Validation of tissue modelization and classification techniques in T1-weighted MR brain images

We propose a deep study on tissue modelization andclassification Techniques on T1-weighted MR images. Threeapproaches have been taken into account to perform thisvalidation study. Two of them are based on FiniteGaussian Mixture (FGM) model. The first one consists onlyin pure gaussian distributions (FGM-EM). The second oneuses a different model for partial volume (PV) (FGM-GA).The third one is based on a Hidden Markov Random Field(HMRF) model. All methods have been tested on a DigitalBrain Phantom image considered as the ground truth. Noiseand intensity non-uniformities have been added tosimulate real image conditions. Also the effect of ananisotropic filter is considered. Results demonstratethat methods relying in both intensity and spatialinformation are in general more robust to noise andinhomogeneities. However, in some cases there is nosignificant differences between all presented methods.

Classification of very high spatial resolution imagery using mathematical morphology and support vector machines

We investigate the relevance of morphological operators for the classification of land use in urban scenes using submetric panchromatic imagery. A support vector machine is used for the classification. Six types of filters have been employed: opening and closing, opening and closing by reconstruction, and opening and closing top hat. The type and scale of the filters are discussed, and a feature selection algorithm called recursive feature elimination is applied to decrease the dimensionality of the input data. The analysis performed on two QuickBird panchromatic images showed that simple opening and closing operators are the most relevant for classification at such a high spatial resolution. Moreover, mixed sets combining simple and reconstruction filters provided the best performance. Tests performed on both images, having areas characterized by different architectural styles, yielded similar results for both feature selection and classification accuracy, suggesting the generalization of the feature sets highlighted.

Prognosis in Duke's B colorectal carcinoma: the Jass classification revisited.

OBJECTIVE: To assess whether Jass staging enhances prognostic prediction in Dukes' B colorectal carcinoma. DESIGN: A historical cohort observational study. SETTING: A university tertiary care centre, Switzerland. SUBJECTS: 108 consecutive patients. INTERVENTIONS: Curative resection of Dukes' B colorectal carcinoma between January 1985 and December 1988, Patients with familial adenomatous polyposis; hereditary non-polyposis colorectal cancer; Crohns' disease; ulcerative colitis and synchronous and recurrent tumours were excluded. A comparable group of 155 consecutive patients with Dukes' C carcinoma were included for reference purposes. MAIN OUTCOME MEASURES: Disease free and overall survival for Dukes' B and overall survival for Dukes' C tumours. RESULTS: Dukes' B tumours in Jass group III or with an infiltrated margin had a significantly worse disease-free survival (p = 0.001 and 0.0001, respectively) and those with infiltrated margins had a significantly worse overall survival (p = 0.002). Overall survival among those with Dukes' B Jass III and Dukes' B with infiltrated margins was no better than overall survival among all patients with Dukes' C tumours. CONCLUSION: Jass staging and the nature of the margin of invasion allow patients undergoing curative surgery for Dukes' B colorectal carcinoma to be separated into prognostic groups. A group of patients with Dukes' B tumours whose prognosis is inseparable from those with Dukes' C tumours can be identified, the nature of the margin of invasion being used to classify a larger number of patients.

Multi-source composite kernels for urban image classification

This letter presents advanced classification methods for very high resolution images. Efficient multisource information, both spectral and spatial, is exploited through the use of composite kernels in support vector machines. Weighted summations of kernels accounting for separate sources of spectral and spatial information are analyzed and compared to classical approaches such as pure spectral classification or stacked approaches using all the features in a single vector. Model selection problems are addressed, as well as the importance of the different kernels in the weighted summation.

GacS sensor domains pertinent to the regulation of exoproduct formation and to the biocontrol potential of Pseudomonas fluorescens CHA0.

In the root-colonizing biocontrol strain CHA0 of Pseudomonas fluorescens, cell density-dependent synthesis of extracellular, plant-beneficial secondary metabolites and enzymes is positively regulated by the GacS/GacA two-component system. Mutational analysis of the GacS sensor kinase using improved single-copy vectors showed that inactivation of each of the three conserved phosphate acceptor sites caused an exoproduct null phenotype (GacS-), whereas deletion of the periplasmic loop domain had no significant effect on the expression of exoproduct genes. Strain CHA0 is known to synthesize a solvent-extractable extracellular signal that advances and enhances the expression of exoproduct genes during the transition from exponential to stationary growth phase when maximal exoproduct formation occurs. Mutational inactivation of either GacS or its cognate response regulator GacA abolished the strain's response to added signal. Deletion of the linker domain of the GacS sensor kinase caused signal-independent, strongly elevated expression of exoproduct genes at low cell densities. In contrast to the wild-type strain CHA0, the gacS linker mutant and a gacS null mutant were unable to protect tomato plants from crown and root rot caused by Fusarium oxysporum f. sp. radicis-lycopersici in a soil-less microcosm, indicating that, at least in this plant-pathogen system, there is no advantage in using a signal-independent biocontrol strain.

