Timely Questions Emerging in Chronobiology: The Circadian Clock Keeps on Ticking.

Chronobiology investigations have revealed much about cellular and physiological clockworks but we are far from having a complete mechanistic understanding of the physiological and ecological implications. Here we present some unresolved questions in circadian biology research as posed by the editorial staff and guest contributors to the Journal of Circadian Rhythms. This collection of ideas is not meant to be comprehensive but does reveal the breadth of our observations on emerging trends in chronobiology and circadian biology. It is amazing what could be achieved with various expected innovations in technologies, techniques, and mathematical tools that are being developed. We fully expect strengthening mechanistic work will be linked to health care and environmental understandings of circadian function. Now that most clock genes are known, linking these to physiological, metabolic, and developmental traits requires investigations from the single molecule to the terrestrial ecological scales. Real answers are expected for these questions over the next decade. Where are the circadian clocks at a cellular level? How are clocks coupled cellularly to generate organism level outcomes? How do communities of circadian organisms rhythmically interact with each other? In what way does the natural genetic variation in populations sculpt community behaviors? How will methods development for circadian research be used in disparate academic and commercial endeavors? These and other questions make it a very exciting time to be working as a chronobiologist.

EgoActive: Integrated Wireless Wearable Sensors for Capturing Infant Egocentric Auditory-Visual Statistics and Autonomic Nervous System Function 'in the Wild'.

There have been sustained efforts toward using naturalistic methods in developmental science to measure infant behaviors in the real world from an egocentric perspective because statistical regularities in the environment can shape and be shaped by the developing infant. However, there is no user-friendly and unobtrusive technology to densely and reliably sample life in the wild. To address this gap, we present the design, implementation and validation of the EgoActive platform, which addresses limitations of existing wearable technologies for developmental research. EgoActive records the active infants' egocentric perspective of the world via a miniature wireless head-mounted camera concurrently with their physiological responses to this input via a lightweight, wireless ECG/acceleration sensor. We also provide software tools to facilitate data analyses. Our validation studies showed that the cameras and body sensors performed well. Families also reported that the platform was comfortable, easy to use and operate, and did not interfere with daily activities. The synchronized multimodal data from the EgoActive platform can help tease apart complex processes that are important for child development to further our understanding of areas ranging from executive function to emotion processing and social learning.

Multiple metals influence distinct properties of the Arabidopsis circadian clock.

Circadian rhythms coordinate endogenous events with external signals, and are essential to biological function. When environmental contaminants affect these rhythms, the organism may experience fitness consequences such as reduced growth or increased susceptibility to pathogens. In their natural environment plants may be exposed to a wide range of industrial and agricultural soil pollutants. Here, we investigate how the addition of various metal salts to the root-interaction environment can impact rhythms, measured via the promoter:luciferase system. The consequences of these environmental changes were found to be varied and complex. Therefore, in addition to traditional Fourier-based analyses, we additionally apply novel wavelet-based spectral hypothesis testing and clustering methodologies to organize and understand the data. We are able to classify broad sets of responses to these metal salts, including those that increase, and those that decrease, the period, or which induce a lack of precision or disrupt any meaningful periodicity. Our methods are general, and may be applied to discover common responses and hidden structures within a wide range of biological time series data.

A wavelet lifting approach to long-memory estimation.

Reliable estimation of long-range dependence parameters is vital in time series. For example, in environmental and climate science such estimation is often key to understanding climate dynamics, variability and often prediction. The challenge of data collection in such disciplines means that, in practice, the sampling pattern is either irregular or blighted by missing observations. Unfortunately, virtually all existing Hurst parameter estimation methods assume regularly sampled time series and require modification to cope with irregularity or missing data. However, such interventions come at the price of inducing higher estimator bias and variation, often worryingly ignored. This article proposes a new Hurst exponent estimation method which naturally copes with data sampling irregularity. The new method is based on a multiscale lifting transform exploiting its ability to produce wavelet-like coefficients on irregular data and, simultaneously, to effect a necessary powerful decorrelation of those coefficients. Simulations show that our method is accurate and effective, performing well against competitors even in regular data settings. Armed with this evidence our method sheds new light on long-memory intensity results in environmental and climate science applications, sometimes suggesting that different scientific conclusions may need to be drawn.