Activation de la voie oncogénique mTOR par les formes mutées de l'isocitrate déshydrogénase 1/2 retrouvées chez les gliomes

Une des caractéristiques principales des cellules cancéreuses est la reprogrammation de leur métabolisme énergétique. Des mutations d’enzymes impliquées dans différentes voies métaboliques sont récurrentes chez plusieurs tumeurs, contribuant ainsi à la dérégulation de ces cellules et à l’oncogénèse. C’est le cas de l’isocitrate déshydrogénase 1 (IDH1) et 2 (IDH2), responsables de la conversion de l’isocitrate en α-kétoglutarate dans le cycle de l’acide citrique. Ces enzymes sont fréquemment mutées chez les gliomes, acquérant ainsi la capacité de convertir l’α-kétoglutarate en 2-hydroxyglutarate (2HG), un oncométabolite inhibant les oxygénases α-kétoglutarate dépendantes parmi lesquelles figure notamment KDM4A, une déméthylase de lysines. À la recherche de nouvelles voies oncogéniques potentiellement régulées par les formes mutées de IDH1/2, nous avons initialement observé que les mutations de ces deux enzymes et de PTEN, un régulateur négatif de la voie mTOR, étaient mutuellement exclusives chez les gliomes. Ceci suggère que les mutations de IDH1/2 reproduiraient certains effets engendrés par les mutations de PTEN, créant ainsi un environnement oncogénique similaire. Nous avons observé que les formes mutées de IDH1/2 stimulent l’activation de mTOR grâce à la production et l’accumulation de 2HG. Cette activation repose en partie sur l’inhibition de KDM4A par cet oncométabolite. KDM4A est impliqué dans la stabilisation de DEPTOR, un inhibiteur de mTOR. Ainsi, l’inhibition de KDM4A par le 2HG entraîne la déstabilisation de DEPTOR et, par conséquent, l’activation de mTOR. Nos travaux ont donc permis l’identification d’un nouveau mécanisme oncogénique régulé par les formes mutées de IDH1/2 retrouvées chez les gliomes, soit l’activation de mTOR.

Implicating the mechanisms of ADP-ribosylation factor activation in the resistance of invasive breast cancer cells to EGFR tyrosine kinase inhibitors

ADP-ribosylation factor-1 (ARF1) est une petite GTPase principalement connue pour son rôle dans la formation de vésicules au niveau de l’appareil de Golgi. Récemment, dans des cellules de cancer du sein, nous avons démontré qu’ARF1 est aussi un médiateur important de la signalisation du récepteur du facteur de croissance épidermique (EGFR) contrôlant la prolifération, la migration et l'invasion cellulaire. Cependant, le mécanisme par lequel l’EGFR active la GTPase ainsi que le rôle de cette dernière dans la régulation de la fonction du récepteur demeure inconnue. Dans cette thèse, nous avions comme objectifs de définir le mécanisme d'activation de ARF1 dans les cellules de cancer du sein hautement invasif et démontrer que l’activation de cette isoforme de ARF joue un rôle essentiel dans la résistance de ces cellules aux inhibiteurs de l'EGFR. Nos études démontrent que les protéines d’adaptatrices Grb2 et p66Shc jouent un rôle important dans l'activation de ARF1. Alors que Grb2 favorise le recrutement d’ARF1 à l'EGFR ainsi que l'activation de cette petite GTPase, p66Shc inhibe le recrutement du complexe Grb2-ARF1 au récepteur et donc contribue à limiter l’activation d’ARF1. De plus, nous démontrons que ARF1 favorise la résistance aux inhibiteurs des tyrosines kinases dans les cellules de cancer du sein hautement invasif. En effet, une diminution de l’expression de ARF1 a augmenté la sensibilité descellules aux inhibiteurs de l'EGFR. Nous montrons également que de hauts niveaux de ARF1 contribuent à la résistance des cellules à ces médicaments en améliorant la survie et les signaux prolifératifs à travers ERK1/2, Src et AKT, tout en bloquant les voies apoptotiques (p38MAPK et JNK). Enfin, nous mettons en évidence le rôle de la protéine ARF1 dans l’apoptose en réponse aux traitements des inhibiteurs de l’EGFR. Nos résultats indiquent que la dépletion d’ARF1 promeut la mort cellulaire induite par gefitinib, en augmentant l'expression de facteurs pro-apoptotiques (p66shc, Bax), en altérant le potentiel de la membrane mitochondriale et la libération du cytochrome C. Ensemble, nos résultats délimitent un nouveau mécanisme d'activation de ARF1 dans les cellules du cancer du sein hautement invasif et impliquent l’activité d’ARF1 comme un médiateur important de la résistance aux inhibiteurs EGFR.

