FKBP51 modulates hippocampal size and function in post-translational regulation of Parkin.

FK506-binding protein 51 (encoded by Fkpb51, also known as Fkbp5) has been associated with stress-related mental illness. To investigate its function, we studied the morphological consequences of Fkbp51 deletion. Artificial Intelligence-assisted morphological analysis revealed that male Fkbp51 knock-out (KO) mice possess more elongated dentate gyrus (DG) but shorter hippocampal height in coronal sections when compared to WT. Primary cultured Fkbp51 KO hippocampal neurons were shown to exhibit larger dendritic outgrowth than wild-type (WT) controls and pharmacological manipulation experiments suggest that this may occur through the regulation of microtubule-associated protein. Both in vitro primary culture and in vivo labeling support a role for FKBP51 in the regulation of microtubule-associated protein expression. Furthermore, Fkbp51 KO hippocampi exhibited decreases in ßIII-tubulin, MAP2, and Tau protein levels, but a greater than 2.5-fold increase in Parkin protein. Overexpression and knock-down FKBP51 demonstrated that FKBP51 negatively regulates Parkin in a dose-dependent and ubiquitin-mediated manner. These results indicate a potential novel post-translational regulatory mechanism of Parkin by FKBP51 and the significance of their interaction on disease onset. KO has more flattened hippocampus using AI-assisted measurement Both pyramidal cell layer (PCL) of CA and granular cell layer (GCL) of DG distinguishable as two layers: deep cell layer and superficial layer. Distinct MAP2 expression between deep and superficial layer between KO and WT, Higher Parkin expression in KO brain Mechanism of FKBP51 inhibition resulting in Parkin, MAP2, Tau, and Tubulin expression differences between KO and WT mice, and resulting neurite outgrowth differences.

Part-based motor neuron recognition in the Drosophila ventral nerve cord.

We exploit the morphological stereotypy and relative simplicity of the Drosophila nervous system to model the diverse neuronal morphologies of individual motor neurons and understand underlying principles of synaptic connectivity in a motor circuit. In our analysis, we use images depicting single neurons labeled with green fluorescent protein (GFP) and serially imaged with laser scanning confocal microscopy. We model morphology with a novel formulation of Conditional Random Fields, a hierarchical latent-state CRF, to capture the highly varying compartment-based structure of the neurons (soma-axon-dendrites). In the training phase, we follow two approaches: (i) hierarchical learning, where compartment labels are given, and (ii) latent-state learning, where compartment labels are not given in the samples. We demonstrate the accuracy of our approach using wild-type motor neurons in the larval ventral nerve cord. However, our method can also be used for the identification of motor neuron mutations, as well as the automated annotation of the motor circuitry in wild type and mutant animals. Our method is directly applicable to the recognition of compartment-defined structures.

A novel analytical method using OCT to describe the corneoscleral junction.

PURPOSE: To develop and test a novel quantitative method of describing the corneoscleral junction, including metrics that reflect both the angle and the topography in this region of the ocular surface. METHODS: Forty-eight neophyte subjects were recruited (16 Asian, 16 white, and 16 Latino). Optical coherence tomography images of the nasal, temporal, superior, and inferior quadrants in both eyes were taken. Custom image analysis software was written in Matlab to allow the observer to select a point defining the center of the junction, from which 20 concentric circles were automatically drawn. The surface of the junction in the image was automatically located by edge-detection routines, and the circles intersecting this edge defined a series of points in the Cartesian plane. A linear regression was fit to these points, and a set of metrics based on the regression residuals was calculated. RESULTS: The sum of the squared orthogonalized residuals (SSRo) was the most repeatable metric and had the advantage of being unaffected by the orientation of the image. The SSRo was significantly greater in the nasal quadrant (p < 0.001), reflecting a more pronounced angle and/or rougher surface. The flattest and smoothest topography was found in the temporal quadrant. Whites had significantly higher SSRo than Asians and Latinos (p < 0.001). CONCLUSIONS: This study presents a novel metric for characterizing the angle and topography of the corneoscleral junction using optical coherence tomography and establishes differences among quadrants and between ethnic groups.

Retinal tumor imaging and volume quantification in mouse model using spectral-domain optical coherence tomography.

We have successfully imaged the retinal tumor in a mouse model using an ultra-high resolution spectral-domain optical coherence tomography (SD-OCT) designed for small animal retinal imaging. For segmentation of the tumor boundaries and calculation of the tumor volume, we developed a novel segmentation algorithm. The algorithm is based on parametric deformable models (active contours) and is driven by machine learning-based region classification, namely a Conditional Random Field. With this algorithm we are able to obtain the tumor boundaries automatically, while the user can specify additional constraints (points on the boundary) to correct the segmentation result, if needed. The system and algorithm were successfully applied to studies on retinal tumor progression and monitoring treatment effects quantitatively in a mouse model of retinoblastoma.

