Association of calcemia and serum vitamin D with 24H-urinary calcium excretion in a swiss population-based study

Background: Elevated urinary calcium excretion is associated with reduced bone mineral density. Population-based data on urinary calcium excretion are scarce. We explored the association of serum calcium and circulating levels of vitamin D (including 25(OH)D2 and 25(OH)D3) with urinary calcium excretion in men and women in a population-based study. Methods: We used data from the "Swiss Survey on Salt" conducted between 2010 and 2012 and including people aged 15 years and over. Twenty-four hour urine collection, blood analysis, clinical examination and anthropometric measures were collected in 11 centres from the 3 linguistic regions of Switzerland. Vitamin D was measured centrally using liquid chromatography - tandem mass spectrometry. Hypercalciuria was defined as urinary calcium excretion >0.1 mmol/kg/24h. Multivariable linear regression was used to explore factors associated with 24-hour urinary calcium excretion (mmol/24h) squared root transformed, taken as the dependant variable. Vitamin D was divided into monthspecific tertiles with the first tertile having the lowest value and the third tertile having the highest value. Results: The 669 men and 624 women had mean (SD) age of 49.2 (18.1) and 47 (17.9) years and a prevalence of hypercalciuria of 8.9% and 8.0%, respectively. In adjusted models, the association of urinary calcium excretion with protein-corrected serum calcium was (β coefficient } standard error, according to urinary calcium squared root transformed) 1.125 } 0.184 mmol/L per square-root (mmol/24h) (P<0.001) in women and 0.374 } 0.224 (P=0.096) in men. Men in the third month-specific vitamin D tertile had higher urinary calcium excretion than men in the first tertile (0.170 } 0.05 nmol/L per mmol/24h, P=0.001) and the corresponding association was 0.048 } 0.043, P= 0.272 in women. Conclusion: About one in eleven person has hypercalciuria in the Swiss population. The positive association of serum calcium with urinary calcium excretion was steeper in women than in men, independently of menopausal status. Circulating vitamin D was associated positively with urinary calcium excretion only in men. The reasons underlying the observed sex differences in the hormonal control of urinary calcium excretion need to be explored in further studies.

Associations between mood, anxiety or substance use disorders and inflammatory markers after adjustment for multiple covariates in a population-based study.

Inflammation is one possible mechanism underlying the associations between mental disorders and cardiovascular diseases (CVD). However, studies on mental disorders and inflammation have yielded inconsistent results and the majority did not adjust for potential confounding factors. We examined the associations of several pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α) and high sensitive C-reactive protein (hsCRP) with lifetime and current mood, anxiety and substance use disorders (SUD), while adjusting for multiple covariates. The sample included 3719 subjects, randomly selected from the general population, who underwent thorough somatic and psychiatric evaluations. Psychiatric diagnoses were made with a semi-structured interview. Major depressive disorder was subtyped into "atypical", "melancholic", "combined atypical-melancholic" and "unspecified". Associations between inflammatory markers and psychiatric diagnoses were assessed using multiple linear and logistic regression models. Lifetime bipolar disorders and atypical depression were associated with increased levels of hsCRP, but not after multivariate adjustment. After multivariate adjustment, SUD remained associated with increased hsCRP levels in men (β = 0.13 (95% CI: 0.03,0.23)) but not in women. After multivariate adjustment, lifetime combined and unspecified depression were associated with decreased levels of IL-6 (β = -0.27 (-0.51,-0.02); β = -0.19 (-0.34,-0.05), respectively) and TNF-α (β = -0.16 (-0.30,-0.01); β = -0.10 (-0.19,-0.02), respectively), whereas current combined and unspecified depression were associated with decreased levels of hsCRP (β = -0.20 (-0.39,-0.02); β = -0.12 (-0.24,-0.01), respectively). Our data suggest that the significant associations between increased hsCRP levels and mood disorders are mainly attributable to the effects of comorbid disorders, medication as well as behavioral and physical CVRFs.

A new early and automated MRI-based predictor of motor improvement after stroke.

