Sleepwalking in Parkinson's disease: a questionnaire-based survey

Sleepwalking (SW) corresponds to a complex sleep-associated behavior that includes locomotion, mental confusion, and amnesia. SW is present in about 10% of children and 2-3% of adults. In a retrospective series of 165 patients with Parkinson's disease (PD), we found adult-onset ("de novo") SW "de novo" in six (4%) of them. The aim of this study was to assess prospectively and systematically the frequency and characteristics of SW in PD patients. A questionnaire including items on sleep quality, sleep disorders, and specifically also SW and REM sleep behavior disorder (RBD), PD characteristics and severity, was sent to the members of the national PD patients organization in Switzerland. In the study, 36/417 patients (9%) reported SW, of which 22 (5%) had adult-onset SW. Patients with SW had significantly longer disease duration (p = 0.035), they reported more often hallucinations (p = 0.004) and nightmares (p = 0.003), and they had higher scores, suggestive for RBD in a validated questionnaire (p = 0.001). Patients with SW were also sleepier (trend to a higher Epworth Sleepiness Scale score, p = 0.055). Our data suggest that SW in PD patients is (1) more common than in the general population, and (2) is associated with RBD, nightmares, and hallucinations. Further studies including polysomnographic recordings are needed to confirm the results of this questionnaire-based analysis, to understand the relationship between SW and other nighttime wandering behaviors in PD, and to clarify the underlying mechanisms.

Population-based epidemiology of rotavirus hospitalisations in Switzerland

BACKGROUND: Rotaviruses (RV) are the most common cause of dehydrating gastroenteritis requiring hospitalisation in children <5 years of age. A new generation of safe and effective RV vaccines is available. Accurate data describing the current burden of RV disease in the community are needed to devise appropriate strategies for vaccine usage. METHODS: Retrospective, population-based analysis of RV hospitalisations in children <5 years of age during a 5-year period (1999-2003) in a both urban and rural area inhabited by 12% of the Swiss population. RESULTS: Of 406 evaluable cases, 328 were community-acquired RV infections in children <5 years of age. RV accounted for 38% of all hospitalisations for gastroenteritis. The overall hospitalisation incidence in the <5-year-old was 1.5/1000 child-years (peak incidence, 2.6/1000 child-years in children aged 13-24 months). The incidence of community-acquired RV hospitalisations was significantly greater in children of non-Swiss origin (3.0 vs. 1.1/1000 child-years, relative risk 2.7; 95% CI 2.2-3.4), who were younger, but tended to be less severely dehydrated on admission than Swiss children. In comparison with children from urban areas, RV hospitalisation incidence was significantly lower among those residing in the remote mountain area (0.71 vs. 1.71/1000 child years, relative risk 2.2, 95% CI 1.6-3.1). CONCLUSION: Population-based RV hospitalisation incidence was low in comparison with other European countries. Significantly greater hospitalisation rates among children living in urban areas and those from non-Swiss families indicate that factors other than the severity of RV-induced dehydration are important driving forces of hospital admission.

Diagnostic accuracy of 64-slice computed tomography for detecting angiographically significant coronary artery stenosis in an unselected consecutive patient population: comparison with conventional invasive angiography

BACKGROUND: Multislice computed tomography (MSCT) is a promising noninvasive method of detecting coronary artery disease (CAD). However, most data have been obtained in selected series of patients. The purpose of the present study was to investigate the accuracy of 64-slice MSCT (64 MSCT) in daily practice, without any patient selection. METHODS AND RESULTS: Using 64-slice MSCT coronary angiography (CTA), 69 consecutive patients, 39 (57%) of whom had previously undergone stent implantation, were evaluated. The mean heart rate during scan was 72 beats/min, scan time 13.6 s and the amount of contrast media 72 mL. The mean time span between invasive coronary angiography (ICAG) and CTA was 6 days. Significant stenosis was defined as a diameter reduction of > 50%. Of 966 segments, 884 (92%) were assessable. Compared with ICAG, the sensitivity of CTA to diagnose significant stenosis was 90%, specificity 94%, positive predictive value (PPV) 89% and negative predictive value (NPV) 95%. With regard to 58 stented lesions, the sensitivity, specificity, PPV and NPV were 93%, 96%, 87% and 98%, respectively. On the patient-based analysis, the sensitivity, specificity, PPV and NPV of CTA to detect CAD were 98%, 86%, 98% and 86%, respectively. Eighty-two (8%) segments were not assessable because of irregular rhythm, calcification or tachycardia. CONCLUSION: Sixty-four-MSCT has a high accuracy for the detection of significant CAD in an unselected patient population and therefore can be considered as a valuable noninvasive technique.

