A prospective observational study comparing a non-operator dependent automatic PWV analyser to pulse pressure, in assessing arterial stiffness in hemodialysis.

BACKGROUND: Chronic kidney disease (CKD) accelerates vascular stiffening related to age. Arterial stiffness may be evaluated measuring the carotid-femoral pulse wave velocity (PWV) or more simply, as recommended by KDOQI, monitoring pulse pressure (PP). Both correlate to survival and incidence of cardiovascular disease. PWV can also be estimated on the brachial artery using a Mobil-O-Graph; a non-operator dependent automatic device. The aim was to analyse whether, in a dialysis population, PWV obtained by Mobil-O-Graph (MogPWV) is more sensitive for vascular aging than PP. METHODS: A cohort of 143 patients from 4 dialysis units has been followed measuring MogPWV and PP every 3 to 6 months and compared to a control group with the same risk factors but an eGFR > 30 ml/min. RESULTS: MogPWV contrarily to PP did discriminate the dialysis population from the control group. The mean difference translated in age between the two populations was 8.4 years. The increase in MogPWV, as a function of age, was more rapid in the dialysis group. 13.3% of the dialysis patients but only 3.0% of the control group were outliers for MogPWV. The mortality rate (16 out of 143) was similar in outliers and inliers (7.4 and 8.0%/year). Stratifying patients according to MogPWV, a significant difference in survival was seen. A high parathormone (PTH) and to be dialysed for a hypertensive nephropathy were associated to a higher baseline MogPWV. CONCLUSIONS: Assessing PWV on the brachial artery using a Mobil-O-Graph is a valid and simple alternative, which, in the dialysis population, is more sensitive for vascular aging than PP. As demonstrated in previous studies PWV correlates to mortality. Among specific CKD risk factors only PTH is associated with a higher baseline PWV. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02327962.

Automatic target validation based on neuroscientific literature mining for tractography.

Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/.

Dynamic and quasistatic trajectories in quasifission reactions and particle emission

We show that the quasifission paths predicted by the one-body dissipation dynamics, in the slowest phase of a binary reaction, follow a quasistatic path, which represents a sequence of states of thermal equilibrium at a fixed value of the deformation coordinate. This establishes the use of the statistical particle-evaporation model in the case of dynamical time-evolving systems. Pre- and post-scission multiplicities of neutrons and total multiplicities of protons and α particles in fission reactions of 63Cu+92Mo, 60Ni+100Mo, 63Cu+100Mo at 10 MeV/u and 20Ne+144,148,154Sm at 20 MeV/u are reproduced reasonably well with statistical model calculations performed along dynamic trajectories whose slow stage (from the most compact configuration up to the point where the neck starts to develop) lasts some 35×10−21 s.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma.

PURPOSE: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. METHODS AND MATERIALS: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. RESULTS: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. CONCLUSION: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Impact of open-ocean convection on particle fluxes and sediment dynamics in the deep margin of the Gulf of Lions.

Abstract. The deep outer margin of the Gulf of Lions and the adjacent basin, in the western Mediterranean Sea, are regularly impacted by open-ocean convection, a major hydrodynamic event responsible for the ventilation of the deep water in the western Mediterranean Basin. However, the impact of open-ocean convection on the flux and transport of particulate matter remains poorly understood. The variability of water mass properties (i.e., temperature and salinity), currents, and particle fluxes were monitored between September 2007 and April 2009 at five instrumented mooring lines deployed between 2050 and 2350-m depth in the deepest continental margin and adjacent basin. Four of the lines followed a NW-SE transect, while the fifth one was located on a sediment wave field to the west. The results of the main, central line SC2350 ("LION") located at 42 02.50 N, 4 410 E, at 2350-m depth, show that open-ocean convection reached midwater depth ( 1000-m depth) during winter 2007-2008, and reached the seabed ( 2350-m depth) during winter 2008-2009. Horizontal currents were unusually strong with speeds up to 39 cm s−1 during winter 2008-2009. The measurements at all 5 different locations indicate that mid-depth and near-bottom currents and particle fluxes gave relatively consistent values of similar magnitude across the study area except during winter 2008-2009, when near-bottom fluxes abruptly increased by one to two orders of magnitude. Particulate organic carbon contents, which generally vary between 3 and 5 %, were abnormally low ( 1 %) during winter 2008-2009 and approached those observed in surface sediments (0.6 %). Turbidity profiles made in the region demonstrated the existence of a bottom nepheloid layer, several hundred meters thick, and related to the resuspension of bottom sediments. These observations support the view that open-ocean deep convection events in the Gulf of Lions can cause significant remobilization of sediments in the deep outer margin and the basin, with a subsequent alteration of the seabed likely impacting the functioning of the deep-sea ecosystem.

