984 resultados para Coolidge, Cornelius--1778-1843
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The tumor suppressor PTEN antagonizes phosphatidylinositol 3-kinase (PI3K), which contributes to tumorigenesis in many cancer types. While PTEN mutations occur in some melanomas, their precise mechanistic consequences have yet to be elucidated. We sought to identify novel downstream effectors of PI3K using a combination of genomic and functional tests. Microarray analysis of 53 melanoma cell lines identified 610 genes differentially expressed (P<0.05) between wild-type lines and those with PTEN aberrations. Many of these genes are known to be involved in the PI3K pathway and other signaling pathways influenced by PTEN. Validation of differential gene expression by qRT-PCR was performed in the original 53 cell lines and an independent set of 18 melanoma lines with known PTEN status. Osteopontin (OPN), a secreted glycophosphoprotein that contributes to tumor progression, was more abundant at both the mRNA and protein level in PTEN mutants. The inverse correlation between OPN and PTEN expression was validated (P<0.02) by immunohistochemistry using melanoma tissue microarrays. Finally, treatment of cell lines with the PI3K inhibitor LY294002 caused a reduction in expression of OPN. These data indicate that OPN acts downstream of PI3K in melanoma and provides insight into how PTEN loss contributes to melanoma development.
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Navigation through tessellated solids in GEANT4 can degrade computational performance, especially if the tessellated solid is large and is comprised of many facets. Redefining a tessellated solid as a mesh of tetrahedra is common in other computational techniques such as finite element analysis as computations need only consider local tetrahedrons rather than the tessellated solid as a whole. Here within we describe a technique that allows for automatic tetrahedral meshing of tessellated solids in GEANT4 and the subsequent loading of these meshes as assembly volumes; loading nested tessellated solids and tetrahedral meshes is also examined. As the technique makes the geometry suitable for automatic optimisation using smartvoxels, navigation through a simple tessellated volume has been found to be more than two orders of magnitude faster than that through the equivalent tessellated solid. Speed increases of more than two orders of magnitude were also observed for a more complex tessellated solid with voids and concavities. The technique was benchmarked for geometry load time, simulation run time and memory usage. Source code enabling the described functionality in GEANT4 has been made freely available on the Internet.
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Often CAD models already exist for parts of a geometry being simulated using GEANT4. Direct import of these CAD models into GEANT4 however,may not be possible and complex components may be diffcult to define via other means. Solutions that allow for users to work around the limited support in the GEANT4 toolkit for loading predefined CAD geometries have been presented by others, however these solutions require intermediate file format conversion using commercial software. Here within we describe a technique that allows for CAD models to be directly loaded as geometry without the need for commercial software and intermediate file format conversion. Robustness of the interface was tested using a set of CAD models of various complexity; for the models used in testing, no import errors were reported and all geometry was found to be navigable by GEANT4. Funding source: Cancer Australia (Department of Health and Ageing) Research Grant 614217
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Particulate matter (PM) emissions involve a complex mixture of solid and liquid particles suspended in a gas, where it is noted that PM emissions from diesel engines are a major contributor to the ambient air pollution problem. Whilst epidemiological studies have shown a link between increased ambient PM emissions and respiratory morbidity and mortality, studies of this design are not able to identify the PM constituents responsible for driving adverse respiratory health effects. This review explores in detail the physico-chemical properties of diesel particulate matter (DPM), and identifies the constituents of this pollution source that are responsible for the development of respiratory disease. In particular, this review shows that the DPM surface area and adsorbed organic compounds play a significant role in manifesting chemical and cellular processes that if sustained can lead to the development of adverse respiratory health effects. The mechanisms of injury involved included: inflammation, innate and acquired immunity, and oxidative stress. Understanding the mechanisms of lung injury from DPM will enhance efforts to protect at-risk individuals from the harmful respiratory effects of air pollutants.
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Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1=n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal. Funding source Cancer Australia (Department of Health and Ageing) Research Grant 614217
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Twitter is now well-established as an important platform for real-time public communication. Twitter research continues to lag behind these developments, with many studies remaining focused on individual case studies and utilizing home-grown, idiosyncratic, non-repeatable, and non-verifiable research methodologies. While the development of a full-blown “science of Twitter” may remain illusory, it is nonetheless necessary to move beyond such individual scholarship and toward the development of more comprehensive, transferable, and rigorous tools and methods for the study of Twitter on a large scale and in close to real time.
