Fluorescence Lifetime Imaging Microscopy (FLIM) Data Analysis with TIMP

Fluorescence Lifetime Imaging Microscopy (FLIM) allows fluorescence lifetime images of biological objects to be collected at 250 nm spatial resolution and at (sub-)nanosecond temporal resolution. Often n_comp kinetic processes underlie the observed fluorescence at all locations, but the intensity of the fluorescence associated with each process varies per-location, i.e., per-pixel imaged. Then the statistical challenge is global analysis of the image: use of the fluorescence decay in time at all locations to estimate the n_comp lifetimes associated with the kinetic processes, as well as the amplitude of each kinetic process at each location. Given that typical FLIM images represent on the order of 10^2 timepoints and 10^3 locations, meeting this challenge is computationally intensive. Here the utility of the TIMP package for R to solve parameter estimation problems arising in FLIM image analysis is demonstrated. Case studies on simulated and real data evidence the applicability of the partitioned variable projection algorithm implemented in TIMP to the problem domain, and showcase options included in the package for the visual validation of models for FLIM data.

Particle Stirring in Turbulent Gas Disks: Including Orbital Oscillations

We describe the diffusion and random velocities of solid particles due to stochastic forcing by turbulent gas. We include the orbital dynamics of Keplerian disks, both in-plane epicycles and vertical oscillations. We obtain a new result for the diffusion of solids. The Schmidt number (ratio of gas to particle diffusivity) is Sc = 1 + (Omega t_stop)^2, in terms of the particle stopping time, t_stop, and the orbital frequency, Omega. The standard result, Sc = 1 + t_stop/t_eddy, in terms of the eddy turnover time, t_eddy, is shown to be incorrect. The main difference is that Sc rises quadratically, not linearly, with stopping time. Consequently, particles larger than ~ 10 cm in protoplanetary disks will suffer less radial diffusion and will settle closer to the midplane. Such a layer of boulders would be more prone to gravitational collapse. Our predictions of RMS speeds, vertical scale height and diffusion coefficients will help interpret numerical simulations. We confirm previous results for the vertical stirring of particles (scale heights and random velocities), and add a correction for arbitrary ratios of eddy to orbital times. The particle layer becomes thinner for t_eddy > 1/Omega, with the strength of turbulent diffusion held fixed. We use two analytic techniques -- the Hinze-Tchen formalism and the Fokker-Planck equation with velocity diffusion -- with identical results when the regimes of validity overlap. We include simple physical arguments for the scaling of our results.Comment: 17 pages, 7 figures, 2 tables, accepted to Icaru

Speciation dynamics of an agent-based evolution model in phenotype space

This dissertation is an exploration of phase transition behavior and clustering of populations of organisms in an agent-based model of evolutionary dynamics. The agents in the model are organisms, described as branching-coalescing random walkers, which are characterized by their coordinates in a two-dimensional phenotype space. Neutral evolutionary conditions are assumed, such that no organism has a fitness advantage regardless of its phenotype location. Lineages of organisms evolve by limiting the maximum possible offspring distance from their parent(s) (mutability, which is the only heritable trait) along each coordinate in phenotype space. As mutability is varied, a non-equilibrium phase transition is shown to occur for populations reproducing by assortative mating and asexual fission. Furthermore, mutability is also shown to change the clustering behavior of populations. Random mating is shown to destroy both phase transition behavior and clustering. The phase transition behavior is characterized in the asexual fission case. By demonstrating that the populations near criticality collapse to universal scaling functions with appropriate critical exponents, this case is shown to belong to the directed percolation universality class. Finally, lineage behavior is explored for both organisms and clusters. The lineage lifetimes of the initial population of organisms are found to have a power-law probability density which scales with the correlation length exponent near critical mutability. The cluster centroid step-sizes obey a probability density function that is bimodal for all mutability values, and the average displays a linear dependence upon mutability in the supercritical range. Cluster lineage tree structures are shown to have Kingman\u27s coalescent universal tree structure at the directed percolation phase transition despite more complicated lineage structures. --Abstract, page iii

Sharing, privacy and trust issues for photo collections

Digital libraries are quickly being adopted by the masses. Technological developments now allow community groups, clubs, and even ordinary individuals to create their own, publicly accessible collections. However, users may not be fully aware of the potential privacy implications of submitting their documents to a digital library, and may hold misconceptions of the technological support for preserving their privacy. We present results from 18 autoethnographic investigations and 19 observations / interviews into privacy issues that arise when people make their personal photo collections available online. The Adams' privacy model is used to discuss the findings according to information receiver, information sensitivity, and information usage. Further issues of trust and ad hoc poorly supported protection strategies are presented. Ultimately while photographic data is potentially highly sensitive, the privacy risks are often hidden and the protection mechanisms are limited

Tests of species‐specific models reveal the importance of drought in postglacial range shifts of a Mediterranean‐climate tree: insights from integrative distributional, demographic and coalescent modelling and ABC model selection

