Single Standard Deviation Research Articles

From Escherichia coli mutant 13C labeling data to a core kinetic model: A kinetic model parameterization pipeline.

Kinetic models of metabolic networks offer the promise of quantitative phenotype prediction. The mechanistic characterization of enzyme catalyzed reactions allows for tracing the effect of perturbations in metabolite concentrations and reaction fluxes in response to genetic and environmental perturbation that are beyond the scope of stoichiometric models. In this study, we develop a two-step computational pipeline for the rapid parameterization of kinetic models of metabolic networks using a curated metabolic model and available 13C-labeling distributions under multiple genetic and environmental perturbations. The first step involves the elucidation of all intracellular fluxes in a core model of E. coli containing 74 reactions and 61 metabolites using 13C-Metabolic Flux Analysis (13C-MFA). Here, fluxes corresponding to the mid-exponential growth phase are elucidated for seven single gene deletion mutants from upper glycolysis, pentose phosphate pathway and the Entner-Doudoroff pathway. The computed flux ranges are then used to parameterize the same (i.e., k-ecoli74) core kinetic model for E. coli with 55 substrate-level regulations using the newly developed K-FIT parameterization algorithm. The K-FIT algorithm employs a combination of equation decomposition and iterative solution techniques to evaluate steady-state fluxes in response to genetic perturbations. k-ecoli74 predicted 86% of flux values for strains used during fitting within a single standard deviation of 13C-MFA estimated values. By performing both tasks using the same network, errors associated with lack of congruity between the two networks are avoided, allowing for seamless integration of data with model building. Product yield predictions and comparison with previously developed kinetic models indicate shifts in flux ranges and the presence or absence of mutant strains delivering flux towards pathways of interest from training data significantly impact predictive capabilities. Using this workflow, the impact of completeness of fluxomic datasets and the importance of specific genetic perturbations on uncertainties in kinetic parameter estimation are evaluated.

69-OR: Mobility, Satisfaction, and Quality of Life among Long-Term Dysvascular/Diabetic Prosthesis Users: Results of a National Cross-Sectional Survey

Objective: To establish the mobility, satisfaction and quality of life among prosthesis users with major lower limb dysvascular/diabetic amputation (transtibial or proximal) at various long-term phases of prosthetic rehabilitation. Methods: A multi-site, cross-sectional outcomes analysis. A total of 341 individuals met inclusion/exclusion criteria. Individuals were grouped in acute phases (0-3 mos (n=24); 4-6 mos (n=72)) and chronic phases (24-36 mos (n=91), 37-48 mos (n=53), 49-60 mos (n=47) and 60-84 mos (n=54)) post-amputation. Mobility was measured with the Prosthetic Limb Users Survey of Mobility (PLUS-M) while quality of life (Qol) and satisfaction (Sat) were reported using 10-point scales adapted from the Prosthesis Evaluation Questionnaire-Well Being (PEQ-WB). Results: The average mobility, Qol and Sat among prosthesis users was, respectively, 44.8±10.6, 7.6±2.2 and 7.6±2.2. There were no observed differences in mobility (F5,330=1.52, p=0.18) or Qol (F5,333=0.78, p=0.57) between any groups. For Sat, there was a group difference (F5,334=2.44, p=0.03) as individuals who receive a prosthesis 0-3 mos experience initial higher Sat values compared to those 25-36 mos (p=0.005), 49-60 mos (p=0.008), and 61-84 mos (p=0.009). Conclusion: Those individuals with amputation secondary to dysvascular disease and diabetes who continue to participate in prosthetic rehabilitation appear to maintain reasonable levels of mobility, satisfaction and quality of life as much as 7 years post amputation. There may be a modest initial increase in satisfaction with the early receipt of a prosthesis. However, transfemoral amputations were under represented in this cohort of individuals fitted shortly after amputation. Notably, the mobility levels observed in the dysvascular population through a range of extended post-amputation durations remain within a single standard deviation of the amputee population mean for mobility. Disclosure P. Stevens: Employee; Self; Hanger Clinic. S.R. Wurdeman: None. Funding American Orthotics & Prosthetics Association (EB-043016)