OBJECTIVES: In this study, we investigated the structural plasticity of the contralesional motor network in ischemic stroke patients using diffusion magnetic resonance imaging (MRI) and explored a model that combines a MRI-based metric of contralesional network integrity and clinical data to predict functional outcome at 6 months after stroke. METHODS: MRI and clinical examinations were performed in 12 patients in the acute phase, at 1 and 6 months after stroke. Twelve age- and gender-matched controls underwent 2 MRIs 1 month apart. Structural remodeling after stroke was assessed using diffusion MRI with an automated measurement of generalized fractional anisotropy (GFA), which was calculated along connections between contralesional cortical motor areas. The predictive model of poststroke functional outcome was computed using a linear regression of acute GFA measures and the clinical assessment. RESULTS: GFA changes in the contralesional motor tracts were found in all patients and differed significantly from controls (0.001 ≤ p < 0.05). GFA changes in intrahemispheric and interhemispheric motor tracts correlated with age (p ≤ 0.01); those in intrahemispheric motor tracts correlated strongly with clinical scores and stroke sizes (p ≤ 0.001). GFA measured in the acute phase together with a routine motor score and age were a strong predictor of motor outcome at 6 months (r(2) = 0.96, p = 0.0002). CONCLUSION: These findings represent a proof of principle that contralesional diffusion MRI measures may provide reliable information for personalized rehabilitation planning after ischemic motor stroke. Neurology® 2012;79:39-46.

Birth weight, weight change, and blood pressure during childhood and adolescence: a school-based multiple cohort study.

OBJECTIVE: We assessed the association between birth weight, weight change, and current blood pressure (BP) across the entire age-span of childhood and adolescence in large school-based cohorts in the Seychelles, an island state in the African region. METHODS: Three cohorts were analyzed: 1004 children examined at age 5.5 and 9.1 years, 1886 children at 9.1 and 12.5, and 1575 children at 12.5 and 15.5, respectively. Birth and 1-year anthropometric data were gathered from medical files. The outcome was BP at age 5.5, 9.1, 12.5 or 15.5 years, respectively. Conditional linear regression analysis was used to estimate the relative contribution of changes in weight (expressed in z-score) during different age periods on BP. All analyses were adjusted for height. RESULTS: At all ages, current BP was strongly associated with current weight. Birth weight was not significantly associated with current BP. Upon adjustment for current weight, the association between birth weight and current BP tended to become negative. Conditional linear regression analyses indicated that changes in weight during successive age periods since birth contributed substantially to current BP at all ages. The strength of the association between weight change and current BP increased throughout successive age periods. CONCLUSION: Weight changes during any age period since birth have substantial impact on BP during childhood and adolescence, with BP being more responsive to recent than earlier weight changes.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

A random linear functional approach to efficiency bounds

This paper suggests a method for obtaining efficiency bounds in models containing either only infinite-dimensional parameters or both finite- and infinite-dimensional parameters (semiparametric models). The method is based on a theory of random linear functionals applied to the gradient of the log-likelihood functional and is illustrated by computing the lower bound for Cox's regression model

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Obesity-related phenotypes are associated to parental longevity in a Swiss population-based study