Functionally relevant coronary artery disease: comparison of 64-section CT angiography with myocardial perfusion SPECT

PURPOSE: To prospectively determine the accuracy of 64-section computed tomographic (CT) angiography for the depiction of coronary artery disease (CAD) that induces perfusion defects at myocardial perfusion imaging with single photon emission computed tomography (SPECT), by using myocardial perfusion imaging as the reference standard. MATERIALS AND METHODS: All patients gave written informed consent after the study details, including radiation exposure, were explained. The study protocol was approved by the local institutional review board. In patients referred for elective conventional coronary angiography, an additional 64-section CT angiography study and a myocardial perfusion imaging study (1-day adenosine stress-rest protocol) with technetium 99m-tetrofosmin SPECT were performed before conventional angiography. Coronary artery diameter narrowing of 50% or greater at CT angiography was defined as stenosis and was compared with the myocardial perfusion imaging findings. Quantitative coronary angiography served as a reference standard for CT angiography. RESULTS: A total of 1093 coronary segments in 310 coronary arteries in 78 patients (mean age, 65 years +/- 9 [standard deviation]; 35 women) were analyzed. CT angiography revealed stenoses in 137 segments (13%) corresponding to 91 arteries (29%) in 46 patients (59%). SPECT revealed 14 reversible, 13 fixed, and six partially reversible defects in 31 patients (40%). Sensitivity, specificity, and negative and positive predictive values, respectively, of CT angiography in the detection of reversible myocardial perfusion imaging defects were 95%, 53%, 94%, and 58% on a per-patient basis and 95%, 75%, 96%, and 72% on a per-artery basis. Agreement between CT and conventional angiography was very good (96% and kappa = 0.92 for patient-based analysis, 93% and kappa = 0.84 for vessel-based analysis). CONCLUSION: Sixty-four-section CT angiography can help rule out hemodynamically relevant CAD in patients with intermediate to high pretest likelihood, although an abnormal CT angiography study is a poor predictor of ischemia.

Pulse contour analysis: a valid assessment of central arterial stiffness in children?

In adults the contour analysis of peripheral pressure waves in the upper limb reflects central aortic stiffness. Here, we wanted to demonstrate the appropriateness of pulse contour analysis to assess large artery stiffness in children. Digital volume pulse analysis, with the computation of the stiffness index and pulse wave velocity between carotid and femoral artery, were simultaneously determined in 79 healthy children between 8 years and 15 years (mean age 11.4 years, 32 girls). The stiffness index of 42 healthy adults (mean age 45.6 years, 26 women) served as control. Pulse wave velocity between carotid and femoral artery was directly correlated with systolic pressure and mean blood pressure, as well as with pulse pressure. The results from the stiffness index of children revealed the expected values extrapolated from the linear regression of adulthood stiffness index vs. age. Childhood stiffness index positively correlated with pulse wave velocity (r(2) = 0.07, P = 0.02) but not with blood pressure parameters. The exclusion of individuals with an increased vascular tone, as indicated by a reflexion index > 90%, improved the correlation between stiffness index and pulse wave velocity (r(2) = 0.13, P = 0.001). Our data indicate that digital volume pulse-based analysis has limitations if compared with pulse wave velocity to measure arterial stiffness, mostly in patients with a high vascular tone.