Reliability-based optimum design of hydraulic water retaining structure constructed on heterogeneous porous media: utilizing stochastic ensemble surrogate model-based linked simulation optimization model

Seepage characteristics under hydraulic water retaining structures (HWRSs) significantly affect the hydraulic serviceability and stability of such structures. The expected hydraulic conductivity value and its spatial and directional variation substantially influence seepage characteristics. Furthermore, the uniform and homogenous hydraulic conductive is rarely seen in the real field. To study the effects of uncertainty and variation in hydraulic conductivity, a random field concept was used to generate different realizations of heterogeneous hydraulic conductivity with constant mean and varied standard deviation. Consequently, the seepage characteristics stochastically varied, creating uncertainty in seepage characteristics which influenced the HWRS design. Therefore, the objective of this paper was to integrate the reliability concept in the linked simulation optimization (S-O) model to address the uncertainty of hydraulic conductivity. Hence, the safest and most cost-effective HWRS design could be attained considering the effects of the uncertainty of hydraulic conductivity. The reliability-based optimum design (RBOD) concept was implemented utilizing the multiple realization optimization technique based on stochastic ensemble surrogate models. The reliability degree of each candidate design was measured based on the number of stochastic constraints satisfying the design requirements to the total number of constraints. The S-O model-based RBOD was formulated to find the most cost-effective HWRS design satisfying a beforehand desired degree of reliability. Each surrogate model was trained utilizing several (input–output) data sets simulated using numerical seepage modeling code (SEEPW). The Gaussian process regression machine learning technique was used to train several surrogate models to imitate the responses of the numerical seepage modeling. Each single input data set was solved (4 × 5) times to simulate four different realizations of spatial variation resulting from one of the five different standard deviation values (0.85, 1.55, 2.25, 2.95, 3.65 m/day) with constant mean (2 m/day). Each group of data for single standard deviation was utilized to train a single surrogate model. The genetic algorithm-based S-O model was utilized as an efficient optimization solver for such complex optimization task. The results of this study demonstrated that the reliability significantly influenced the design of HWRS. Further, the deterministic optimum design of HWRS was insufficient to be considered a reliable design, especially when a high degree of uncertainty due to the hydraulic conductivity estimation is included. Hence, RBOD for such problem is essential and helps the designer make a decision.

Timing performance of organic scintillators coupled to silicon photomultipliers

This work compares the time resolution obtained from coincidence measurements using combinations of four types of silicon photomultipliers (SiPMs), five types of organic scintillators, and two timing algorithms. Organic scintillators in combination with SiPMs have shown to have equivalent or better time resolution and pulse shape discrimination (PSD) capability than with photo-multiplier tubes (PMTs). In addition, SiPMs are more compact and require low operating voltage. These factors have made them suitable for the development of compact neutron scatter cameras (NSCs) and potentially low-cost positron emission tomography (PET) systems. The following measurements analyze combinations of organic scintillators and SiPMs that could be used for these applications. Measurements and analyses assessed the time resolution of standard-output and fast-output pulses of the various scintillator and SiPM combinations. The coincidence measurements were performed using a Na-22 source to characterize time resolution where all coincident events above about a 40 keVee threshold were analyzed. Uncertainties were determined by applying bootstrapping to the acquired data sets. The full width at half maximum (FWHM) of the time difference distribution for each combination is reported as the time resolution of the system. For standard-output pulses, we found that using a digital implementation of analogue constant fraction discrimination (DIACFD) improved timing resolution greater than a single standard deviation for six of the fourteen tested combinations compared to using digital constant fraction discrimination (DCFD). Conversely, for fast-output pulses, DCFD with a moving average filter produced the best timing resolution. Among the tested non-PSD capable organic scintillators, EJ-228 coupled to a MicroFJ-SMA-60035 SensL SiPM yielded the best time resolution of 303 ± 4 ps for standard-output pulses and 227 ± 4 ps for fast-output pulses. The best time resolution found for PSD capable organic scintillators was obtained using Inrad Optics stilbene coupled to a MicroFJ-SMA-60035 SensL SiPM which yielded a time resolution of 428 ± 6 ps for standard-output pulses and 293 ± 4 ps for fast-output pulses.

