214 resultados para 570
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Background Parasitic wasps constitute one of the largest group of venomous animals. Although some physiological effects of their venoms are well documented, relatively little is known at the molecular level on the protein composition of these secretions. To identify the majority of the venom proteins of the endoparasitoid wasp Chelonus inanitus (Hymenoptera: Braconidae), we have randomly sequenced 2111 expressed sequence tags (ESTs) from a cDNA library of venom gland. In parallel, proteins from pure venom were separated by gel electrophoresis and individually submitted to a nano-LC-MS/MS analysis allowing comparison of peptides and ESTs sequences. Results About 60% of sequenced ESTs encoded proteins whose presence in venom was attested by mass spectrometry. Most of the remaining ESTs corresponded to gene products likely involved in the transcriptional and translational machinery of venom gland cells. In addition, a small number of transcripts were found to encode proteins that share sequence similarity with well-known venom constituents of social hymenopteran species, such as hyaluronidase-like proteins and an Allergen-5 protein. An overall number of 29 venom proteins could be identified through the combination of ESTs sequencing and proteomic analyses. The most highly redundant set of ESTs encoded a protein that shared sequence similarity with a venom protein of unknown function potentially specific of the Chelonus lineage. Venom components specific to C. inanitus included a C-type lectin domain containing protein, a chemosensory protein-like protein, a protein related to yellow-e3 and ten new proteins which shared no significant sequence similarity with known sequences. In addition, several venom proteins potentially able to interact with chitin were also identified including a chitinase, an imaginal disc growth factor-like protein and two putative mucin-like peritrophins. Conclusions The use of the combined approaches has allowed to discriminate between cellular and truly venom proteins. The venom of C. inanitus appears as a mixture of conserved venom components and of potentially lineage-specific proteins. These new molecular data enrich our knowledge on parasitoid venoms and more generally, might contribute to a better understanding of the evolution and functional diversity of venom proteins within Hymenoptera.
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Introduction: As a previous study revealed, arts speech therapy (AST) affects cardiorespiratory interaction [1]. The aim of the present study was to investigate whether AST also has effects on brain oxygenation and hemodynamics measured non-invasively using near-infrared spectroscopy (NIRS). Material and methods: NIRS measurements were performed on 17 subjects (8 men and 9 women, mean age: 35.6 ± 12.7 y) during AST. Each measurement lasted 35 min, comprising 8 min pre-baseline, 10 min recitation and 20 min post-baseline. For each subject, measurements were performed for three different AST recitation tasks (recitation of alliterative, hexameter and prose verse). Relative concentration changes of oxyhemoglobin (Δ[O2Hb]) and deoxyhemoglobin (Δ[HHb]) as well as the tissue oxygenation index (TOI) were measured using a Hamamatsu NIRO300 NIRS device and a sensor placed on the subjects forehead. Movement artifacts were removed using a novel method [2]. Statistical analysis (Wilcoxon test) was applied to the data to investigate (i) if the recitation causes changes in the median values and/or in the Mayer wave power spectral density (MW-PSD, range: 0.07–0.13 Hz) of Δ[O2Hb], Δ[HHb] or TOI, and (ii) if these changes vary between the 3 recitation forms. Results: For all three recitation styles a significant (p < 0.05) decrease in Δ[O2Hb] and TOI was found, indicating a decrease in blood flow. These decreases did not vary significantly between the three styles. MW-PSD increased significantly for Δ[O2Hb] when reciting the hexameter and prose verse, and for Δ[HHb] and TOI when reciting alliterations and hexameter, representing an increase in Mayer waves. The MW-PSD increase for Δ[O2Hb] was significantly larger for the hexameter verse compared to alliterative and prose verse Conclusion: The study showed that AST affects brain hemodynamics (oxygenation, blood flow and Mayer waves). Recitation caused a significant decrease in cerebral blood flow for all recitation styles as well as an increase in Mayer waves, particularly for the hexameter, which may indicate a sympathetic activation. References 1. D. Cysarz, D. von Bonin, H. Lackner, P. Heusser, M. Moser, H. Bettermann. Am J Physiol Heart Circ Physiol, 287 (2) (2004), pp. H579–H587 2. F. Scholkmann, S. Spichtig, T. Muehlemann, M. Wolf. Physiol Meas, 31 (5) (2010), pp. 649–662
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Three novel glycine-rich peptides, named ctenidin 1-3, with activity against the Gram-negative bacterium E. coli, were isolated and characterized from hemocytes of the spider Cupiennius salei. Ctenidins have a high glycine content (>70%), similarly to other glycine-rich peptides, the acanthoscurrins, from another spider, Acanthoscurria gomesiana. A combination of mass spectrometry, Edman degradation, and cDNA cloning revealed the presence of three isoforms of ctenidin, at least two of them originating from simple, intronless genes. The full-length sequences of the ctenidins consist of a 19 amino acid residues signal peptide followed by the mature peptides of 109, 119, or 120 amino acid residues. The mature peptides are post-translationally modified by the cleavage of one or two C-terminal cationic amino acid residue(s) and amidation of the newly created mature C-terminus. Tissue expression analysis revealed that ctenidins are constitutively expressed in hemocytes and to a small extent also in the subesophageal nerve mass.
