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. In addition, we show how to use DFA appropriately to minimize the effects of trends, and how to recognize if a crossover indicates indeed a transition from one type to a different type of underlying correlation, or the crossover is due to a trend without any transition in the dynamical properties of the noise.

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. We find that introducing nonstationarities to stationary correlated signals leads to the appearance of crossovers in the scaling behavior and we study how the characteristics of these crossovers depend on: (a) the fraction and size of the parts cut out from the signal; (b) the concentration of spikes and their amplitudes; (c) the proportion between segments with different standard deviations or different correlations; and (d) the correlation properties of the stationary signal. We show how to develop strategies for pre-processing "raw" data prior to analysis, which will minimize the effects of nonstationarities on the scaling properties of the data and how to interpret the results of DFA for complex signals with different local characteristics.

Dysfunction in 24-h circadian rhythms is a common occurrence in aging adults, however, circadian rhythm disruptions (CRD) are more severe in people with age-related neurodegenerative diseases, including Alzheimer's disease and related dementias (ADRD) and Parkinson's disease (PD). Manifestations of CRD differ according to type and severity of neurodegenerative disease, and importantly, could occur before onset of typical clinical symptoms of neurodegeneration. Evidence from preliminary studies suggest that-in addition to being a symptom of neurodegeneration-CRD might also be a potential risk factor for developing ADRD and PD, although large, longitudinal studies are needed to confirm this. The mechanistic link between *

Shift work is a risk factor for hypertension, inflammation, and cardiovascular disease. This increased risk cannot be fully explained by classic risk factors. One of the key features of shift workers is that their behavioral and environmental cycles are typically misaligned relative to their endogenous circadian system. However, there is little information on the impact of acute circadian misalignment on cardiovascular disease risk in humans. Here we show-by using two 8-d laboratory protocols-that short-term circadian misalignment (12-h inverted behavioral and environmental cycles for three days) adversely affects cardiovascular risk factors in healthy adults. Circadian misalignment increased 24-h systolic blood pressure (SBP) and diastolic blood pressure (DBP) by 3.0 mmHg and 1.5 mmHg, respectively. These results were primarily explained by an increase in blood pressure during sleep opportunities (SBP, +5.6 mmHg; DBP, +1.9 mmHg) and, to a lesser extent, by raised blood pressure during wake periods (SBP, +1.6 mmHg; DBP, +1.4 mmHg). Circadian misalignment decreased wake cardiac vagal modulation by 8-15%, as determined by heart rate variability analysis, and decreased 24-h urinary epinephrine excretion rate by 7%, without a significant effect on 24-h urinary norepinephrine excretion rate. Circadian misalignment increased 24-h serum interleukin-6, C-reactive protein, resistin, and tumor necrosis factor-α levels by 3-29%. We demonstrate that circadian misalignment per se increases blood pressure and inflammatory markers. Our findings may help explain why shift work increases hypertension, inflammation, and cardiovascular disease risk.circadian misalignment | hypertension | inflammatory markers | night work | shift work

Sudden cardiac death exhibits diurnal variation in both acquired and hereditary forms of heart disease 1, 2, but the molecular basis is unknown. A common mechanism that underlies susceptibility to ventricular arrhythmias is abnormalities in the duration (e.g. short or long QT syndromes, heart failure) 3-5 or pattern (e.g. Brugada syndrome) 6 of myocardial repolarization. Here we provide the first molecular evidence that links circadian rhythms to vulnerability in ventricular arrhythmias in mice. Specifically, we show that cardiac ion channel expression and QT interval duration (an index of myocardial repolarization) exhibit endogenous circadian rhythmicity under the control of a novel clock-dependent oscillator, Krüppel-like factor 15 (Klf15). Klf15 transcriptionally controls rhythmic expression of KChIP2, a critical subunit required for generating the transient outward potassium current (Ito). 7 Deficiency or excess of Klf15 causes loss of rhythmic QT variation, abnormal repolarization and enhanced susceptibility to ventricular arrhythmias. In sum, these findings identify circadian transcription of ion channels as a novel mechanism for cardiac arrhythmogenesis.

The risk of adverse cardiovascular events peaks in the morning (≈9:00 AM) with a secondary peak in the evening (≈8:00 PM) and a trough at night. This pattern is generally believed to be caused by the day/night distribution of behavioral triggers, but it is unknown whether the endogenous circadian system contributes to these daily fluctuations. Thus, we tested the hypotheses that the circadian system modulates autonomic, hemodynamic, and hemostatic risk markers at rest, and that behavioral stressors have different effects when they occur at different internal circadian phases. Twelve healthy adults were each studied in a 240-h forced desynchrony protocol in dim light while standardized rest and exercise periods were uniformly distributed across the circadian cycle. At rest, there were large circadian variations in plasma cortisol (peak-to-trough ≈85% of mean, peaking at a circadian phase corresponding to ≈9:00 AM) and in circulating catecholamines (epinephrine, ≈70%; norepinephrine, ≈35%, peaking during the biological day). At ≈8:00 PM, there was a circadian peak in blood pressure and a trough in cardiac vagal modulation. Sympathetic variables were consistently lowest and vagal markers highest during the biological night. We detected no simple circadian effect on hemostasis, although platelet aggregability had two peaks: at ≈noon and ≈11:00 PM. There was circadian modulation of the cardiovascular reactivity to exercise, with greatest vagal withdrawal at ≈9:00 AM and peaks in catecholamine reactivity at ≈9:00 AM and ≈9:00 PM. Thus, the circadian system modulates numerous cardiovascular risk markers at rest as well as their reactivity to exercise, with resultant profiles that could potentially contribute to the day/night pattern of adverse cardiovascular events.