Association of blood pressure with estimates of 24-h urinary sodium and potassium excretion from repeated single-spot urine samples.

While the association between 24-h urinary sodium and potassium excretion with blood pressure is well established, the relationships of these ions to spot urine measurements are unclear. Our purpose is to assess the association between blood pressure and the estimated 24-h sodium and potassium excretion from repeated single-spot urine samples. Spot urine and blood pressure were collected annually during a 5-year period from 4360 Japanese workers with ages ranging from 19 to 55 years. Estimates of 24-h sodium and potassium excretion were based on Tanaka's formula. Overall, a single standard deviation increase in the estimated sodium excretion (36.5 mmol/day) was associated with a 1.3 mmHg higher systolic blood pressure and a 0.8 mmHg higher diastolic blood pressure (P < 0.001). A single standard deviation increase in estimated potassium excretion (8.9 mmol/day) was associated with a 1.1 mmHg lower systolic blood pressure and a 0.7 mmHg lower diastolic blood pressure (P < 0.001). As a combined measure of the excretion of both electrolytes, the estimated 24-h sodium-to-potassium ratio was positively associated with both blood pressures (P < 0.001). Associations of blood pressure with sodium and the sodium-to-potassium ratio increased with age and were stronger in men compared to women. Associations with potassium and the sodium-to-potassium ratio were stronger in individuals who were overweight. The findings provide evidence for an association between blood pressure and the estimated 24-h sodium and potassium excretion from repeated single-spot urine samples. As convenient measures of dietary intake for each electrolyte, repeated spot urine samples may be useful for assessing hypertension risk, especially in men, older individuals, and overweight individuals.

Murine vs human tissue compositions: implications of using human tissue compositions for photon energy absorption in mice.

Dual energy CT (DECT) images of 9 female mice were used to extract the effective atomic number Zeff and the relative electron density ρe for each voxel in the images. To investigate the influence of the tissue compositions on the absorbed radiation dose for a typical kilovoltage photon beam, mass energy-absorption coefficients μen/ρ were calculated for 10 different tissues in each mouse. Differences between human and murine tissue compositions can lead to errors around 7.5 % for soft tissues and 20.1 % for bone tissues in μen/ρ values for kilovoltage photon beams. When considering the spread within tissues, these errors can increase up to 17.5 % for soft tissues and 53.9 % for bone tissues within only a single standard deviation away from the mean tissue value. This study illustrates the need for murine reference tissue data. However, assigning only a single mean reference value to an entire tissue can still lead to large errors in dose calculations given the large spread within tissues of μen/ρ values found in this study. Therefore, new methods such as DECT and spectral CT imaging need to be explored, which can be important next steps in improving tissue assignment for dose calculations in small animal radiotherapy. This is the first study that investigates the implications of using human tissue compositions for dose calculations in mice for kilovoltage photon beams.

