We built a digital nuclear atlas of the newly hatched, first larval stage (L1) of the wild-type hermaphrodite of Caenorhabditis elegans at single-cell resolution from confocal image stacks of 15 individual worms. The atlas quantifies the stereotypy of nuclear locations and provides other statistics on the spatial patterns of the 357 nuclei that could be faithfully segmented and annotated out of the 558 present at this developmental stage. We then developed an automated approach to assign cell names to each nucleus in a three-dimensional image of an L1 worm. We achieved 86% accuracy in identifying the 357 nuclei automatically. This computational method will allow high-throughput single-cell analyses of the post-embryonic worm, such as gene expression analysis, or ablation or stimulation of cells under computer control in a high-throughput functional screen.

Realistic computational models of single neurons require component ion channels that reproduce experimental findings. Here, a topology-mutating genetic algorithm that searches for the best state diagram and transition-rate parameters to model macroscopic ion-channel behavior is described. Important features of the algorithm include a topology-altering strategy, automatic satisfaction of equilibrium constraints (microscopic reversibility), and multiple-protocol fitting using sequential goal programming rather than explicit weighting. Application of this genetic algorithm to design a sodium-channel model exhibiting both fast and prolonged inactivation yields a six-state model that produces realistic activity-dependent attenuation of action-potential backpropagation in current-clamp simulations of a CA1 pyramidal neuron.

In this paper we propose a framework for fully automatic, robust and accurate segmentation of the human pelvis and proximal femur in CT data. We propose a composite statistical shape model of femur and pelvis with a flexible hip joint, for which we extend the common definition of statistical shape models as well as the common strategy for their adaptation. We do not analyze the joint flexibility statistically, but model it explicitly by rotational parameters describing the bent in a ball-and-socket joint. A leave-one-out evaluation on 50 CT volumes shows that image driven adaptation of our composite shape model robustly produces accurate segmentations of both proximal femur and pelvis. As a second contribution, we evaluate a fine grain multi-object segmentation method based on graph optimization. It relies on accurate initializations of femur and pelvis, which our composite shape model can generate. Simultaneous optimization of both femur and pelvis yields more accurate results than separate optimizations of each structure. Shape model adaptation and graph based optimization are embedded in a fully automatic framework.

Synaptic plasticity in adult neural circuits may involve the strengthening or weakening of existing synapses as well as structural plasticity, including synapse formation and elimination. Indeed, long-term in vivo imaging studies are beginning to reveal the structural dynamics of neocortical neurons in the normal and injured adult brain. Although the overall cell-specific morphology of axons and dendrites, as well as of a subpopulation of small synaptic structures, are remarkably stable, there is increasing evidence that experience-dependent plasticity of specific circuits in the somatosensory and visual cortex involves cell type-specific structural plasticity: some boutons and dendritic spines appear and disappear, accompanied by synapse formation and elimination, respectively. This Review focuses on recent evidence for such structural forms of synaptic plasticity in the mammalian cortex and outlines open questions.

We have approached the problem of reverse-engineering the flight control mechanism of the fruit fly by studying the dynamics of the responses to a visual stimulus during takeoff. Building upon a prior framework [G. Card and M. Dickinson, J. Exp. Biol., vol. 211, pp. 341-353, 2008], we seek to understand the strategies employed by the animal to stabilize attitude and orientation during these evasive, highly dynamical maneuvers. As a first step, we consider the dynamics from a gray-box perspective: examining lumped forces produced by the insect’s legs and wings. The reconstruction of the flight initiation dynamics, based on the unconstrained motion formulation for a rigid body, allows us to assess the fly’s responses to a variety of initial conditions induced by its jump. Such assessment permits refinement by using a visual tracking algorithm to extract the kinematic envelope of the wings [E. I. Fontaine, F. Zabala, M. Dickinson, and J. Burdick, "Wing and body motion during flight initiation in Drosophila revealed by automated visual tracking," submitted for publication] in order to estimate lift and drag forces [F. Zabala, M. Dickinson, and R. Murray, "Control and stability of insect flight during highly dynamical maneuvers," submitted for publication], and recording actual leg-joint kinematics and using them to estimate jump forces [F. Zabala, "A bio-inspired model for directionality control of flight initiation," to be published.]. In this paper, we present the details of our approach in a comprehensive manner, including the salient results.

