Comparative bioluminescence dynamics among multiple Armillaria gallica, A. mellea, and A. tabescens genets

Bioluminescence is well known among white-spored species of Basidiomycota including several species of the white-rot wood decay genus Armillaria. Previous work demonstrated consistent differences among A. gallica, A. mellea, and A. tabescens in luminescence magnitude and in luminescence expression relative to environmental stimuli. In the present studies, temporal fluctuations in mycelial luminescence were quantitatively characterized using genets matched for geographical location. All genets derived from rhizomorphs or basdiomata were constitutively luminescent while six of 13 genets originating from mycelial fans were inconsistently luminescent. Using time series of 1000 consecutive measurements over 800 ms intervals, fluctuation patterns had significantly quantifiable structure and were not simply ‘white noise’. Fluctuation patterns were qualitatively similar with alternating periods of rapid fluctuation and relative stability, regardless of luminescence magnitude. Anomalous spikes or shifts in luminescence were recorded for several genets suggesting further work to identify the transient stimuli which elicited these altered luminescence patterns.     

Non-stationary time series and the robustness of circadian rhythms

Circadian rhythms are regular oscillations in the value of behavioral and physiological variables of organisms that recur on a daily basis. The purpose of this study was to evaluate the extent of non-stationarity of circadian rhythms over several days, to determine how damaging is the violation of the assumption of stationarity in the analysis of circadian rhythms, and to formalize the concept of "rhythm robustness" as an index of oscillatory ("weak") stationarity. Simulated (computer-generated) and experimental data sets (rhythms of body temperature and running-wheel activity in several rodent species) were analysed. Tests of stationarity based on the variance of the daily means and the variance of the daily variances revealed that most experimental data sets are not stationary. Analysis of linear trends indicated that significant trends are rare in experimental data sets. Although the non-stationarity of the experimental data sets reduced the spectral energy of the Enright periodogram used to assess rhythmicity, detection of circadian rhythmicity was not prevented in any of the rhythmic data sets. The results of the various analyses allow the inference that, after high-frequency noise is filtered out, the value of the periodogram's Q(P) statistic reflects the extent of stationarity of the time series. Thus, the "robustness" of a circadian rhythm (i.e. the magnitude of the empirical Q(P) value as compared to the Q(P) value associated with a perfectly rhythmic time series) can serve as an index of the stationarity of the rhythm.     

Effective gene prediction by high resolution frequency estimator based on least-norm solution technique

Linear algebraic concept of subspace plays a significant role in the recent techniques of spectrum estimation. In this article, the authors have utilized the noise subspace concept for finding hidden periodicities in DNA sequence. With the vast growth of genomic sequences, the demand to identify accurately the protein-coding regions in DNA is increasingly rising. Several techniques of DNA feature extraction which involves various cross fields have come up in the recent past, among which application of digital signal processing tools is of prime importance. It is known that coding segments have a 3-base periodicity, while non-coding regions do not have this unique feature. One of the most important spectrum analysis techniques based on the concept of subspace is the least-norm method. The least-norm estimator developed in this paper shows sharp period-3 peaks in coding regions completely eliminating background noise. Comparison of proposed method with existing sliding discrete Fourier transform (SDFT) method popularly known as modified periodogram method has been drawn on several genes from various organisms and the results show that the proposed method has better as well as an effective approach towards gene prediction. Resolution, quality factor, sensitivity, specificity, miss rate, and wrong rate are used to establish superiority of least-norm gene prediction method over existing method.     

Bright Light Therapy: Improved Sensitivity to Its Effects on Rest-Activity Rhythms in Alzheimer Patients by Application of Nonparametric Methods

Sleep-wake rhythm disturbances in patients with Alzheimer's disease (AD) make a strong demand on caregivers and are among the most important reasons for institutionalization. Several previous studies reported that the disturbances improve with increased environmental light, which, through the retinohypothalamic tract, activates the suprachiasmatic nucleus (SCN), the biological clock of the brain. The data of recently published positive and negative reports on the effect of bright light on actigraphically assessed rest-activity rhythms in demented elderly were reanalyzed using several statistical procedures. It was demonstrated that the light-induced improvement in coupling of the rest-activity rhythm to the environmental zeitgeber of bright light is better detected using nonparametric procedures. Cosinor, complex demodulation, and Lomb-Scargle periodogram-derived variables are much less sensitive to this effect because of the highly nonsinusoidal waveform of the rest-activity rhythm. Guidelines for analyses of actigraphic data are given to improve the sensitivity to treatment effects in future studies.