We present an algorithm for automatic segmentation of the human pelvic bones from CT datasets that is based on the application of a statistical shape model. The proposed method is divided into three steps: 1) The averaged shape of the pelvis model is initially placed within the CT data using the Generalized Hough Transform, 2) the statistical shape model is then adapted to the image data by a transformation and variation of its shape modes, and 3) a final free-form deformation step based on optimal graph searching is applied to overcome the restrictive character of the statistical shape representation. We thoroughly evaluated the method on 50 manually segmented CT datasets by performing a leave-one-out study. The Generalized Hough Transform proved to be a reliable method for an automatic initial placement of the shape model within the CT data. Compared to the manual gold standard segmentations, our automatic segmentation approach produced an average surface distance of 1.2 ± 0.3mm after the adaptation of the statistical shape model, which could be reduced to 0.7±0.3mm using a final free-form deformation step. Together with an average segmentation time of less than 5 minutes, the results of our study indicate that our method meets the requirements of clinical routine.

Neurons and glia are functionally organized into circuits and higher-order structures via synaptic connectivity, well-orchestrated molecular signaling, and activity-dependent refinement. Such organization allows the precise information processing required for complex behaviors. Disruption of nervous systems by genetic deficiency or events such as trauma or environmental exposure may produce a diseased state in which certain aspects of inter-neuron signaling are impaired. Optical imaging techniques allow the direct visualization of individual neurons in a circuit environment. Imaging probes specific for given biomolecules may help elucidate their contribution to proper circuit function. Genetically encoded sensors can visualize trafficking of particular molecules in defined neuronal populations, non-invasively in intact brain or reduced preparations. Sensor analysis in healthy and diseased brains may reveal important differences and shed light on the development and progression of nervous system disorders. We review the field of genetically encoded sensors for molecules and cellular events, and their potential applicability to the study of nervous system disease.

Pfam is a comprehensive collection of protein domains and families, represented as multiple sequence alignments and as profile hidden Markov models. The current release of Pfam (22.0) contains 9318 protein families. Pfam is now based not only on the UniProtKB sequence database, but also on NCBI GenPept and on sequences from selected metagenomics projects. Pfam is available on the web from the consortium members using a new, consistent and improved website design in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/), as well as from mirror sites in France (http://pfam.jouy.inra.fr/) and South Korea (http://pfam.ccbb.re.kr/).

The conditional expression of hairpin constructs in Drosophila melanogaster has emerged in recent years as a method of choice in functional genomic studies. To date, upstream activating site-driven RNA interference constructs have been inserted into the genome randomly using P-element-mediated transformation, which can result in false negatives due to variable expression. To avoid this problem, we have developed a transgenic RNA interference vector based on the phiC31 site-specific integration method.

Long-term potentiation (LTP) of synaptic transmission underlies aspects of learning and memory. LTP is input-specific at the level of individual synapses, but neural network models predict interactions between plasticity at nearby synapses. Here we show in mouse hippocampal pyramidal cells that LTP at individual synapses reduces the threshold for potentiation at neighbouring synapses. After input-specific LTP induction by two-photon glutamate uncaging or by synaptic stimulation, subthreshold stimuli, which by themselves were too weak to trigger LTP, caused robust LTP and spine enlargement at neighbouring spines. Furthermore, LTP induction broadened the presynaptic-postsynaptic spike interval for spike-timing-dependent LTP within a dendritic neighbourhood. The reduction in the threshold for LTP induction lasted approximately 10 min and spread over approximately 10 microm of dendrite. These local interactions between neighbouring synapses support clustered plasticity models of memory storage and could allow for the binding of behaviourally linked information on the same dendritic branch.

