Fast subplasma membrane Ca2+ transients control exo-endocytosis of synaptic-like microvesicles in astrocytes

Astrocytes are the most abundant glial cell type in the brain. Although not apposite for long-range rapid electrical communication, astrocytes share with neurons the capacity of chemical signaling via Ca(2+)-dependent transmitter exocytosis. Despite this recent finding, little is known about the specific properties of regulated secretion and vesicle recycling in astrocytes. Important differences may exist with the neuronal exocytosis, starting from the fact that stimulus-secretion coupling in astrocytes is voltage independent, mediated by G-protein-coupled receptors and the release of Ca(2+) from internal stores. Elucidating the spatiotemporal properties of astrocytic exo-endocytosis is, therefore, of primary importance for understanding the mode of communication of these cells and their role in brain signaling. We here take advantage of fluorescent tools recently developed for studying recycling of glutamatergic vesicles at synapses (Voglmaier et al., 2006; Balaji and Ryan, 2007); we combine epifluorescence and total internal reflection fluorescence imaging to investigate with unprecedented temporal and spatial resolution, the stimulus-secretion coupling underlying exo-endocytosis of glutamatergic synaptic-like microvesicles (SLMVs) in astrocytes. Our main findings indicate that (1) exo-endocytosis in astrocytes proceeds with a time course on the millisecond time scale (tau(exocytosis) = 0.24 +/- 0.017 s; tau(endocytosis) = 0.26 +/- 0.03 s) and (2) exocytosis is controlled by local Ca(2+) microdomains. We identified submicrometer cytosolic compartments delimited by endoplasmic reticulum tubuli reaching beneath the plasma membrane and containing SLMVs at which fast (time-to-peak, approximately 50 ms) Ca(2+) events occurred in precise spatial-temporal correlation with exocytic fusion events. Overall, the above characteristics of transmitter exocytosis from astrocytes support a role of this process in fast synaptic modulation.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.