Mood assessment via animated characters: a novel instrument to evaluate feelings in young children with anxiety disorders.

We evaluated a novel, computerized feelings assessment instrument (MAAC) in 54 children with anxiety disorders and 35 nonanxious children ages 5 to 11. They rated their feelings relative to 16 feeling animations. Ratings of feelings, order of feeling selection, and correlations with standardized anxiety measures were examined. Positive emotions were rated more highly and visited earlier by nonanxious children. Children with anxiety disorders explored fewer emotions. MAAC ratings on several positive emotions showed inverse correlations with state anxiety. Although needing further evaluation, MAAC may facilitate feelings assessment in young children and may distinguish children with anxiety disorders from nonanxious children.

One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death III: diffusion pulse death zones.

This is the third of three papers in which we study a mathematical model of cytoskeleton-induced neuron death. In the first two papers of this suite [Lomasko, T., Clarke, G., Lumsden, C., 2007a. One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death I: cell fate arrival times. J. Theor. Biol. 249, 1-17, doi:10.1016/j.jtbi.2007.05.031; Lomasko, T., Clarke, G., Lumsden, C., 2007b. One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death II: transition state metastability. J. Theor. Biol. 249, 18-28, doi:10.1016/j.jtbi.2007.05.032], we established that the mean-field limit of our model relates the known patterns of neuron decline to specific scales of cytoskeleton reorganization and cell-cell interaction by diffusible death factors. In the mean-field limit, the spatially variable concentration of diffusing death factor is replaced by a constant average value. Recent empirical advances now permit the actual diffusion of such factors to be followed in intact neuropil. In this paper we therefore extend the model beyond the mean-field limit, to include the diffusion dynamics of death factor bursts released from dying neurons. A range of novel tissue degeneration patterns is observed, for which we confirm and extend the mean-field prediction that sigmoidal patterns of neuron population decay are a principal hallmark of cell death in the presence of death factor release.

One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death II: transition state metastability.

This is the second of two papers in which we study a mathematical model of cytoskeleton-induced neuron death. Recent evidence indicates that aggravated assembly or destruction of the cytoskeleton can trigger programmed death in neurons, by mechanisms as yet poorly understood. In our model, assembly control of the neuronal cytoskeleton interacts with both cellular stress levels and cytosolic free radical concentrations to trigger neurodegeneration. This trigger mechanism is further modulated by a diffusible toxic factor released from dying neurons. In the companion report we established that the model relates the observed general patterns of neuron decline to specific scales of cytoskeleton reorganization and cell-cell interaction strength. In this paper we study the transit of neurons through states intermediate between initial viability and cell death in our model. We find that the stochastic flow of neuron fate, from viability to cell death, self-organizes into two distinct temporal phases. There is a rapid relaxation of the initial neuron population to a more disordered phase that is long-lived, or metastable, with respect to the time scales of change in single cells. Strikingly, cellular egress from this metastable phase follows the one-hit kinetic pattern of exponential decline now established as a principal hallmark of cell death in neurodegenerative disorders. Intermediate state metastability may therefore be an important element in the systems biology of one-hit neurodegeneration.

The effects of irregular sampling and missing data on largest Lyapunov exponents.

Human self-report time series data are typically marked by irregularities in sampling rates arising from the data generation process. The largest Lyapunov exponent lamda1 is an indicator of chaos in time series data. Relatively little has been published to assist the calculation of lamda1's using irregularly sampled data. We report the results of a series of computational experiments on synthetic data sets assessing techniques for handling irregular time series data in the calculation of lamda1 . Regularly sampled data sets were disrupted by data point removal using an empirically motivated data gap distribution of either uniform random or power law form. Missing data segments were patched using segment concatenation, segment filling with average data values, or local interpolation in phase space. We compared results of lamda1 calculations using complete and patched sets. The greatest proportion of missing data possible that will allow an accurate estimate of lamda1 depends on the nature of the underlying system and the patching technique used. Self-similar data patched with segment concatenation was particularly robust. Local interpolation in phase space was successful in many cases, but required potentially impractical quantities of intact data as a primer. Optimally, estimates of lamda1 can readily be recovered with 15%-20% or greater amounts of missing data.

One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death I: cell-fate arrival times.

