Congenital ataxia and hemiplegic migraine with cerebral edema associated with a novel gain of function mutation in the calcium channel CACNA1A.

Mutations in the CACNA1A gene, encoding the α1 subunit of the voltage-gated calcium channel Ca(V)2.1 (P/Q-type), have been associated with three neurological phenotypes: familial and sporadic hemiplegic migraine type 1 (FHM1, SHM1), episodic ataxia type 2 (EA2), and spinocerebellar ataxia type 6 (SCA6). We report a child with congenital ataxia, abnormal eye movements and developmental delay who presented severe attacks of hemiplegic migraine triggered by minor head traumas and associated with hemispheric swelling and seizures. Progressive cerebellar atrophy was also observed. Remission of the attacks was obtained with acetazolamide. A de novo 3 bp deletion was found in heterozygosity causing loss of a phenylalanine residue at position 1502, in one of the critical transmembrane domains of the protein contributing to the inner part of the pore. We characterized the electrophysiology of this mutant in a Xenopus oocyte in vitro system and showed that it causes gain of function of the channel. The mutant Ca(V)2.1 activates at lower voltage threshold than the wild type. These findings provide further evidence of this molecular mechanism as causative of FHM1 and expand the phenotypic spectrum of CACNA1A mutations with a child exhibiting severe SHM1 and non-episodic ataxia of congenital onset.

A Bayesian approach for pervasive estimation of breaststroke velocity using a wearable IMU

A ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every cycle using a low-cost wearable inertial measurement unit (IMU). The statistical validation of the method on 15 swimmers shows that an average relative error of 0.1 ± 9.6% and high correlation with the tethered reference system (rX,Y=0.91 ) is achievable. Besides, a simple tool to analyze the influence of sacrum kinematics on the performance is provided.

Epithelial Na+ channel mutants causing Liddle's syndrome retain ability to respond to aldosterone and vasopressin.

Liddle's syndrome is a monogenic form of hypertension caused by mutations in the PY motif of the COOH terminus of beta- and gamma-epithelial Na+ channel (ENaC) subunits. These mutations lead to retention of active channels at the cell surface. Because of the critical role of this PY motif in the stability of ENaCs at the cell surface, we have investigated its contribution to the ENaC response to aldosterone and vasopressin. Mutants of the PY motif in beta- and gamma-ENaC subunits (beta-Y618A, beta-P616L, beta-R564stop, and gamma-K570stop) were stably expressed by retroviral gene transfer in a renal cortical collecting duct cell line (mpkCCDcl4), and transepithelial Na+ transport was assessed by measurements of the benzamil-sensitive short-circuit current (Isc). Cells that express ENaC mutants of the PY motif showed a five- to sixfold higher basal Isc compared with control cells and responded to stimulation by aldosterone (10(-6) M) or vasopressin (10(-9) M) with a further increase in Isc. The rates of the initial increases in Isc after aldosterone or vasopressin stimulation were comparable in cells transduced with wild-type and mutant ENaCs, but reversal of the effects of aldosterone and vasopressin was slower in cells that expressed the ENaC mutants. The conserved sensitivity of ENaC mutants to stimulation by aldosterone and vasopressin together with the prolonged activity at the cell surface likely contribute to the increased Na+ absorption in the distal nephron of patients with Liddle's syndrome.

The Ca(V)3.3 calcium channel is the major sleep spindle pacemaker in thalamus.

Low-threshold (T-type) Ca(2+) channels encoded by the Ca(V)3 genes endow neurons with oscillatory properties that underlie slow waves characteristic of the non-rapid eye movement (NREM) sleep EEG. Three Ca(V)3 channel subtypes are expressed in the thalamocortical (TC) system, but their respective roles for the sleep EEG are unclear. Ca(V)3.3 protein is expressed abundantly in the nucleus reticularis thalami (nRt), an essential oscillatory burst generator. We report the characterization of a transgenic Ca(V)3.3(-/-) mouse line and demonstrate that Ca(V)3.3 channels are indispensable for nRt function and for sleep spindles, a hallmark of natural sleep. The absence of Ca(V)3.3 channels prevented oscillatory bursting in the low-frequency (4-10 Hz) range in nRt cells but spared tonic discharge. In contrast, adjacent TC neurons expressing Ca(V)3.1 channels retained low-threshold bursts. Nevertheless, the generation of synchronized thalamic network oscillations underlying sleep-spindle waves was weakened markedly because of the reduced inhibition of TC neurons via nRt cells. T currents in Ca(V)3.3(-/-) mice were <30% compared with those in WT mice, and the remaining current, carried by Ca(V)3.2 channels, generated dendritic [Ca(2+)](i) signals insufficient to provoke oscillatory bursting that arises from interplay with Ca(2+)-dependent small conductance-type 2 K(+) channels. Finally, naturally sleeping Ca(V)3.3(-/-) mice showed a selective reduction in the power density of the σ frequency band (10-12 Hz) at transitions from NREM to REM sleep, with other EEG waves remaining unaltered. Together, these data identify a central role for Ca(V)3.3 channels in the rhythmogenic properties of the sleep-spindle generator and provide a molecular target to elucidate the roles of sleep spindles for brain function and development.