Activation of Progesterone Receptor by ATP

Progesterone-receptor complex from freshly prepared hen oviduct cytosol acquired the ability to bind to isolated nuclei, DNA-cellulose and ATP-Sepharose when incubated with 5-10 mM ATP at 4°C. The extent of this ATP-dependent activation was higher when compared with heat-activation achieved by warming the progesterone- receptor complex at 23 °C. The transformation of progesterone-receptor complex which occurred in a time-dependent manner was only partially dependent on hormone presence. The ATP effect was selective in causing this transformation whereas ADP, AMP and cAMP failed to show any such effect. The non-hydrolizable analogs of ATP, adenosine 5'-[a,/3-methylene]triphosphate and adenosine 5-[/l,y-imido]triphosphate were also found to be ineffective. Presence of 10 mM sodium molybdate blocked both the ATP and the heat-activation of progesterone-receptor complex. Mn" or Mg` had no detectable effect on the receptor activation but the presence of Ca" increased the extent of ATP-activation slightly. EDTA presence (> 5 mM) decreased the extent of receptor activation by about 40 % and was, therefore, not included in the buffers used for activation studies. Divalent cations were also ineffective when tested in the presence of 1- 5 mM EDTA. The properties of progesterone-receptor complex remained intact under the above conditions when analyzed for steroid-binding specificity and Scatchard analysis. However, the ATP-activated progesterone-receptor complex lost the ability to aggregate when tested on low-salt sucrose gradients. ATP was equally effective in activating the rat-uterine estradiol-receptor complex at 4 "C and influenced the transformation of 4-S receptor form into a 5-S form when analyzed on sucrose gradients containing 0.3 M KCI. The presence of ATP also increased the rate of activation of progesterone-receptor complex at 23 °C. These findings suggest a role for ATP in receptor function and offer a convenient method of studying the process of receptor activation at low temperature and mild assay conditions.

Polyaniline as an Automatic Beam Steering Material

This 'study' deals with a preliminary study of automatic beam steering properly in conducting polyaniline . Polyaniline in its undoped and doped .state was prepared from aniline by the chemical oxidative polymerization method. Dielectric properties of the samples were studied at S-band microwave frequencies using cavity perturbation technique. It is found that undoped po/vanihne is having greater dielectric loss and conductivity contpared with the doped samples. The beam steering property is studied using a perspex rod antenna and HP 85/OC vector network analyzer. The shift in the radiated beam is studied for different do voltages. The results show that polyaniline is a good nutterial far beam steering applications.

Electron donor sites on Y2O3 catalyst as a function of the activation temperature

Cochin University of Science and Technology

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

Molecular characterization of the nitrifying bacterial consortia employed for the activation of bioreactors used in brackish and marine aquaculture systems

The addition of commercial nitrifying bacterial products has resulted in significant improvement of nitrification efficiency in recirculating aquaculture systems (RAS). We developed two nitrifying bacterial consortia (NBC) from marine and brackish water as start up cultures for immobilizing commercialized nitrifying bioreactors for RAS. In the present study, the community compositions of the NBC were analyzed by universal 16S rRNA gene and bacterial amoA gene sequencing and fluorescence in situ hybridization (FISH). This study demonstrated that both the consortia involved autotrophic nitrifiers, denitrifiers as well as heterotrophs. Abundant taxa of the brackish water heterotrophic bacterial isolates were Paenibacillus and Beijerinckia spp. whereas in the marine consortia they were Flavobacterium, Cytophaga and Gramella species. The bacterial amoA clones were clustered together with high similarity to Nitrosomonas sp. and uncultured beta Proteobacteria. FISH analysis detected ammonia oxidizers belonging to b subclass of proteobacteria and Nitrosospira sp. in both the consortia, and Nitrosococcus mobilis lineage only in the brackish water consortium and the halophilic Nitrosomonas sp. only in the marine consortium. However, nitrite oxidizers, Nitrobacter sp. and phylum Nitrospira were detected in both the consortia. The metabolites from nitrifiers might have been used by heterotrophs as carbon and energy sources making the consortia a stable biofilm.