Much experimental evidence shows that the cytoskeleton is a downstream target and effector during cell death in numerous neurodegenerative diseases, including Parkinson's, Huntington's, and Alzheimer's diseases. However, recent evidence indicates that cytoskeletal dysfunction can also trigger neuronal death, by mechanisms as yet poorly understood. This is the first of two papers in which we study a mathematical model of cytoskeleton-induced neuron death. In our model, assembly control of the neuronal cytoskeleton interacts with both cellular stress levels and cytosolic free radical concentrations to trigger neurodegeneration. This trigger mechanism is further modulated by the presence of cell interactions in the form of a diffusible toxic factor released by dying neurons. We find that, consistent with empirical observations, our model produces one-hit exponential and sigmoid patterns of cell dropout. In all cases, cell dropout is exponential-tailed and described accurately by a gamma distribution. The transition between exponential and sigmoidal is gradual, and determined by a synergetic interaction between the magnitude of fluctuations in cytoskeleton assembly control and by the degree of cell coupling. We conclude that a single mechanism involving neuron interactions and fluctuations in cytoskeleton assembly control is compatible with the experimentally observed range of neuronal attrition kinetics.

The effects of the irregular sample and missing data in time series analysis.

Human self-report time series data are typically marked by irregularities in sampling rates; furthermore, these irregularities are typically natural outcomes of the data generation process. Relatively little has been published to assist the analysis of irregularly sampled data. We report the results of a series of computational experiments on synthetic data sets designed to assess the utility of techniques for handling irregular time series data. The behavior of a conservative quasiperiodic, a dissipative chaotic, and a self-organized critical dynamics were sampled regularly in time and the regular sampling was disrupted by data point removal or by stochastic shifts in time. Missing data segments were then patched by means of segment concatenation, by segment filling with average data values, or by local interpolation in phase space. We compared results of nonlinear analytical tools such as autocorrelations and correlation dimensions using complete and patched sets, as well as power spectra with Lomb periodograms of the decimated sets. Local interpolation in phase space was particularly successful at preserving key features of the original data, but required potentially impractical quantities of intact data as a primer. While the other patching methods are not limited by the need for intact data, they distort results relative to the intact series. We conclude that irregularly sampled data sets with as much as 15 percent missing data can potentially be re-sampled or repaired for analysis with techniques that assume regular sampling without introducing substantial errors.

In vitro, in vivo, in silico: computational systems in tissue engineering and regenerative medicine.

The emergence of computational systems in tissue engineering and regenerative medicine is paralleling the rapid rise of new technology. Developments in software and hardware have allowed access to the huge data streams that are now available. The Human Genome Project led the way and opened many avenues for other branches of science and biology with extensive but contained databanks. The availability of vast amounts of data means nothing without the ability to integrate the information into a useful form. Tissue engineering has always been a practical science in which function and utility are key objectives. This review delineates key areas of this rapidly ascending branch of science and illustrates examples central to the successful integration of computational methods.

Scale-free neurodegeneration: cellular heterogeneity and the stretched exponential kinetics of cell death.

Neurodegenerative disorders are an insidious group of diseases characterized by severe physical and cognitive effects that often have devastating consequences for the lives of affected individuals and their families. One feature common to a significant proportion of these diseases is that affected neurons commit to undergoing an active form of degeneration known as programmed cell death, or apoptosis. Although intense effort over the past several years has resulted is a remarkable increase in our understanding of the molecular events involved in neurodegeneration, our knowledge regarding the cellular and tissue properties that determine the temporal patterns of neuronal attrition is limited. We recently demonstrated that neurodegenerative kinetics in various diseases fit well to exponential decay functions, and proposed a universal one-hit switch mechanism in which mutant and injured neurons exist in a viable state characterized by an increased but constant risk of initiating apoptosis (Nature, 406, p. 195). Here we show that a heavy-tailed stretched exponential function is better able to account for neurodegenerative kinetic data. Moreover, normalization of all available data according to their corresponding best-fit stretched exponential parameters suggest that the generalized model is consistent with a universal mechanism of neuronal cell death that is greatly improved over the constant risk model. In contrast to the original model in which all cells exhibit an identical risk of initiating apoptosis, the stretched exponential model is consistent with each neuron experiencing a constant risk that is different from that experienced by other cells in the degenerating population, perhaps due to spatial differences in the cellular microenvironment. Intriguingly, the predicted distribution of risk across the cell population can be fit by a power-law function, further suggesting that scale-free properties of degenerating neuronal tissues might act as potent regulators of the kinetics of cell death in neural tissue.