Stochastic knock detection model for spark ignited engines

This report presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. Knock Signal Simulator (KSS) was developed as the plant model for the engine. The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies. The SKD method is implemented in Knock Detection Module (KDM) which processes the knock intensities generated by KSS with a stochastic distribution estimation algorithm and outputs estimates of high and low knock intensity levels which characterize knock and reference level respectively. These estimates are then used to determine a knock factor which provides quantitative measure of knock level and can be used as a feedback signal to control engine knock. The knock factor is analyzed and compared with a traditional knock detection method to detect engine knock under various engine operating conditions. To verify the effectiveness of the SKD method, a knock controller was also developed and tested in a model-in-loop (MIL) system. The objective of the knock controller is to allow the engine to operate as close as possible to its border-line spark-timing without significant engine knock. The controller parameters were tuned to minimize the cycle-to-cycle variation in spark timing and the settling time of the controller in responding to step increase in spark advance resulting in the onset of engine knock. The simulation results showed that the combined system can be used adequately to model engine knock and evaluated knock control strategies for a wide range of engine operating conditions.

Generating Dutiful Members in Communities of 'Rational Choice'

The study 'Youth Welfare as Prevention - The reconfiguration of support and control in advanced liberalism' is part of the Graduate program 'Youth Welfare in Transition' funded by the 'German Research Association'. In empirical terms it is based on both interviews with professionals, reconstructive discourse analysis based on documents and programs as well as a secondary analysis of a range of existing studies.

Dynamic Chemical Shift Imaging for Image-Guided Thermal Therapy

Magnetic resonance temperature imaging (MRTI) is recognized as a noninvasive means to provide temperature imaging for guidance in thermal therapies. The most common method of estimating temperature changes in the body using MR is by measuring the water proton resonant frequency (PRF) shift. Calculation of the complex phase difference (CPD) is the method of choice for measuring the PRF indirectly since it facilitates temperature mapping with high spatiotemporal resolution. Chemical shift imaging (CSI) techniques can provide the PRF directly with high sensitivity to temperature changes while minimizing artifacts commonly seen in CPD techniques. However, CSI techniques are currently limited by poor spatiotemporal resolution. This research intends to develop and validate a CSI-based MRTI technique with intentional spectral undersampling which allows relaxed parameters to improve spatiotemporal resolution. An algorithm based on autoregressive moving average (ARMA) modeling is developed and validated to help overcome limitations of Fourier-based analysis allowing highly accurate and precise PRF estimates. From the determined acquisition parameters and ARMA modeling, robust maps of temperature using the k-means algorithm are generated and validated in laser treatments in ex vivo tissue. The use of non-PRF based measurements provided by the technique is also investigated to aid in the validation of thermal damage predicted by an Arrhenius rate dose model.