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Defensins are a major family of antimicrobial peptides found throughout the phylogenetic tree. From the spider species: Cupiennius salei, Phoneutria reidyi, Polybetes pythagoricus, Tegenaria atrica, and Meta menardi, defensins belonging to the 'ancestral' class of invertebrate defensins were cloned and sequenced. The deduced amino acid sequences contain the characteristic six cysteines of this class of defensins and reveal precursors of 60 or 61 amino acid residues. The mature peptides consist of 37 amino acid residues, showing up to 70% identities with tick and scorpion defensins. In C. salei, defensin mRNA was found to be constitutively expressed in hemocytes, ovaries, subesophageal nerve mass, hepatopancreas, and muscle tissue. This is the first report presenting and comparing antimicrobial peptides belonging to the family of defensins from spiders.
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Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.
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Computerized soft-tissue simulation can provide unprecedented means for predicting facial outlook pre-operatively. Surgeons can virtually perform several surgical plans to have the best surgical results for their patients while considering corresponding soft-tissue outcome. It could be used as an interactive communication tool with their patients as well. There has been comprehensive amount of works for simulating soft-tissue for cranio-maxillofacial surgery. Although some of them have been realized as commercial products, none of them has been fully integrated into clinical practice due to the lack of accuracy and excessive amount of processing time. In this chapter, state-of-the-art and general workflow in facial soft-tissue simulation will be presented, along with an example of patient-specific facial soft-tissue simulation method.
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Osteoarticular allograft transplantation is a popular treatment method in wide surgical resections with large defects. For this reason hospitals are building bone data banks. Performing the optimal allograft selection on bone banks is crucial to the surgical outcome and patient recovery. However, current approaches are very time consuming hindering an efficient selection. We present an automatic method based on registration of femur bones to overcome this limitation. We introduce a new regularization term for the log-domain demons algorithm. This term replaces the standard Gaussian smoothing with a femur specific polyaffine model. The polyaffine femur model is constructed with two affine (femoral head and condyles) and one rigid (shaft) transformation. Our main contribution in this paper is to show that the demons algorithm can be improved in specific cases with an appropriate model. We are not trying to find the most optimal polyaffine model of the femur, but the simplest model with a minimal number of parameters. There is no need to optimize for different number of regions, boundaries and choice of weights, since this fine tuning will be done automatically by a final demons relaxation step with Gaussian smoothing. The newly developed synthesis approach provides a clear anatomically motivated modeling contribution through the specific three component transformation model, and clearly shows a performance improvement (in terms of anatomical meaningful correspondences) on 146 CT images of femurs compared to a standard multiresolution demons. In addition, this simple model improves the robustness of the demons while preserving its accuracy. The ground truth are manual measurements performed by medical experts.
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Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.
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In this paper we present a new population-based method for the design of bone fixation plates. Standard pre-contoured plates are designed based on the mean shape of a certain population. We propose a computational process to design implants while reducing the amount of required intra-operative shaping, thus reducing the mechanical stresses applied to the plate. A bending and torsion model was used to measure and minimize the necessary intra-operative deformation. The method was applied and validated on a population of 200 femurs that was further augmented with a statistical shape model. The obtained results showed substantial reduction in the bending and torsion needed to shape the new design into any bone in the population when compared to the standard mean-based plates.
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Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.
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We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.
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Loading is important to maintain the balance of matrix turnover in the intervertebral disc (IVD). Daily cyclic diurnal assists in the transport of large soluble factors across the IVD and its surrounding circulation and applies direct and indirect stimulus to disc cells. Acute mechanical injury and accumulated overloading, however, could induce disc degeneration. Recently, there is more information available on how cyclic loading, especially axial compression and hydrostatic pressure, affects IVD cell biology. This review summarises recent studies on the response of the IVD and stem cells to applied cyclic compression and hydrostatic pressure. These studies investigate the possible role of loading in the initiation and progression of disc degeneration as well as quantifying a physiological loading condition for the study of disc degeneration biological therapy. Subsequently, a possible physiological/beneficial loading range is proposed. This physiological/beneficial loading could provide insight into how to design loading regimes in specific system for the testing of various biological therapies such as cell therapy, chemical therapy or tissue engineering constructs to achieve a better final outcome. In addition, the parameter space of 'physiological' loading may also be an important factor for the differentiation of stem cells towards most ideally 'discogenic' cells for tissue engineering purpose.
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Erratum to: Eur Spine J DOI 10.1007/s00586-011-1827-1 In the original article ‘‘Acknowledgments’’ was missing. The Acknowledgment is given below: Acknowledgments This project was supported by the Swiss National Science Foundation (SNF # 310030-127586/1) and the Department for Orthopedic Research, Insel University Hospital, Bern, Switzerland.