Automatic segmentation of nuclei in 3D microscopy images is essential for many biological studies including high throughput analysis of gene expression level, morphology, and phenotypes in single cell level. The complexity and variability of the microscopy images present many difficulties to the traditional image segmentation methods. In this paper, we present a new method based on 3D watershed algorithm to segment such images. By using both the intensity information of the image and the geometry information of the appropriately detected foreground mask, our method is robust to intensity fluctuation within nuclei and at the same time sensitive to the intensity and geometrical cues between nuclei. Besides, the method can automatically correct potential segmentation errors by using several post-processing steps. We tested this algorithm on the 3D confocal images of C.elegans, an organism that has been widely used in biological studies. Our results show that the algorithm can segment nuclei in high accuracy despite the non-uniform background, tightly clustered nuclei with different sizes and shapes, fluctuated intensities, and hollow-shaped staining patterns in the images.

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.

In this paper, we present an automatic method for estimating the trajectories of Escherichia coli bacteria from in vivo phase-contrast microscopy videos. To address the low-contrast boundaries in cellular images, an adaptive kernel-based technique is applied to detect cells in sequence of frames. Then a novel matching gain measure is introduced to cope with the challenges such as dramatic changes of cells’ appearance and serious overlapping and occlusion. For multiple cell tracking, an optimal matching strategy is proposed to improve the handling of cell collision and broken trajectories. The results of successful tracking of Escherichia coli from various phase-contrast sequences are reported and compared with manually-determined trajectories, as well as those obtained from existing tracking methods. The stability of the algorithm with different parameter values is also analyzed and discussed.

In this paper, we present an automatic method for estimating the trajectories of Escherichia coli bacteria from in vivo phase-contrast microscopy. To address the low-contrast boundaries in cellular images, an adaptive kernel-based technique is applied to detect cells in each frame. In addition to intensity features, region homogeneity measure and class uncertainty are also applied in this detection technique. To track cells with complex motion, a novel matching gain measure is introduced to cope with the challenges, particularly the presence of low-contrast boundary, the variations of appearance, and the frequent overlapping and occlusion. For multicell tracking over time, an optimal matching strategy is introduced to improve the handling of cell collision and broken trajectories. The results of successful tracking of Escherichia coli from various phase-contrast sequences are reported and compared with manually determined trajectories, as well as those obtained from existing tracking schemes. The stability of the algorithm with different parameter values is also analyzed and discussed.

We describe an approach for automation of the process of reconstruction of neural tissue from serial section transmission electron micrographs. Such reconstructions require 3D segmentation of individual neuronal processes (axons and dendrites) performed in densely packed neuropil. We first detect neuronal cell profiles in each image in a stack of serial micrographs with multi-scale ridge detector. Short breaks in detected boundaries are interpolated using anisotropic contour completion formulated in fuzzy-logic framework. Detected profiles from adjacent sections are linked together based on cues such as shape similarity and image texture. Thus obtained 3D segmentation is validated by human operators in computer-guided proofreading process. Our approach makes possible reconstructions of neural tissue at final rate of about 5 microm3/manh, as determined primarily by the speed of proofreading. To date we have applied this approach to reconstruct few blocks of neural tissue from different regions of rat brain totaling over 1000microm3, and used these to evaluate reconstruction speed, quality, error rates, and presence of ambiguous locations in neuropil ssTEM imaging data.

NDP52 is an autophagy receptor involved in the recognition and degradation of invading pathogens and damaged organelles. Although NDP52 was first identified in the nucleus and is expressed throughout the cell, to date, there is no clear nuclear functions for NDP52. Here, we use a multidisciplinary approach to characterise the biochemical properties and nuclear roles of NDP52. We find that NDP52 clusters with RNA Polymerase II (RNAPII) at transcription initiation sites and that its overexpression promotes the formation of additional transcriptional clusters. We also show that depletion of NDP52 impacts overall gene expression levels in two model mammalian cells, and that transcription inhibition affects the spatial organisation and molecular dynamics of NDP52 in the nucleus. This directly links NDP52 to a role in RNAPII-dependent transcription. Furthermore, we also show that NDP52 binds specifically and with high affinity to double-stranded DNA (dsDNA) and that this interaction leads to changes in DNA structure in vitro. This, together with our proteomics data indicating enrichment for interactions with nucleosome remodelling proteins and DNA structure regulators, suggests a possible function for NDP52 in chromatin regulation. Overall, here we uncover nuclear roles for NDP52 in gene expression and DNA structure regulation.