Automatic Image Annotation Using SURF Descriptors

In recent years there is an apparent shift in research from content based image retrieval (CBIR) to automatic image annotation in order to bridge the gap between low level features and high level semantics of images. Automatic Image Annotation (AIA) techniques facilitate extraction of high level semantic concepts from images by machine learning techniques. Many AIA techniques use feature analysis as the first step to identify the objects in the image. However, the high dimensional image features make the performance of the system worse. This paper describes and evaluates an automatic image annotation framework which uses SURF descriptors to select right number of features and right features for annotation. The proposed framework uses a hybrid approach in which k-means clustering is used in the training phase and fuzzy K-NN classification in the annotation phase. The performance of the system is evaluated using standard metrics.

The Effect of SIFT Features as Content Descriptors in the Context of Automatic Writer Identification in Malayalam Language

The span of writer identification extends to broad domes like digital rights administration, forensic expert decisionmaking systems, and document analysis systems and so on. As the success rate of a writer identification scheme is highly dependent on the features extracted from the documents, the phase of feature extraction and therefore selection is highly significant for writer identification schemes. In this paper, the writer identification in Malayalam language is sought for by utilizing feature extraction technique such as Scale Invariant Features Transform (SIFT).The schemes are tested on a test bed of 280 writers and performance evaluated

Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques

This paper describes a novel framework for automatic segmentation of primary tumors and its boundary from brain MRIs using morphological filtering techniques. This method uses T2 weighted and T1 FLAIR images. This approach is very simple, more accurate and less time consuming than existing methods. This method is tested by fifty patients of different tumor types, shapes, image intensities, sizes and produced better results. The results were validated with ground truth images by the radiologist. Segmentation of the tumor and boundary detection is important because it can be used for surgical planning, treatment planning, textural analysis, 3-Dimensional modeling and volumetric analysis

A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing

Automatic Optic Disc Boundary Extraction from Color Fundus Images

Efficient optic disc segmentation is an important task in automated retinal screening. For the same reason optic disc detection is fundamental for medical references and is important for the retinal image analysis application. The most difficult problem of optic disc extraction is to locate the region of interest. Moreover it is a time consuming task. This paper tries to overcome this barrier by presenting an automated method for optic disc boundary extraction using Fuzzy C Means combined with thresholding. The discs determined by the new method agree relatively well with those determined by the experts. The present method has been validated on a data set of 110 colour fundus images from DRION database, and has obtained promising results. The performance of the system is evaluated using the difference in horizontal and vertical diameters of the obtained disc boundary and that of the ground truth obtained from two expert ophthalmologists. For the 25 test images selected from the 110 colour fundus images, the Pearson correlation of the ground truth diameters with the detected diameters by the new method are 0.946 and 0.958 and, 0.94 and 0.974 respectively. From the scatter plot, it is shown that the ground truth and detected diameters have a high positive correlation. This computerized analysis of optic disc is very useful for the diagnosis of retinal diseases

Lateral spreading in basal reinforced embankments supported by pile-like elements

