Public Articles
Bootstrap Distillation: Non-parametric Internal Validation of GWAS Results by Subgroup Resampling
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Personalised medical treatment based on genome profiles is a major goal of genetic research in the 21st century \citep[see][]{avery09,province08}. However, complex genotype-environment interactions for common diseases make it difficult to determine which specific genetic features should be used to construct such profiles. Hence the prediction of genetic risk is a major challenge of the 21st century.
The introduction of large-scale Single Nucleotide Polymorphism (SNP) genotyping systems has enabled genetic variants to be typed en-masse, shifting the main effort required in a genetic risk study from genotyping to data analysis (or bioinformatics). Here we investigate genetic markers for Type 1 Diabetes (T1D), demonstrating how a population sub-sampling method may assist in the identification of risk markers for a complex disease.
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Type 1 Diabetes mellitus (T1D) is a disorder typically characterised by an absence of insulin-producing beta cells in the pancreas, either through loss of the cells themselves, or through the reduction in capacity of the cells to produce insulin \citep[see][]{atkinson14}. This disorder shares with the more common Type 2 Diabetes mellitus (T2D) a characteristic symptom of high blood glucose levels. In some cases, this glucose also passes through to the urine, creating a sticky/sweet substance that attracts ants \citep[see][pp. 7,11]{ekoe02}. In T2D, this high blood glucose is caused by cells not responding to insulin (insulin resistance), while in T1D the excess is caused by a reduction in insulin production (insulin dependence).
The incidence of T1D varies throughout the world, with rates of incidence as low as 0.0006% per year in China, 0.02% in the UK, up to nearly 0.05% per year in Finland. About 50-60% of cases of T1D manifest in childhood (younger than 18 years), and the disease is believed to be caused by an abnormal immune response after exposure to environmental triggers such as viruses, toxins or food \citep[see][]{daneman06}. While a spring birth is correlated with T1D risk, the diagnosis of Type 1 Diabetes is more common in autumn and winter \citep[see][]{atkinson14}.
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Typical symptoms of T1D include excess urine output (polyuria), thirst and increased fluid intake (polydypsia),blurred vision, and weight loss. When left untreated, this form of diabetes can lead to a build-up of ketone bodies and a reduction of blood pH (ketoacidosis), reducing mental faculties and causing a loss of consciousness \citep[see][p. 7]{ekoe02}.
Diabetes can be diagnosed by a single random1 blood glucose test, as long as symptoms are present and blood glucose levels are found to be in excess (typically >11.1 mmol l−1) of those normally observed. In situations where symptoms are less obvious and/or glucose levels are at the high end of the normal range, a glucose tolerance test (GTT) is used for diagnosis. In this test, fasting patients have their blood glucose level tested, patients then consume a measured dose of oral glucose, and blood glucose levels are measured 2 hours later. A fasting glucose level in excess of 6.1 mmol l−1, or post-load level in excess of 11.1 mmol l−1 is considered diagnostic for both forms of Diabetes Mellitus. Type 1 Diabetes (as distinct from T2D) encompasses a range of diseases that involve autoimmunity. It can be diagnosed by the presence of antibodies to glutamic acid decarboxylase, islet cells, insulin, or ICA512 \citep[see][p. 19]{ekoe02}.
As the symptoms of T1D are caused by high blood glucose levels (hyperglycaemia) due to a lack of insulin, these symptoms can be relieved by the introduction of insulin into the blood. This is typically carried out by supplying measured doses of insulin via intramuscular injections or by the use of insulin pumps \citep[see][]{daneman06}. Individuals with T1D need a constant supply of insulin for survival, together with occasional insulin bursts to control variable blood glucose levels throughout the day (e.g. after meals). In contrast, individuals with T2D only require insulin for survival in rare cases \citep[see][p. 16]{ekoe02}. Slow-release insulin and consumption of foods with a low glycaemic index can help to reduce the extremes of T1D symptoms.
