Gestational Pemphigoid: Placental Morphology and Function

Peer reviewe

Estimating long range dependence: finite sample properties and confidence intervals

A major issue in financial economics is the behavior of asset returns over long horizons. Various estimators of long range dependence have been proposed. Even though some have known asymptotic properties, it is important to test their accuracy by using simulated series of different lengths. We test R/S analysis, Detrended Fluctuation Analysis and periodogram regression methods on samples drawn from Gaussian white noise. The DFA statistics turns out to be the unanimous winner. Unfortunately, no asymptotic distribution theory has been derived for this statistics so far. We were able, however, to construct empirical (i.e. approximate) confidence intervals for all three methods. The obtained values differ largely from heuristic values proposed by some authors for the R/S statistics and are very close to asymptotic values for the periodogram regression method.Comment: 16 pages, 11 figures New version: 14 pages (smaller fonts), 11 figures, new Section on application

Cyclosporine Treatment in Severe Gestational Pemphigoid

Gestational pemphigoid, a rare autoimmune skin disease typically occurring during pregnancy, is caused by autoantibodies against collagen XVII. Clinically it is characterised by severe itching followed by erythematous and bullous lesions of the skin. Topical or oral glucocorticoids usually relieve symptoms, but in more severe cases systemic immunosuppressive treatments are needed. Data on immunosuppressive medication controlling gestational pemphigoid are sparse. We report 3 intractable cases of gestational pemphigoid treated with cyclosporine.Peer reviewe

Ross-Konno and Endocardial Fibroelastosis Resection After Hybrid Stage I Palliation in Infancy: Successful Staged Left-Ventricular Rehabilitation and Conversion to Biventricular Circulation After Fetal Diagnosis of Aortic Stenosis

We report a patient who presented during fetal life with severe aortic stenosis, left-ventricular dysfunction, and endocardial fibroelastosis (evolving hypoplastic left heart syndrome). Management involved in utero and postnatal balloon aortic valvuloplasty for partial relief of obstruction and early postnatal hybrid stage I palliation until recovery of left-ventricular systolic function had occurred. The infant subsequently had successful conversion to a biventricular circulation by combining resection of endocardial fibroelastosis with single-stage Ross-Konno, aortic arch reconstruction, hybrid takedown, and pulmonary artery reconstruction

Moderate and heavy metabolic stress interval training improve arterial stiffness and heart rate dynamics in humans

Traditional continuous aerobic exercise training attenuates age-related increases of arterial stiffness, however, training studies have not determined whether metabolic stress impacts these favourable effects. Twenty untrained healthy participants (n = 11 heavy metabolic stress interval training, n = 9 moderate metabolic stress interval training) completed 6 weeks of moderate or heavy intensity interval training matched for total work and exercise duration. Carotid artery stiffness, blood pressure contour analysis, and linear and non-linear heart rate variability were assessed before and following training. Overall, carotid arterial stiffness was reduced (p  0.05). This study demonstrates the effectiveness of interval training at improving arterial stiffness and autonomic function, however, the metabolic stress was not a mediator of this effect. In addition, these changes were also independent of improvements in aerobic capacity, which were only induced by training that involved a high metabolic stress

Standard Model Extension and Casimir effect for fermions at finite temperature

AbstractLorentz and CPT symmetries are foundations for important processes in particle physics. Recent studies in Standard Model Extension (SME) at high energy indicate that these symmetries may be violated. Modifications in the lagrangian are necessary to achieve a hermitian hamiltonian. The fermion sector of the standard model extension is used to calculate the effects of the Lorentz and CPT violation on the Casimir effect at zero and finite temperature. The Casimir effect and Stefan–Boltzmann law at finite temperature are calculated using the thermo field dynamics formalism