Particle Size Analysis of Pharmaceutical Powders by Laser Diffraction

Raaka-aineen hiukkaskoko on lääkekehityksessä keskeinen materiaaliparametri. Lääkeaineen partikkelikoko vaikuttaa moneen lääketuotteen tärkeään ominaisuuteen, esimerkiksi lääkkeen biologiseen hyväksikäytettävyyteen. Tässä diplomityössä keskityttiin jauhemaisten lääkeaineiden hiukkaskoon määrittämiseen laserdiffraktiomenetelmällä. Menetelmä perustuu siihen, että partikkeleista sironneen valon intensiteetin sirontakulmajakauma on riippuvainen partikkelien kokojakaumasta. Työn kirjallisuusosassa esiteltiin laserdiffraktiomenetelmän teoriaa. PIDS (Polarization Intensity Differential Scattering) tekniikka, jota voidaan käyttää laserdiffraktion yhteydessä, on myös kuvattu kirjallisuusosassa. Muihin menetelmiin perustuvista analyysimenetelmistä tutustuttiin mikroskopiaan sekä aerodynaamisen lentoajan määrittämiseen perustuvaan menetelmään. Kirjallisuusosassa esiteltiin myös partikkelikoon yleisimpiä esitystapoja. Työn kokeellisen osan tarkoituksena oli kehittää ja validoida laserdiffraktioon perustuva partikkelikoon määritysmenetelmä tietylle lääkeaineelle. Menetelmäkehitys tehtiin käyttäen Beckman Coulter LS 13 320 laserdiffraktoria. Laite mahdollistaa PIDS-tekniikan käytön laserdiffraktiotekniikan ohella. Menetelmäkehitys aloitettiin arvioimalla, että kyseinen lääkeaine soveltuu parhaiten määritettäväksi nesteeseen dispergoituna. Liukoisuuden perusteella väliaineeksi valittiin tällä lääkeaineella kyllästetty vesiliuos. Dispergointiaineen sekä ultraäänihauteen käyttö havaittiin tarpeelliseksi dispergoidessa kyseistä lääkeainetta kylläiseen vesiliuokseen. Lopuksi sekoitusnopeus näytteensyöttöyksikössä säädettiin sopivaksi. Validointivaiheessa kehitetyn menetelmän todettiin soveltuvan hyvin kyseiselle lääkeaineelle ja tulosten todettiin olevan oikeellisia sekä toistettavia. Menetelmä ei myöskään ollut herkkä pienille häiriöille.

Papaya seedlings growth using a low-cost, automatic watering controller

The study assessed growth and physiological parameters of 'Sunrise Golden' and 'Tainung 01' papaya seedlings grown in 280mL plastic tubes and watered using a low-cost automatic irrigation system adjusted to operate at substrate water tension for starting irrigation (STI) of 3.0, 6.0 or 9.0 kPa. The water depths applied by the dripping system and drainage were monitored during germination and seedling growth. Germination, emergence velocity index (EVI), leaf area, plant height, shoot and root dry weight, stomatal conductance, relative water content (RWC) and relative chlorophyll content (RCC) were evaluated. Soil nutrient levels were determined by electrical conductivity (EC). Water use efficiency (WUE) corresponded to the ratio of plant dry mass to depth of water applied. STI settings did not affect papaya germination or EVI. System configuration to 3.0 and 6.0 kPa STI exhibited the highest drainage and lowest EC and RCC, indicating soil nutrient loss and plant nutrient deficiency. Drainage was greater in tubes planted with the 'Tainung 01' variety, which developed smaller root systems and lower stomatal conductance than 'Sunrise Golden' seedlings. The highest values for shoot dry weight and WEU were obtained at 6.0 kPa STI for 'Sunrise Golden' (0.62 g and 0.69 g L-1) and at 9.0 kPa in 'Tainung 01' (0.35 g and 0.82 g L-1). RWC at 9.0 kPa STI was lower than at 3.0 kPa in both varieties. The results indicate that the low-cost technology developed for irrigation automation is promising. Even so, new studies are needed to evaluate low-flow irrigation systems as well as the nutrient and water needs of different papaya varieties.