METHODS. We analyzed data from a population-based sample of 2561 participants (1163 men and 1398 women) aged 55-75 years from the city of Lausanne, Switzerland (CoLaus study). Participants were stratified by the number of parents (0, 1, 2) who survived to 85 years or more. Trend across these strata was assessed using a non-parametric kmean test. The associations of parental age (independent covariate used as a proxy for longevity) with fasting blood glucose, blood pressures, blood lipids, body mass index (BMI), weight, height or liver enzymes (continuous dependent variables) were analyzed using multiple linear regressions. Models were adjusted for age, sex, alcohol consumption, smoking and educational level, and BMI for liver enzymes. RESULTS. For subjects with 0 (N = 1298), 1 (N = 991) and 2 (N = 272) long-lived parents, median BMI (interquartile range) was 25.4 (6.5), 24.9 (6.1) and 23.7 (4.8) kg/m2 in women (P <0.001), and 27.3 (4.8), 27.0 (4.5) and 25.9 (4.9) kg/m2 in men (P = 0.04), respectively; median weight was 66.5 (16.1), 65.0 (16.4) and 63.4 (13.7) kg in women (P = 0.003), and 81.5 (17.0), 81.4 (16.4) and 80.3 (17.1) kg in men (P = 0.36). Median height was 161 (8), 162 (9) and 163 (8) cm in women (P = 0.005) and 173 (9), 174 (9) and 174 (11) cm in men (P = 0.09). The corresponding medians for AST (Aspartate Aminotransferase) were 31 (13), 29 (11) and 28 (10) U/L (P = 0.002), and 28 (17), 27 (14) and 26 (19) U/L for ALT (Alanin Aminotransferase, P = 0.053) in men. In multivariable analyses, greater parental longevity was associated with lower BMI, lower weight and taller stature in women (P < 0.01) and lower AST in men (P = 0.011). No significant associations were observed for the other variables analyzed. Sensitivity analyses restricted to subjects whose parents were dead (N = 1844) led to similar results, with even stronger associations of parental longevity with liver enzymes in men. CONCLUSIONS. In women, increased parental longevity was associated with smaller BMI, attributable to lower weight and taller stature. In men, the association of increased parental longevity with lower liver enzymes, independently of BMI, suggests that parental longevity may be associated with decreased nonalcoholic fatty liver disease.

Evidence for chronic low-grade systemic inflammation in individuals with agoraphobia from a population-based prospective study.

BACKGROUND: Anxiety disorders have been linked to an increased risk of incident coronary heart disease in which inflammation plays a key pathogenic role. To date, no studies have looked at the association between proinflammatory markers and agoraphobia. METHODS: In a random Swiss population sample of 2890 persons (35-67 years, 53% women), we diagnosed a total of 124 individuals (4.3%) with agoraphobia using a validated semi-structured psychiatric interview. We also assessed socioeconomic status, traditional cardiovascular risk factors (i.e., body mass index, hypertension, blood glucose levels, total cholesterol/high-density lipoprotein-cholesterol ratio), and health behaviors (i.e., smoking, alcohol consumption, and physical activity), and other major psychiatric diseases (other anxiety disorders, major depressive disorder, drug dependence) which were treated as covariates in linear regression models. Circulating levels of inflammatory markers, statistically controlled for the baseline demographic and health-related measures, were determined at a mean follow-up of 5.5 ± 0.4 years (range 4.7 - 8.5). RESULTS: Individuals with agoraphobia had significantly higher follow-up levels of C-reactive protein (p = 0.007) and tumor-necrosis-factor-α (p = 0.042) as well as lower levels of the cardioprotective marker adiponectin (p = 0.032) than their non-agoraphobic counterparts. Follow-up levels of interleukin (IL)-1β and IL-6 did not significantly differ between the two groups. CONCLUSIONS: Our results suggest an increase in chronic low-grade inflammation in agoraphobia over time. Such a mechanism might link agoraphobia with an increased risk of atherosclerosis and coronary heart disease, and needs to be tested in longitudinal studies.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

An embedded real-time red peach detection system based on an OV7670 camera, ARM Cortex-M4 processor and 3D Look-Up Tables

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second.

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

Design and implementation of FPGA-based LQ control of active magnetic bearings

The need for high performance, high precision, and energy saving in rotating machinery demands an alternative solution to traditional bearings. Because of the contactless operation principle, the rotating machines employing active magnetic bearings (AMBs) provide many advantages over the traditional ones. The advantages such as contamination-free operation, low maintenance costs, high rotational speeds, low parasitic losses, programmable stiffness and damping, and vibration insulation come at expense of high cost, and complex technical solution. All these properties make the use of AMBs appropriate primarily for specific and highly demanding applications. High performance and high precision control requires model-based control methods and accurate models of the flexible rotor. In turn, complex models lead to high-order controllers and feature considerable computational burden. Fortunately, in the last few years the advancements in signal processing devices provide new perspective on the real-time control of AMBs. The design and the real-time digital implementation of the high-order LQ controllers, which focus on fast execution times, are the subjects of this work. In particular, the control design and implementation in the field programmable gate array (FPGA) circuits are investigated. The optimal design is guided by the physical constraints of the system for selecting the optimal weighting matrices. The plant model is complemented by augmenting appropriate disturbance models. The compensation of the force-field nonlinearities is proposed for decreasing the uncertainty of the actuator. A disturbance-observer-based unbalance compensation for canceling the magnetic force vibrations or vibrations in the measured positions is presented. The theoretical studies are verified by the practical experiments utilizing a custom-built laboratory test rig. The test rig uses a prototyping control platform developed in the scope of this work. To sum up, the work makes a step in the direction of an embedded single-chip FPGA-based controller of AMBs.

