471 research outputs found

    Metabolic alterations during the growth of tumour spheroids

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    Solid tumours undergo considerable alterations in their metabolism of nutrients in order to generate sufficient energy and biomass for sustained growth and proliferation. During growth, the tumour microenvironment exerts a number of influences (e.g. hypoxia and acidity) that affect cellular biology and the flux or utilisation of fuels including glucose. The tumour spheroid model was used to characterise the utilisation of glucose and describe alterations to the activity and expression of key glycolytic enzymes during the tissue growth curve. Glucose was avidly consumed and associated with the production of lactate and an acidified medium, confirming the reliance on glycolytic pathways and a diminution of oxidative phosphorylation. The expression levels and activities of hexokinase, phosphofructokinase-1, pyruvate kinase and lactate dehydrogenase in the glycolytic pathway were measured to assess glycolytic capacity. Similar measurements were made for glucose-6-phosphate dehydrogenase, the entry point and regulatory step of the pentose-phosphate pathway (PPP) and for cytosolic malate dehydrogenase, a key link to TCA cycle intermediates. The parameters for these key enzymes were shown to undergo considerable variation during the growth curve of tumour spheroids. In addition, they revealed that the dynamic alterations were influenced by both transcriptional and posttranslational mechanisms

    Metabolic alterations during the growth of tumour spheroids

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    Solid tumours undergo considerable alterations in their metabolism of nutrients in order to generate sufficient energy and biomass for sustained growth and proliferation. During growth, the tumour microenvironment exerts a number of influences (e.g. hypoxia and acidity) that affect cellular biology and the flux or utilisation of fuels including glucose. The tumour spheroid model was used to characterise the utilisation of glucose and describe alterations to the activity and expression of key glycolytic enzymes during the tissue growth curve. Glucose was avidly consumed and associated with the production of lactate and an acidified medium, confirming the reliance on glycolytic pathways and a diminution of oxidative phosphorylation. The expression levels and activities of hexokinase, phosphofructokinase-1, pyruvate kinase and lactate dehydrogenase in the glycolytic pathway were measured to assess glycolytic capacity. Similar measurements were made for glucose-6-phosphate dehydrogenase, the entry point and regulatory step of the pentose-phosphate pathway (PPP) and for cytosolic malate dehydrogenase, a key link to TCA cycle intermediates. The parameters for these key enzymes were shown to undergo considerable variation during the growth curve of tumour spheroids. In addition, they revealed that the dynamic alterations were influenced by both transcriptional and posttranslational mechanisms

    Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants

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    BACKGROUND: Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. METHODS: A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. RESULTS: CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0–1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data originally used for the development of the prediction tool. CONCLUSION: State-of-the-art, machine-learning methods can be employed for the development of sophisticated tools to aid clinicians' decisions. We identified numerous variables considered relevant for extubation decisions for mechanically ventilated premature infants with RDS. We then developed a web-based decision-support tool for clinicians which can be made widely available and potentially improve patient care world wide

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

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    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

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    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

    X-ray emission from the Sombrero galaxy: discrete sources

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    We present a study of discrete X-ray sources in and around the bulge-dominated, massive Sa galaxy, Sombrero (M104), based on new and archival Chandra observations with a total exposure of ~200 ks. With a detection limit of L_X = 1E37 erg/s and a field of view covering a galactocentric radius of ~30 kpc (11.5 arcminute), 383 sources are detected. Cross-correlation with Spitler et al.'s catalogue of Sombrero globular clusters (GCs) identified from HST/ACS observations reveals 41 X-rays sources in GCs, presumably low-mass X-ray binaries (LMXBs). We quantify the differential luminosity functions (LFs) for both the detected GC and field LMXBs, whose power-low indices (~1.1 for the GC-LF and ~1.6 for field-LF) are consistent with previous studies for elliptical galaxies. With precise sky positions of the GCs without a detected X-ray source, we further quantify, through a fluctuation analysis, the GC LF at fainter luminosities down to 1E35 erg/s. The derived index rules out a faint-end slope flatter than 1.1 at a 2 sigma significance, contrary to recent findings in several elliptical galaxies and the bulge of M31. On the other hand, the 2-6 keV unresolved emission places a tight constraint on the field LF, implying a flattened index of ~1.0 below 1E37 erg/s. We also detect 101 sources in the halo of Sombrero. The presence of these sources cannot be interpreted as galactic LMXBs whose spatial distribution empirically follows the starlight. Their number is also higher than the expected number of cosmic AGNs (52+/-11 [1 sigma]) whose surface density is constrained by deep X-ray surveys. We suggest that either the cosmic X-ray background is unusually high in the direction of Sombrero, or a distinct population of X-ray sources is present in the halo of Sombrero.Comment: 11 figures, 5 tables, ApJ in pres

    Compressed representation of a partially defined integer function over multiple arguments

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    In OLAP (OnLine Analitical Processing) data are analysed in an n-dimensional cube. The cube may be represented as a partially defined function over n arguments. Considering that often the function is not defined everywhere, we ask: is there a known way of representing the function or the points in which it is defined, in a more compact manner than the trivial one

    Performance of the CMS Cathode Strip Chambers with Cosmic Rays

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    The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

    Molecular Dynamics of Mesophilic-Like Mutants of a Cold-Adapted Enzyme: Insights into Distal Effects Induced by the Mutations

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    Networks and clusters of intramolecular interactions, as well as their “communication” across the three-dimensional architecture have a prominent role in determining protein stability and function. Special attention has been dedicated to their role in thermal adaptation. In the present contribution, seven previously experimentally characterized mutants of a cold-adapted α-amylase, featuring mesophilic-like behavior, have been investigated by multiple molecular dynamics simulations, essential dynamics and analyses of correlated motions and electrostatic interactions. Our data elucidate the molecular mechanisms underlying the ability of single and multiple mutations to globally modulate dynamic properties of the cold-adapted α-amylase, including both local and complex unpredictable distal effects. Our investigation also shows, in agreement with the experimental data, that the conversion of the cold-adapted enzyme in a warm-adapted variant cannot be completely achieved by the introduction of few mutations, also providing the rationale behind these effects. Moreover, pivotal residues, which are likely to mediate the effects induced by the mutations, have been identified from our analyses, as well as a group of suitable candidates for protein engineering. In fact, a subset of residues here identified (as an isoleucine, or networks of mesophilic-like salt bridges in the proximity of the catalytic site) should be considered, in experimental studies, to get a more efficient modification of the features of the cold-adapted enzyme
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