Accurate determination of the relative positions of proteins within localized regions of the cell is essential for understanding their biological function. Although fluorescent fusion proteins are targeted with molecular precision, the position of these genetically expressed reporters is usually known only to the resolution of conventional optics ( approximately 200 nm). Here, we report the use of two-color photoactivated localization microscopy (PALM) to determine the ultrastructural relationship between different proteins fused to spectrally distinct photoactivatable fluorescent proteins (PA-FPs). The nonperturbative incorporation of these endogenous tags facilitates an imaging resolution in whole, fixed cells of approximately 20-30 nm at acquisition times of 5-30 min. We apply the technique to image different pairs of proteins assembled in adhesion complexes, the central attachment points between the cytoskeleton and the substrate in migrating cells. For several pairs, we find that proteins that seem colocalized when viewed by conventional optics are resolved as distinct interlocking nano-aggregates when imaged via PALM. The simplicity, minimal invasiveness, resolution, and speed of the technique all suggest its potential to directly visualize molecular interactions within cellular structures at the nanometer scale.

Commentary: Identifies the photoactivatable fluorescent proteins (PA-FPs) Dronpa and PS-CFP2 as green partners to orange-red PA-FPs such as Kaede and Eos for dual color PALM imaging. Very low crosstalk is demonstrated between the two color channels. Furthermore, since the probes are genetically expressed, they are closely bound to their target proteins and exhibit zero non-specific background. All these properties are essential to unambiguously identify regions of co-localization or separate compartmentalization at the nanoscale, as demonstrated in the examples here.

Recent advances in single-neuron biophysics have enhanced our understanding of information processing on the cellular level, but how the detailed properties of individual neurons give rise to large-scale behavior remains unclear. Here, we present a model of the hippocampal network based on observed biophysical properties of hippocampal and entorhinal cortical neurons. We assembled our model to simulate spatial alternation, a task that requires memory of the previous path through the environment for correct selection of the current path to a reward site. The convergence of inputs from entorhinal cortex and hippocampal region CA3 onto CA1 pyramidal cells make them potentially important for integrating information about place and temporal context on the network level. Our model shows how place and temporal context information might be combined in CA1 pyramidal neurons to give rise to splitter cells, which fire selectively based on a combination of place and temporal context. The model leads to a number of experimentally testable predictions that may lead to a better understanding of the biophysical basis of information processing in the hippocampus.

Bacterial small non-coding RNAs (sRNAs) are being recognized as novel widespread regulators of gene expression in response to environmental signals. Here, we present the first search for sRNA-encoding genes in the nitrogen-fixing endosymbiont Sinorhizobium meliloti, performed by a genome-wide computational analysis of its intergenic regions. Comparative sequence data from eight related alpha-proteobacteria were obtained, and the interspecies pairwise alignments were scored with the programs eQRNA and RNAz as complementary predictive tools to identify conserved and stable secondary structures corresponding to putative non-coding RNAs. Northern experiments confirmed that eight of the predicted loci, selected among the original 32 candidates as most probable sRNA genes, expressed small transcripts. This result supports the combined use of eQRNA and RNAz as a robust strategy to identify novel sRNAs in bacteria. Furthermore, seven of the transcripts accumulated differentially in free-living and symbiotic conditions. Experimental mapping of the 5’-ends of the detected transcripts revealed that their encoding genes are organized in autonomous transcription units with recognizable promoter and, in most cases, termination signatures. These findings suggest novel regulatory functions for sRNAs related to the interactions of alpha-proteobacteria with their eukaryotic hosts.

We present a model for olfactory coding based on spatial representation of glomerular responses. In this model distinct odorants activate specific subsets of glomeruli, dependent on the odorant’s chemical identity and concentration. The glomerular response specificities are understood statistically, based on experimentally measured distributions of activation thresholds. A simple version of the model, in which glomerular responses are binary (the all-or-nothing model), allows us to account quantitatively for the following results of human/rodent olfactory psychophysics: 1) just noticeable differences in the perceived concentration of a single odor (Weber ratios) are as low as dC/C approximately 0.04; 2) the number of simultaneously perceived odors can be as high as 12; and 3) extensive lesions of the olfactory bulb do not lead to significant changes in detection or discrimination thresholds. We conclude that a combinatorial code based on a binary glomerular response is sufficient to account for several important features of the discrimination capacity of the mammalian olfactory system.

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.