Point-Collocation Non-intrusive Polynomial Chaos 기법을 활용한 평판 주위 난류 유동장 해석

In the present work, uncertainty quantification based on the point-collocation Non-intrusive Polynomial Chaos was studied in turbulent flow around the flat plate using Menter’s SST k-ω model. Two random variables of β* , model coefficient of Menter’s SST k-ω model and USUB∞/SUB, the freestream velocity are considered. β*, model coefficient was assumed to be uniformly distributed and the freestream velocity USUB∞/SUB, normally distributed with a certain value of variance. First, the uncertainty quantification with the single random variable of each one was simulated for sensitivity analysis of each parameter on the outputs such as drag coefficient and skin friction one. When the normal distribution of freestream velocity is considered, the drag coefficient showed the same type of distribution with 0.9% standard deviation. The uniform distribution of β* with the internals of 0.0784 and 0.1024 had an effect on 5% variance on drag coefficient. When two random variables are considered simultaneously, the distribution of drag coefficient showed closer type with one of model coefficient β* .The convergence rate of mean value was late than that with single random variable and standard deviation was not converged until the 5th order of gPC.

ASSOCIATION BETWEEN SITTING TIME AND MAJOR DISEASES IN BRAZILIAN OCTOGENARIANS

The aim of this study was to associate sitting time with major diseases affecting octogenarians. This observational cross-sectional study involved 351 octogenarians, being 323 women and 28 men, with a mean age of 84.1 (SD = 3.9). Sociodemographic data, health conditions and responses to Section 5 of the International Physical Activity Questionnaire (IPAQ) were entered into a diagnostic program in order to determine the weekly time spent sitting down. Descriptive (single frequency, percentage, mean, and standard deviation) and inferential statistics (Mann-Whitney U test and binary logistic regression) were used. The data were examined at a 5% significance level. The most frequent diseases in the octogenarians were high blood pressure (60.1%), heart diseases (26.5%), diabetes (21.9%), dyslipidemia (21.7%), osteoporosis (18.5%), and osteoarthritis (14.5%). The longer they spent sitting down, the greater the risk of developing diabetes (OR = 4.5, 95% CI 2.5 to 8.2) and dyslipidemia (OR = 2.9, 95% CI 1.6 to 5.0). A sitting time of more than 1,710 minutes per week can predict the occurrence of diabetes (p = 0.002), while sitting for more than 1,380 minutes per week can predict the occurrence of dyslipidemia (p = 0.002). Sitting time was found to be a risk factor for the occurrence of diabetes and dyslipidemia in the studied octogenarians. Chronic diseases were associated with sedentary behavior.

Strontium carbonate precipitation as a sample preparation technique for isotope ratio analysis of Sr in mineral water and wine by quadrupole-based inductively coupled plasma mass spectrometry.

The defined origin of food products is nowadays often seen as a marker of quality. Stontium (Sr) isotope ratio determination can be used to verify the origin of such food products and it has thus become an important technique. Wine samples in particular are often investigated using this technique. Sr isotopic ratio measurements are often disturbed by isobaric Rb interference, making a separation procedure necessary. In this investigation a very simple and effective procedure for the separation of Rb+ and Sr2+ ions for Sr isotope ratio determination in mineral water and wine samples was developed. The classical Sr-carbonate precipitation reaction for the separation of Sr2+ ions from highly soluble Rb+ ions was used. For liquid samples, such as mineral water or wine, a prior digestion is not required. This sample preparation procedure was successfully applied for Sr isotope measurements on a widely available quadrupole-based inductively coupled plasma mass spectrometry (ICP-MS) device in combination with the Concentration-Gradient-Method (CGM). The separation achieved Sr/Rb concentration ratios of 50,000 to 150,000 in water and wine samples. The addition of Ca2+ ions to co-precipitate with the traces of Sr improved the Rb separation and the reproducibility of isotope ratio determination to an uncertainty of ±0.4 ‰ (single standard deviation). This sample preparation approach achieved 2 to 6 times better Rb separation than the commonly applied ion-exchange resin materials. The quality of the separation is only limited by the number of precipitation repetitions. Moreover, the applicability of quadrupole-based ICP-MS for the characterisation of samples with respect to their origin by means of Sr isotope ratio determination was demonstrated.

