: There is barely any evidence of antipsychotic drugs affecting the molecular clockwork in human, yet it is suggested that clock genes are associated with dopaminergic transmission, i.e. the main target of this therapeutics. We decided to verify if haloperidol and olanzapine affect expression of and in a human central nervous system cell line model. : U-87MG human glioblastoma cell line was used as an experimental model. The cells were incubated with or without haloperidol and olanzapine in the concentration of 5 and 20 μM for 24 h. Real-time quantitative polymerase chain reaction with the Δ analysis was used to examine the effect of haloperidol and olanzapine on the mRNA expression of the genes. : At 5 μM, haloperidol decreased expression of almost 20-fold. There was nearly a 1.5-fold increase in expression of . Considering the 20 μM haloperidol concentration and both olanzapine concentrations, no other statistically significant effect was observed. : At certain concentration, haloperidol seems to affect expression of particular clock genes in a human central nervous system cell line model, yet mechanism underlying this phenomenon remains elusive.

Significant circadian variations exist in the frequency of cardiac arrhythmia, but few studies have examined the relation between cardiac ion channels genes and biological clocks. We investigated this relation using suprachiasmatic nuclei lesion (SCNX) and pharmacological autonomic nervous system block (ANSB) mice. Significant 24-h variations were observed in the expression of clock genes Per2, Bmal1, and Dbp and ion channel genes KCNA5, KCND2, KCHIP2, and KCNK3 in the control mice hearts. In the SCNX mice, all genes examined lost circadian rhythm. In the ANSB mice, the expressions of the three clock genes were dampened significantly but still had circadian rhythm, whereas the four ion channel gene expressions lost rhythm. Heart rate also lost circadian rhythm in both the SCNX and ANSB mice. These results suggest that some ion channel gene expressions might be regulated by the central clock in the SCN through the ANS but not the peripheral clock in the heart.

Bright light in the blue-green range, administered in the early morning hours (prior to waking) may be particularly effective in shifting circadian rhythms and may increase gonadotropin production. Accordingly, we tested the feasibility and utility of a mask that emits bright blue/green light (compared to a similar mask that emitted a dim red light) towards the end of sleep in a randomized, placebo-controlled pilot study. The study included a 3-day baseline period, immediately followed by a 12-day intervention period. Subjects were 30 healthy young men with minimal-mild depression. The bright light masks were well-tolerated and demonstrated adequate safety and feasibility. Following the intervention, those who wore the bright light mask demonstrated altered sleep timing suggestive of an earlier sleep period, and excreted a slight increase in follicle-stimulating hormone. Overall, light masks may prove useful in future studies of bright light therapy.

Examples of hormonal phase-shifting of circadian gene expression began to emerge a few years ago. Vitamin A fulfills a hormonal function by binding of retinoic acid to its nuclear receptors, RARs and RXRs. We found retinoid- as well as clock-responsive sites on regulatory regions of Glutathione reductase (GR) and Glutathione peroxidase (GPx) genes. Interestingly, we observed retinoid receptors, as well as GSH, GR and GPx, display daily oscillating patterns in the rat liver. We also found that feeding animals with a vitamin A-free diet, dampened daily rhythms of RARα and RXRβ mRNA, GR expression and activity, GSH, BMAL1 protein levels and locomotor activity. Differently, day-night oscillations of RXRα, GPx mRNA levels and activity and PER1 protein levels, were phase-shifted in the liver of vitamin A-deficient rats. These observations would emphasize the importance of micronutrient vitamin A in the modulation of biological rhythms of GSH and cellular redox state in liver.

Sleep deprivation has a complex set of neurological effects that go beyond a mere slowing of mental processes. While cognitive and perceptual impairments in sleep deprived individuals are widespread, some abilities remain intact. In an effort to characterize these effects, some have suggested an impairment of complex decision making ability despite intact ability to follow simple rules. To examine this trade-off, 24-hour total sleep deprived individuals performed two versions of a resource acquisition foraging task, one in which exploration is optimal (to succeed, abandon low value, high saliency options) and another in which exploitation is optimal (to succeed, refrain from switching between options). Sleep deprived subjects exhibited decreased performance on the exploitation task compared to non-sleep deprived controls, yet both groups exhibited increased performance on the exploratory task. These results speak to previous neuropsychological work on cognitive control.

