Optimal experimental design to estimate statistically significant periods of oscillations in time course data

Prolactin blood concentration relies on the scalability of the TIDA neurons' network efficiency in vivo

Our understanding and management of reproductive health and related disorders such as infertility, menstrual irregularities, and pituitary disorders depend on understanding the intricate sex-specific mechanisms governing prolactin secretion. Using ex vivo experiments in acute slices, in parallel with in vivo calcium imaging (GRIN lens technology), we found that dopamine neurons inhibiting PRL secretion (TIDA), organize as functional networks both in and ex vivo. We defined an index of efficiency of networking (Ieff) using the duration of calcium events and the ability to form plastic economic networks. It determined TIDA neurons' ability to inhibit PRL secretion in vivo. Ieff variations in both sexes demonstrated TIDA neurons' adaptability to physiological changes. A variation in the number of active neurons contributing to the network explains the sexual dimorphism in basal [PRL]blood secretion patterns. These sex-specific differences in neuronal activity and network organization contribute to the understanding of hormone regulation.

Computational Approaches and Tools as Applied to the Study of Rhythms and Chaos in Biology

The temporal dynamics in biological systems displays a wide range of behaviors, from periodic oscillations, as in rhythms, bursts, long-range (fractal) correlations, chaotic dynamics up to brown and white noise. Herein, we propose a comprehensive analytical strategy for identifying, representing, and analyzing biological time series, focusing on two strongly linked dynamics: periodic (oscillatory) rhythms and chaos. Understanding the underlying temporal dynamics of a system is of fundamental importance; however, it presents methodological challenges due to intrinsic characteristics, among them the presence of noise or trends, and distinct dynamics at different time scales given by molecular, dcellular, organ, and organism levels of organization. For example, in locomotion circadian and ultradian rhythms coexist with fractal dynamics at faster time scales. We propose and describe the use of a combined approach employing different analytical methodologies to synergize their strengths and mitigate their weaknesses. Specifically, we describe advantages and caveats to consider for applying probability distribution, autocorrelation analysis, phase space reconstruction, Lyapunov exponent estimation as well as different analyses such as harmonic, namely, power spectrum; continuous wavelet transforms; synchrosqueezing transform; and wavelet coherence. Computational harmonic analysis is proposed as an analytical framework for using different types of wavelet analyses. We show that when the correct wavelet analysis is applied, the complexity in the statistical properties, including temporal scales, present in time series of signals, can be unveiled and modeled. Our chapter showcase two specific examples where an in-depth analysis of rhythms and chaos is performed: (1) locomotor and food intake rhythms over a 42-day period of mice subjected to different feeding regimes; and (2) chaotic calcium dynamics in a computational model of mitochondrial function.

Sperm physiology varies according to ultradian and infradian rhythms

The spermatozoon must be physiologically prepared to fertilize the egg, process called capacitation. Human sperm samples are heterogeneous in their ability to capacitate themselves, which leads to variability between samples from the same or different donors, and even along the seasons. Here we studied sperm variation in the capacitation state according to the ability of capacitated spermatozoa to acrosome react upon stimulation (% ARi) and to be recruited by chemotaxis (% Chex). Both indirect indicators of sperm capacitation increased along the incubation time with fluctuations. Those capacitated sperm recruited by chemotaxis showed an ultradian rhythm with a cycle every 2 h, which might be influenced by unknown intrinsic sperm factors. Two infradian rhythms of 12 months for the % ARi and of 6 months for % Chex were observed, which are associated with the joint action of temperature and photoperiod. Thus, to avoid false negative results, human sperm samples are recommended to be incubated for a long period (e.g. 18 h) preferably in spring time. This innovative point of view would lead to better comprehend human reproductive biology and to think experimental designs in the light of sperm cyclicity or to improve sperm aptitude for clinical purposes.

The fractal organization of ultradian rhythms in avian behavior

Living systems exhibit non-randomly organized biochemical, physiological, and behavioral processes that follow distinctive patterns. In particular, animal behavior displays both fractal dynamics and periodic rhythms yet the relationship between these two dynamic regimens remain unexplored. Herein we studied locomotor time series of visually isolated Japanese quails sampled every 0.5 s during 6.5 days (>10⁶ data points). These high-resolution, week-long, time series enabled simultaneous evaluation of ultradian rhythms as well as fractal organization according to six different analytical methods that included Power Spectrum, Enright, Empirical Mode Decomposition, Wavelet, and Detrended Fluctuation analyses. Time series analyses showed that all birds exhibit circadian rhythms. Although interindividual differences were detected, animals presented ultradian behavioral rhythms of 12, 8, 6, 4.8, 4 h and/or lower and, irrespective of visual isolation, synchronization between these ultradian rhythms was observed. Moreover, all birds presented similar overall fractal dynamics (for scales ∼30 s to >4.4 h). This is the first demonstration that avian behavior presents fractal organization that predominates at shorter time scales and coexists with synchronized ultradian rhythms. This chronobiological pattern is advantageous for keeping the organism’s endogenous rhythms in phase with internal and environmental periodicities, notably the feeding, light-dark and sleep-wake cycles.

Network dynamics: quantitative analysis of complex behavior in metabolism, organelles, and cells, from experiments to models and back

Advancing from two core traits of biological systems: multilevel network organization and nonlinearity, we review a host of novel and readily available techniques to explore and analyze their complex dynamic behavior within the framework of experimental-computational synergy. In the context of concrete biological examples, analytical methods such as wavelet, power spectra, and metabolomics-fluxomics analyses, are presented, discussed, and their strengths and limitations highlighted. Further shown is how time series from stationary and nonstationary biological variables and signals, such as membrane potential, high-throughput metabolomics, O₂ and CO₂ levels, bird locomotion, at the molecular, (sub)cellular, tissue, and whole organ and animal levels, can reveal important information on the properties of the underlying biological networks. Systems biology-inspired computational methods start to pave the way for addressing the integrated functional dynamics of metabolic, organelle and organ networks. As our capacity to unravel the control and regulatory properties of these networks and their dynamics under normal or pathological conditions broadens, so is our ability to address endogenous rhythms and clocks to improve health-span in human aging, and to manage complex metabolic disorders, neurodegeneration, and cancer. WIREs Syst Biol Med 2017, 9:e1352. doi: 10.1002/wsbm.1352 For further resources related to this article, please visit the WIREs website.