Improperly managed treatment can cause further medical complications in a diabetic patient. Too much insulin, excessive physical activity, or not enough dietary sugar can result in low blood glucose levels (hypoglycaemia), which produce short-term autonomic and neurological problems such as trembling, dizziness, blurred vision, and difficulty concentrating. Hypoglycaemia is treated either by ingestion of sugar, or by intravenous glucose in severe cases \citep[see][]{daneman06}.
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The initial symptoms of T1D are not usually severe, and the disease may progress for a few years before a diagnosis is made and treatment is given. However, long-term complications can appear when the disease is not managed appropriately \cite[see][p. 8]{ekoe02}. Retinal damage progresses in about 20-25% of individuals with T1D, with later stages causing retinal detachment and consequent loss of sight. Renal failure is also a problem in diabetic individuals, which is indicated by high urinary protein levels. When individuals have these high levels, progression to end-stage renal disease occurs in about 50% of cases. Neural defects are also a potential complication of T1D, most commonly damage to peripheral nerves, leading to ulceration, poor healing and gangrene unless good care is taken of the body extremities \citep[see][]{daneman06}.
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Type 1 Diabetes has a heritability of around 88% \cite{hyttinen03}, indicating that a substantial proportion of variance in disease susceptibility can be attributed to genetic factors. About 50% of the genetic contribution to T1D can be accounted for by variation in the HLA region on chromosome 6, and 15% is accounted for by variation in two other genes, IDDM2 and IDDM12 \citep[see][]{daneman06}. Incidence rates in migrant populations quickly converge to those of the background population, suggesting that although the genetic contribution to the disease is high, environmental factors probably play a significant role in triggering the onset of disease \citep[see][]{daneman06}.
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The Wellcome Trust Case Control Consortium (WTCCC, http://www.wtccc.org.uk) was established in 2005 to identify novel genetic variants associated with seven common diseases, including Type 1 Diabetes \cite{wellcome07}. 2000 individuals with T1D, and 1500 individuals from the National Blood Service (NBS)2 were genotyped for the WTCCC using an Affymetrix GeneChip 500k Mapping Array Set.
The \citet{wellcome07} reported associations near five gene regions that had been previously associated with T1D: The major histocompatibility complex (MHC) on chromosome 6, CTLA4 and IFIH1 on chromosome 2, PTPN22 on chromosome 1, and IL2RA on chromosome 10. The insulin gene (INS) on chromosome 11 was also associated with T1D; the only SNP tagging INS failed quality control filters, but also indicated strong association with T1D when examined. A number of other regions showed evidence of association with T1D in the \citet{wellcome07} study: 4q27 (chromosome 4); 10p15 (chromosome 10); 12p13, 12q13 and 12q24 (chromosome 12) 16p13 (chromosome 16); and 18p11 (chromosome 18). Most of these regions include genes involved in the immune system. However, only two genes are in 16p13, and both have unknown functions (KIAA0350 and dexamethasone-induced transcript). The strongest association signal for T1D was detected within the HLA region of chromosome 6, a region in which multiple SNPs had strong associations with T1D, but only one of those SNPs (rs9272346) was reported in the results table of the strongest associations \citep[see][table 3]{wellcome07}.
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The Genome-wide Association Study (GWAS) is a common method for discovering genetic contributions to complex human diseases. The outcome of these studies is to determine the degree of association between single genetic markers and a heritable trait. Commonly, an analysis is carried out on a large number of genetic variants in a large number of people, allowing the detection of small genetic effects that are associated with a trait. In recent years, an initial search for variants is carried out by whole-genome sequencing in a small sub-population to identify variants that are common in the population of interest.
A study style that is built around correlation and association rather than a hunt for causal variants requires extreme care to ensure that observed associations are valid and causal. Studies need to have good within-study validation to reduce the likelihood of false-positive results being obtained and treated as true associations, and need to be supported by good independent validation. The distinction between association and causation is important – GWAS are used as hypothesis-generating tools to narrow down, through association, the search for potential causative loci. After the associations have been validated, it is expected that they will be followed up with studies attempting to determine the true causative status of that association. Such causative studies are difficult, and progress towards understanding the aetiology of common disease has been slow \citep[see][]{dermitzakis09}.