Comparison of lung tumor motion measured using a model-based 4DCT technique and a commercial protocol

PurposeTo compare lung tumor motion measured with a model-based technique to commercial 4-dimensional computed tomography (4DCT) scans and describe a workflow for using model-based 4DCT as a clinical simulation protocol. Methods and materialsTwenty patients were imaged using a model-based technique and commercial 4DCT. Tumor motion was measured on each commercial 4DCT dataset and was calculated on model-based datasets for 3 breathing amplitude percentile intervals: 5th to 85th, 5th to 95th, and 0th to 100th. Internal target volumes (ITVs) were defined on the 4DCT and 5th to 85th interval datasets and compared using Dice similarity. Images were evaluated for noise and rated by 2 radiation oncologists for artifacts. ResultsMean differences in tumor motion magnitude between commercial and model-based images were 0.47 ± 3.0, 1.63 ± 3.17, and 5.16 ± 4.90 mm for the 5th to 85th, 5th to 95th, and 0th to 100th amplitude intervals, respectively. Dice coefficients between ITVs defined on commercial and 5th to 85th model-based images had a mean value of 0.77 ± 0.09. Single standard deviation image noise was 11.6 ± 9.6 HU in the liver and 6.8 ± 4.7 HU in the aorta for the model-based images compared with 57.7 ± 30 and 33.7 ± 15.4 for commercial 4DCT. Mean model error within the ITV regions was 1.71 ± 0.81 mm. Model-based images exhibited reduced presence of artifacts at the tumor compared with commercial images. ConclusionTumor motion measured with the model-based technique using the 5th to 85th percentile breathing amplitude interval corresponded more closely to commercial 4DCT than the 5th to 95th or 0th to 100th intervals, which showed greater motion on average. The model-based technique tended to display increased tumor motion when breathing amplitude intervals wider than 5th to 85th were used because of the influence of unusually deep inhalations. These results suggest that care must be taken in selecting the appropriate interval during image generation when using model-based 4DCT methods.

Extra-axial cerebrospinal fluid spaces in children with benign external hydrocephalus: A case-control study.

Background The distinction between normal and pathological extra-axial cerebrospinal fluid (CSF) spaces is unclear, with the use of the term benign external hydrocephalus (BEH) not being well defined in clinical practice. This study aimed to establish a distribution of metrics of the subarachnoid space in a population of children diagnosed as normal, and investigate the clinical use of the term BEH. Methods A retrospective case-control study on magnetic resonance image scans was performed on 150 children diagnosed as normal and 10 children diagnosed with BEH. Measurements were taken in the axial plane for CSF width (CSFW), and interhemispheric width (IHW). Results Normal controls had a mean age of 11.1 ± 7.6 months (78 male, 72 female) and the BEH sample had a mean age of 10.6 ± 7.8 months (six male, four female). Mean CSFW was 7.96 ± 4.79 mm in the BEH sample compared to 4.58 ± 2.25 mm in the normal sample ( p < 0.05). Mean IHW was 6.30 ± 2.79 mm in the BEH sample compared to 3.89 ± 1.83 mm in the normal sample ( p < 0.05). However, a substantial overlap between the two distributions of CSFW was found, with 50% of BEH patients lying within a single standard deviation of the mean of normal individuals. Conclusion The absence of diagnostic criteria for BEH means reporting is variable. Patients being diagnosed with BEH who have no other clinical defects may represent the extreme of the normal population rather than a distinct clinical entity.

A short note on the inclusion of sultriness issues in perceived temperature in mild climates

