896 resultados para ADAMS-TYPE CYCLIC METHODS


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Background: Type 2 diabetes is linked to several complications which add to both physical and mental distress. Depression is a common co-morbidity of diabetes which can occur both as a cause and a consequence of type 2 diabetes. Depression has been shown to correlate with glucose regulation and treating depression might prove beneficial for glucose regulation as well as for mental well being. Another complication which might affect diabetes management is cognitive decline. Several risk factors and complications of diabetes might modify the risk for developing cognitive impairment, which is increased 1.5 times among subjects with type 2 diabetes. Type 2 diabetes, depression and impaired cognitive performance have all been linked to low birth weight. This thesis aimed to explore the effects and interactions of birth weight, depression and cognitive ability in relation to type 2 diabetes from a life course perspective. Subjects and methods: Studies I, II and V were part of the Helsinki Birth Cohort Study. 2003 subjects participated in an extensive clinical examination at an average age of 61 years. A standard glucose tolerance test (OGTT) was performed and depressive symptoms were assessed using the Beck Depression Inventory (BDI). In addition data was obtained from child welfare clinics and national registers. A subset of the cohort (n=1247) also performed a test on cognitive performance (CogState ®) at the average age of 64. Studies III and IV were randomised clinical trials where mildly depressed diabetic subjects were treated with paroxetine or placebo and the effect on metabolic parameters and quality of life was assessed. The first trial included 14 women and lasted 10 weeks, while the second trial included 43 subjects, both men and women, and lasted 6 months. Results: Type 2 diabetes was positively associated with the occurrence of depressive symptoms. Among diabetic subjects 23.6% had depressive symptoms, compared to 16.7% of subjects with normal glucose tolerance (OR = 1.77, p<0.001). Formal mediation analysis revealed that cardiovascular disease (CVD) is likely to act as a mediator in the association. Furthermore, low birth weight was found to modify the association between type 2 diabetes, CVD and depression. The association between BDI score and having type 2 diabetes or CVD was twice as strong in the subgroup with low birth weight (≤ 2500g) compared with the group with birth weight > 2500g (p for interaction 0.058). In the six months long randomised clinical trial (study IV) paroxetine had a transient beneficial effect on glycosylated haemoglobin A1c (GHbA1c) and quality of life when compared to placebo after three months of treatment. In study V we found that subjects with known diabetes had a consistently poorer level of cognitive performance than subjects with normal glucose tolerance in most of the tested cognitive domains. This effect was further amplified among those born with a small birth weight (p for interaction 0.002). Conclusions: Type 2 diabetes is associated with a higher occurrence of depressive symptoms compared to subjects with normal glucose tolerance. This association is especially strong among subjects with CVD and those born with a low birth weight. Treating depressed diabetic subjects with paroxetine has no long term effect on glucose regulation. Physicians should be aware of depression as an important co-morbidity of type 2 diabetes. Both depression and the cognitive decline often seen among diabetic subjects are increased if the subject is born with a low birth weight. Physicians should recognise low birth weight as an additional risk factor and modifier of diabetic complications.

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The analysis of lipid compositions from biological samples has become increasingly important. Lipids have a role in cardiovascular disease, metabolic syndrome and diabetes. They also participate in cellular processes such as signalling, inflammatory response, aging and apoptosis. Also, the mechanisms of regulation of cell membrane lipid compositions are poorly understood, partially because a lack of good analytical methods. Mass spectrometry has opened up new possibilities for lipid analysis due to its high resolving power, sensitivity and the possibility to do structural identification by fragment analysis. The introduction of Electrospray ionization (ESI) and the advances in instrumentation revolutionized the analysis of lipid compositions. ESI is a soft ionization method, i.e. it avoids unwanted fragmentation the lipids. Mass spectrometric analysis of lipid compositions is complicated by incomplete separation of the signals, the differences in the instrument response of different lipids and the large amount of data generated by the measurements. These factors necessitate the use of computer software for the analysis of the data. The topic of the thesis is the development of methods for mass spectrometric analysis of lipids. The work includes both computational and experimental aspects of lipid analysis. The first article explores the practical aspects of quantitative mass spectrometric analysis of complex lipid samples and describes how the properties of phospholipids and their concentration affect the response of the mass spectrometer. The second article describes a new algorithm for computing the theoretical mass spectrometric peak distribution, given the elemental isotope composition and the molecular formula of a compound. The third article introduces programs aimed specifically for the analysis of complex lipid samples and discusses different computational methods for separating the overlapping mass spectrometric peaks of closely related lipids. The fourth article applies the methods developed by simultaneously measuring the progress curve of enzymatic hydrolysis for a large number of phospholipids, which are used to determine the substrate specificity of various A-type phospholipases. The data provides evidence that the substrate efflux from bilayer is the key determining factor for the rate of hydrolysis.