Dual-channel electrospray microchip.

A dual-channel electrospray microchip has been developed for electrospray ionization mass spectrometry (ESI-MS) where aqueous samples are mixed at the Taylor cone with an organic buffer. Due to the fast and effective mixing in the Taylor cone, the aqueous sample can be well ionized with a high ion intensity. The influence of geometric parameters such as the distance between the two microchannels at their junction at the tip of the emitter has been investigated together with chemical parameters such as the organic buffer composition.

Neuronal in vitro models for the estimation of acute systemic toxicity.

The objective of the EU funded integrated project "ACuteTox" is to develop a strategy in which general cytotoxicity, together with organ-specific endpoints and biokinetic features, are taken into consideration in the in vitro prediction of oral acute systemic toxicity. With regard to the nervous system, the effects of 23 reference chemicals were tested with approximately 50 endpoints, using a neuronal cell line, primary neuronal cell cultures, brain slices and aggregated brain cell cultures. Comparison of the in vitro neurotoxicity data with general cytotoxicity data generated in a non-neuronal cell line and with in vivo data such as acute human lethal blood concentration, revealed that GABA(A) receptor function, acetylcholine esterase activity, cell membrane potential, glucose uptake, total RNA expression and altered gene expression of NF-H, GFAP, MBP, HSP32 and caspase-3 were the best endpoints to use for further testing with 36 additional chemicals. The results of the second analysis showed that no single neuronal endpoint could give a perfect improvement in the in vitro-in vivo correlation, indicating that several specific endpoints need to be analysed and combined with biokinetic data to obtain the best correlation with in vivo acute toxicity.

Estimation de la fonction rénale par l'equation MDRD: intérêt et limites pour l'adaptation des doses de médicaments [Renal function estimation by MDRD equation: interest and limitations for drug dosing].

The MDRD (Modification of diet in renal disease) equation enables glomerular filtration rate (GFR) estimation from serum creatinine only. Thus, the laboratory can report an estimated GFR (eGFR) with each serum creatinine assessment, increasing therefore the recognition of renal failure. Predictive performance of MDRD equation is better for GFR < 60 ml/min/1,73 m2. A normal or near-normal renal function is often underestimated by this equation. Overall, MDRD provides more reliable estimations of renal function than the Cockcroft-Gault (C-G) formula, but both lack precision. MDRD is not superior to C-G for drug dosing. Being adjusted to 1,73 m2, MDRD eGFR has to be back adjusted to the patient's body surface area for drug dosing. Besides, C-G has the advantage of a greater simplicity and a longer use.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Adaptively weighted maximum likelihood estimation of discrete distributions

SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

Evolution of a debris flow channel monitored using a 3D terrestrial laser scanner

Like numerous torrents in mountainous regions, the Illgraben creek (canton of Wallis, SW Switzerland) produces almost every year several debris flows. The total area of the active catchment is only 4.7 km², but large events ranging from 50'000 to 400'000 m³ are common (Zimmermann 2000). Consequently, the pathway of the main channel often changes suddenly. One single event can for instance fill the whole river bed and dig new several-meters-deep channels somewhere else (Bardou et al. 2003). The quantification of both, the rhythm and the magnitude of these changes, is very important to assess the variability of the bed's cross section and long profile. These parameters are indispensable for numerical modelling, as they should be considered as initial conditions. To monitor the channel evolution an Optech ILRIS 3D terrestrial laser scanner (LIDAR) was used. LIDAR permits to make a complete high precision 3D model of the channel and its surroundings by scanning it from different view points. The 3D data are treated and interpreted with the software Polyworks from Innovmetric Software Inc. Sequential 3D models allow for the determination of the variation in the bed's cross section and long profile. These data will afterwards be used to quantify the erosion and the deposition in the torrent reaches. To complete the chronological evolution of the landforms, precise digital terrain models, obtained by high resolution photogrammetry based on old aerial photographs, will be used. A 500 m long section of the Illgraben channel was scanned on 18th of August 2005 and on 7th of April 2006. These two data sets permit identifying the changes of the channel that occurred during the winter season. An upcoming scanning campaign in September 2006 will allow for the determination of the changes during this summer. Preliminary results show huge variations in the pathway of the Illgraben channel, as well as important vertical and lateral erosion of the river bed. Here we present the results of a river bank on the left (north-western) flank of the channel (Figure 1). For the August 2005 model the scans from 3 viewpoints were superposed, whereas the April 2006 3D image was obtained by combining 5 separate scans. The bank was eroded. The bank got eroded essentially on its left part (up to 6.3 m), where it is hit by the river and the debris flows (Figures 2 and 3). A debris cone has also formed (Figure 3), which suggests that a part of the bank erosion is due to shallow landslides. They probably occur when the river erosion creates an undercut slope. These geometrical data allow for the monitoring of the alluvial dynamics (i.e. aggradation and degradation) on different time scales and the influence of debris flows occurrence on these changes. Finally, the resistance against erosion of the bed's cross section and long profile will be analysed to assess the variability of these two key parameters. This information may then be used in debris flow simulation.