600 resultados para descent
Resumo:
La population canadienne-française a une histoire démographique unique faisant d’elle une population d’intérêt pour l’épidémiologie et la génétique. Cette thèse vise à mettre en valeur les caractéristiques de la population québécoise qui peuvent être utilisées afin d’améliorer la conception et l’analyse d’études d’épidémiologie génétique. Dans un premier temps, nous profitons de la présence d’information généalogique détaillée concernant les Canadiens français pour estimer leur degré d’apparentement et le comparer au degré d’apparentement génétique. L’apparentement génétique calculé à partir du partage génétique identique par ascendance est corrélé à l’apparentement généalogique, ce qui démontre l'utilité de la détection des segments identiques par ascendance pour capturer l’apparentement complexe, impliquant entre autres de la consanguinité. Les conclusions de cette première étude pourront guider l'interprétation des résultats dans d’autres populations ne disposant pas d’information généalogique. Dans un deuxième temps, afin de tirer profit pleinement du potentiel des généalogies canadienne-françaises profondes, bien conservées et quasi complètes, nous présentons le package R GENLIB, développé pour étudier de grands ensembles de données généalogiques. Nous étudions également le partage identique par ascendance à l’aide de simulations et nous mettons en évidence le fait que la structure des populations régionales peut faciliter l'identification de fondateurs importants, qui auraient pu introduire des mutations pathologiques, ce qui ouvre la porte à la prévention et au dépistage de maladies héréditaires liées à certains fondateurs. Finalement, puisque nous savons que les Canadiens français ont accumulé des segments homozygotes, à cause de la présence de consanguinité lointaine, nous estimons la consanguinité chez les individus canadiens-français et nous étudions son impact sur plusieurs traits de santé. Nous montrons comment la dépression endogamique influence des traits complexes tels que la grandeur et des traits hématologiques. Nos résultats ne sont que quelques exemples de ce que nous pouvons apprendre de la population canadienne-française. Ils nous aideront à mieux comprendre les caractéristiques des autres populations de même qu’ils pourront aider la recherche en épidémiologie génétique au sein de la population canadienne-française.
Resumo:
Red blood cells (RBCs) are key players in systemic oxygen transport. RBCs respond to in vitro hypoxia through the so-called oxygen-dependent metabolic regulation, which involves the competitive binding of deoxyhemoglobin and glycolytic enzymes to the N-terminal cytosolic domain of band 3. This mechanism promotes the accumulation of 2,3-DPG, stabilizing the deoxygenated state of hemoglobin, and cytosol acidification, triggering oxygen off-loading through the Bohr effect. Despite in vitro studies, in vivo adaptations to hypoxia have not yet been completely elucidated. Within the framework of the AltitudeOmics study, erythrocytes were collected from 21 healthy volunteers at sea level, after exposure to high altitude (5260m) for 1, 7 and 16days, and following reascent after 7days at 1525m. UHPLC-MS metabolomics results were correlated to physiological and athletic performance parameters. Immediate metabolic adaptations were noted as early as a few hours from ascending to >5000m, and maintained for 16 days at high altitude. Consistent with the mechanisms elucidated in vitro, hypoxia promoted glycolysis and deregulated the pentose phosphate pathway, as well purine catabolism, glutathione homeostasis, arginine/nitric oxide and sulphur/H2S metabolism. Metabolic adaptations were preserved one week after descent, consistently with improved physical performances in comparison to the first ascendance, suggesting a mechanism of metabolic memory.
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Dynamics of biomolecules over various spatial and time scales are essential for biological functions such as molecular recognition, catalysis and signaling. However, reconstruction of biomolecular dynamics from experimental observables requires the determination of a conformational probability distribution. Unfortunately, these distributions cannot be fully constrained by the limited information from experiments, making the problem an ill-posed one in the terminology of Hadamard. The ill-posed nature of the problem comes from the fact that it has no unique solution. Multiple or even an infinite number of solutions may exist. To avoid the ill-posed nature, the problem needs to be regularized by making assumptions, which inevitably introduce biases into the result.
