Performance of a new, 3D-monitor based random-dot stereotest for children under 4 years of age

BACKGROUND: The aim of this study was to determine the performance of a new, 3D-monitor based, objective stereotest in children under the age of four. METHODS: Random-dot circles (diameter 10 cm, crossed, disparity of 0.34 degrees) randomly changing their position were presented on an 3D-monitor while eye movements were monitored by infrared photo-oculography. If > or = 3 consecutive stimuli were seen, a positive response was assumed. One hundred thirty-four normal children aged 2 months to 4 years (average 17+/-15.3 months) were examined. RESULTS: Below the age of 12 months, we were not able to obtain a response to the 3D stimulus. For older children the following rates of positive responses were found: 12-18 months 25%, 18-24 months 10%, 24-30 months 16%, 30-36 months 57%, 36-42 months 100%, and 42-48 months 91%. Multiple linear logistic regression showed a significant influence on stimulus recognition of the explanatory variables age (p<0.00001) and child cooperation (p<0.001), but not of gender (p>0.1). CONCLUSIONS: This 3D-monitor based stereotest allows an objective measurement of random-dot stereopsis in younger children. It might open new ways to screen children for visual abnormalities and to study the development of stereovision. However, the current experimental setting does not allow determining random-dot stereopsis in children younger than 12 months.

Water quality in dental chair units. A random sample in the canton of St. Gallen

This study aimed to identify the microbial contamination of water from dental chair units (DCUs) using the prevalence of Pseudomonas aeruginosa, Legionella species and heterotrophic bacteria as a marker of pollution in water in the area of St. Gallen, Switzerland. Water (250 ml) from 76 DCUs was collected twice (early on a morning before using all the instruments and after using the DCUs for at least two hours) either from the high-speed handpiece tube, the 3 in 1 syringe or the micromotor for water quality testing. An increased bacterial count (>300 CFU/ml) was found in 46 (61%) samples taken before use of the DCU, but only in 29 (38%) samples taken two hours after use. Pseudomonas aeruginosa was found in both water samples in 6/76 (8%) of the DCUs. Legionella were found in both samples in 15 (20%) of the DCUs tested. Legionella anisa was identified in seven samples and Legionella pneumophila was found in eight. DCUs which were less than five years old were contaminated less often than older units (25% und 77%, p<0.001). This difference remained significant (0=0.0004) when adjusted for manufacturer and sampling location in a multivariable logistic regression. A large proportion of the DCUs tested did not comply with the Swiss drinking water standards nor with the recommendations of the American Centers for Disease Control and Prevention (CDC).

Ultrasonic acoustic emissions in drought-stressed trees - more than signals from cavitation?

Ultrasonic acoustic emission (UAE) in trees is often related to collapsing water columns in the flow path as a result of tensions that are too strong (cavitation). However, in a decibel (dB) range below that associated with cavitation, a close relationship was found between UAE intensities and stem radius changes. • UAE was continuously recorded on the stems of mature field-grown trees of Scots pine (Pinus sylvestris) and pubescent oak (Quercus pubescens) at a dry inner-Alpine site in Switzerland over two seasons. The averaged 20-Hz records were related to microclimatic conditions in air and soil, sap-flow rates and stem-radius fluctuations de-trended for growth (ΔW). • Within a low-dB range (27 ± 1 dB), UAE regularly increased and decreased in a diurnal rhythm in parallel with ΔW on cloudy days and at night. These low-dB emissions were interrupted by UAE abruptly switching between the low-dB range and a high-dB range (36 ± 1 dB) on clear, sunny days, corresponding to the widely supported interpretation of UAE as sound from cavitations. • It is hypothesized that the low-dB signals in drought-stressed trees are caused by respiration and/or cambial growth as these physiological activities are tissue water-content dependent and have been shown to produce courses of CO2 efflux similar to our courses of ΔW and low-dB UAE.

Hierarchical Markov Random Fields Applied to Model Soft Tissue Deformations on Graphics Hardware

Many methodologies dealing with prediction or simulation of soft tissue deformations on medical image data require preprocessing of the data in order to produce a different shape representation that complies with standard methodologies, such as mass–spring networks, finite element method s (FEM). On the other hand, methodologies working directly on the image space normally do not take into account mechanical behavior of tissues and tend to lack physics foundations driving soft tissue deformations. This chapter presents a method to simulate soft tissue deformations based on coupled concepts from image analysis and mechanics theory. The proposed methodology is based on a robust stochastic approach that takes into account material properties retrieved directly from the image, concepts from continuum mechanics and FEM. The optimization framework is solved within a hierarchical Markov random field (HMRF) which is implemented on the graphics processor unit (GPU See Graphics processing unit ).

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Species-specific stomatal response of trees to drought - a link to vegetation dynamics?

Question: Is stomatal regulation specific for climate and tree species, and does it reveal species-specific responses to drought? Is there a link to vegetation dynamics? Location: Dry inner alpine valley, Switzerland Methods: Stomatal aperture (θE) of Pinus sylvestris, Quercus pubescens, Juniperus communis and Picea abies were continuously estimated by the ratio of measured branch sap flow rates to potential transpiration rates (adapted Penman-Monteith single leaf approach) at 10-min intervals over four seasons. Results: θE proved to be specific for climate and species and revealed distinctly different drought responses: Pinus stomata close disproportionately more than neighbouring species under dry conditions, but has a higher θE than the other species when weather was relatively wet and cool. Quercus keeps stomata more open under drought stress but has a lower θE under humid conditions. Juniperus was most drought-tolerant, whereas Picea stomata close almost completely during summer. Conclusions: The distinct microclimatic preferences of the four tree species in terms of θE strongly suggest that climate (change) is altering tree physiological performances and thus species-specific competitiveness. Picea and Pinus currently live at the physiological limit of their ability to withstand increasing temperature and drought intensities at the sites investigated, whereas Quercus and Juniperus perform distinctly better. This corresponds, at least partially, with regional vegetation dynamics: Pinus has strongly declined, whereas Quercus has significantly increased in abundance in the past 30 years. We conclude that θE provides an indication of a species' ability to cope with current and predicted climate.

Evaluation of a Bayesian MCMC Random Effects Inference Methodology for Capture-Mark-Recapture Data

Monte Carlo simulation was used to evaluate properties of a simple Bayesian MCMC analysis of the random effects model for single group Cormack-Jolly-Seber capture-recapture data. The MCMC method is applied to the model via a logit link, so parameters p, S are on a logit scale, where logit(S) is assumed to have, and is generated from, a normal distribution with mean μ and variance σ2 . Marginal prior distributions on logit(p) and μ were independent normal with mean zero and standard deviation 1.75 for logit(p) and 100 for μ ; hence minimally informative. Marginal prior distribution on σ2 was placed on τ2=1/σ2 as a gamma distribution with α=β=0.001 . The study design has 432 points spread over 5 factors: occasions (t) , new releases per occasion (u), p, μ , and σ . At each design point 100 independent trials were completed (hence 43,200 trials in total), each with sample size n=10,000 from the parameter posterior distribution. At 128 of these design points comparisons are made to previously reported results from a method of moments procedure. We looked at properties of point and interval inference on μ , and σ based on the posterior mean, median, and mode and equal-tailed 95% credibility interval. Bayesian inference did very well for the parameter μ , but under the conditions used here, MCMC inference performance for σ was mixed: poor for sparse data (i.e., only 7 occasions) or σ=0 , but good when there were sufficient data and not small σ .