Effect of nonstationarities on detrended fluctuation analysis

Detrended fluctuation analysis (DFA) is a scaling analysis method used to quantify long-range power-law correlations in signals. Many physical and biological signals are ``noisy'', heterogeneous and exhibit different types of nonstationarities, which can affect the correlation properties of these signals. We systematically study the effects of three types of nonstationarities often encountered in real data. Specifically, we consider nonstationary sequences formed in three ways: (i) stitching together segments of data obtained from discontinuous experimental recordings, or removing some noisy and unreliable parts from continuous recordings and stitching together the remaining parts -- a ``cutting'' procedure commonly used in preparing data prior to signal analysis; (ii) adding to a signal with known correlations a tunable concentration of random outliers or spikes with different amplitude, and (iii) generating a signal comprised of segments with different properties -- e.g. different standard deviations or different correlation exponents. We compare the difference between the scaling results obtained for stationary correlated signals and correlated signals with these three types of nonstationarities.Comment: 17 pages, 10 figures, corrected some typos, added one referenc

Effect of Trends on Detrended Fluctuation Analysis

Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-range power-law correlation exponents in noisy signals. Many noisy signals in real systems display trends, so that the scaling results obtained from the DFA method become difficult to analyze. We systematically study the effects of three types of trends -- linear, periodic, and power-law trends, and offer examples where these trends are likely to occur in real data. We compare the difference between the scaling results for artificially generated correlated noise and correlated noise with a trend, and study how trends lead to the appearance of crossovers in the scaling behavior. We find that crossovers result from the competition between the scaling of the noise and the ``apparent'' scaling of the trend. We study how the characteristics of these crossovers depend on (i) the slope of the linear trend; (ii) the amplitude and period of the periodic trend; (iii) the amplitude and power of the power-law trend and (iv) the length as well as the correlation properties of the noise. Surprisingly, we find that the crossovers in the scaling of noisy signals with trends also follow scaling laws -- i.e. long-range power-law dependence of the position of the crossover on the parameters of the trends. We show that the DFA result of noise with a trend can be exactly determined by the superposition of the separate results of the DFA on the noise and on the trend, assuming that the noise and the trend are not correlated. If this superposition rule is not followed, this is an indication that the noise and the superimposed trend are not independent, so that removing the trend could lead to changes in the correlation properties of the noise.Comment: 20 pages, 16 figure

Deterministic Chaos and Fractal Complexity in the Dynamics of Cardiovascular Behavior: Perspectives on a New Frontier

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts

Influence of mercury exposure on blood pressure, resting heart rate and heart rate variability in French Polynesians: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Populations which diet is rich in seafood are highly exposed to contaminants such as mercury, which could affect cardiovascular risk factors</p> <p>Objective</p> <p>To assess the associations between mercury and blood pressure (BP), resting heart rate (HR) and HR variability (HRV) among French Polynesians</p> <p>Methods</p> <p>Data were collected among 180 adults (≥ 18 years) and 101 teenagers (12-17 years). HRV was measured using a two-hour ambulatory electrocardiogram (Holter) and BP was measured using a standardized protocol. The association between mercury and HRV and BP parameters was studied using analysis of variance (ANOVA) and analysis of covariance (ANCOVA)</p> <p>Results</p> <p>Among teenagers, the high frequency (HF) decreased between the 2^ndand 3^rdtertile (380 vs. 204 ms², p = 0.03) and a similar pattern was observed for the square root of the mean squared differences of successive R-R intervals (rMSSD) (43 vs. 30 ms, p = 0.005) after adjusting for confounders. In addition, the ratio low/high frequency (LF/HF) increased between the 2^ndand 3^rdtertile (2.3 vs. 3.0, p = 0.04). Among adults, the standard deviation of R-R intervals (SDNN) tended to decrease between the 1^stand 2^ndtertile (84 vs. 75 ms, p = 0.069) after adjusting for confounders. Furthermore, diastolic BP tended to increase between the 2^ndand 3^rdtertile (86 vs. 91 mm Hg, p = 0.09). No significant difference was observed in resting HR or pulse pressure (PP)</p> <p>Conclusions</p> <p>Mercury was associated with decreased HRV among French Polynesian teenagers while no significant association was observed with resting HR, BP, or PP among teenagers or adults</p