ACID-SENSING ION CHANNELS: functional and molecular characterization in putative nociceptors, and modulation by nerve injury and serine protease

Résumé Les canaux ioniques ASICs (acid-sensing ion channels) appartiennent à la famille des canaux ENaC/Degenerin. Pour l'instant, quatre gènes (1 à 4) ont été clonés dont certains présentent des variants d'épissage. Leur activation par une acidification rapide du milieu extracellulaire génère un courant entrant transitoire essentiellement sodique accompagné pour certains types d'ASICs d'une phase soutenue. Les ASICs sont exprimés dans le système nerveux, central (SNC) et périphérique (SNP). On leur attribue un rôle dans l'apprentissage, la mémoire et l'ischémie cérébrale au niveau central ainsi que dans la nociception (douleur aiguë et inflammatoire) et la méchanotransduction au niveau périphérique. Toutefois, les données sont parfois contradictoires. Certaines études suggèrent qu'ils sont des senseurs primordiaux impliqués dans la détection de l'acidification et la douleur. D'autres études suggèrent plutôt qu'ils ont un rôle modulateur inhibiteur dans la douleur. De plus, le fait que leur activation génère majoritairement un courant transitoire alors que les fibres nerveuses impliquées dans la douleur répondent à un stimulus nocif avec une adaptation lente suggère que leurs propriétés doivent être modulés par des molécules endogènes. Dans une première partie de ma thèse, nous avons abordé la question de l'expression fonctionnelle des ASICs dans les neurones sensoriels primaires afférents du rat adulte pour clarifier le rôle des ASICs dans les neurones sensoriels. Nous avons caractérisé leurs propriétés biophysiques et pharmacologiques par la technique du patch-clamp en configuration « whole-cell ». Nous avons pu démontrer que près de 60% des neurones sensoriels de petit diamètre expriment des courants ASICs. Nous avons mis en évidence trois types de courant ASIC dans ces neurones. Les types 1 et 3 ont des propriétés compatibles avec un rôle de senseur du pH alors que le type 2 est majoritairement activé par des pH inférieurs à pH6. Le type 1 est médié par des homomers de la sous-unité ASIC1 a qui sont perméables aux Ca2+. Nous avons étudié leur co-expression avec des marqueurs des nocicepteurs ainsi que la possibilité d'induire une activité neuronale suite à une acidification qui soit dépendante des ASICs. Le but était d'associer un type de courant ASIC avec une fonction potentielle dans les neurones sensoriels. Une majorité des neurones exprimant les courants ASIC co-expriment des marqueurs des nocicepteurs. Toutefois, une plus grande proportion des neurones exprimant le type 1 n'est pas associée à la nociception par rapport aux types 2 et 3. Nous avons montré qu'il est possible d'induire des potentiels d'actions suite à une acidification. La probabilité d'induction est proportionnelle à la densité des courants ASIC et à l'acidité de la stimulation. Puis, nous avons utilisé cette classification comme un outil pour appréhender les potentielles modulations fonctionnelles des ASICs dans un model de neuropathie (spared nerve injury). Cette approche fut complétée par des expériences de «quantitative RT-PCR ». En situation de neuropathie, les courants ASIC sont dramatiquement changés au niveau de leur expression fonctionnelle et transcriptionnelle dans les neurones lésés ainsi que non-lésés. Dans une deuxième partie de ma thèse, suite au test de différentes substances sécrétées lors de l'inflammation et l'ischémie sur les propriétés des ASICs, nous avons caractérisé en détail la modulation des propriétés des courants ASICs notamment ASIC1 par les sérines protéases dans des systèmes d'expression recombinants ainsi que dans des neurones d'hippocampe. Nous avons montré que l'exposition aux sérine-protéases décale la dépendance au pH de l'activation ainsi que la « steady-state inactivation »des ASICs -1a et -1b vers des valeurs plus acidiques. Ainsi, l'exposition aux serine protéases conduit à une diminution du courant quand l'acidification a lieu à partir d'un pH7.4 et conduit à une augmentation du courant quand l'acidification alleu à partir d'un pH7. Nous avons aussi montré que cette régulation a lieu des les neurones d'hippocampe. Nos résultats dans les neurones sensoriels suggèrent que certains courants ASICs sont impliqués dans la transduction de l'acidification et de la douleur ainsi que dans une des phases du processus conduisant à la neuropathie. Une partie des courants de type 1 perméables au Ca 2+ peuvent être impliqués dans la neurosécrétion. La modulation par les sérines protéases pourrait expliquer qu'en situation d'acidose les canaux ASICs soient toujours activables. Résumé grand publique Les neurones sont les principales cellules du système nerveux. Le système nerveux est formé par le système nerveux central - principalement le cerveau, le cervelet et la moelle épinière - et le système nerveux périphérique -principalement les nerfs et les neurones sensoriels. Grâce à leur nombreux "bras" (les neurites), les neurones sont connectés entre eux, formant un véritable réseau de communication qui s'étend dans tout le corps. L'information se propage sous forme d'un phénomène électrique, l'influx nerveux (ou potentiels d'actions). A la base des phénomènes électriques dans les neurones il y a ce que l'on appelle les canaux ioniques. Un canal ionique est une sorte de tunnel qui traverse l'enveloppe qui entoure les cellules (la membrane) et par lequel passent les ions. La plupart de ces canaux sont normalement fermés et nécessitent d'être activés pour s'ouvrire et générer un influx