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3924 Publications
Showing 3321-3330 of 3924 resultsArrays of actin filaments (F-actin) near the apical surface of epithelial cells (medioapical arrays) contribute to apical constriction and morphogenesis throughout phylogeny. Here, superresolution approaches (grazing incidence structured illumination, GI-SIM, and lattice light sheet, LLSM) microscopy resolve individual, fluorescently labeled F-actin and bipolar myosin filaments that drive amnioserosa cell shape changes during dorsal closure in . In expanded cells, F-actin and myosin form loose, apically domed meshworks at the plasma membrane. The arrays condense as cells contract, drawing the domes into the plane of the junctional belts. As condensation continues, individual filaments are no longer uniformly apparent. As cells expand, arrays of actomyosin are again resolved-some F-actin turnover likely occurs, but a large fraction of existing filaments rearrange. In morphologically isotropic cells, actin filaments are randomly oriented and during contraction are drawn together but remain essentially randomly oriented. In anisotropic cells, largely parallel actin filaments are drawn closer to one another. Our images offer unparalleled resolution of F-actin in embryonic tissue, show that medioapical arrays are tightly apposed to the plasma membrane and are continuous with meshworks of lamellar F-actin. Medioapical arrays thereby constitute modified cell cortex. In concert with other tagged array components, superresolution imaging of live specimens will offer new understanding of cortical architecture and function.
We address the problem of labeling individual datapoints given some knowledge about (small) subsets or groups of them. The knowledge we have for a group is the likelihood value for each group member to satisfy a certain model. This problem is equivalent to hypergraph labeling problem where each datapoint corresponds to a node and the each subset correspond to a hyperedge with likelihood value as its weight. We propose a novel method to model the label dependence using an Undirected Graphical Model and reduce the problem of hypergraph labeling into an inference problem. This paper describes the structure and necessary components of such model and proposes useful cost functions. We discuss the behavior of proposed algorithm with different forms of the cost functions, identify suitable algorithms for inference and analyze required properties when it is theoretically guaranteed to have exact solution. Examples of several real world problems are shown as applications of the proposed method.
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method for low-level image processing. As an example of our approach, convolutional networks are trained using gradient learning to solve the problem of restoring noisy or degraded images. For our training data, we have used electron microscopic images of neural circuitry with ground truth restorations provided by human experts. On this dataset, Markov random field (MRF), conditional random field (CRF), and anisotropic diffusion algorithms perform about the same as simple thresholding, but superior performance is obtained with a convolutional network containing over 34,000 adjustable parameters. When restored by this convolutional network, the images are clean enough to be used for segmentation, whereas the other approaches fail in this respect. We do not believe that convolutional networks are fundamentally superior to MRFs as a representation for image processing algorithms. On the contrary, the two approaches are closely related. But in practice, it is possible to train complex convolutional networks, while even simple MRF models are hindered by problems with Bayesian learning and inference procedures. Our results suggest that high model complexity is the single most important factor for good performance, and this is possible with convolutional networks.
Sum-frequency vibrational spectroscopy was used to obtain the first surface vibrational spectra of shear-deposited highly oriented poly(tetrafluoroethylene) (PTFE, Teflon) thin films. The surface PTFE chains appeared to lie along the shearing direction. Vibrational modes observed at 1142 and 1204 cm-1 were found to have the E1 symmetry, in support of some earlier analysis in the long-lasting controversy over the assignment of these modes.
