25 resultados para signal reconstruction

em Duke University


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Compressive sampling enables signal reconstruction using less than one measurement per reconstructed signal value. Compressive measurement is particularly useful in generating multidimensional images from lower dimensional data. We demonstrate single frame 3D tomography from 2D holographic data.

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PURPOSE: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D+dual energy+time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. METHODS: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction problem using the split Bregman method and GPU-based implementations of backprojection, reprojection, and kernel regression. Using a preclinical mouse model, the authors apply the proposed algorithm to study myocardial injury following radiation treatment of breast cancer. RESULTS: Quantitative 5D simulations are performed using the MOBY mouse phantom. Twenty data sets (ten cardiac phases, two energies) are reconstructed with 88 μm, isotropic voxels from 450 total projections acquired over a single 360° rotation. In vivo 5D myocardial injury data sets acquired in two mice injected with gold and iodine nanoparticles are also reconstructed with 20 data sets per mouse using the same acquisition parameters (dose: ∼60 mGy). For both the simulations and the in vivo data, the reconstruction quality is sufficient to perform material decomposition into gold and iodine maps to localize the extent of myocardial injury (gold accumulation) and to measure cardiac functional metrics (vascular iodine). Their 5D CT imaging protocol represents a 95% reduction in radiation dose per cardiac phase and energy and a 40-fold decrease in projection sampling time relative to their standard imaging protocol. CONCLUSIONS: Their 5D CT data acquisition and reconstruction protocol efficiently exploits the rank-sparse nature of spectral and temporal CT data to provide high-fidelity reconstruction results without increased radiation dose or sampling time.

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This paper reports a new strategy, recursive directional ligation by plasmid reconstruction (PRe-RDL), to rapidly clone highly repetitive polypeptides of any sequence and specified length over a large range of molecular weights. In a single cycle of PRe-RDL, two halves of a parent plasmid, each containing a copy of an oligomer, are ligated together, thereby dimerizing the oligomer and reconstituting a functional plasmid. This process is carried out recursively to assemble an oligomeric gene with the desired number of repeats. PRe-RDL has several unique features that stem from the use of type IIs restriction endonucleases: first, PRe-RDL is a seamless cloning method that leaves no extraneous nucleotides at the ligation junction. Because it uses type IIs endonucleases to ligate the two halves of the plasmid, PRe-RDL also addresses the major limitation of RDL in that it abolishes any restriction on the gene sequence that can be oligomerized. The reconstitution of a functional plasmid only upon successful ligation in PRe-RDL also addresses two other limitations of RDL: the significant background from self-ligation of the vector observed in RDL, and the decreased efficiency of ligation due to nonproductive circularization of the insert. PRe-RDL can also be used to assemble genes that encode different sequences in a predetermined order to encode block copolymers or append leader and trailer peptide sequences to the oligomerized gene.

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In this paper, we propose generalized sampling approaches for measuring a multi-dimensional object using a compact compound-eye imaging system called thin observation module by bound optics (TOMBO). This paper shows the proposed system model, physical examples, and simulations to verify TOMBO imaging using generalized sampling. In the system, an object is modulated and multiplied by a weight distribution with physical coding, and the coded optical signal is integrated on to a detector array. A numerical estimation algorithm employing a sparsity constraint is used for object reconstruction.

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Functional MRI (fMRI) can detect blood oxygenation level dependent (BOLD) hemodynamic responses secondary to neuronal activity. The most commonly used method for detecting fMRI signals is the gradient-echo echo-planar imaging (EPI) technique because of its sensitivity and speed. However, it is generally believed that a significant portion of these signals arises from large veins, with additional contribution from the capillaries and parenchyma. Early experiments using diffusion-weighted gradient-echo EPI have suggested that intra-voxel incoherent motion (IVIM) weighting inherent in the sequence can selectively attenuate contributions from different vessels based on the differences in the mobility of the blood within them. In the present study, we used similar approach to characterize the apparent diffusion coefficient (ADC) distribution within the activated areas of BOLD contrast. It is shown that the voxel values of the ADCs obtained from this technique can infer various vascular contributions to the BOLD signal.

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Deregulation of the Sonic hedgehog pathway has been implicated in an increasing number of human cancers. In this pathway, the seven-transmembrane (7TM) signaling protein Smoothened regulates cellular proliferation and differentiation through activation of the transcription factor Gli. The activity of mammalian Smoothened is controlled by three different hedgehog proteins, Indian, Desert, and Sonic hedgehog, through their interaction with the Smoothened inhibitor Patched. However, the mechanisms of signal transduction from Smoothened are poorly understood. We show that a kinase which regulates signaling by many "conventional" 7TM G-protein-coupled receptors, G protein-coupled receptor kinase 2 (GRK2), participates in Smoothened signaling. Expression of GRK2, but not catalytically inactive GRK2, synergizes with active Smoothened to mediate Gli-dependent transcription. Moreover, knockdown of endogenous GRK2 by short hairpin RNA (shRNA) significantly reduces signaling in response to the Smoothened agonist SAG and also inhibits signaling induced by an oncogenic Smoothened mutant, Smo M2. We find that GRK2 promotes the association between active Smoothened and beta-arrestin 2. Indeed, Gli-dependent signaling, mediated by coexpression of Smoothened and GRK2, is diminished by beta-arrestin 2 knockdown with shRNA. Together, these data suggest that GRK2 plays a positive role in Smoothened signaling, at least in part, through the promotion of an association between beta-arrestin 2 and Smoothened.