Considerable progress has been made over the past couple of decades concerning the molecular bases of neurobehavioral function and dysfunction. The field of neurobehavioral genetics is becoming mature. Genetic factors contributing to neurologic diseases such as Alzheimer's disease have been found and evidence for genetic factors contributing to other diseases such as schizophrenia and autism are likely. This genetic approach can also benefit the field of behavioral neurotoxicology. It is clear that there is substantial heterogeneity of response with behavioral impairments resulting from neurotoxicants. Many factors contribute to differential sensitivity, but it is likely that genetic variability plays a prominent role. Important discoveries concerning genetics and behavioral neurotoxicity are being made on a broad front from work with invertebrate and piscine mutant models to classic mouse knockout models and human epidemiologic studies of polymorphisms. Discovering genetic factors of susceptibility to neurobehavioral toxicity not only helps identify those at special risk, it also advances our understanding of the mechanisms by which toxicants impair neurobehavioral function in the larger population. This symposium organized by Edward Levin and Annette Kirshner, brought together researchers from the laboratories of Michael Aschner, Douglas Ruden, Ulrike Heberlein, Edward Levin and Kathleen Welsh-Bohmer conducting studies with Caenorhabditis elegans, Drosophila, fish, rodents and humans studies to determine the role of genetic factors in susceptibility to behavioral impairment from neurotoxic exposure.

Although the vinegar fly, Drosophila melanogaster, has been a biological model organism for over a century, its emergence as a model system for the study of neurophysiology is comparatively recent. The primary reason for this is that the vinegar fly and its neurons are tiny; up until 5 years ago, it was prohibitively difficult to record intracellularly from individual neurons in the intact Drosophila brain (Wilson et al., 2004). Today, fly electrophysiologists can genetically label neurons with GFP and reliably record from many (but not all) neurons in the fruit fly brain. Using genetic tools to drive expression of fluorescent calcium indicators, light-sensitive ion channels, or cell activity suppressors, we are beginning to understand how the external environment is represented with electrical potentials in Drosophila neurons (for review, see Olsen and Wilson, 2008).

Presynaptic, electron-dense, cytoplasmic protrusions such as the T-bar (Drosophila) or ribbon (vertebrates) are believed to facilitate vesicle movement to the active zone (AZ) of synapses throughout the nervous system. The molecular composition of these structures including the T-bar and ribbon are largely unknown, as are the mechanisms that specify their synapse-specific assembly and distribution. In a large-scale, forward genetic screen, we have identified a mutation termed air traffic controller (atc) that causes T-bar-like protein aggregates to form abnormally in motoneuron axons. This mutation disrupts a gene that encodes for a serine-arginine protein kinase (SRPK79D). This mutant phenotype is specific to SRPK79D and is not secondary to impaired kinesin-dependent axonal transport. The srpk79D gene is neuronally expressed, and transgenic rescue experiments are consistent with SRPK79D kinase activity being necessary in neurons. The SRPK79D protein colocalizes with the T-bar-associated protein Bruchpilot (Brp) in both the axon and synapse. We propose that SRPK79D is a novel T-bar-associated protein kinase that represses T-bar assembly in peripheral axons, and that SRPK79D-dependent repression must be relieved to facilitate site-specific AZ assembly. Consistent with this model, overexpression of SRPK79D disrupts AZ-specific Brp organization and significantly impairs presynaptic neurotransmitter release. These data identify a novel AZ-associated protein kinase and reveal a new mechanism of negative regulation involved in AZ assembly. This mechanism could contribute to the speed and specificity with which AZs are assembled throughout the nervous system.

Thioredoxin-interacting protein (Txnip), originally characterized as an inhibitor of thioredoxin, is now known to be a critical regulator of glucose metabolism in vivo. Txnip is a member of the alpha-arrestin protein family; the alpha-arrestins are related to the classical beta-arrestins and visual arrestins. Txnip is the only alpha-arrestin known to bind thioredoxin, and it is not known whether the metabolic effects of Txnip are related to its ability to bind thioredoxin or related to conserved alpha-arrestin function. Here we show that wild type Txnip and Txnip C247S, a Txnip mutant that does not bind thioredoxin in vitro, both inhibit glucose uptake in mature adipocytes and in primary skin fibroblasts. Furthermore, we show that Txnip C247S does not bind thioredoxin in cells, using thiol alkylation to trap the Txnip-thioredoxin complex. Because Txnip function was independent of thioredoxin binding, we tested whether inhibition of glucose uptake was conserved in the related alpha-arrestins Arrdc4 and Arrdc3. Both Txnip and Arrdc4 inhibited glucose uptake and lactate output, while Arrdc3 had no effect. Structure-function analysis indicated that Txnip and Arrdc4 inhibit glucose uptake independent of the C-terminal WW-domain binding motifs, recently identified as important in yeast alpha-arrestins. Instead, regulation of glucose uptake was intrinsic to the arrestin domains themselves. These data demonstrate that Txnip regulates cellular metabolism independent of its binding to thioredoxin and reveal the arrestin domains as crucial structural elements in metabolic functions of alpha-arrestin proteins.