. The work presented in this study can be applied to humanoid robots in industrial assembly lines and hazardous environment recovery tasks, amongst other applications.

<p>Drug discovery and development has experienced a tremendous growth in the recent</p> <p>years, and methods to accelerate the process are necessary as the demand for effective drugs</p> <p>to treat a wide range of diseases continue to increase. Nevertheless, the majority of conventional</p> <p>techniques are labor-intensive or have relatively low yields. As a result, academia</p> <p>and the pharmaceutical industry are continuously seeking for rapid and efficient methods to</p> <p>accelerate the drug discovery pipeline. Therefore, in order to expedite the drug discovery</p> <p>process, recent developments in physical and artificial intelligence models have been utilized</p> <p>extensively. However, the overarching problem is how to use these cutting-edge advancements</p> <p>in artificial intelligence to enhance drug discovery? Therefore, this dissertation work</p> <p>focused on developing and applying artificial intelligence and physical models to accelerate</p> <p>the drug discovery pipeline at different stages. As the first study reported in the dissertation,</p> <p>the potential to apply graph neural network-based machine learning architectures</p> <p>with the assistance of molecular modeling features to identify plausible drug leads out of</p> <p>structurally similar chemical databases is assessed. Then, the capability of applying molecular</p> <p>modeling methods including molecular docking and molecular dynamics simulations to</p> <p>identify prospective targets and biological pathways for small molecular drugs is discussed</p> <p>and evaluated in the following chapter. Further, the capability of applying state-of-the-art</p> <p>deep learning architectures such as multi-layer perceptron and recurrent neural networks</p> <p>to optimize the formulation development stage has been assessed. Moreover, this dissertation</p> <p>has contributed to assist functionality identification of unknown compounds using</p> <p>simple machine learning based computational frameworks. The developed omics data analysis</p> <p>pipeline is then discussed in order to comprehend the effects of a particular treatment</p> <p>on the proteome and lipidome levels of cells. In conclusion, the potential for developing and</p> <p>utilizing various artificial intelligence-based approaches to accelerate the drug discovery and</p> <p>development process is explored in this research. Thus, these collaborative studies intend</p> <p>to contribute to ongoing acceleration efforts and advancements in the drug discovery and</p> <p>development field.</p>

<p dir="ltr">The BRG1/BRM-associated factor (BAF) complexes, also called SWI/SNF, are multi-subunit chromatin remodelers that regulate chromatin compaction in an ATP-dependent manner. In the past decade, BAF complexes have been under the spotlight in cancer research, especially after proteomic analyses revealed the genes encoding the subunits are amongst the most frequently mutated genes in cancer. The present dissertation focuses on prostate cancer (PCa), a disease in which the role of the BAF subunits is increasingly being explored but is yet to be defined as a potential therapeutic target. According to the GLOBOCAN report, PCa is the second most frequent cancer in males worldwide. Since most of the variants of PCa rely on the androgen receptor (AR) axis, surgical or chemical castration and androgen deprivation therapy (ADT) are the main treatment strategies for PCa patients. Even though these therapeutic approaches prolong survival, reduce tumor burden, and relieve symptoms, PCa patients eventually relapse and develop castration resistant PCa (CRPC). At present, the mechanisms underlying ADT resistance are not fully understood, current efforts focus on finding new targets for PCa treatment.</p><p dir="ltr">In the projects included in this dissertation we explored the function of the PBAF complex, a BAF subtype, in a variety of models of PCa and its potential as a therapeutic target by inhibiting or depleting its different subunits. To do so we (i) developed the first inhibitors for BRD7 (a subunit unique to PBAF) and (ii) established cell-based assays in multiple PCa cell lines to study BRD7 and other PBAF unique subunits.</p><p dir="ltr">Bromodomain-containing proteins are readers of acetylated lysine and play important roles in cancer. Bromodomain-containing protein 7 (BRD7) has been implicated in multiple malignancies; however, there are no selective chemical probes to study its function in disease. Using crystal structures of BRD7 and BRD9 bromodomains (BDs) bound to BRD9-selective ligands, we identified a binding pocket exclusive to BRD7. We synthesized a series of ligands designed to occupy this binding region and identified two inhibitors with increased selectivity towards BRD7, 1-78 and 2-77, which bind with submicromolar affinity to the BRD7 BD. Our binding mode analyses indicate that these ligands occupy a uniquely accessible binding cleft in BRD7 and maintain key interactions with the asparagine and tyrosine residues critical for acetylated lysine binding. Finally, we validated the utility and selectivity of the compounds in cell-based models of prostate cancer.</p><p dir="ltr">There are three BAF complexes that have been biochemically characterized up to date: canonical BAF (cBAF), polybromo-associated BAF (PBAF) and GLTSCR1/like-containing BAF (GBAF or ncBAF). All BAF complexes are characterized by containing an ATPase and accessory subunits that may be shared between them or unique to each subtype. PBAF, the BAF subtype of interest of this dissertation, contains four unique subunits: BRD7, PBRM1, ARID2 and BAF45A. We showed that knocking down BRD7 and ARID2 leads to reduction of cell viability in PCa cells with ligand-dependent and independent AR signaling, while knocking down PBRM1 leads to reduction in viability of cells with only ligand-dependent AR signaling. We also performed a chromatin immunoprecipitation assay with BAF45A and observed that it does not colocalize with AR binding sites, indicating that the mechanism by which PBAF regulates AR signaling is indirect. This observation was further supported by the fact that knocking down BRD7 prevents expression of genes related to adaptive processes, but not AR target genes, in response to androgen treatment. Further mechanistic studies will aid in understanding the function of PBAF in PCa. However, overall, our results indicate that PBAF is a promising therapeutic target in PCa models expressing AR, including CRPC systems.</p>