nerveux. Les canaux ASICs sont activés par l'acidification et sont exprimés dans tout le système nerveux. Cette acidification a lieu notamment lors d'une attaque cérébrale (ischémie cérébrale) ou lors de l'inflammation. Les expériences sur les animaux ont montré que les canaux ASICs avaient entre autre un rôle dans la mort des neurones lors d'une attaque cérébrale et dans la douleur inflammatoire. Lors de ma thèse je me suis intéressé au rôle des ASICs dans la douleur et à l'influence des substances produites pendant l'inflammation sur leur activation par l'acidification. J'ai ainsi pu montrer chez le rat que la majorité des neurones sensoriels impliqués dans la douleur ont des canaux ASICs et que l'activation de ces canaux induit des potentiels d'action. Nous avons opéré des rats pour qu'ils présentent les symptômes d'une maladie chronique appelée neuropathie. La neuropathie se caractérise par une plus grande sensibilité à la douleur. Les rats neuropathiques présentent des changements de leurs canaux ASICs suggérant que ces canaux ont une peut-être un rôle dans la genèse ou les symptômes de cette maladie. J'ai aussi montré in vitro qu'un type d'enryme produit lors de l'inflammation et l'ischémie change les propriétés des ASICs. Ces résultats confirment un rôle des ASICs dans la douleur suggérant notamment un rôle jusque là encore non étudié dans la douleur neuropathique. De plus, ces résultats mettent en évidence une régulation des ASICs qui pourrait être importante si elle se confirmait in vivo de part les différents rôles des ASICs. Abstract Acid-sensing ion channels (ASICs) are members of the ENaC/Degenerin superfamily of ion channels. Their activation by a rapid extracellular acidification generates a transient and for some ASIC types also a sustained current mainly mediated by Na+. ASICs are expressed in the central (CNS) and in the peripheral (PNS) nervous system. In the CNS, ASICs have a putative role in learning, memory and in neuronal death after cerebral ischemia. In the PNS, ASICs have a putative role in nociception (acute and inflammatory pain) and in mechanotransduction. However, studies on ASIC function are somewhat controversial. Some studies suggest a crucial role of ASICs in transduction of acidification and in pain whereas other studies suggest rather a modulatory inhibitory role of ASICs in pain. Moreover, the basic property of ASICs, that they are activated only transiently is irreconcilable with the well-known property of nociception that the firing of nociceptive fibers demonstrated very little adaptation. Endogenous molecules may exist that can modulate ASIC properties. In a first part of my thesis, we addressed the question of the functional expression of ASICs in adult rat dorsal root ganglion (DRG) neurons. Our goal was to elucidate ASIC roles in DRG neurons. We characterized biophysical and pharmacological properties of ASIC currents using the patch-clamp technique in the whole-cell configuration. We observed that around 60% of small-diameter sensory neurons express ASICs currents. We described in these neurons three ASIC current types. Types 1 and 3 have properties compatible with a role of pH-sensor whereas type 2 is mainly activated by pH lower than pH6. Type 1 is mediated by ASIC1a homomultimers which are permeable to Ca 2+. We studied ASIC co-expression with nociceptor markers. The goal was to associate an ASIC current type with a potential function in sensory neurons. Most neurons expressing ASIC currents co-expressed nociceptor markers. However, a higher proportion of the neurons expressing type 1 was not associated with nociception compared to type 2 and -3. We completed this approach with current-clamp measurements of acidification-induced action potentials (APs). We showed that activation of ASICs in small-diameter neurons can induce APs. The probability of AP induction is positively correlated with the ASIC current density and the acidity of stimulation. Then, we used this classification as a tool to characterize the potential functional modulation of ASICs in the spared nerve injury model of neuropathy. This approach was completed by quantitative RT-PCR experiments. ASICs current expression was dramatically changed at the functional and transcriptional level in injured and non-injured small-diameter DRG neurons. In a second part of my thesis, following an initial screening of the effect of various substances secreted during inflammation and ischemia on ASIC current properties, we characterized in detail the modulation of ASICs, in particular of ASIC1 by serine proteases in a recombinant expression system as well as in hippocampal neurons. We showed that protease exposure shifts the pH dependence of ASIC1 activation and steady-state inactivation to more acidic pH. As a consequence, protease exposure leads to a decrease in the current response if ASIC1 is activated by a pH drop from pH 7.4. If, however, acidification occurs from a basal pH of 7, protease-exposed ASIC1a shows higher activity than untreated ASIC1a. We provided evidence that this bi-directional regulation of ASIC1a function also occurs in hippocampal neurons. Our results in DRG neurons suggest that some ASIC currents are involved in the transduction of peripheral acidification and pain. Furthermore, ASICs may participate to the processes leading to neuropathy. Some Ca 2+-permeable type 1 currents may be involved in neurosecretion. ASIC modulation by serine proteases may be physiologically relevant, allowing ASIC activation under sustained slightly acidic conditions.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