Axial collision induced dissociation (CID) and high-pressure resonance CID were implemented and compared with normal low-pressure resonance CID in a miniature ion trap mass spectrometer to obtain more complete fragmentation spectra. Axial CID was realized simply by applying a potential to the discontinuous atmospheric pressure interface (DAPI) capillary without performing parent ion isolation before dissociation. High-pressure resonance CID employed a double-introduction pulse scan function, by means of which precursor ions isolated at low-pressure (<10(-3) torr) were dissociated at high-pressure (0.1 torr-1 torr) with higher excitation energy, so that tandem MS of isolated precursor ions was achieved and extensive fragmentation was obtained. A simple peptide (Leu-enkephalin) and dye molecule (rhodamine B) ionized by ESI were used to investigate both methods and compare them with normal low-pressure resonance CID.

Axon pruning is widely used for the refinement of neural circuits in both vertebrates and invertebrates, and may also contribute to the pathogenesis of neurodegenerative diseases. However, little is known about the cellular and molecular mechanisms of axon pruning. We use the stereotyped pruning of gamma neurons of the Drosophila mushroom bodies (MB) during metamorphosis to investigate these mechanisms. Detailed time course analyses indicate that MB axon pruning is mediated by local degeneration rather than retraction and that the disruption of the microtubule cytoskeleton precedes axon pruning. In addition, multiple lines of genetic evidence demonstrate an intrinsic role of the ubiquitin-proteasome system in axon pruning; for example, loss-of-function mutations of the ubiquitin activating enzyme (E1) or proteasome subunits in MB neurons block axon pruning. Our findings suggest that some forms of axon pruning during development may share similarities with degeneration of axons in response to injury.

Although the endoplasmic reticulum (ER) extends throughout axons and axonal ER dysfunction is implicated in numerous neurological diseases, its role at nerve terminals is poorly understood. We developed novel genetically encoded ER-targeted low-affinity Ca(2+) indicators optimized for examining axonal ER Ca(2+). Our experiments revealed that presynaptic function is tightly controlled by ER Ca(2+) content. We found that neuronal activity drives net Ca(2+) uptake into presynaptic ER although this activity does not contribute significantly to shaping cytosolic Ca(2+) except during prolonged repetitive firing. In contrast, we found that axonal ER acts as an actuator of plasma membrane (PM) function: [Ca(2+)]ER controls STIM1 activation in presynaptic terminals, which results in the local modulation of presynaptic function, impacting activity-driven Ca(2+) entry and release probability. These experiments reveal a critical role of presynaptic ER in the control of neurotransmitter release and will help frame future investigations into the molecular basis of ER-driven neuronal disease states.

In CA1 pyramidal neurons, correlated inputs trigger dendritic plateau potentials that drive neuronal plasticity and firing rate modulation. Given the strong electrotonic coupling between soma and axon, the >25 mV depolarization associated with the plateau could propagate through the axon to influence action potential initiation, propagation, and neurotransmitter release. We examined this issue in brain slices, awake mice, and a computational model. Despite profoundly inactivating somatic and proximal axon Na(+) channels, plateaus evoked action potentials that recovered to full amplitude in the distal axon (>150 μm) and triggered neurotransmitter release similar to regular spiking. This effect was due to strong attenuation of plateau depolarizations by axonal K(+) channels, allowing full axon repolarization and Na(+) channel deinactivation. High-pass filtering of dendritic plateaus by axonal K(+) channels should thus enable accurate transmission of gain-modulated firing rates, allowing neuronal firing to be efficiently read out by downstream regions as a simple rate code.