252 resultados para Extract


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Osteoblast lineage cells are direct effectors of osteogenesis and are, therefore, commonly used to evaluate the in vitro osteogenic capacity of bone substitute materials. This method has served its purposes when testing novel bone biomaterials; however, inconsistent results between in vitro and in vivo studies suggest the mechanisms that govern a material's capacity to mediate osteogenesis are not well understood. The emerging field of osteoimmunology and immunomodulation has informed a paradigm shift in our view of bone biomaterials–from one of an inert to an osteoimmunomodulatory material–highlighting the importance of immune cells in materials-mediated osteogenesis. Neglecting the importance of the immune response during this process is a major shortcoming of the current evaluation protocol. In this study we evaluated a potential angiogenic bone substitute material cobalt incorporated with β-tricalcium phosphate (CCP), comparing the traditional “one cell type” approach with a “multiple cell types” approach to assess osteogenesis, the latter including the use of immune cells. We found that CCP extract by itself was sufficient to enhance osteogenic differentiation of bone marrow stem cells (BMSCs), whereas this effect was cancelled out when macrophages were involved. In response to CCP, the macrophage phenotype switched to the M1 extreme, releasing pro-inflammatory cytokines and bone catabolic factors. When the CCP materials were implanted into a rat femur condyle defect model, there was a significant increase of inflammatory markers and bone destruction, coupled with fibrous encapsulation rather than new bone formation. These findings demonstrated that the inclusion of immune cells (macrophages) in the in vitro assessment matched the in vivo tissue response, and that this method provides a more accurate indication of the essential role of immune cells when assessing materials-stimulated osteogenesis in vitro.

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Erythropoietin (EPO), a glycoprotein hormone of ∼34 kDa, is an important hematopoietic growth factor, mainly produced in the kidney and controls the number of red blood cells circulating in the blood stream. Sensitive and rapid recombinant human EPO (rHuEPO) detection tools that improve on the current laborious EPO detection techniques are in high demand for both clinical and sports industry. A sensitive aptamer-functionalized biosensor (aptasensor) has been developed by controlled growth of gold nanostructures (AuNS) over a gold substrate (pAu/AuNS). The aptasensor selectively binds to rHuEPO and, therefore, was used to extract and detect the drug from horse plasma by surface enhanced Raman spectroscopy (SERS). Due to the nanogap separation between the nanostructures, the high population and distribution of hot spots on the pAu/AuNS substrate surface, strong signal enhancement was acquired. By using wide area illumination (WAI) setting for the Raman detection, a low RSD of 4.92% over 150 SERS measurements was achieved. The significant reproducibility of the new biosensor addresses the serious problem of SERS signal inconsistency that hampers the use of the technique in the field. The WAI setting is compatible with handheld Raman devices. Therefore, the new aptasensor can be used for the selective extraction of rHuEPO from biological fluids and subsequently screened with handheld Raman spectrometer for SERS based in-field protein detection.

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Cortical connectivity is associated with cognitive and behavioral traits that are thought to vary between sexes. Using high-angular resolution diffusion imaging at 4 Tesla, we scanned 234 young adult twins and siblings (mean age: 23.4 2.0 SD years) with 94 diffusion-encoding directions. We applied a novel Hough transform method to extract fiber tracts throughout the entire brain, based on fields of constant solid angle orientation distribution functions (ODFs). Cortical surfaces were generated from each subject's 3D T1-weighted structural MRI scan, and tracts were aligned to the anatomy. Network analysis revealed the proportions of fibers interconnecting 5 key subregions of the frontal cortex, including connections between hemispheres. We found significant sex differences (147 women/87 men) in the proportions of fibers connecting contralateral superior frontal cortices. Interhemispheric connectivity was greater in women, in line with long-standing theories of hemispheric specialization. These findings may be relevant for ongoing studies of the human connectome.

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Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.

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There is a major effort in medical imaging to develop algorithms to extract information from DTI and HARDI, which provide detailed information on brain integrity and connectivity. As the images have recently advanced to provide extraordinarily high angular resolution and spatial detail, including an entire manifold of information at each point in the 3D images, there has been no readily available means to view the results. This impedes developments in HARDI research, which need some method to check the plausibility and validity of image processing operations on HARDI data or to appreciate data features or invariants that might serve as a basis for new directions in image segmentation, registration, and statistics. We present a set of tools to provide interactive display of HARDI data, including both a local rendering application and an off-screen renderer that works with a web-based viewer. Visualizations are presented after registration and averaging of HARDI data from 90 human subjects, revealing important details for which there would be no direct way to appreciate using conventional display of scalar images.