Copeptin is associated with kidney length, renal function, and prevalence of simple cysts in a population-based study.

Arginine vasopressin (AVP) has a key role in osmoregulation by facilitating water transport in the collecting duct. Recent evidence suggests that AVP may have additional effects on renal function and favor cyst growth in polycystic kidney disease. Whether AVP also affects kidney structure in the general population is unknown. We analyzed the association of copeptin, an established surrogate for AVP, with parameters of renal function and morphology in a multicentric population-based cohort. Participants from families of European ancestry were randomly selected in three Swiss cities. We used linear multilevel regression analysis to explore the association of copeptin with renal function parameters as well as kidney length and the presence of simple renal cysts assessed by ultrasound examination. Copeptin levels were log-transformed. The 529 women and 481 men had median copeptin levels of 3.0 and 5.2 pmol/L, respectively (P<0.001). In multivariable analyses, the copeptin level was associated inversely with eGFR (β=-2.1; 95% confidence interval [95% CI], -3.3 to -0.8; P=0.002) and kidney length (β=-1.2; 95% CI, -1.9 to -0.4; P=0.003) but positively with 24-hour urinary albumin excretion (β=0.11; 95% CI, 0.01 to 0.20; P=0.03) and urine osmolality (β=0.08; 95% CI, 0.05 to 0.10; P<0.001). A positive association was found between the copeptin level and the presence of renal cysts (odds ratio, 1.6; 95% CI, 1.1 to 2.4; P=0.02). These results suggest that AVP has a pleiotropic role in renal function and may favor the development of simple renal cysts.

LC-MS/MS based assay and reference intervals in children and adolescents for oxysterols elevated in Niemann-Pick diseases.

BACKGROUND: Niemann-Pick type C (NP-C) is a rare progressive neurodegenerative lipid storage disorder with heterogeneous clinical presentation and challenging diagnostic procedures. Recently oxysterols have been reported to be specific biomarkers for NP-C but knowledge on the intra-individual variation and on reference intervals in children and adolescents are lacking. METHODS: We established a LC-MS/MS assay to measure Cholestane-3β, 5α, 6β-triol (C-triol) and 7-Ketocholesterol (7-KC) following Steglich esterification. To assess reference intervals and intra-individual variation we determined oxysterols in 148 children and adolescents from 0 to 18 years and repeat measurements in 19 of them. RESULTS: The reported method is linear (r>0.99), sensitive (detection limit of 0.03 ng/mL [0.07 nM] for C-triol, and 0.54 ng/mL [1.35 nM] for 7-KC) and precise, with an intra-day imprecision of 4.8% and 4.1%, and an inter-day imprecision of 7.0% and 11.0% for C-triol (28 ng/ml, 67 nM) and 7-KC (32 ng/ml, 80 nM), respectively. Recoveries for 7-KC and C-triol range between 93% and 107%. The upper reference limit obtained for C-triol is 40.4 ng/mL (95% CI: 26.4-61.7 ng/mL, 96.0 nM, 95% CI: 62.8-146.7 nM) and 75.0 ng/mL for 7-KC (95% CI: 55.5-102.5 ng/mL, 187.2 nM, 95% CI: 138.53-255.8 nM), with no age or gender dependency. Both oxysterols have a broad intra-individual variation of 46%±23% for C-triol and 52%±29% for 7-KC. Nevertheless, all Niemann-Pick patients showed increased C-triol levels including Niemann-Pick type A and B patients. CONCLUSIONS: The LC-MS/MS assay is a robust assay to quantify C-triol and 7-KC in plasma with well documented reference intervals in children and adolescents to screen for NP-C in the pediatric population. In addition our results suggest that especially the C-triol is a biomarker for all three Niemann-Pick diseases.