Listen to genes : dealing with microarray data in the frequency domain

Background: We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes. Methodology: Genes are normalized using an error model based uniform normalization method aimed at identifying and estimating the sources of variations. The model minimizes the correlation among error terms across replicates. The normalized gene expressions are then clustered in terms of their power spectrum density. The method of complex Granger causality is introduced to reveal interactions between sets of genes. Complex Granger causality along with partial Granger causality is applied in both time and frequency domains to selected as well as all the genes to reveal the interesting networks of interactions. The approach is successfully applied to Arabidopsis leaf microarray data generated from 31,000 genes observed over 22 time points over 22 days. Three circuits: a circadian gene circuit, an ethylene circuit and a new global circuit showing a hierarchical structure to determine the initiators of leaf senescence are analyzed in detail. Conclusions: We use a totally data-driven approach to form biological hypothesis. Clustering using the power-spectrum analysis helps us identify genes of potential interest. Their dynamics can be captured accurately in the time and frequency domain using the methods of complex and partial Granger causality. With the rise in availability of temporal microarray data, such methods can be useful tools in uncovering the hidden biological interactions. We show our method in a step by step manner with help of toy models as well as a real biological dataset. We also analyse three distinct gene circuits of potential interest to Arabidopsis researchers

Regulation of Mesenchymal Stem to Transit-Amplifying Cell Transition in the Continuously Growing Mouse Incisor

Summary In adult tissues and organs with high turnover rates, the generation of transit-amplifying cell (TAC) populations from self-renewing stem cells drives cell replacement. The role of stem cells is to provide a renewable source of cells that give rise to TACs to provide the cell numbers that are necessary for cell differentiation. Regulation of the formation of TACs is thus fundamental to controlling cell replacement. Here, we analyze the properties of a population of mesenchymal TACs in the continuously growing mouse incisor to identify key components of the molecular regulation that drives proliferation. We show that the polycomb repressive complex 1 acts as a global regulator of the TAC phenotype by its direct action on the expression of key cell-cycle regulatory genes and by regulating Wnt/β-catenin-signaling activity. We also identify an essential requirement for TACs in maintaining mesenchymal stem cells, which is indicative of a positive feedback mechanism

A quiescent cell population replenishes mesenchymal stem cells to drive accelerated growth in mouse incisors

The extent to which heterogeneity within mesenchymal stem cell (MSC) populations is related to function is not understood. Using the archetypal MSC in vitro surface marker, CD90/Thy1, here we show that 30% of the MSCs in the continuously growing mouse incisor express CD90/Thy1 and these cells give rise to 30% of the differentiated cell progeny during postnatal development. In adulthood, when growth rate homeostasis is established, the CD90/Thy1+ MSCs decrease dramatically in number. When adult incisors are cut, the growth rate increases to rapidly re-establish tooth length and homeostasis. This accelerated growth rate correlates with the re-appearance of CD90/Thy+ MSCs and re-establishment of their contribution to cell differentiation. A population of Celsr1+ quiescent cells becomes mitotic following clipping and replenishes the CD90/Thy1 population. A sub-population of MSCs thus exists in the mouse incisor, distinguished by expression of CD90/Thy1 that plays a specific role only during periods of increased growth rat

The Precursors and Products of Justice Climates: Group Leader Antecedents and Employee Attitudinal Consequences

Drawing on the organizational justice, organizational climate, leadership and personality, and social comparison theory literatures, we develop hypotheses about the effects of leader personality on the development of three types of justice climates (e.g., procedural, interpersonal, and informational), and the moderating effects of these climates on individual level justice- attitude relationships. Largely consistent with the theoretically-derived hypotheses, the results showed that leader (a) agreeableness was positively related to procedural, interpersonal and informational justice climates, (b) conscientiousness was positively related to a procedural justice climate, and (c) neuroticism was negatively related to all three types of justice climates. Further, consistent with social comparison theory, multilevel data analyses revealed that the relationship between individual justice perceptions and job attitudes (e.g., job satisfaction, commitment) was moderated by justice climate such that the relationships were stronger when justice climate was high