Direction Selectivity in Drosophila Proprioceptors Requires the Mechanosensory Channel Tmc.

Drosophila Transmembrane channel-like (Tmc) is a protein that functions in larval proprioception. The closely related TMC1 protein is required for mammalian hearing and is a pore-forming subunit of the hair cell mechanotransduction channel. In hair cells, TMC1 is gated by small deflections of microvilli that produce tension on extracellular tip-links that connect adjacent villi. How Tmc might be gated in larval proprioceptors, which are neurons having a morphology that is completely distinct from hair cells, is unknown. Here, we have used high-speed confocal microscopy both to measure displacements of proprioceptive sensory dendrites during larval movement and to optically measure neural activity of the moving proprioceptors. Unexpectedly, the pattern of dendrite deformation for distinct neurons was unique and differed depending on the direction of locomotion: ddaE neuron dendrites were strongly curved by forward locomotion, while the dendrites of ddaD were more strongly deformed by backward locomotion. Furthermore, GCaMP6f calcium signals recorded in the proprioceptive neurons during locomotion indicated tuning to the direction of movement. ddaE showed strong activation during forward locomotion, while ddaD showed responses that were strongest during backward locomotion. Peripheral proprioceptive neurons in animals mutant for Tmc showed a near-complete loss of movement related calcium signals. As the strength of the responses of wild-type animals was correlated with dendrite curvature, we propose that Tmc channels may be activated by membrane curvature in dendrites that are exposed to strain. Our findings begin to explain how distinct cellular systems rely on a common molecular pathway for mechanosensory responses.

Three-dimensional motor neuron morphology estimation in the Drosophila ventral nerve cord.

Type-specific dendritic arborization patterns dictate synaptic connectivity and are fundamental determinants of neuronal function. We exploit the morphological stereotypy and relative simplicity of the Drosophila nervous system to model the diverse neuronal morphologies of individual motor neurons (MNs) and understand underlying principles of synaptic connectivity in a motor circuit. Our computational approach aims at the reconstruction of the neuron morphology, namely the robust segmentation of the neuron volumes from their surroundings with the simultaneous partitioning into their compartments, namely the soma, axon, and dendrites. We use the idea of cosegmentation, where every image along the z -axis (depth) is segmented using information from "neighboring" depths. We use 3-D Haar-like features to model appearance. Because soma and axon are determined by their distinctive shapes, we define an implicit shape representation of the 2-D segmentation sets to drive cosegmentation and achieve the desired partitioning. We validate our method using image stacks depicting single neurons labeled with green fluorescent protein (GFP) and serially imaged with laser scanning confocal microscopy.

bFGF-containing electrospun gelatin scaffolds with controlled nano-architectural features for directed angiogenesis.

Current therapeutic angiogenesis strategies are focused on the development of biologically responsive scaffolds that can deliver multiple angiogenic cytokines and/or cells in ischemic regions. Herein, we report on a novel electrospinning approach to fabricate cytokine-containing nanofibrous scaffolds with tunable architecture to promote angiogenesis. Fiber diameter and uniformity were controlled by varying the concentration of the polymeric (i.e. gelatin) solution, the feed rate, needle to collector distance, and electric field potential between the collector plate and injection needle. Scaffold fiber orientation (random vs. aligned) was achieved by alternating the polarity of two parallel electrodes placed on the collector plate thus dictating fiber deposition patterns. Basic fibroblast growth factor (bFGF) was physically immobilized within the gelatin scaffolds at variable concentrations and human umbilical vein endothelial cells (HUVEC) were seeded on the top of the scaffolds. Cell proliferation and migration was assessed as a function of growth factor loading and scaffold architecture. HUVECs successfully adhered onto gelatin B scaffolds and cell proliferation was directly proportional to the loading concentrations of the growth factor (0-100 bFGF ng/mL). Fiber orientation had a pronounced effect on cell morphology and orientation. Cells were spread along the fibers of the electrospun scaffolds with the aligned orientation and developed a spindle-like morphology parallel to the scaffold's fibers. In contrast, cells seeded onto the scaffolds with random fiber orientation, did not demonstrate any directionality and appeared to have a rounder shape. Capillary formation (i.e. sprouts length and number of sprouts per bead), assessed in a 3-D in vitro angiogenesis assay, was a function of bFGF loading concentration (0 ng, 50 ng and 100 ng per scaffold) for both types of electrospun scaffolds (i.e. with aligned or random fiber orientation).

Motor neuron morphology estimation for its classification in the Drosophila brain.