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In aerosol research, a common approach for the collection of particulate matter (PM) is the use of filters in order to obtain sufficient material to undertake analysis. For subsequent chemical and toxicological analyses, in most of cases the PM needs to be extracted from the filters. Sonication is commonly used to most efficiently extract the PM from the filters. Extraction protocols generally involve 10 - 60 min of sonication. The energy of ultrasonic waves causes the formation and collapse of cavitation bubbles in the solution. Inside the collapsing cavities the localised temperatures and pressures can reach extraordinary values. Although fleeting, such conditions can lead to pyrolysis of the molecules present inside the cavitation bubbles (gases dissolved in the liquid and solvent vapours), which results in the production of free radicals and the generation of new compounds formed by reactions with these free radicals. For example, simple sonication of pure water will result in the formation of detectable levels of hydroxyl radicals. As hydroxyl radicals are recognised as playing key roles as oxidants in the atmosphere the extraction of PM from filters using sonication is therefore problematic. Sonication can result in significant chemical and physical changes to PM through thermal degradation and other reactions. In this article, an overview of sonication technique as used in aerosol research is provided, the capacity for radical generation under these conditions is described and an analysis is given of the impact of sonication-derived free radicals on three molecular probes commonly used by researchers in this field to detect Reactive Oxygen Species in PM.

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The Eating Disorder Risk Composite (EDRC) comprises the Drive for Thinness, Bulimia, and Body Dissatisfaction subscales of the Eating Disorder Inventory, Third Edition (EDI-3, Garner, 2004). Past research conducted with Latina college women (LCW) has found older versions of the EDRC subscales to be reliable, but the EDI-3's EDRC factor structure has yet to be studied among LCW. The present study investigated the pattern of responses to and the factor structure of the EDRC in LCW. It was hypothesized that eating pathology would be present and that a factor analysiswould find some discrepancies between the original factor structure of the EDRC and the factor structure from LCW. Analyses of data on a 6-point Likert scale indicate that drive for thinness and body dissatisfaction are far more prevalent than is bulimic symptomology in LCW. Principal Axis Factoring with promax rotation was used to extract three factors very similar to the original EDRC. Some discrepancies in the item loadings were observed, most notably that half of the items from the original Body Dissatisfaction subscale did not load together on one factor. Overall, the EDRC appears to be a goodmeasurement of eating- and body-related phenomena among LCW. Implications, limitations, and future directions are discussed.

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Patent law provides exclusive rights to exploit scientific inventions, which are novel, inventive, and useful. The regime is intended to promote innovation, investment in research and development, and access to scientific information. In recent times, there have been concerns that the patent system has been abused by opportunistic companies known by the phrase “patent trolls”. It has been alleged that such entities have stunted innovation and spurred unnecessary patent litigation. Adam Jaffe and Josh Lerner discuss such pathologies of patent law in their book, Innovation and Its Discontents: How our Broken Patent System is Endangering Innovation and Progress, and What To Do About It. James Bessen and Michael Meurer have addressed such concerns in their recent text, Patent Failure: How Judges, Bureaucrats, and Lawyers Put Innovators at Risk. There have been particular fears about the rise of “patent trolls” in the field of information technology. Peter Dekin, an assistant general counsel at Intel, used the phrase “patent troll” to describe firms, which acquired patents only to extract settlements from companies on dubious infringement claims.

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We present a methodology to extract legal norms from regulatory documents for their formalisation and later compliance checking. The need for the methodology is motivated from the shortcomings of existing approaches where the rule type and process aspects relevant to the rules are largely overlook. The methodology incorporates the well–known IF. . . THEN structure extended with the process aspect and rule type, and guides how to properly extract the conditions and logical structure of the legal rules for reasoning and modelling of obligations for compliance checking.

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The makers of Dallas Buyers Club have been dealt a blow in their attempt to extract payment from people alleged to have downloaded illegal copies of the movie. Voltage Pictures, which owns Dallas Buyers Club, has been trying to identify over 4,700 iiNet subscribers who it alleges downloaded illicit copies of the movie. Earlier this year, the Federal Court agreed that iiNet should hand over subscriber details, but warned that any letter sent to account holders must first be approved by the court to protect consumers from abuse of the legal system. In a win for consumer protection, the Federal Court has now rejected Voltage’s draft letters, criticising Voltage’s attempts to avoid explaining what fee it would demand.