Random walk with barriers: Diffusion restricted by permeable membranes

Restrictions to molecular motion by barriers (membranes) are ubiquitous in biological tissues, porous media and composite materials. A major challenge is to characterize the microstructure of a material or an organism nondestructively using a bulk transport measurement. Here we demonstrate how the long-range structural correlations introduced by permeable membranes give rise to distinct features of transport. We consider Brownian motion restricted by randomly placed and oriented permeable membranes and focus on the disorder-averaged diffusion propagator using a scattering approach. The renormalization group solution reveals a scaling behavior of the diffusion coefficient for large times, with a characteristically slow inverse square root time dependence. The predicted time dependence of the diffusion coefficient agrees well with Monte Carlo simulations in two dimensions. Our results can be used to identify permeable membranes as restrictions to transport in disordered materials and in biological tissues, and to quantify their permeability and surface area.Comment: 8 pages, 3 figures; origin of dispersion clarified, refs adde

Do female association preferences predict the likelihood of reproduction?

Sexual selection acting on male traits through female mate choice is commonly inferred from female association preferences in dichotomous mate choice experiments. However, there are surprisingly few empirical demonstrations that such association preferences predict the likelihood of females reproducing with a particular male. This information is essential to confirm association preferences as good predictors of mate choice. We used green swordtails (<i>Xiphophorus helleri</i>) to test whether association preferences predict the likelihood of a female reproducing with a male. Females were tested for a preference for long- or short-sworded males in a standard dichotomous choice experiment and then allowed free access to either their preferred or non-preferred male. If females subsequently failed to produce fry, they were provided a second unfamiliar male with similar sword length to the first male. Females were more likely to reproduce with preferred than non-preferred males, but for those that reproduced, neither the status (preferred/non-preferred) nor the sword length (long/short) of the male had an effect on brood size or relative investment in growth by the female. There was no overall preference based on sword length in this study, but male sword length did affect likelihood of reproduction, with females more likely to reproduce with long- than short-sworded males (independent of preference for such males in earlier choice tests). These results suggest that female association preferences are good indicators of female mate choice but that ornament characteristics of the male are also important

Agent-Based Modeling of Endotoxin-Induced Acute Inflammatory Response in Human Blood Leukocytes

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions.An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades.The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system

Psychometric properties and the prevalence, intensity and causes of oral impacts on daily performance (OIDP) in a population of older Tanzanians

BACKGROUND: The objective was to study whether a Kiswahili version of the OIDP (Oral Impacts on Daily Performance) inventory was valid and reliable for use in a population of older adults in urban and rural areas of Tanzania; and to assess the area specific prevalence, intensity and perceived causes of OIDP. METHOD: A cross-sectional survey was conducted in Pwani region and in Dar es Salaam in 2004/2005. A two-stage stratified cluster sample design was utilized. Information became available for 511 urban and 520 rural subjects (mean age 62.9 years) who were interviewed and participated in a full mouth clinical examination in their own homes. RESULTS: The Kiswahili version of the weighted OIDP inventory preserved the overall concept of the original English version. Cronbach's alpha was 0.83 and 0.90 in urban and rural areas, respectively, and the OIDP inventory varied systematically in the expected direction with self-reported oral health measures. The respective prevalence of oral impacts was 51.2% and 62.1% in urban and rural areas. Problems with eating was the performance reported most frequently (42.5% in urban, 55.1% in rural) followed by cleaning teeth (18.2% in urban, 30.6% in rural). More than half of the urban and rural residents with impacts had very little, little and moderate impact intensity. The most frequently reported causes of impacts were toothache and loose teeth. CONCLUSION: The Kiswahili OIDP inventory had acceptable psychometric properties among non-institutionalized adults 50 years and above in Tanzania. The impacts affecting their performances were relatively common but not very severe