Alzheimer Disease Diagnosis based on Automatic Spontaneous Speech Analysis

Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to improvement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.

Particle shape and orientation in laser diffraction and static image analysis size distribution analysis of micrometer sized rectangular particles

Laser diffraction (LD) and static image analysis (SIA) of rectangular particles [United States Pharmacopeia, USP30-NF25, General Chapter <776>, Optical Miroscopy.] have been systematically studied. To rule out sample dispersion and particle orientation as the root cause of differences in size distribution profiles, we immobilize powder samples on a glass plate by means of a dry disperser. For a defined region of the glass plate, we measure the diffraction pattern as induced by the dispersed particles, and the 2D dimensions of the individual particles using LD and optical microscopy, respectively. We demonstrate a correlation between LD and SIA, with the scattering intensity of the individual particles as the dominant factor. In theory, the scattering intensity is related to the square of the projected area of both spherical and rectangular particles. In traditional LD the size distribution profile is dominated by the maximum projected area of the particles (A). The diffraction diameters of a rectangular particle with length L and breadth B as measured by the LD instrument approximately correspond to spheres of diameter ØL and ØB respectively. Differences in the scattering intensity between spherical and rectangular particles suggest that the contribution made to the overall LD volume probability distribution by each rectangular particle is proportional to A2/L and A2/B. Accordingly, for rectangular particles the scattering intensity weighted diffraction diameter (SIWDD) explains an overestimation of their shortest dimension and an underestimation of their longest dimension. This study analyzes various samples of particles whose length ranges from approximately 10 to 1000 μm. The correlation we demonstrate between LD and SIA can be used to improve validation of LD methods based on SIA data for a variety of pharmaceutical powders all with a different rectangular particle size and shape.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Radial dose function of a 90Sr 90Y seed in water and A150: Comment on Calibration and characterization of beta-particle sources for intravascular brachytherapy

Intravascular brachytherapy with beta sources has become a useful technique to prevent restenosis after cardiovascular intervention. In particular, the Beta-Cath high-dose-rate system, manufactured by Novoste Corporation, is a commercially available 90Sr 90Y source for intravascular brachytherapy that is achieving widespread use. Its dosimetric characterization has attracted considerable attention in recent years. Unfortunately, the short ranges of the emitted beta particles and the associated large dose gradients make experimental measurements particularly difficult. This circumstance has motivated the appearance of a number of papers addressing the characterization of this source by means of Monte Carlo simulation techniques.

Effects of vacancy-type defects in silicon based particle detectors

The semiconductor particle detectors used at CERN experiments are exposed to radiation. Under radiation, the formation of lattice defects is unavoidable. The defects affect the depletion voltage and leakage current of the detectors, and hence affect on the signal-to-noise ratio of the detectors. This shortens the operational lifetime of the detectors. For this reason, the understanding of the formation and the effects of radiation induced defects is crucial for the development of radiation hard detectors. In this work, I have studied the effects of radiation induced defects-mostly vacancy related defects-with a simulation package, Silvaco. Thus, this work essentially concerns the effects of radiation induced defects, and native defects, on leakage currents in particle detectors. Impurity donor atom-vacancy complexes have been proved to cause insignificant increase of leakage current compared with the trivacancy and divacancy-oxygen centres. Native defects and divacancies have proven to cause some of the leakage current, which is relatively small compared with trivacancy and divacancy-oxygen.

Automatic Brain Extraction in Fetal MRI using Multi-Atlas-based Segmentation

In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.