Here, I present two continuous probability density function approaches to solve an important inverse problem called the RDC trigonometric moment problem. By focusing on interdomain orientations we reduced the problem to determination of a distribution on the 3D rotational space from residual dipolar couplings (RDCs). We derived an analytical equation that relates alignment tensors of adjacent domains, which serves as the foundation of the two methods. In the first approach, the ill-posed nature of the problem was avoided by introducing a continuous distribution model, which enjoys a smoothness assumption. To find the optimal solution for the distribution, we also designed an efficient branch-and-bound algorithm that exploits the mathematical structure of the analytical solutions. The algorithm is guaranteed to find the distribution that best satisfies the analytical relationship. We observed good performance of the method when tested under various levels of experimental noise and when applied to two protein systems. The second approach avoids the use of any model by employing maximum entropy principles. This 'model-free' approach delivers the least biased result which presents our state of knowledge. In this approach, the solution is an exponential function of Lagrange multipliers. To determine the multipliers, a convex objective function is constructed. Consequently, the maximum entropy solution can be found easily by gradient descent methods. Both algorithms can be applied to biomolecular RDC data in general, including data from RNA and DNA molecules.
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Numerous epidemiological findings suggest that we live in an era that can only be described as the “age of melancholy” in that more and more individuals are diagnosed with depression every year. The aim of this study was to gain a phenomenological understanding of how individuals who experienced depression understood and made sense of their experience of depression through a methodology of interpretative phenomenological analysis. In-depth semi-structured interviews explored the lived experience of depression for eight individuals and identified how social discourses contributed to their understanding. Following rigorous analysis of twelve interview transcripts, data was broken down into four recurrent superordinate themes which related directly to how individuals made sense of their experience of depression; The Descent; The Worlds Conversations and Me - Engagement with Social Discourses; Broken Self - Transforming the Self; Embracing myself and my Mind - Transformation of the Self. Further interrogative analysis identified how some social discourses communicated by healthcare professionals, the media and academia, contributed to individuals experiencing an additional layer of distress, namely meta-distress which in essence is distress about distress.
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La population canadienne-française a une histoire démographique unique faisant d’elle une population d’intérêt pour l’épidémiologie et la génétique. Cette thèse vise à mettre en valeur les caractéristiques de la population québécoise qui peuvent être utilisées afin d’améliorer la conception et l’analyse d’études d’épidémiologie génétique. Dans un premier temps, nous profitons de la présence d’information généalogique détaillée concernant les Canadiens français pour estimer leur degré d’apparentement et le comparer au degré d’apparentement génétique. L’apparentement génétique calculé à partir du partage génétique identique par ascendance est corrélé à l’apparentement généalogique, ce qui démontre l'utilité de la détection des segments identiques par ascendance pour capturer l’apparentement complexe, impliquant entre autres de la consanguinité. Les conclusions de cette première étude pourront guider l'interprétation des résultats dans d’autres populations ne disposant pas d’information généalogique. Dans un deuxième temps, afin de tirer profit pleinement du potentiel des généalogies canadienne-françaises profondes, bien conservées et quasi complètes, nous présentons le package R GENLIB, développé pour étudier de grands ensembles de données généalogiques. Nous étudions également le partage identique par ascendance à l’aide de simulations et nous mettons en évidence le fait que la structure des populations régionales peut faciliter l'identification de fondateurs importants, qui auraient pu introduire des mutations pathologiques, ce qui ouvre la porte à la prévention et au dépistage de maladies héréditaires liées à certains fondateurs. Finalement, puisque nous savons que les Canadiens français ont accumulé des segments homozygotes, à cause de la présence de consanguinité lointaine, nous estimons la consanguinité chez les individus canadiens-français et nous étudions son impact sur plusieurs traits de santé. Nous montrons comment la dépression endogamique influence des traits complexes tels que la grandeur et des traits hématologiques. Nos résultats ne sont que quelques exemples de ce que nous pouvons apprendre de la population canadienne-française. Ils nous aideront à mieux comprendre les caractéristiques des autres populations de même qu’ils pourront aider la recherche en épidémiologie génétique au sein de la population canadienne-française.