DUAL ENERGY COMPUTED TOMOGRAPHY FOR PROTON THERAPY TREATMENT PLANNING

Proton radiation therapy is gaining popularity because of the unique characteristics of its dose distribution, e.g., high dose-gradient at the distal end of the percentage-depth-dose curve (known as the Bragg peak). The high dose-gradient offers the possibility of delivering high dose to the target while still sparing critical organs distal to the target. However, the high dose-gradient is a double-edged sword: a small shift of the highly conformal high-dose area can cause the target to be substantially under-dosed or the critical organs to be substantially over-dosed. Because of that, large margins are required in treatment planning to ensure adequate dose coverage of the target, which prevents us from realizing the full potential of proton beams. Therefore, it is critical to reduce uncertainties in the proton radiation therapy. One major uncertainty in a proton treatment is the range uncertainty related to the estimation of proton stopping power ratio (SPR) distribution inside a patient. The SPR distribution inside a patient is required to account for tissue heterogeneities when calculating dose distribution inside the patient. In current clinical practice, the SPR distribution inside a patient is estimated from the patient’s treatment planning computed tomography (CT) images based on the CT number-to-SPR calibration curve. The SPR derived from a single CT number carries large uncertainties in the presence of human tissue composition variations, which is the major drawback of the current SPR estimation method. We propose to solve this problem by using dual energy CT (DECT) and hypothesize that the range uncertainty can be reduced by a factor of two from currently used value of 3.5%. A MATLAB program was developed to calculate the electron density ratio (EDR) and effective atomic number (EAN) from two CT measurements of the same object. An empirical relationship was discovered between mean excitation energies and EANs existing in human body tissues. With the MATLAB program and the empirical relationship, a DECT-based method was successfully developed to derive SPRs for human body tissues (the DECT method). The DECT method is more robust against the uncertainties in human tissues compositions than the current single-CT-based method, because the DECT method incorporated both density and elemental composition information in the SPR estimation. Furthermore, we studied practical limitations of the DECT method. We found that the accuracy of the DECT method using conventional kV-kV x-ray pair is susceptible to CT number variations, which compromises the theoretical advantage of the DECT method. Our solution to this problem is to use a different x-ray pair for the DECT. The accuracy of the DECT method using different combinations of x-ray energies, i.e., the kV-kV, kV-MV and MV-MV pair, was compared using the measured imaging uncertainties for each case. The kV-MV DECT was found to be the most robust against CT number variations. In addition, we studied how uncertainties propagate through the DECT calculation, and found general principles of selecting x-ray pairs for the DECT method to minimize its sensitivity to CT number variations. The uncertainties in SPRs estimated using the kV-MV DECT were analyzed further and compared to those using the stoichiometric method. The uncertainties in SPR estimation can be divided into five categories according to their origins: the inherent uncertainty, the DECT modeling uncertainty, the CT imaging uncertainty, the uncertainty in the mean excitation energy, and SPR variation with proton energy. Additionally, human body tissues were divided into three tissue groups – low density (lung) tissues, soft tissues and bone tissues. The uncertainties were estimated separately because their uncertainties were different under each condition. An estimate of the composite range uncertainty (2s) was determined for three tumor sites – prostate, lung, and head-and-neck, by combining the uncertainty estimates of all three tissue groups, weighted by their proportions along typical beam path for each treatment site. In conclusion, the DECT method holds theoretical advantages in estimating SPRs for human tissues over the current single-CT-based method. Using existing imaging techniques, the kV-MV DECT approach was capable of reducing the range uncertainty from the currently used value of 3.5% to 1.9%-2.3%, but it is short to reach our original goal of reducing the range uncertainty by a factor of two. The dominant source of uncertainties in the kV-MV DECT was the uncertainties in CT imaging, especially in MV CT imaging. Further reduction in beam hardening effect, the impact of scatter, out-of-field object etc. would reduce the Hounsfeld Unit variations in CT imaging. The kV-MV DECT still has the potential to reduce the range uncertainty further.

Assessing the Potential of Multiple Imputation in Sequence Analysis

Sequence analysis and optimal matching are useful heuristic tools for the descriptive analysis of heterogeneous individual pathways such as educational careers, job sequences or patterns of family formation. However, to date it remains unclear how to handle the inevitable problems caused by missing values with regard to such analysis. Multiple Imputation (MI) offers a possible solution for this problem but it has not been tested in the context of sequence analysis. Against this background, we contribute to the literature by assessing the potential of MI in the context of sequence analyses using an empirical example. Methodologically, we draw upon the work of Brendan Halpin and extend it to additional types of missing value patterns. Our empirical case is a sequence analysis of panel data with substantial attrition that examines the typical patterns and the persistence of sex segregation in school-to-work transitions in Switzerland. The preliminary results indicate that MI is a valuable methodology for handling missing values due to panel mortality in the context of sequence analysis. MI is especially useful in facilitating a sound interpretation of the resulting sequence types.

VIRTOPSY--scientific documentation, reconstruction and animation in forensic: individual and real 3D data based geo-metric approach including optical body/object surface and radiological CT/MRI scanning.