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Natural variation of genotypes within populations means that any particular sample from the population may not represent the true genotype frequencies within that population. This may lead to the observation of marker-disease associations when no such association exists. This is particularly important when considering populations with mixed ancestry, where markers that are informative for distinguishing population ancestry may become accidentally associated with a particular disease \citep[see][]{pritchard01}.
Bootstrapping by repeated re-sampling of a representative draw made from a group can estimate population variation in genotype frequencies by observing variation within the sub-samples. A re-sampling technique, as presented here, can reduce the influence of allele frequency variation by excluding false-positive results that are specific for particular samplings of the population.
177B Paper
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AnakBertanya.com -- Mengapa ada petir saat letusan gunung api?
CE264 Problem Set 1- Jan 31, 2017
Mechanical Designs of Active Upper-Limb Exoskeleton Robots
This report will explain the article written by Kazuo Kiguchi about the state of art and different difficulties on the designs of upper-limb exoskeleton robots. This document called Mechanical Designs of Active Upper-Limb Exoskeleton Robots and published at the IEEE 11th International Conference on Rehabilitation Robotics in 2009, explains the anatomy analysis necessary to develop this type of exoskeleton, their requirements and characteristics to be useful and the design obstacles at the moment of the conception. Also it explains the methods used to evaluate the performance of the exoskeleton and makes a review of different designs of active upper-limb exoskeleton robots developed.
Kazuo Kiguchi, professor in Systems and Control at Kyushu University, Doctor of Engineering specialized on Robotics and Biorobotics.
Paper 2 Reliability and maintenance
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Métodos Matemáticos II Apunte del Curso 11Cuakquier error en el apunte por favor enviar un mail a cualquiera de los siguientes correos: [email protected] [email protected] [email protected] [email protected]
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Collaborative robotics and field deployment
The ISOLDE LEGO® Robot: Playing with nuclear physics or The ISOLDE LEGO® Robot: Building interest in nuclear physics ?
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An outreach programme centred around nuclear physics making use of a LEGO Mindstorm kit is presented. It consists in a presentation given by trained undergraduate students as science ambassadors followed by a workshop where the target audience manipulates the LEGO Mindstorm robots to familiarise themselves with the concepts in an interactive and exciting way. This programme has been coupled to the CERN-ISOLDE 50th anniversary and the launch of the CERN-MEDICIS facility in Geneva, Switzerland. The modular aspect of the programme readily allows its application to other topics.
Without Data, Are We Just Telling Nice Stories?
"If people had deposited raw data and full protocols at the time of publication, we wouldn’t have to go back to the original authors," says Iorns. That would make it much easier for scientists to truly check each other’s work.- The Atlantic
État des travaux
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Approaches to KBE Design
Collaborative learning environments generally follow either of two models. One is a message model, derived from e-mail and bulletin boards and extended to threaded discussions. “The most common element... is the discussion forum” that “allows people to respond to notes posted by one another. Typically there is a thread of responses to posted notes, with a tree of divergent opinions” (Stahl, 2000). In this model, messages appear in a serial or downward-branching order, as they do in conversation; they are typically unmodifiable - in fact, the only thing participants can do with them is respond with other messages. The other is a folder model, based on the familiar Macintosh and Windows desktops, expanded to accommodate shared folders. In this model the basic units are notes or documents, with some affordances for annotation, and the organizational framework is that of a filing cabinet. Neither of these models is based on any theory of learning, knowledge creation, or collaborative action. Instead, their basis is technical-taking an existing technology and repurposing it to serve educational needs.
[…] A focus on toolsets is especially unfortunate if it is constrained by arbitrary characteristics of message- and folder-based technologies. There has been one short-lived effort to design the KBE “killer ap” through agreement on a set of interoperable tools that would combine to constitute such an application. A component-oriented approach to software design makes good sense at the programming level, but when applied at the level of functional design it tends to result in what critics call “featuritis” - a proliferation of individually attractive features that cumulatively defeat the basic purpose of the software.