The Lomb-Scargle periodogram was introduced in astrophysics to detect sinusoidal signals in noisy unevenly sampled time series. It proved to be a powerful tool in time series analysis and has recently been adapted in biomedical sciences. Its use is motivated by handling non-uniform data which is a common characteristic due to the restricted and irregular observations of, for instance, free-living animals. However, the observational data often contain fractions of non-Gaussian noise or may consist of periodic signals with non-sinusoidal shapes. These properties can make more difficult the interpretation of Lomb-Scargle periodograms and can lead to misleading estimates. In this letter we illustrate these difficulties for noise-free bimodal rhythms and sinusoidal signals with outliers. The examples are aimed to emphasize limitations and to complement the recent discussion on Lomb-Scargle periodograms.

With respect to the first example in Schimmel (2001), Van Dongen et al. (2001) conclude from their Lomb-Scargle analysis that the noise I used 'contains new periodicities that are added to the signal (these periodicities by themselves resemble a harmonic series of a 38-hour rhythm).' They infer that 'the variance of the added noise is about five times as large as the variance of the signal' causing the detection of the new significant periodicities in the noise prior to the 24-h bimodal rhythm. Moreover the 'example reflects a combination of an extremely non-sinusoidal signal with noise that is not independent, which results in a time series that is difficult to analyze with virtually any know method.' In the following, I briefly examine these concerns to avoid misunderstandings and to alert that with an adequate use of the statistical significance test, misleading conclusions can be obtained. Although this paper further emphasizes difficulties in the detection with Lomb-Scargle periodograms, this should not be used as de-motivation. As stated in Schimmel (2001) Lomb-Scargle is a powerful technique but such as any other method one should be aware about its limitations, and use additional tools to constrain the true data characteristics.

Fifteen healthy female subjects were studied for eight days while living conventionally. Subjects were free to choose the ways they spent their time within a framework of regular times of retiring and rising; in practice, much of the waking time was spent in sedentary activities. Nine of the subjects were aware of the natural light-dark cycle, this approximating to a 12:12 L:D schedule at the time of year when the study took place. Before the study, subjects were assessed for their degree of "morningness" by questionnaire; throughout the study, they wore a rectal probe, and an activity meter on their non-dominant wrist. The timing (phase) and amplitude of the circadian rectal temperature rhythm were assessed on each day by cosinor analysis as well as by a method based on visual inspection of the data. These two parameters were also assessed after the temperature data for each day had been "purified" by a number of methods. From these results it was possible to investigate the effect of purification upon the amplitude of the circadian rhythm of temperature. Also, the day-by-day variability of phase, and the relationship between morningness and phase, were compared using these methods of phase estimation, and using cross-correlation between data sets from adjacent days; in all cases, raw and purified temperature data were used. There was a significantly greater amount of daily variation in phase using purified rather than raw data sets, and this difference was present with all methods of purification as well as with all methods for estimating phase. Purification decreased the amplitude of the circadian temperature rhythm by about 30%. Finally, there was a significant correlation between the morningness score of the subjects and the phase of the circadian temperature rhythm, the phase becoming earlier with increasing morningness; when this relationship was re-examined using purified data, it became more marked. These results reflect the masking effects exerted upon raw temperature data by lifestyle. The extent to which the purification methods enable the endogenous component of a circadian rhythm - and, by implication, the output of the endogenous circadian oscillator - to be estimated in subjects living normally is addressed.

Studies of human circadian rhythms are typically conducted in artificial environments that are low in ecological validity. In the current study, six subjects and the field director lived in temporal isolation in a completely natural environment with constant daylight (a high Arctic research camp) for six weeks. Detailed daily sleep logs were kept. In keeping with past findings, five of the six subjects developed a free-running sleep-wake cycle longer than 24 hours. Unlike past results, the isolated subjects did not exhibit any synchronicity in their rhythins. There was a high degree of intersubject variability in circadian patterns. The findings have important implications for the comparison of the results of laboratory and field investigations of sleep-wake cycles.