Sultriness is a specific case in thermal perception under warm/humid environments and frequently applied in German operational weather forecast and is assumed if the dew-point temperature t d exceeds a threshold of 16.5 °C. In perceived temperature (PT), which is based on the ASHRAE two-node-model, a Central European climatology was prepared of the classical predicted mean vote (PMV), exclusively linked to thermal stress, and the so-called rational PMV* that additionally accounts for the humidity in the meteorological environment and is closely linked to thermal strain. The standard deviation of the difference ΔPMV = PMV* − PMV over PMV reveals a similarity to the appearance of sultriness that suggests as side effect of the PT parameterisation a thermophysiologically based definition of sultriness: “Under warm/humid conditions a subject adapted to mild climatologic conditions perceives sultriness if the actual value of ΔPMV exceeds the long-term mean by more than its single standard deviation”. This definition accounts for all environmental and subject related variables influencing the thermal state of the body and is in accordance with all in the literature described properties in the perception of sultriness. The two definitions coincide more or less at daylight hours for t d values markedly beyond the threshold. However, in the t d threshold region, the PT-derived definition offers stronger differentiated patterns and is significantly less frequent at nighttime than the mono-causal definition. For given PT values, the sensible heat flux via the skin shows an increase under a sultry environment, whereas the latent is reduced; skin and core temperatures as well as the skin blood flow are also less. In any case, PT-derived sultriness is linked with an increased thermal strain on the body temperatures, which is a measure of discomfort caused by increased humidity and/or dissatisfaction with the thermal environment. This confirms the thermal uncomfortable feeling accompanying the perception of sultriness. Therefore, the PT-derived sultriness can be presumed to be a more appropriate measure for the perception of sultriness, because it accounts for all environmental impacts on thermoregulation.

FPGA implementation of a high‐speed, real‐time, windowed standard deviation filter

Characterisation of the standard deviation of a time-series signal has uncommon, yet widespread applications. The usual requirement for a representation of signal standard deviation in real-time implies a high computation speed. A method based on a field programmable gate array (FPGA) implementation is presented. The technique is benchmarked against conventional computational approaches and shows a single windowed standard deviation update calculation of a 16 bit sample can be achieved in 11 ns on a modern CPU. The FPGA implementation is found to be superior to all other approaches examined with an operation time of below 10 ns, and thus provides a useful tool for the real-time measurement of the standard deviation of signals above 100 MHz.

The Effect of Pulsatility Index on Infarct Volume in Acute Lacunar Stroke.

PurposeLacunar stroke, in the context of small vessel disease, is a type of cerebral infarction caused by occlusion of a penetrating artery. Pulsatility index (PI) is an easily measurable parameter in Transcranial Doppler ultrasound (TCD) study. PI reflects distal cerebral vascular resistance and has been interpreted as a surrogate marker of small vessel disease. We hypothesized that an increased PI, a marker of small vessel disease, might be associated with a larger infarct volume in acute lacunar stroke.Materials and MethodsThis study included 64 patients with acute lacunar stroke who underwent TCD and brain MRI. We evaluated the association between the mean PI value of bilateral middle cerebral arteries and infarct volume on diffusion-weighted MRI using univariate and multivariate linear regression.ResultsThe mean infarct volume and PI were 482.18±406.40 mm3 and 0.86±0.18, respectively. On univariate linear regression, there was a significant positive association between PI and infarct volume (p=0.001). In the multivariate model, a single standard deviation increase of PI (per 0.18) was associated with an increase of 139.05 mm3 in infarct volume (95% confidence interval, 21.25 to 256.85; p=0.022).ConclusionWe demonstrated that PI was an independent determinant of infarct volume in acute lacunar stroke. The PI value measured in acute stroke may be a surrogate marker of the extent of ischemic injury.

Multi-spectrum retrieval of Venus IR surface emissivity maps from VIRTIS/VEX nightside measurements at Themis Regio