[…] There are vast differences between CSILE’s oft-cited components, and implementations in other environments. For example, its knowledge building discourse, including co-authorship of notes and views, is fundamentally different from threaded discussion; its scaffolds differ in design, function, and goals from the prompts, hints, and templates that are referred to as scaffolds in other environments; its community knowledge spaces reflect the socio-cultural underpinnings of idea advancement, designed to support the central workings of knowledge creating organizations, with ideas living and growing there. Knowledge Forum® (second-generation CSILE) reflects the further development of knowledge building theory based on extensive research with CSILE. It adds a second layer of knowledge building activity in the form of rise-above notes and views that encourage higher-order knowledge constructions, means for representing ideas in multiple contexts, and coherence-producing resources such as automatic referencing and linking of notes from different views and external sources.
Nonlinear Dimensionality Reduction by Locally Linear Embedding
This report will explain the article written by Sam T. Roweis and Lawrence K. Saul about the Locally Linear Embedding (LLE) algorithm used for the analysis and visualization of big amounts of data. This document called Nonlinear Dimensionality Reduction by Locally Linear Embedding and published at the American Association for the Advancement of Science in 2000, shows how the use of this algorithm improves the problem of dimensionality reduction mapping the inputs into a coordinate to be applied in nonlinear manifold data.
Sam T. Roweis, associate professor in Department of Computer Science at the University of Toronto since 2006, is a Research Scientist & Consultant for Google. And Lawrence K. Saul, professor in Department of Computer Science and Engineering at the UC San Diego since 2006, is now focused on applications of machine learning to problems in computer systems and security.
Hard X-Ray Emission from Partially Occulted Solar Flares
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Where is the centroid of a half-\(n\)-ball?
At Centroids of semicircles and hemispheres, Nick Berry deduces the formulas for coordinates of a centroid of a unit half-circle and a half-ball (in 3D) centered at origin. In fact, he does it for general r, but since only the ratio with r is important at the end, we can without loss of generality assume r = 1. Of course, only one coordinate is nontrivial (the one in which the ball is sliced in half), the rest are zeros. He expresses his surprise at the fact that the half-circle has an irrational coordinate for the centroid, while the half-ball has a rational one. Since deducing general patterns from just 2 samples is very error-prone, we’ll explore the situation in higher dimensions, to see whether irrational or rational centroid coordinate is a surprising—or perhaps none of them are.
The formula for the centroid coordinates is well-known: every coordinate is the average value of that coordinate accross all the points in the body, usually computed via an integral. Also, the integral can be calculated with respect to the coordinate itself, giving the formula
\begin{equation} C_i = \frac{\int x_iS_i(x_i)\,dx_i}{\int S_i(x_i)\,dx_i} \end{equation}
Durée antibiothérapie des maladies courantes, dernières recommandations Infections SNC
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Chemistry Project
This experiment involves an Iodine clock reaction, using Peroxidisulfate(VI) ions and Iodide ions in solution to form Sulfate(VI) ions and iodine: \begin{equation}
S_2O_8^{2-}(\textup{aq}) + 2I^-(\textup{aq})\rightarrow SO_4^{2-}(\textup{aq})+I_2(\textup{aq})
\end{equation} As both of the reactants are colourless, the progress of the reaction is shown by the blue colour of the Iodine. If starch is added, this becomes clear.
To measure the rate of the reaction, the time for a set amount of Iodine to be produced can be measured. To do this, Thiosulfate(VI) ions were added to the reaction mixture. These turn Iodine back into Iodide ions, so no Iodine will be evident until all the Thiosulfate is used up. \begin{equation}
2S_2O_3^{2-}(\textup{aq})+I_2(\textup{aq})\rightarrow S_4O_6^{2-}(\textup{aq})+2I^-(\textup{aq})
\end{equation} This will result in a sudden blue colour. The time for this colour to appear will be quantified as the rate of the reaction.
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Topics for Physics Lab Works Using X-ray Microtomography and Micro-Diffraction
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EncoMPASS: an Encyclopedia of Membrane Proteins Analyzed by Structure and Symmetry
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How to compose a scholarly article in Authorea
Protein expression as an environmental assay in two commercial aquaculture species
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