Bei Dämmen auf wenig tragfähigem Untergrund ist es zwischenzeitlich Stand der Technik, an der Dammbasis eine Bewehrung aus hochzugfesten Geokunststoffen (Gewebe oder Geogitter) einzulegen. Dabei können die Bewehrungslagen direkt auf den weichen Boden oder über Pfahlelementen angeordnet werden, die die Dammlasten in tiefere, tragfähigere Schichten abtragen. Die horizontale Bewehrung an der Dammbasis hat die Aufgabe, die vertikalen Dammlasten und die nach außen wirkenden Spreizkräfte aufzunehmen. Dies ist besonders für bewehrte Tragschichten über Pfählen von großer Bedeutung, da sonst die Pfähle/Säulen eine Biegebeanspruchung erhalten, die sie aufgrund des geringen Durchmessers (oftmals unbewehrt) nicht aufnehmen können. Abgesicherte wissenschaftliche Erkenntnisse über Größe und Verteilung der Spreizspannung in Höhe ober- und unterhalb der Bewehrungslagen liegen derzeit noch nicht vor, aus denen dann auch die Beanspruchung abzuleiten ist, die aus der Spreizwirkung bei der Geokunststoffbemessung zu berücksichtigen ist. Herr Dr.-Ing. Gourge Fahmi hat dafür zunächst den Kenntnisstand zur Spreizbeanspruchung ohne und mit Bewehrung sowie ohne und mit Pfahlelementen zusammengefasst. Ein wesentlicher Teil einer wissenschaftlichen Untersuchungen stellt die Modellversuche in einem relativ großen Maßstab dar, die u. a. auch zur Validierung von numerischen Berechnungen zur Fragestellung vorgesehen waren. Dabei konnte nach gewissen Parameteranpassungen überwiegend eine gute Übereinstimmung zwischen Modellversuchen und FEM-Berechnungen erreicht werden. Lediglich bei den Dehnungen bzw. Zugkräften in den Geogittern über Pfahlelementen ergab die FEM bei dem verwendeten Programmsystem viel zu niedrige Werte. Es wurde dazu in der Arbeit anhand eigener Untersuchungen und Vergleichsergebnissen aus der Literatur eine Hypothese formuliert und zunächst die Berechnungsergebnisse mit einem Faktor angepasst. Mit den durchgeführten Verifikationen stand damit dann ein weitestgehend abgesichertes numerisches Berechnungsmodell zur Verfügung. Aufbauend auf diesen Vorarbeiten konnten Parameterstudien mit numerischen und analytischen Methoden zur Spreizproblematik durchgeführt werden. Dabei wurden die Randbedingungen und Parametervariationen sinnvoll und für die Fragestellung zutreffend gewählt. Die numerischen Verfahren ergaben vertiefte Erkenntnisse zur Mechanik und zum Verhalten der Konstruktion. Die analytischen Vergleichsberechnungen validierten primär die Güte dieser vereinfachten Ansätze für praktische Berechnungen. Zusammenfassend wurde festgestellt, dass erwartungsgemäß die Spreizkräfte im Geogitter nahezu linear mit der Dammhöhe anwachsen. Von besonderer Bedeutung für die Größe der Spreizkräfte ist die Steifigkeit der Weichschichten. Dieser Parameter wird bei den bisher bekannten analytischen Berechnungsverfahren nicht berücksichtigt. Je weicher der Untergrund, je größer wird das Verhältnis zwischen Spreiz- und Membranbeanspruchung. Eine steilere Dammböschung hat erwartungsgemäß ebenfalls eine höhere Spreizwirkung zur Folge. Des Weiteren ergeben sich bei mehrlagigen Geogittern die höheren Beanspruchungen in der unteren Lage aus dem Membraneffekt und in der oberen Lage aus dem Spreizeffekt. Zu diesen Erkenntnissen wurden in der Arbeit erste Vorschläge für die praktischen Bemessungen gemacht, die aber noch weiter zu optimieren sind. Schließlich erfolgt von Herrn Fahmi eine Betrachtung der Pfahlelementbeanspruchung aus Pfahlkopfverschiebung und Biegemomenten. Dabei wurde ersichtlich, dass die Pfahlelemente bei hohen Dämmen erhebliche Beanspruchungen erhalten können, wenn relativ weicher Untergrund vorhanden ist, und es zeigt die Notwendigkeit entsprechend abgesicherter Bemessungsverfahren auf.

Femtosecond pump-probe study of the spreading and recurrence of a vibrational wave packet in Na_2

The motion of a vibrational wave packet in the bound A(^1 \summe^+_u) electronic state of the sodium dimer is detected in a femtosecond pump/probe molecular beam experiment. For short times harmonic motion is seen in the total ion yield of Na^+_2 as a function of delay time between the two laser pulses. The spreading of the wave packet results in the loss of the periodic variation of the ion signal. For longer delay times (47 ps) the wave packet regains its initial form which is reflected in the revival structure of the Na^+_2 signal. Time-dependent quantum calculations reproduce the measured effects.