BACKGROUND: Previous studies suggest that mechanical feedback could coordinate morphogenetic events in embryos. Furthermore, embryonic tissues have complex structure and composition and undergo large deformations during morphogenesis. Hence we expect highly non-linear and loading-rate dependent tissue mechanical properties in embryos. METHODOLOGY/PRINCIPAL FINDINGS: We used micro-aspiration to test whether a simple linear viscoelastic model was sufficient to describe the mechanical behavior of gastrula stage Xenopus laevis embryonic tissue in vivo. We tested whether these embryonic tissues change their mechanical properties in response to mechanical stimuli but found no evidence of changes in the viscoelastic properties of the tissue in response to stress or stress application rate. We used this model to test hypotheses about the pattern of force generation during electrically induced tissue contractions. The dependence of contractions on suction pressure was most consistent with apical tension, and was inconsistent with isotropic contraction. Finally, stiffer clutches generated stronger contractions, suggesting that force generation and stiffness may be coupled in the embryo. CONCLUSIONS/SIGNIFICANCE: The mechanical behavior of a complex, active embryonic tissue can be surprisingly well described by a simple linear viscoelastic model with power law creep compliance, even at high deformations. We found no evidence of mechanical feedback in this system. Together these results show that very simple mechanical models can be useful in describing embryo mechanics.
The anatomy of the mammalian visual system, from the retina to the neocortex, is organized hierarchically. However, direct observation of cellular-level functional interactions across this hierarchy is lacking due to the challenge of simultaneously recording activity across numerous regions. Here we describe a large, open dataset-part of the Allen Brain Observatory-that surveys spiking from tens of thousands of units in six cortical and two thalamic regions in the brains of mice responding to a battery of visual stimuli. Using cross-correlation analysis, we reveal that the organization of inter-area functional connectivity during visual stimulation mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas. We find that four classical hierarchical measures-response latency, receptive-field size, phase-locking to drifting gratings and response decay timescale-are all correlated with the hierarchy. Moreover, recordings obtained during a visual task reveal that the correlation between neural activity and behavioural choice also increases along the hierarchy. Our study provides a foundation for understanding coding and signal propagation across hierarchically organized cortical and thalamic visual areas.
Taste is responsible for evaluating the nutritious content of food, guiding essential appetitive behaviours, preventing the ingestion of toxic substances, and helping to ensure the maintenance of a healthy diet. Sweet and bitter are two of the most salient sensory percepts for humans and other animals; sweet taste allows the identification of energy-rich nutrients whereas bitter warns against the intake of potentially noxious chemicals. In mammals, information from taste receptor cells in the tongue is transmitted through multiple neural stations to the primary gustatory cortex in the brain. Recent imaging studies have shown that sweet and bitter are represented in the primary gustatory cortex by neurons organized in a spatial map, with each taste quality encoded by distinct cortical fields. Here we demonstrate that by manipulating the brain fields representing sweet and bitter taste we directly control an animal's internal representation, sensory perception, and behavioural actions. These results substantiate the segregation of taste qualities in the cortex, expose the innate nature of appetitive and aversive taste responses, and illustrate the ability of gustatory cortex to recapitulate complex behaviours in the absence of sensory input.
Transcriptional mechanisms that govern cellular differentiation typically include sequence-specific DNA-binding proteins and chromatin-modifying activities. These regulatory factors are assumed necessary and sufficient to drive both divergent programs of proliferation and terminal differentiation. By contrast, potential contributions of the basal transcriptional apparatus to orchestrate cell-specific gene expression have been poorly explored. In order to probe alternative mechanisms that control differentiation, we have assessed the fate of the core promoter recognition complex, TFIID, during skeletal myogenesis. Here we report that differentiation of myoblast to myotubes involves the disruption of the canonical holo-TFIID and replacement by a novel TRF3/TAF3 (TBP-related factor 3/TATA-binding protein-associated factor 3) complex. This required switching of core promoter complexes provides organisms a simple yet effective means to selectively turn on one transcriptional program while silencing many others. Although this drastic but parsimonious transcriptional switch had previously escaped our attention, it may represent a more general mechanism for regulating cell type-specific terminal differentiation.
Slit is secreted by cells at the midline of the central nervous system, where it binds to Roundabout (Robo) receptors and functions as a potent repellent. We found that migrating mesodermal cells in vivo respond to Slit as both an attractant and a repellent and that Robo receptors are required for both functions. Mesoderm cells expressing Robo receptors initially migrate away from Slit at the midline. A few hours after migration, these same cells change their behavior and require Robo to extend toward Slit-expressing muscle attachment sites. Thus, Slit functions as a chemoattractant to provide specificity for muscle patterning.