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This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

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As of today, user-generated information such as online reviews has become increasingly significant for customers in decision making process. Meanwhile, as the volume of online reviews proliferates, there is an insistent demand to help the users tackle the information overload problem. In order to extract useful information from overwhelming reviews, considerable work has been proposed such as review summarization and review selection. Particularly, to avoid the redundant information, researchers attempt to select a small set of reviews to represent the entire review corpus by preserving its statistical properties (e.g., opinion distribution). However, one significant drawback of the existing works is that they only measure the utility of the extracted reviews as a whole without considering the quality of each individual review. As a result, the set of chosen reviews may consist of low-quality ones even its statistical property is close to that of the original review corpus, which is not preferred by the users. In this paper, we proposed a review selection method which takes review quality into consideration during the selection process. Specifically, we examine the relationships between product features based upon a domain ontology to capture the review characteristics based on which to select reviews that have good quality and preserve the opinion distribution as well. Our experimental results based on real world review datasets demonstrate that our proposed approach is feasible and able to improve the performance of the review selection effectively.

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Background Context There are differences in definitions of end plate lesions (EPLs), often referred to as Schmorl’s nodes, that may, to some extent, account for the large range of reported prevalence (3.8 to 76%). Purpose To develop a technique to measure the size, prevalence and location of EPLs in a consistent manner. Study Design/Setting This study proposed a method using a detection algorithm which was applied to five adolescent females (average age 15.1 years, range 13.0 to 19.2 years) with idiopathic scoliosis (average major Cobb angle 60°, range 55 to 67°). Methods Existing low-dose, computed tomography scans were segmented semi-automatically to extract 3D morphology of each vertebral endplate. Any remaining attachments to the posterior elements of adjacent vertebrae or endplates were then manually sectioned. An automatic algorithm was used to determine the presence and position of EPLs. Results EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 11/15 of the EPLs were seen in the lumbar spine. The algorithm was found to be most sensitive to changes in the minimum EPL gradient at the edges of the EPL. Conclusions This study describes an imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs. The technique can be used to analyse large populations without observer errors in EPL definitions.

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Even though crashes between trains and road users are rare events at railway level crossings, they are one of the major safety concerns for the Australian railway industry. Nearmiss events at level crossings occur more frequently, and can provide more information about factors leading to level crossing incidents. In this paper we introduce a video analytic approach for automatically detecting and localizing vehicles from cameras mounted on trains for detecting near-miss events. To detect and localize vehicles at level crossings we extract patches from an image and classify each patch for detecting vehicles. We developed a region proposals algorithm for generating patches, and we use a Convolutional Neural Network (CNN) for classifying each patch. To localize vehicles in images we combine the patches that are classified as vehicles according to their CNN scores and positions. We compared our system with the Deformable Part Models (DPM) and Regions with CNN features (R-CNN) object detectors. Experimental results on a railway dataset show that the recall rate of our proposed system is 29% higher than what can be achieved with DPM or R-CNN detectors.

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INTRODUCTION There is a large range in the reported prevalence of end plate lesions (EPLs), sometimes referred to as Schmorl's nodes in the general population (3.8-76%). One possible reason for this large range is the differences in definitions used by authors. Previous research has suggested that EPLs may potentially be a primary disturbance of growth plates that leads to the onset of scoliosis. The aim of this study was to develop a technique to measure the size, prevalence and location of EPLs on Computed Tomography (CT) images of scoliosis patients in a consistent manner. METHODS A detection algorithm was developed and applied to measure EPLs for five adolescent females with idiopathic scoliosis (average age 15.1 years, average major Cobb 60°). In this algorithm, the EPL definition was based on the lesion depth, the distance from the edge of the vertebral body and the gradient of the lesion edge. Existing low-dose, CT scans of the patients' spines were segmented semi-automatically to extract 3D vertebral endplate morphology. Manual sectioning of any attachments between posterior elements of adjacent vertebrae and, if necessary, endplates was carried out before the automatic algorithm was used to determine the presence and position of EPLs. RESULTS EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 73% of the EPLs were seen in the lumbar spines (11/15). A sensitivity study demonstrated that the algorithm was most sensitive to changes in the minimum gradient required at the lesion edge. CONCLUSION An imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs on CT images has been developed. Although the technique was tested on scoliosis patients, it can be used to analyse other populations without observer errors in EPL definitions.