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In the Bahamas, ELLs consist mainly of Haitian descent students. Unfortunately, this demographic of students continuously score below their Bahamian counterparts in Creative Writing. This research examined the affects the 6 + 1 Writing Traits assessment had on the attitudes and writing abilities of fifteen, fifth grade, Haitian descent students.
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Invasive species allow an investigation of trait retention and adaptations after exposure to new habitats. Recent work on corals from the Gulf of Aqaba (GoA) shows that tolerance to high temperature persists thousands of years after invasion, without any apparent adaptive advantage. Here we test whether thermal tolerance retention also occurs in another symbiont-bearing calcifying organism. To this end, we investigate the thermal tolerance of the benthic foraminifera Amphistegina lobifera from the GoA (29° 30.14167 N 34° 55.085 E) and compare it to a recent "Lessepsian invader population" from the Eastern Mediterranean (EaM) (32° 37.386 N, 34°55.169 E). We first established that the studied populations are genetically homogenous but distinct from a population in Australia, and that they contain a similar consortium of diatom symbionts, confirming their recent common descent. Thereafter, we exposed specimens from GoA and EaM to elevated temperatures for three weeks and monitored survivorship, growth rates and photophysiology. Both populations exhibited a similar pattern of temperature tolerance. A consistent reduction of photosynthetic dark yields was observed at 34°C and reduced growth was observed at 32°C. The apparent tolerance to sustained exposure to high temperature cannot have a direct adaptive importance, as peak summer temperatures in both locations remain <32°C. Instead, it seems that in the studied foraminifera tolerance to high temperature is a conservative trait and the EaM population retained this trait since its recent invasion. Such pre-adaptation to higher temperatures confers A. lobifera a clear adaptive advantage in shallow and episodically high temperature environments in the Mediterranean under further warming.
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Ten-month time series of mean volume backscattering strength (MVBS) and vertical velocity obtained from three moored acoustic Doppler current profilers (ADCPs) deployed from February until December 2005 at 64°S, 66.5°S and 69°S along the Greenwich Meridian were used to analyse the diel vertical zooplankton migration (DVM) and its seasonality and regional variability in the Lazarev Sea. The estimated MVBS exhibited distinct patterns of DVM at all three mooring sites. Between February and October, the timing of the DVM and the residence time of zooplankton at depth were clearly governed by the day-night rhythm. Mean daily cycles of the ADCP-derived vertical velocity were calculated for successive months and showed maximum ascent and descent velocities of 16 and -15 mm/s. However, a change of the MVBS pattern occurred in late spring/early austral summer (October/November), when the zooplankton communities ceased their synchronous vertical migration at all three mooring sites. Elevated MVBS values were then concentrated in the uppermost layers (<50 m) at 66.5°S. This period coincided with the decay of sea ice coverage at 64°S and 66.5°S between early November and mid-December. Elevated chlorophyll concentrations, which were measured at the end of the deployment, extended from 67°S to 65°S and indicated a phytoplankton bloom in the upper 50 m. Thus, we propose that the increased food supply associated with an ice edge bloom caused the zooplankton communities to cease their DVM in favour of feeding.