Surface emissivity maps in the infrared can contribute to explore Venus’ geology. Nightside radiance spectra at Themis Regio acquired by the IR mapping channel of the Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS-M-IR) aboard Venus EXpress (VEX) are used to derive emissivity data from the three accessible spectral surface windows at 1.02, 1.10, and 1.18μm. The measured spectra are simulated by applying a full radiative transfer model. Neglecting geologic activity, a multi-spectrum retrieval algorithm is utilized to determine the emissivity maps of the surface target as parameter vectors that are common to many spectrally resolved images that cover this target.Absolute emissivity values are difficult to obtain due to strong interferences from other parameters. The true emissivity mean of the target cannot be retrieved, nor can the emissivity mean of a retrieved map be strictly preset. The retrieved map can exhibit trends with latitude and topography that are probably artificial. Once the trends have been removed in a post-processing step, it can be observed that the magnitude of the resulting spatial emissivity fluctuations around their mean value increases with increasing mean value. A linear transformation is applied that converts the de-trended map to exhibit a defined emissivity mean value called reference emissivity, here 0.5, yielding the ‘renormalized emissivity map’ with accordingly transformed fluctuations. It is verified that renormalized emissivity maps are largely independent of the emissivity mean before renormalization, of modifications to interfering atmospheric, surface, and instrumental parameters, and of selected details of the retrieval pipeline and data calibration and preprocessing. Extremely large emissivity retrieval errors due to imperfect or unconsidered forward model parameters are effectively avoided. If the absolute emissivity at a given bin of the target were known, the absolute emissivity map of the entire target could be computed according to the mentioned transformation, assuming absent true trends with latitude and topography. Until then, the renormalized emissivities are interpreted as spatial variations relative to the reference emissivity. They represent an important step toward the retrieval of absolute emissivities.Renormalized emissivity maps of Themis Regio at the three surface windows are determined from 64 measurement repetitions. Retrieval errors are estimated by a statistical evaluation of maps derived from various disjoint selections of spectra and using different assumptions on the interfering parameters. Double standard deviation errors for the three surface windows amount to 3%, 8%, and 4%, respectively, allowing geologic interpretation. A comparison to results from an earlier error analysis based on synthetic spectra shows that unconsidered time variations of interfering atmospheric parameters are a major error source. Spatial variations of the 1.02μm surface emissivity of 20% that correspond to the difference between unweathered granitic and basaltic rocks would be easily detectable, but such variations are ruled out for the studied target area. Emissivity anomalies of up to 8% are detected at both 1.02 and 1.18μm. At present sensitivity, no anomalies are identified at 1.10μm, but anomalies exceeding the determined error level can be excluded. With single standard deviation significance, all three maps show interesting spatial emissivity variations.

Genetic risk and age in Parkinson's disease: Continuum not stratum.

Recent genomewide association study meta-analyses have identified 28 loci associated with risk of Parkinson's disease (PD). We sought to investigate whether these genetic risk factors are associated with PD age at onset. Genetic risk scores from these loci were calculated for 6,249 cases. Linear regression tested associations between cumulative genetic risk and PD age at onset. Increasing genetic risk scores were associated with earlier age at onset (beta = -0.10, P = 2.92 × 10(-8) , adjusted r(2) = 0.27). Single standard deviation increase in genetic risk score is associated with 37.44 d earlier age at onset. Highest genetic risk was found at 31 to 60 y, onset slightly below average age at onset (AAO). Common genetic risk factors have a small but consistent association with AAO in PD.

Interlaboratory Study and Precision Statement for AASHTO T 336 Test Method

With the recent release of AASHTOWare Pavement ME Design software, there will be a greater emphasis on measuring the coefficient of thermal expansion (CTE) of concrete because of its significance on predicted distress and design life. The most widely used test method to measure the CTE of concrete is the AASHTO T 336 test method. Data are presented from an interlaboratory (round robin) study conducted by FHWA; this study included 20 CTE units and laboratories representing FHWA, state highway agencies, universities, commercial testing laboratories, and the concrete paving industry. As part of the study, each laboratory tested nine concrete specimens (three concrete mixtures 3 three specimens per mixture) that spanned the typical range of CTE values for concrete. On the basis of this interlaboratory study for the AASHTO T 336 test method, the within-laboratory single operator standard deviation was found to be 0.12 mstrain/°C and the between-laboratory standard deviation was found to be 0.28 mstrain/°C. Data from the study also showed that there was no statistically significant difference between custom-built CTE devices versus commercially available testing devices. This demonstrates the ruggedness of the current test method.