Until today, most of the documentation of forensic relevant medical findings is limited to traditional 2D photography, 2D conventional radiographs, sketches and verbal description. There are still some limitations of the classic documentation in forensic science especially if a 3D documentation is necessary. The goal of this paper is to demonstrate new 3D real data based geo-metric technology approaches. This paper present approaches to a 3D geo-metric documentation of injuries on the body surface and internal injuries in the living and deceased cases. Using modern imaging methods such as photogrammetry, optical surface and radiological CT/MRI scanning in combination it could be demonstrated that a real, full 3D data based individual documentation of the body surface and internal structures is possible in a non-invasive and non-destructive manner. Using the data merging/fusing and animation possibilities, it is possible to answer reconstructive questions of the dynamic development of patterned injuries (morphologic imprints) and to evaluate the possibility, that they are matchable or linkable to suspected injury-causing instruments. For the first time, to our knowledge, the method of optical and radiological 3D scanning was used to document the forensic relevant injuries of human body in combination with vehicle damages. By this complementary documentation approach, individual forensic real data based analysis and animation were possible linking body injuries to vehicle deformations or damages. These data allow conclusions to be drawn for automobile accident research, optimization of vehicle safety (pedestrian and passenger) and for further development of crash dummies. Real 3D data based documentation opens a new horizon for scientific reconstruction and animation by bringing added value and a real quality improvement in forensic science.

Ventilation/perfusion SPECT/CT in patients with pulmonary emphysema. Evaluation of software-based analysing

UNLABELLED The purpose of this study was to evaluate the reproducibility of a new software based analysing system for ventilation/perfusion single-photon emission computed tomography/computed tomography (V/P SPECT/CT) in patients with pulmonary emphysema and to compare it to the visual interpretation. PATIENTS, MATERIAL AND METHODS 19 patients (mean age: 68.1 years) with pulmonary emphysema who underwent V/P SPECT/CT were included. Data were analysed by two independent observers in visual interpretation (VI) and by software based analysis system (SBAS). SBAS PMOD version 3.4 (Technologies Ltd, Zurich, Switzerland) was used to assess counts and volume per lung lobe/per lung and to calculate the count density per lung, lobe ratio of counts and ratio of count density. VI was performed using a visual scale to assess the mean counts per lung lobe. Interobserver variability and association for SBAS and VI were analysed using Spearman's rho correlation coefficient. RESULTS Interobserver agreement correlated highly in perfusion (rho: 0.982, 0.957, 0.90, 0.979) and ventilation (rho: 0.972, 0.924, 0.941, 0.936) for count/count density per lobe and ratio of counts/count density in SBAS. Interobserver agreement correlated clearly for perfusion (rho: 0.655) and weakly for ventilation (rho: 0.458) in VI. CONCLUSIONS SBAS provides more reproducible measures than VI for the relative tracer uptake in V/P SPECT/CTs in patients with pulmonary emphysema. However, SBAS has to be improved for routine clinical use.

Car, parce que, puisque’ revisited: Three empirical studies on French causal connectives

In French, a causal relation is often conveyed by the connectives car, parce que or puisque. Since the seminal work of the Lambda-l Group (1975), it has generally been assumed that parce que, used to relate semantic content, contrasts with car and puisque, both used to connect either speech act or epistemic content. However, this analysis leaves a number of questions unanswered. In this paper, I present a reanalysis of this trio, using empirical methods such as corpus analysis and constrained elicitation. Results indicate that car and parce que are interchangeable in many contexts, even if they are still prototypically used in their respective domain in writing. As for puisque, its distribution does not overlap with car, despite their similar domains of use. I argue that the specificity of puisque with respect to the other two connectives is to introduce a cause with an echoic meaning.

Network-based genome-wide association study of Crohn's disease

Genome-wide association studies (GWAS) have rapidly become a standard method for disease gene discovery. Many recent GWAS indicate that for most disorders, only a few common variants are implicated and the associated SNPs explain only a small fraction of the genetic risk. The current study incorporated gene network information into gene-based analysis of GWAS data for Crohn's disease (CD). The purpose was to develop statistical models to boost the power of identifying disease-associated genes and gene subnetworks by maximizing the use of existing biological knowledge from multiple sources. The results revealed that Markov random field (MRF) based mixture model incorporating direct neighborhood information from a single gene network is not efficient in identifying CD-related genes based on the GWAS data. The incorporation of solely direct neighborhood information might lead to the low efficiency of these models. Alternative MRF models looking beyond direct neighboring information are necessary to be developed in the future for the purpose of this study.^

Gene-gene interaction and gene-pathway analysis of genome-wide association for schizophrenia

Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^