The degree of multiscale complexity in human behavioral regulation, such as that required for postural control, appears to decrease with advanced aging or disease. To help delineate causes and functional consequences of complexity loss, we examined the effects of visual and somatosensory impairment on the complexity of postural sway during quiet standing and its relationship to postural adaptation to cognitive dual tasking. Participants of the MOBILIZE Boston Study were classified into mutually exclusive groups: controls [intact vision and foot somatosensation, n = 299, 76 ± 5 (SD) yr old], visual impairment only (<20/40 vision, n = 81, 77 ± 4 yr old), somatosensory impairment only (inability to perceive 5.07 monofilament on plantar halluxes, n = 48, 80 ± 5 yr old), and combined impairments (n = 25, 80 ± 4 yr old). Postural sway (i.e., center-of-pressure) dynamics were assessed during quiet standing and cognitive dual tasking, and a complexity index was quantified using multiscale entropy analysis. Postural sway speed and area, which did not correlate with complexity, were also computed. During quiet standing, the complexity index (mean ± SD) was highest in controls (9.5 ± 1.2) and successively lower in the visual (9.1 ± 1.1), somatosensory (8.6 ± 1.6), and combined (7.8 ± 1.3) impairment groups (P = 0.001). Dual tasking resulted in increased sway speed and area but reduced complexity (P < 0.01). Lower complexity during quiet standing correlated with greater absolute (R = -0.34, P = 0.002) and percent (R = -0.45, P < 0.001) increases in postural sway speed from quiet standing to dual-tasking conditions. Sensory impairments contributed to decreased postural sway complexity, which reflected reduced adaptive capacity of the postural control system. Relatively low baseline complexity may, therefore, indicate control systems that are more vulnerable to cognitive and other stressors.

OBJECTIVE -The aim of this study was to evaluate the regional effects of type 2 diabetes and associated conditions on cerebral tissue volumes and cerebral blood flow (CBF) regulation.RESEARCH DESIGN AND METHODS -CBF was examined in 26 diabetic (aged 61.6 Ϯ 6.6 years) and 25 control (aged 60.4 Ϯ 8.6 years) subjects using continuous arterial spin labeling (CASL) imaging during baseline, hyperventilation, and CO 2 rebreathing. Regional gray and white matter, cerebrospinal fluid (CSF), and white matter hyperintensity (WMH) volumes were measured on a T1-weighted inversion recovery fast-gradient echo and a fluid attenuation inversion recovery magnetic resonance imaging at 3 Tesla.RESULTS -The diabetic group had smaller global white (P ϭ 0.006) and gray (P ϭ 0.001) matter and larger CSF (36.3%, P Ͻ 0.0001) volumes than the control group. Regional differences were observed for white matter (Ϫ13.1%, P ϭ 0.0008) and CSF (36.3%, P Ͻ 0.0001) in the frontal region, for CSF (20.9%, P ϭ 0.0002) in the temporal region, and for gray matter (Ϫ3.0%, P ϭ 0.04) and CSF (17.6%, P ϭ 0.01) in the parieto-occipital region. Baseline regional CBF (P ϭ 0.006) and CO 2 reactivity (P ϭ 0.005) were reduced in the diabetic group. Hypoperfusion in the frontal region was associated with gray matter atrophy (P Ͻ 0.0001). Higher A1C was associated with lower CBF (P Ͻ 0.0001) and greater CSF (P ϭ 0.002) within the temporal region.CONCLUSIONS -Type 2 diabetes is associated with cortical and subcortical atrophy involving several brain regions and with diminished regional cerebral perfusion and vasoreactivity. Uncontrolled diabetes may further contribute to hypoperfusion and atrophy. Diabetic metabolic disturbance and blood flow dysregulation that affects preferentially frontal and temporal regions may have implications for cognition and balance in elderly subjects with diabetes. Diabetes Care 30:1193-1199, 2007D iabetes is a prevalent condition associated with substantial morbidity attributed to vascular complications (1). Diabetes alters endothelial function (2) and permeability of the bloodbrain barrier, thus affecting microcirculation and regional metabolism (3).Studies in type 1 diabetes have shown that the fronto-temporal cortex and periventricular white matter (3) are more affected by diabetic metabolic disturbance. Single proton emission computed tomography (SPECT) studies suggest that chronic hyperglycemia alters cerebral blood flow (CBF) in the frontal, temporal, parietal, occipital, and cerebellar regions of interest (ROIs) (4,5). Vasoreactivity to acetazolamide is not homogeneous, with a majority of hypoperfused and some hyperperfused ROIs (6). White matter hyperintensities (WMHs) on T2-weighted magnetic resonance imaging (MRI) (7) have been associated with arteriolosclerosis, arising as consequences of aging, diabetes, and other cardiovascular risk factors (8,9). Vascular and neurodegenerative changes in these structures have consequences for regional perfusion, cognitive impairment, and balance in elderly people with type 2 diabetes (10,...