Past climate change has caused shifts in species distributions and undoubtedly impacted patterns of genetic variation, but the biological processes mediating responses to climate change, and their genetic signatures, are often poorly understood. We test six species‐specific biologically informed hypotheses about such processes in canyon live oak (Quercus chrysolepis) from the California Floristic Province. These hypotheses encompass the potential roles of climatic niche, niche multidimensionality, physiological trade‐offs in functional traits, and local‐scale factors (microsites and local adaptation within ecoregions) in structuring genetic variation. Specifically, we use ecological niche models (ENMs) to construct temporally dynamic landscapes where the processes invoked by each hypothesis are reflected by differences in local habitat suitabilities. These landscapes are used to simulate expected patterns of genetic variation under each model and evaluate the fit of empirical data from 13 microsatellite loci genotyped in 226 individuals from across the species range. Using approximate Bayesian computation (ABC), we obtain very strong support for two statistically indistinguishable models: a trade‐off model in which growth rate and drought tolerance drive habitat suitability and genetic structure, and a model based on the climatic niche estimated from a generic ENM, in which the variables found to make the most important contribution to the ENM have strong conceptual links to drought stress. The two most probable models for explaining the patterns of genetic variation thus share a common component, highlighting the potential importance of seasonal drought in driving historical range shifts in a temperate tree from a Mediterranean climate where summer drought is common.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134178/1/mec13804-sup-0001-Supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134178/2/mec13804.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134178/3/mec13804_am.pd

Fluorescence Lifetime Imaging Microscopy (FLIM) data analysis with TIMP

Fluorescence Lifetime Imaging Microscopy (FLIM) allows fluorescence lifetime images of biological objects to be collected at 250 nm spatial resolution and at (sub-)nanosecond temporal resolution. Often ncomp kinetic processes underlie the observed fluorescence at all locations, but the intensity of the fluorescence associated with each process varies per-location, i.e., per-pixel imaged. Then the statistical challenge is global analysis of the image: use of the fluorescence decay in time at all locations to estimate the ncomp lifetimes associated with the kinetic processes, as well as the amplitude of each kinetic process at each location. Given that typical FLIM images represent on the order of 102 timepoints and 103 locations, meeting this challenge is computationally intensive. Here the utility of the TIMP package for R to solve parameter estimation problems arising in FLIM image analysis is demonstrated. Case studies on simulated and real data evidence the applicability of the partitioned variable projection algorithm implemented in TIMP to the problem domain, and showcase options included in the package for the visual validation of models for FLIM data

Tensor-Based Preprocessing of Combined EEG/MEG Data

5 pagesInternational audienceDue to their good temporal resolution, electroencephalography (EEG) and magnetoencephalography (MEG) are two often used techniques for brain source analysis. In order to improve the results of source localization algorithms applied to EEG or MEG data, tensor-based preprocessing techniques can be used to separate the sources and reduce the noise. These methods are based on the Canonical Polyadic (CP) decomposition (also called Parafac) of space-time-frequency (STF) or space-time-wave-vector (STWV) data. In this paper, we analyze the combination of EEG and MEG data to enhance the performance of the tensor-based preprocessing. To this end, we consider the joint CP decomposition of two (or more) third order tensors with one or two identical loading matrices. We present the necessary modifications for several classical CP decomposition algorithms and examine the gain on performance in the EEG/MEG context by means of simulations

An assay to image neuronal microtubule dynamics in mice

Microtubule dynamics in neurons play critical roles in physiology, injury and disease and determine microtubule orientation, the cell biological correlate of neurite polarization. Several microtubule binding proteins, including end-binding protein 3 (EB3), specifically bind to the growing plus tip of microtubules. In the past, fluorescently tagged end-binding proteins have revealed microtubule dynamics in vitro and in non-mammalian model organisms. Here, we devise an imaging assay based on transgenic mice expressing yellow fluorescent protein-tagged EB3 to study microtubules in intact mammalian neurites. Our approach allows measurement of microtubule dynamics in vivo and ex vivo in peripheral nervous system and central nervous system neurites under physiological conditions and after exposure to microtubule-modifying drugs. We find an increase in dynamic microtubules after injury and in neurodegenerative disease states, before axons show morphological indications of degeneration or regrowth. Thus increased microtubule dynamics might serve as a general indicator of neurite remodelling in health and disease

Variability in Tuberculosis Granuloma T Cell Responses Exists, but a Balance of Pro- and Anti-inflammatory Cytokines Is Associated with Sterilization

Lung granulomas are the pathologic hallmark of tuberculosis (TB). T cells are a major cellular component of TB lung granulomas and are known to play an important role in containment of Mycobacterium tuberculosis (Mtb) infection. We used cynomolgus macaques, a non-human primate model that recapitulates human TB with clinically active disease, latent infection or early infection, to understand functional characteristics and dynamics of T cells in individual granulomas. We sought to correlate T cell cytokine response and bacterial burden of each granuloma, as well as granuloma and systemic responses in individual animals. Our results support that each granuloma within an individual host is independent with respect to total cell numbers, proportion of T cells, pattern of cytokine response, and bacterial burden. The spectrum of these components overlaps greatly amongst animals with different clinical status, indicating that a diversity of granulomas exists within an individual host. On average only about 8% of T cells from granulomas respond with cytokine production after stimulation with Mtb specific antigens, and few “multi-functional” T cells were observed. However, granulomas were found to be “multi-functional” with respect to the combinations of functional T cells that were identified among lesions from individual animals. Although the responses generally overlapped, sterile granulomas had modestly higher frequencies of T cells making IL-17, TNF and any of T-1 (IFN-γ, IL-2, or TNF) and/or T-17 (IL-17) cytokines than non-sterile granulomas. An inverse correlation was observed between bacterial burden with TNF and T-1/T-17 responses in individual granulomas, and a combinatorial analysis of pair-wise cytokine responses indicated that granulomas with T cells producing both pro- and anti-inflammatory cytokines (e.g. IL-10 and IL-17) were associated with clearance of Mtb. Preliminary evaluation suggests that systemic responses in the blood do not accurately reflect local T cell responses within granulomas