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Stimulation of a mutant angiotensin type 1A receptor (DRY/AAY) with angiotensin II (Ang II) or of a wild-type receptor with an Ang II analog ([sarcosine1,Ile4,Ile8]Ang II) fails to activate classical heterotrimeric G protein signaling but does lead to recruitment of beta-arrestin 2-GFP and activation of extracellular signal-regulated kinases 1 and 2 (ERK1/2) (maximum stimulation approximately 50% of wild type). This G protein-independent activation of mitogen-activated protein kinase is abolished by depletion of cellular beta-arrestin 2 but is unaffected by the PKC inhibitor Ro-31-8425. In parallel, stimulation of the wild-type angiotensin type 1A receptor with Ang II robustly stimulates ERK1/2 activation with approximately 60% of the response blocked by the PKC inhibitor (G protein dependent) and the rest of the response blocked by depletion of cellular beta-arrestin 2 by small interfering RNA (beta-arrestin dependent). These findings imply the existence of independent G protein- and beta-arrestin 2-mediated pathways leading to ERK1/2 activation and the existence of distinct "active" conformations of a seven-membrane-spanning receptor coupled to each.

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Using both confocal immunofluorescence microscopy and biochemical approaches, we have examined the role of beta-arrestins in the activation and targeting of extracellular signal-regulated kinase 2 (ERK2) following stimulation of angiotensin II type 1a receptors (AT1aR). In HEK-293 cells expressing hemagglutinin-tagged AT1aR, angiotensin stimulation triggered beta-arrestin-2 binding to the receptor and internalization of AT1aR-beta-arrestin complexes. Using red fluorescent protein-tagged ERK2 to track the subcellular distribution of ERK2, we found that angiotensin treatment caused the redistribution of activated ERK2 into endosomal vesicles that also contained AT1aR-beta-arrestin complexes. This targeting of ERK2 reflects the formation of multiprotein complexes containing AT1aR, beta-arrestin-2, and the component kinases of the ERK cascade, cRaf-1, MEK1, and ERK2. Myc-tagged cRaf-1, MEK1, and green fluorescent protein-tagged ERK2 coprecipitated with Flag-tagged beta-arrestin-2 from transfected COS-7 cells. Coprecipitation of cRaf-1 with beta-arrestin-2 was independent of MEK1 and ERK2, whereas the coprecipitation of MEK1 and ERK2 with beta-arrestin-2 was significantly enhanced in the presence of overexpressed cRaf-1, suggesting that binding of cRaf-1 to beta-arrestin facilitates the assembly of a cRaf-1, MEK1, ERK2 complex. The phosphorylation of ERK2 in beta-arrestin complexes was markedly enhanced by coexpression of cRaf-1, and this effect is blocked by expression of a catalytically inactive dominant inhibitory mutant of MEK1. Stimulation with angiotensin increased the binding of both cRaf-1 and ERK2 to beta-arrestin-2, and the association of beta-arrestin-2, cRaf-1, and ERK2 with AT1aR. These data suggest that beta-arrestins function both as scaffolds to enhance cRaf-1 and MEK-dependent activation of ERK2, and as targeting proteins that direct activated ERK to specific subcellular locations.

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We have previously shown that second-messenger-dependent kinases (cAMP-dependent kinase, protein kinase C) in the olfactory system are essential in terminating second-messenger signaling in response to odorants. We now document that subtype 2 of the beta-adrenergic receptor kinase (beta ARK) is also involved in this process. By using subtype-specific antibodies to beta ARK-1 and beta ARK-2, we show that beta ARK-2 is preferentially expressed in the olfactory epithelium in contrast to findings in most other tissues. Heparin, an inhibitor of beta ARK, as well as anti-beta ARK-2 antibodies, (i) completely prevents the rapid decline of second-messenger signals (desensitization) that follows odorant stimulation and (ii) strongly inhibits odorant-induced phosphorylation of olfactory ciliary proteins. In contrast, beta ARK-1 antibodies are without effect. Inhibitors of protein kinase A and protein kinase C also block odorant-induced desensitization and phosphorylation. These data suggest that a sequential interplay of second-messenger-dependent and receptor-specific kinases is functionally involved in olfactory desensitization.