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The real-time optimization of large-scale systems is a difficult problem due to the need for complex models involving uncertain parameters and the high computational cost of solving such problems by a decentralized approach. Extremum-seeking control (ESC) is a model-free real-time optimization technique which can estimate unknown parameters and can optimize nonlinear time-varying systems using only a measurement of the cost function to be minimized. In this thesis, we develop a distributed version of extremum-seeking control which allows large-scale systems to be optimized without models and with minimal computing power. First, we develop a continuous-time distributed extremum-seeking controller. It has three main components: consensus, parameter estimation, and optimization. The consensus provides each local controller with an estimate of the cost to be minimized, allowing them to coordinate their actions. Using this cost estimate, parameters for a local input-output model are estimated, and the cost is minimized by following a gradient descent based on the estimate of the gradient. Next, a similar distributed extremum-seeking controller is developed in discrete-time. Finally, we consider an interesting application of distributed ESC: formation control of high-altitude balloons for high-speed wireless internet. These balloons must be steered into a favourable formation where they are spread out over the Earth and provide coverage to the entire planet. Distributed ESC is applied to this problem, and is shown to be effective for a system of 1200 ballons subjected to realistic wind currents. The approach does not require a wind model and uses a cost function based on a Voronoi partition of the sphere. Distributed ESC is able to steer balloons from a few initial launch sites into a formation which provides coverage to the entire Earth and can maintain a similar formation as the balloons move with the wind around the Earth.
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BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk
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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.
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In this work we explore optimising parameters of a physical circuit model relative to input/output measurements, using the Dallas Rangemaster Treble Booster as a case study. A hybrid metaheuristic/gradient descent algorithm is implemented, where the initial parameter sets for the optimisation are informed by nominal values from schematics and datasheets. Sensitivity analysis is used to screen parameters, which informs a study of the optimisation algorithm against model complexity by fixing parameters. The results of the optimisation show a significant increase in the accuracy of model behaviour, but also highlight several key issues regarding the recovery of parameters.
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Reassembled, Slightly Askew is an autobiographical, immersive audio-based artwork based on Shannon Sickels’ experience of falling critically ill with a rare brain infection and her journey of rehabilitation with an acquired brain injury. Audience members experience Reassembled individually, listening to the audio via headphones while lying on a bed. The piece makes use of binaural microphone technology and spatial sound design techniques, causing listeners to feel they are inside Shannon’s head, viscerally experiencing her descent into coma, brain surgeries, early days in the hospital, and re-integration into the world with a hidden disability. It is a new kind of storytelling, never done before about this topic, that places the listener safely in the first-person perspective with the aim of increasing empathy and understanding. Reassembled… was made through a 5-year collaboration with an interdisciplinary team of artists led by Shannon Sickels (writer & performer), Paul Stapleton (composer & sound designer), Anna Newell (director), Hanna Slattne (dramaturgy), Stevie Prickett (choreography), and Shannon’s consultant neurosurgeon and head injury nurse. It’s development and production has been made possible with the support of a Wellcome Trust Arts Award, the Arts Council NI, Sonic Arts Research Centre, Belfast's Metropolitan Arts Centre, and grants from the Arts & Disability Award Ireland scheme. In its 2015 premiere year, Reassembled had 99 shows across Northern Ireland, including at the Cathedral Quarter Arts Festival (the MAC, Belfast) and BOUNCE Arts & Disability Forum Festival (Lyric Theatre, Belfast). It was awarded 5 stars in the Stage, a Hospital Club h100 Theatre & Performance Award, and been shared at medical conferences and trainings across the UK. It continues to be presented in diverse artistic and educational contexts, including as part of A Nation’s Theatre Festival in 2016 at Battersea Arts Centre in London where it was given 4 star reviews in the Guardian, Time Out London and the Evening Standard. "A real-life ordeal, captured by a daring, disorientating artistic collaboration, which works brilliantly on so many levels…It should be available on prescription.” — The Stage ★★★★★ www.reassembled.co.uk Audio clips and documentary footage available here: http://www.paulstapleton.net/portfolio/reassembled-slightly-askew
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Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD)1, 2. These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case–control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer’s disease in seven independent case–control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer’s disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer’s disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer’s disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.
Resumo:
Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.