Heterogeneous cellular environments modulate one-hit neuronal death kinetics.

We recently demonstrated that cell loss kinetics in diverse forms of neurodegeneration (ND) suggests a universal death switch mechanism in which each cell is at a constant risk to initiate apoptosis. We proposed that mutant and injured neurons exist in a viable state typified by an increased risk of initiating death processes [Clarke, Collins, Leavitt, Andrews, Hayden, Lumsden, McInnes, A one-hit model of cell death in inherited neuronal degenerations, Nature 406 (2000) 195-199]. To date, however, measurements of cell death risk have been available only as averages across the affected cell population. Here we develop and apply a method of death kinetic analysis in which the risk factors vary across the neuronal population, as for example due to regional heterogeneities in the cellular microenvironment. We find that most cases of ND for which cell loss data has been obtained are better explained by death risks that vary from cell to cell, compared to death risk that is constant across the neuronal population. Strikingly, a common form of the frequency distribution defining the death risk heterogeneity is shared across most of these cases. This first characterization of the kinetic heterogeneity in one-hit neuronal death, therefore, suggests that the wide variety of ND now known may share mechanisms through which regional differences in the cellular microenvironment modulate the kinetics of cell loss.

Portable mood mapping: the validity and reliability of analog scale displays for mood assessment via hand-held computer.

The long-term natural time course of mood change remains poorly understood, and improved methods that assay multiple mood symptoms quickly and reliably are crucial to further progress. This study describes the reliability and validity of the new visual analog scale (VAS) display method for a recently developed 19-item VAS-based mood questionnaire, the VMQ, administered via hand-held computer (HHC). The effect of the smaller HHC screen size on accuracy and precision of VAS completion was investigated in 28 subjects using 4- and 10-cm paper-based VASs to indicate six specified dates within the year. The influence of digital vs. paper medium was then tested in 39 subjects who completed the same task, using 10-cm paper and 4-cm HHC-based VASs. Test-retest reliability was evaluated in 29 subjects who completed the questionnaire on a HHC twice, 10 min apart. Since the HHC presents VMQ scales with text anchor orientation set randomly, we also considered whether subjects might inadvertently transpose responses on the HHC. We found that reducing VAS size produced no significant loss of response precision or accuracy in subject response. Moreover, there was no significant loss of accuracy or precision between 10-cm paper and 4-cm HHC-based versions of the VAS. HHC-based items also demonstrated excellent test-retest reliability, with excellent values of Cronbach's alpha. The transposition error rate was negligible (0.27%). Our study provides initial evidence that the HHC-based VAS display used in the VMQ is a reliable and valid tool for comprehensive collection of analog mood scale data.

Photoreceptor death: spatiotemporal patterns arising from one-hit death kinetics and a diffusible cell death factor.

Retinitis pigmentosa (RP) is an inherited disease affecting approximately 1:4000 individuals in North America. It is characterized clinically by the gradual apoptotic death of photoreceptor cells that occurs nonuniformly across the surface of the retina. Recently, it has been demonstrated that the time of death of many individual photoreceptors is random, a fact that must be reconciled with the spatiotemporal patterns of photoreceptor degeneration that are observed in patients with RP. One possible explanation is that a diffusible toxic factor is released by dying photoreceptors and induces adjacent cells to likewise undergo apoptosis. To determine if such a mechanism can result in patchy distributions of photoreceptor death, as frequently observed in RP patients, we studied cell attrition produced by a bistable biochemical switch in an idealized one-dimensional retina. We found that with a reasonable choice of parameter values, our model was able to produce patterns of cell death resembling those observed in RP. In the context of this model, patches on the order of histologically observable size could develop from a single release event, but their rates of formation were independent of the concentration of toxic factor released. Instead, factor concentration affected the overall rate of cell death, the number of degenerating patches, and their distribution across the retina.