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Adrenergic receptors are prototypic models for the study of the relations between structure and function of G protein-coupled receptors. Each receptor is encoded by a distinct gene. These receptors are integral membrane proteins with several striking structural features. They consist of a single subunit containing seven stretches of 20-28 hydrophobic amino acids that represent potential membrane-spanning alpha-helixes. Many of these receptors share considerable amino acid sequence homology, particularly in the transmembrane domains. All of these macromolecules share other similarities that include one or more potential sites of extracellular N-linked glycosylation near the amino terminus and several potential sites of regulatory phosphorylation that are located intracellularly. By using a variety of techniques, it has been demonstrated that various regions of the receptor molecules are critical for different receptor functions. The seven transmembrane regions of the receptors appear to form a ligand-binding pocket. Cysteine residues in the extracellular domains may stabilize the ligand-binding pocket by participating in disulfide bonds. The cytoplasmic domains contain regions capable of interacting with G proteins and various kinases and are therefore important in such processes as signal transduction, receptor-G protein coupling, receptor sequestration, and down-regulation. Finally, regions of these macromolecules may undergo posttranslational modifications important in the regulation of receptor function. Our understanding of these complex relations is constantly evolving and much work remains to be done. Greater understanding of the basic mechanisms involved in G protein-coupled, receptor-mediated signal transduction may provide leads into the nature of certain pathophysiological states.

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BACKGROUND: Anterior cruciate ligament (ACL) reconstruction is associated with a high incidence of second tears (graft tears and contralateral ACL tears). These secondary tears have been attributed to asymmetrical lower extremity mechanics. Knee bracing is one potential intervention that can be used during rehabilitation that has the potential to normalize lower extremity asymmetry; however, little is known about the effect of bracing on movement asymmetry in patients following ACL reconstruction. HYPOTHESIS: Wearing a knee brace would increase knee joint flexion and joint symmetry. It was also expected that the joint mechanics would become more symmetrical in the braced condition. OBJECTIVE: To examine how knee bracing affects knee joint function and symmetry over the course of rehabilitation in patients 6 months following ACL reconstruction. STUDY DESIGN: Controlled laboratory study. LEVEL OF EVIDENCE: Level 3. METHODS: Twenty-three adolescent patients rehabilitating from ACL reconstruction surgery were recruited for the study. The subjects all underwent a motion analysis assessment during a stop-jump activity with and without a functional knee brace on the surgical side that resisted extension for 6 months following the ACL reconstruction surgery. Statistical analysis utilized a 2 × 2 (limb × brace) analysis of variance with a significant alpha level of 0.05. RESULTS: Subjects had increased knee flexion on the surgical side when they were braced. The brace condition increased knee flexion velocity, decreased the initial knee flexion angle, and increased the ground reaction force and knee extension moment on both limbs. Side-to-side asymmetry was present across conditions for the vertical ground reaction force and knee extension moment. CONCLUSION: Wearing a knee brace appears to increase lower extremity compliance and promotes normalized loading on the surgical side. CLINICAL RELEVANCE: Knee extension constraint bracing in postoperative ACL patients may improve symmetry of lower extremity mechanics, which is potentially beneficial in progressing rehabilitation and reducing the incidence of second ACL tears.

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Asymmetries in sagittal plane knee kinetics have been identified as a risk factor for anterior cruciate ligament (ACL) re-injury. Clinical tools are needed to identify the asymmetries. This study examined the relationships between knee kinetic asymmetries and ground reaction force (GRF) asymmetries during athletic tasks in adolescent patients following ACL reconstruction (ACL-R). Kinematic and GRF data were collected during a stop-jump task and a side-cutting task for 23 patients. Asymmetry indices between the surgical and non-surgical limbs were calculated for GRF and knee kinetic variables. For the stop-jump task, knee kinetics asymmetry indices were correlated with all GRF asymmetry indices (P < 0.05), except for loading rate. Vertical GRF impulse asymmetry index predicted peak knee moment, average knee moment, and knee work (R(2)  ≥ 0.78, P < 0.01) asymmetry indices. For the side-cutting tasks, knee kinetic asymmetry indices were correlated with the peak propulsion vertical GRF and vertical GRF impulse asymmetry indices (P < 0.05). Vertical GRF impulse asymmetry index predicted peak knee moment, average knee moment, and knee work (R(2)  ≥ 0.55, P < 0.01) asymmetry indices. The vertical GRF asymmetries may be a viable surrogate for knee kinetic asymmetries and therefore may assist in optimizing rehabilitation outcomes and minimizing re-injury rates.

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A framework for adaptive and non-adaptive statistical compressive sensing is developed, where a statistical model replaces the standard sparsity model of classical compressive sensing. We propose within this framework optimal task-specific sensing protocols specifically and jointly designed for classification and reconstruction. A two-step adaptive sensing paradigm is developed, where online sensing is applied to detect the signal class in the first step, followed by a reconstruction step adapted to the detected class and the observed samples. The approach is based on information theory, here tailored for Gaussian mixture models (GMMs), where an information-theoretic objective relationship between the sensed signals and a representation of the specific task of interest is maximized. Experimental results using synthetic signals, Landsat satellite attributes, and natural images of different sizes and with different noise levels show the improvements achieved using the proposed framework when compared to more standard sensing protocols. The underlying formulation can be applied beyond GMMs, at the price of higher mathematical and computational complexity. © 1991-2012 IEEE.