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Our paper approaches Twitter through the lens of “platform politics” (Gillespie, 2010), focusing in particular on controversies around user data access, ownership, and control. We characterise different actors in the Twitter data ecosystem: private and institutional end users of Twitter, commercial data resellers such as Gnip and DataSift, data scientists, and finally Twitter, Inc. itself; and describe their conflicting interests. We furthermore study Twitter’s Terms of Service and application programming interface (API) as material instantiations of regulatory instruments used by the platform provider and argue for a more promotion of data rights and literacy to strengthen the position of end users.
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The aim of this work is to develop software that is capable of back projecting primary fluence images obtained from EPID measurements through phantom and patient geometries in order to calculate 3D dose distributions. In the first instance, we aim to develop a tool for pretreatment verification in IMRT. In our approach, a Geant4 application is used to back project primary fluence values from each EPID pixel towards the source. Each beam is considered to be polyenergetic, with a spectrum obtained from Monte Carlo calculations for the LINAC in question. At each step of the ray tracing process, the energy differential fluence is corrected for attenuation and beam divergence. Subsequently, the TERMA is calculated and accumulated to an energy differential 3D TERMA distribution. This distribution is then convolved with monoenergetic point spread kernels, thus generating energy differential 3D dose distributions. The resulting dose distributions are accumulated to yield the total dose distribution, which can then be used for pre-treatment verification of IMRT plans. Preliminary results were obtained for a test EPID image comprised of 100 9 100 pixels of unity fluence. Back projection of this field into a 30 cm9 30 cm 9 30 cm water phantom was performed, with TERMA distributions obtained in approximately 10 min (running on a single core of a 3 GHz processor). Point spread kernels for monoenergetic photons in water were calculated using a separate Geant4 application. Following convolution and summation, the resulting 3D dose distribution produced familiar build-up and penumbral features. In order to validate the dose model we will use EPID images recorded without any attenuating material in the beam for a number of MLC defined square fields. The dose distributions in water will be calculated and compared to TPS predictions.
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Dose kernels may be used to calculate dose distributions in radiotherapy (as described by Ahnesjo et al., 1999). Their calculation requires use of Monte Carlo methods, usually by forcing interactions to occur at a point. The Geant4 Monte Carlo toolkit provides a capability to force interactions to occur in a particular volume. We have modified this capability and created a Geant4 application to calculate dose kernels in cartesian, cylindrical, and spherical scoring systems. The simulation considers monoenergetic photons incident at the origin of a 3 m x 3 x 9 3 m water volume. Photons interact via compton, photo-electric, pair production, and rayleigh scattering. By default, Geant4 models photon interactions by sampling a physical interaction length (PIL) for each process. The process returning the smallest PIL is then considered to occur. In order to force the interaction to occur within a given length, L_FIL, we scale each PIL according to the formula: PIL_forced = L_FIL 9 (1 - exp(-PIL/PILo)) where PILo is a constant. This ensures that the process occurs within L_FIL, whilst correctly modelling the relative probability of each process. Dose kernels were produced for an incident photon energy of 0.1, 1.0, and 10.0 MeV. In order to benchmark the code, dose kernels were also calculated using the EGSnrc Edknrc user code. Identical scoring systems were used; namely, the collapsed cone approach of the Edknrc code. Relative dose difference images were then produced. Preliminary results demonstrate the ability of the Geant4 application to reproduce the shape of the dose kernels; median relative dose differences of 12.6, 5.75, and 12.6 % were found for an incident photon energy of 0.1, 1.0, and 10.0 MeV respectively.
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Purpose The aim of this study was to determine the early time course of exercise-induced signaling after divergent contractile activity associated with resistance and endurance exercise. Methods Sixteen male subjects were randomly assigned to either a cycling (CYC; n = 8, 60 min, 70% V?O2peak) or resistance (REX; n = 8, 8×5 leg extension, 80% one-repetition maximum, 3-min recovery) exercise group. Serial muscle biopsies were obtained from vastus lateralis at rest before, immediately after, and after 15, 30, and 60 min of passive recovery to determine early signaling responses after exercise. Results There were comparable increases from rest in AktThr308/Ser473 and mTORSer2448 phosphorylation during the postexercise time course that peaked 30-60 min after both CYC and REX (P<0.05). There were also similar patterns in p70S6K Thr389 and 4E-BP1Thr37/46 phosphorylation, but a greater magnitude of effect was observed for REX and CYC, respectively (P<0.05). However, AMPKThr172 phosphorylation was only significantly elevated after CYC (P<0.05), and we observed divergent responses for glycogen synthaseSer641 and AS160 phosphorylation that were enhanced after CYC but not REX (P<0.05). Conclusions We show a similar time course for Akt-mTOR-S6K phosphorylation during the initial 60-min recovery period after divergent contractile stimuli. Conversely, enhanced phosphorylation status of proteins that promote glucose transport and glycogen synthesis only occurred after endurance exercise. Our results indicate that endurance and resistance exercise initiate translational signaling, but high-load, low-repetition contractile activity failed to promote phosphorylation of pathways regulating glucose metabolism.