Measurement with an automated oscillometric wrist device with position sensor leads to lower values than measurements obtained with an automated oscillometric arm device from the same manufacturer in elderly persons.

OBJECTIVE: Home blood pressure (BP) monitoring is recommended by several clinical guidelines and has been shown to be feasible in elderly persons. Wrist manometers have recently been proposed for such home BP measurement, but their accuracy has not been previously assessed in elderly patients. METHODS: Forty-eight participants (33 women and 15 men, mean age 81.3±8.0 years) had their BP measured with a wrist device with position sensor and an arm device in random order in a sitting position. RESULTS: Average BP measurements were consistently lower with the wrist than arm device for systolic BP (120.1±2.2 vs. 130.5±2.2 mmHg, P<0.001, means±SD) and diastolic BP (66.0±1.3 vs. 69.7±1.3 mmHg, P<0.001). Moreover, a 10 mmHg or greater difference between the arm and wrist device was observed in 54.2 and 18.8% of systolic and diastolic measures, respectively. CONCLUSION: Compared with the arm device, the wrist device with position sensor systematically underestimated systolic as well as diastolic BP. The magnitude of the difference is clinically significant and questions the use of the wrist device to monitor BP in elderly persons. This study points to the need to validate BP measuring devices in all age groups, including in elderly persons.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

Current Issues in the Diagnosis and Classification of Peripheral T-Cell Lymphomas

Mature T-cell and T/NK-cell neoplasms are both uncommon and heterogeneous, among the broad category of non-Hodgkin's lymphomas. Due to the lack of specific genetic alterations in the vast majority of cases, most currently defined entities show overlapping morphologic and immunophenotypic features and therefore pose a challenge to the diagnostic pathologist. The goal of the symposium is to address current criteria for the recognition of specific subtypes of T-cell lymphoma, and to highlight new data regarding emerging immunophenotypic or molecular markers. This activity has been designed to meet the needs of practicing pathologists, and residents and fellows enrolled in training programs in anatomic and clinical pathology. It should be a particular benefit to those with an interest in hematopathology. Upon completion of this activity, participants should be better able to: -To be able to state the basis for the classification of mature T-cell malignancies involving nodal and extranodal sites. -To recognize and accurately diagnose the various subtypes of nodal and extranodal peripheral T-cell lymphomas. -To utilize immunohistochemical and molecular tests to characterize atypical T-cell proliferations. -To recognize and accurately diagnose T-cell lymphoproliferative lesions involving the skin and gastrointestinal tract, and be able to provide guidance regarding their clinical aggressiveness and management -To be able to utilize flow cytometric data to identify diverse functional T-cell subsets.

Real-time monitoring of protein conformational changes using a nano-mechanical sensor.

Proteins can switch between different conformations in response to stimuli, such as pH or temperature variations, or to the binding of ligands. Such plasticity and its kinetics can have a crucial functional role, and their characterization has taken center stage in protein research. As an example, Topoisomerases are particularly interesting enzymes capable of managing tangled and supercoiled double-stranded DNA, thus facilitating many physiological processes. In this work, we describe the use of a cantilever-based nanomotion sensor to characterize the dynamics of human topoisomerase II (Topo II) enzymes and their response to different kinds of ligands, such as ATP, which enhance the conformational dynamics. The sensitivity and time resolution of this sensor allow determining quantitatively the correlation between the ATP concentration and the rate of Topo II conformational changes. Furthermore, we show how to rationalize the experimental results in a comprehensive model that takes into account both the physics of the cantilever and the dynamics of the ATPase cycle of the enzyme, shedding light on the kinetics of the process. Finally, we study the effect of aclarubicin, an anticancer drug, demonstrating that it affects directly the Topo II molecule inhibiting its conformational changes. These results pave the way to a new way of studying the intrinsic dynamics of proteins and of protein complexes allowing new applications ranging from fundamental proteomics to drug discovery and development and possibly to clinical practice.