Appropriately complex modelling of healthy human walking

Modelling human gait has become an invaluable tool in a wide range of fields such as robotics and rehabilitation. With progress in computing, model complexity has advanced quickly but nevertheless, the contributions of incremental increases in model complexity are poorly understood. This thesis addresses this through a series of modelling studies. The first investigation examined the advantages and disadvantages of inverted pendulum (IP) models of walking, using a forward dynamics approach, by comparing to a normal set of experimental gait data. It was shown that the biggest failing of these models is their inability to adequately simulate double stance. The second investigation sought to highlight the effects of additional model complexities on the kinematics and kinetics, using optimisation. The additions, added one-by-one, were a knee joint, an ankle and static foot, a moving foot and a swing leg. The presence of a knee joint and an ankle moment were shown to be largely responsible for the initial peak in the vertical ground force reaction (GRF) curve. The second peak in this curve was achieved through a combination of heel rise and the presence of a swing leg. This gave mathematical evidence for the true determinants of human gait. A double support model was produced next, using a novel method to constrain both feet to the ground and calculate the GRF distribution. This was run in conjunction with the best single support model to simulate a whole gait cycle. Despite the problem of discontinuities at the transitions between double and single support, the whole gait cycle simulation had mean kinematic and mean GRF errors of less than a single standard deviation from the normal experimental data set. The final study collected gait and anthropometric data from ten subjects, which was then applied to the full gait cycle model. The model was shown to be adaptable to different people; a property that would be important for any computational model to be used in clinical assessment and diagnostics.

An experimental and theoretical study on the size of bubbles formed between a rotating disc and a stationary wall

This paper comprises an experimental and theoretical study on gas bubble formation in a liquid in a spinning disc device. Measurements were done in a device with a rotor radius of 0.135m and a distance of 2×10−3m between the rotating disc and the stationary wall. Experiments have been performed at rotational velocities where the Von Kármán boundary layer at the rotor and the Bödewadt layer at the stationary wall interfere. It was found that the highest angular velocities resulted in the smallest average bubble diameters (3.32±0.662mm), while at the highest gas mass flow rate and lowest rotational velocities, the largest bubbles were produced (15.3±1.89mm). Variation of liquid density from 1000 to 1150kgm−3 and liquid viscosity from 0.81 to 1.70mPas appeared to have a negligible effect on the bubble size. A model was derived from a mass and momentum balance, which incorporates the unsteady effects of added mass, gas momentum, bubble growth rate, drag force and centrifugal buoyancy. The general trends in calculated average bubble size are in agreement with the experimental results and the model calculations were able to simulate average bubble diameters within a single experimental standard deviation.

Serum cystatin C and cerebral microbleeds in patients with acute cerebral stroke

Recent studies have shown that kidney dysfunction is associated with cerebral microbleeds (CMB). Cystatin C is a more useful measurement than creatinine-based estimating equations for evaluating kidney function. The purpose of this study was to clarify the relationship between cystatin C levels and CMB in patients with acute cerebral stroke. This cross-sectional study included a total of 485 patients with acute ischemic stroke and 129 patients with cerebral hemorrhage. The serum levels of cystatin C were significantly higher in acute cerebral stroke patients with CMB than in those without (p<0.001). Multivariate logistic regression analyses showed that for each single standard deviation increase of cystatin C levels, there was a significant increase in the presence of CMB after adjusting for age and sex, and after additional adjustment for cardiovascular risk factors, silent lacunar infarction, and white matter hyperintensity in patients with acute stroke. The odds ratio (95% confidence interval) in patients with acute cerebral infarction and cerebral hemorrhage were 2.92 (1.81–6.93) and 2.98 (1.76–6.97), respectively. The present study suggests that elevated levels of cystatin C are associated with the presence of CMB in acute stroke patients, independent of conventional risk factors.