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The high burden of parental concern in children with chronic cough has been well documented. Acute cough in children (lasting less than 2 weeks) also has a significant impact on families, reflected by the number of doctor visits for cough. Currently there is no validated acute cough specific quality of life (QOL) measure for children. The objective of this study is to develop and validate an acute cough specific QOL questionnaire (PAC-QOL) for paediatric use. Here we present our data on item selection. Methods Two independent focus groups were conducted to determine relevant items. Parents discussed the impact of their child’s current or previous episodes of acute cough on their child, themselves and their family functioning. Transcripts were analyzed to determine whether discussions had reached an item saturation point. Items were also compared against our previously validated parent-centred children’s chronic cough specific QOL questionnaire (PC-QOL), which was used as a model. The newly developed acute cough specific QOL questionnaire is designed to assess the level of frequency of parents’ feelings and worry related to their child’s acute cough, using a 24-h time-point reference. Results Newly identified acute cough specific items include parental worry around whether or not they should take their child to a doctor or emergency department, and frequency of seeking assistance from friends and family. Conclusions While there are similarities between items identified for both acute and chronic cough, there are distinct features. Further data will be collected for item reduction and validation of this children’s acute cough specific QOL questionnaire.
Resumo:
Background: Findings from the phase 3 FLEX study showed that the addition of cetuximab to cisplatin and vinorelbine significantly improved overall survival, compared with cisplatin and vinorelbine alone, in the first-line treatment of EGFR-expressing, advanced non-small-cell lung cancer (NSCLC). We investigated whether candidate biomarkers were predictive for the efficacy of chemotherapy plus cetuximab in this setting. Methods: Genomic DNA extracted from formalin-fixed paraffin-embedded (FFPE) tumour tissue of patients enrolled in the FLEX study was screened for KRAS codon 12 and 13 and EGFR kinase domain mutations with PCR-based assays. In FFPE tissue sections, EGFR copy number was assessed by dual-colour fluorescence in-situ hybridisation and PTEN expression by immunohistochemistry. Treatment outcome was investigated according to biomarker status in all available samples from patients in the intention-to-treat population. The primary endpoint in the FLEX study was overall survival. The FLEX study, which is ongoing but not recruiting participants, is registered with ClinicalTrials.gov, number NCT00148798. Findings: KRAS mutations were detected in 75 of 395 (19%) tumours and activating EGFR mutations in 64 of 436 (15%). EGFR copy number was scored as increased in 102 of 279 (37%) tumours and PTEN expression as negative in 107 of 303 (35%). Comparisons of treatment outcome between the two groups (chemotherapy plus cetuximab vs chemotherapy alone) according to biomarker status provided no indication that these biomarkers were of predictive value. Activating EGFR mutations were identified as indicators of good prognosis, with patients in both treatment groups whose tumours carried such mutations having improved survival compared with those whose tumours did not (chemotherapy plus cetuximab: median 17·5 months [95% CI 11·7-23·4] vs 8·5 months [7·1-10·8], hazard ratio [HR] 0·52 [0·32-0·84], p=0·0063; chemotherapy alone: 23·8 months [15·2-not reached] vs 10·0 months [8·7-11·0], HR 0·35 [0·21-0·59], p<0·0001). Expression of PTEN seemed to be a potential indicator of good prognosis, with patients whose tumours expressed PTEN having improved survival compared with those whose tumours did not, although this finding was not significant (chemotherapy plus cetuximab: median 11·4 months [8·6-13·6] vs 6·8 months [5·9-12·7], HR 0·80 [0·55-1·16], p=0·24; chemotherapy alone: 11·0 months [9·2-12·6] vs 9·3 months [7·6-11·9], HR 0·77 [0·54-1·10], p=0·16). Interpretation: The efficacy of chemotherapy plus cetuximab in the first-line treatment of advanced NSCLC seems to be independent of each of the biomarkers assessed. Funding: Merck KGaA. © 2011 Elsevier Ltd.