Free-running circadian rhythms of locomotor activity of Tenebrionid beetles Trigonoscelis gigas Reitt., taken from the Turkmenian sand desert, were monitored in DD. The effects of microgravity --11 days in space flight aboard the Russian BION-10 "COSMOS" satellite, and of 2G hypergravity--seven days on a centrifuge, were determined. Two kinds of effects were found. In stable 2-peak records, there was a moderate decrease of tau in microgravity and an increase of tau in 2G, both of about 0.3 hr. In unstable records, alterations of gravity caused drastic deviations of tau and phi. Remarkably, two peaks of the activity rhythm, which are supposed to be controlled by separate oscillators, responded to gravity transitions in different ways. Gravity effects on the circadian system could be explained from a direct effect on the oscillator(s) itself or from a feed-back by altered locomotion to the pacemaker. Thus, for the first time the gravity dependence of a free-running circadian rhythm was proved in a combination of real space flight and centrifuge experiments.

Periodogram analysis of unequally spaced time-series, as part of many biological rhythm investigations, is complicated. The mathematical framework is scattered over the literature, and the interpretation of results is often debatable. In this paper, we show that the Lomb-Scargle method is the appropriate tool for periodogram analysis of unequally spaced data. A unique procedure of multiple period searching is derived, facilitating the assessment of the various rhythms that may be present in a time-series. All relevant mathematical and statistical aspects are considered in detail, and much attention is given to the correct interpretation of results. The use of the procedure is illustrated by examples, and problems that may be encountered are discussed. It is argued that, when following the procedure of multiple period searching, we can even benefit from the unequal spacing of a time-series in biological rhythm research.

This article reviews various procedures used in the analysis of circadian rhythms at the populational, organismal, cellular and molecular levels. The procedures range from visual inspection of time plots and actograms to several mathematical methods of time series analysis. Computational steps are described in some detail, and additional bibliographic resources and computer programs are listed.

We investigated effects of mutation ap on circadian locomotor activity, eclosion rhythms, and transcript levels of and in . We investigated circadian locomotor activity and eclosion rhythms in and wild-type flies, their F1 and F2 offspring, and wingless mutants and show that disrupts circadian locomotor rhythms in a genetically recessive manner, that is not caused by the absence of wings. The strain also showed impaired circadian activity rhythms, providing independent evidence for a significant role of in circadian locomotor rhythm expression. The mutation did not disrupt a circadian eclosion rhythm or rhythmic expression of the and clock genes, indicating that is not essential for circadian clock function, but is necessary for coupling locomotor activity to a circadian clock. transcription was reduced in flies in 12:12 LD, suggesting that may modulate core clock gene expression.

By collecting data continuously over 24 hours, accelerometers and other wearable devices can provide novel insights into circadian rhythms and their relationship to human health. Existing approaches for analyzing diurnal patterns using these data, including the cosinor model and functional principal components analysis, have revealed and quantified population-level diurnal patterns, but considerable subject-level variability remained uncaptured in features such as wake/sleep times and activity intensity. This remaining informative variability could provide a better understanding of chronotypes, or behavioral manifestations of one's underlying 24-hour rhythm. Curve registration, or alignment, is a technique in functional data analysis that separates "vertical" variability in activity intensity from "horizontal" variability in time-dependent markers like wake and sleep times; this data-driven approach is well-suited to studying chronotypes using accelerometer data. We develop a parametric registration framework for 24-hour accelerometric rest-activity profiles represented as dichotomized into epoch-level states of activity or rest. Specifically, we estimate subject-specific piecewise linear time-warping functions parametrized with a small set of parameters. We apply this method to data from the Baltimore Longitudinal Study of Aging and illustrate how estimated parameters give a more flexible quantification of chronotypes compared to traditional approaches.