Type-specific dendritic arborization patterns dictate synaptic connectivity and are fundamental determinants of neuronal function. We exploit the morphological stereotypy and relative simplicity of the Drosophila nervous system to model the diverse dendritic morphologies of individual motor neurons (MNs) to understand underlying principles of synaptic connectivity in a motor circuit. The genetic tractability of Drosophila allows us to label single MNs with green fluorescent protein (GFP) and serially reconstruct identifiable MNs in 3D with confocal microscopy. Our computational approach aims at the robust segmentation of the MN volumes and the simultaneous partitioning into their compartments, namely the soma, axon and dendrites. We use the idea of co-segmentation, where every image along the z-axis (depth) is clustered using information from 'neighboring' depths. As appearance we use a 3D extension of Haar features and for the shape we define an implicit representation of the segmentation domain.

Synergistic angiogenic effect of codelivering fibroblast growth factor 2 and granulocyte-colony stimulating factor from fibrin scaffolds and bone marrow transplantation in critical limb ischemia.

Increasing evidence suggests that therapeutic angiogenesis strategies utilizing cytokines and stem cells are necessary to treat traumatic vascular events such as critical limb ischemia and peripheral artery disease. In this study, basic fibroblast growth factor 2 (FGF-2) and granulocyte-colony stimulating factor (G-CSF) were immobilized in fibrin matrices and codelivered in combination with unfractionated bone marrow cells. Hindlimb ischemia was induced on young (6-7 weeks) Balb/C mice, and fibrin gels containing 100 ng/mL of FGF-2 and G-CSF were implanted adjacent to the ligation points. In addition, 1×10(6) bone marrow (BM) cells were injected into five locations in the ischemic muscle immediately after ligation and artery excision. Hindlimb reperfusion was determined by Laser Doppler Perfusion Imaging and immunohistochemistry for CD31+ and smooth muscle actin-positive cells at 2, 4, and 8 weeks postsurgery to identify capillary formation and maturation. A fluorescent vessel painting technique was also utilized to determine the extent of angiogenesis and arteriogenesis in the hindlimb at 8 weeks postsurgery. The codelivery of FGF-2 and G-CSF in combination with BM cells led to enhanced therapeutic recovery in critical limb ischemia Balb/C mice after 8 weeks of treatment with 87.2% blood flow recovery and a significant increase (p<0.05) in capillary formation in comparison to growth factor delivery or BM cell administration alone.

CoCRF deformable model: a geometric model driven by collaborative conditional random fields.

We present a hybrid framework for integrating deformable models with learning-based classification, for image segmentation with region ambiguities. We show how a region-based geometric model is coupled with conditional random fields (CRF) in a simple graphical model, such that the model evolution is driven by a dynamically updated probability field. We define the model shape with the signed distance function, while we formulate the internal energy with a C(1) continuity constraint, a shape prior, and a term that forces the zero level of the shape function towards a connected form. The latter can be seen as a term that forces different closed curves on the image plane to merge, and, therefore, our model inherently carries the property of merging regions. We calculate the image likelihood that drives the evolution using a collaborative formulation of conditional random fields (CoCRF), which is updated during the evolution in an online learning manner. The CoCRF infers class posteriors to regions with feature ambiguities by assessing the joint appearance of neighboring sites, and using the classification confidence to regulate the inference. The novelties of our approach are (i) the tight coupling of deformable models with classification, combining the estimation of smooth region boundaries with the robustness of the probabilistic region classification, (ii) the handling of feature variations, by updating the region statistics in an online learning manner, and (iii) the improvement of the region classification using our CoCRF. We demonstrate the performance of our method in a variety of images with clutter, region inhomogeneities, boundary ambiguities, and complex textures, from the zebra and cheetah examples to medical images.

Optical analysis of circuitry for respiratory rhythm in isolated brainstem of foetal mice.

Respiratory rhythms arise from neurons situated in the ventral medulla. We are investigating their spatial and functional relationships optically by measuring changes in intracellular calcium using the fluorescent, calcium-sensitive dye Oregon Green 488 BAPTA-1 AM while simultaneously recording the regular firing of motoneurons in the phrenic nerve in isolated brainstem/spinal cord preparations of E17 to E19 mice. Responses of identified cells are associated breath by breath with inspiratory and expiratory phases of respiration and depend on CO(2) and pH levels. Optical methods including two-photon microscopy are being developed together with computational analyses. Analysis of the spatial pattern of neuronal activity associated with respiratory rhythm, including cross-correlation analysis, reveals a network distributed in the ventral medulla with intermingling of neurons that are active during separate phases of the rhythm. Our experiments, aimed at testing whether initiation of the respiratory rhythm depends on pacemaker neurons, on networks or a combination of both, suggest an important role for networks.