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Tämän tutkimuksen tarkoitus oli tutkia T-tyypin kalsiumkanavan toimintaa ja sen mahdollista roolia neuronaalisten kantasolujen migraatiossa. T-tyypin kalsiumkanavan tehtävän kehittyneissä aivoissa tiedetään olevan elektroenkefalografisten oskillaatioiden tuottaminen. Nämä taas ovat eräiden fysiologisten ja patofysiologisten tapahtumien säätelyssä avainasemassa. Tällaisia tapahtumia ovat uni, muisti, oppiminen ja epileptiset poissaolokohtaukset. Näiden lisäksi T-tyypin kalsiumkanavalla on myös periferaalisia vaikutuksia, mutta tämä tutkielma keskittyy sen neuronaalisiin toimintoihin. Tämän matalan jännitteen säätelemän kanavan toiminta neurogeneesin aikana on vähemmän tutkittua ja tunnettua kuin sen vaikutukset kehittyneissä aivoissa. T-tyypin kalsiumkanavan tiedetään edistävän kantasolujen proliferaatiota ja erilaistumista neurogeneesiksen aikana, mutta vaikutukset niiden migraatioon ovat vähemmän tunnetut. Tämä tutkimus näyttää T-tyypin kalsiumkanavan todennäköisesti osallistuvan neuronaaliseen migraatioon hiiren alkion subventrikkeli alueelta eristetyillä kanta- tai progeniittorisoluilla tehdyissä kokeissa. Selektiiviset T-tyypin kalsiumkanavan antagonistit, etosuksimidi, nikkeli ja skorpionitoksiini, kurtoxin hidastivat migraatiota erilaistuvissa progeniittorisoluissa. Tämä tutkimus koostuu kirjallisuuskatsauksesta ja kokeellisesta osasta. Tämän tutkimuksen toinen tarkoitus oli esitellä vaihtoehtoinen lähestymistapa invasiiviselle kantasoluterapialle, joka vaatii kantasolujen viljelyä ja siirtämistä ihmiseen. Tämä toinen tapa on endogeenisten kantasolujen eiinvasiivinen stimulointi, jolla ne saadaan migratoitumaan kohdekudokseen, erilaistumaan siellä ja tehtävänsä suoritettuaan lopettamaan jakaantumisen. Non-invasiivinen kantasoluterapia on vasta tiensä alussa, ja tarvitsee farmakologista osaamista kehittyäkseen. Joitain onnistuneita ei-invasiivisia hoitoja on jo tehty selkärangan vaurioiden korjaamisessa. Vastaavanlaisia menetelmiä voitaisiin käyttää myös keskushermoston vaurioiden ja neurodegeneratiivisten sairauksien hoidossa. Näiden menetelmien kehittäminen vaatii endogeenisten kantasoluja inhiboivien ja indusoivien mekanismien tuntemista. Yksi tärkeä kantasolujen erilaistumista stimuloiva tekijä on kalsiumioni. Jänniteherkät kalsiumkanavat osallistuvat kaikkiin neurogeneesiksen eri vaiheisiin. T-tyypin kalsiumkanava, joka ekspressoituu suuressa määrin keskushermoston kehityksen alkuvaiheessa ja vähenee neuronaalisen kehityksen edetessä, saattaa olla oleellisessa asemassa progeniittorisolujen ohjaamisessa.

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This work is a case study of applying nonparametric statistical methods to corpus data. We show how to use ideas from permutation testing to answer linguistic questions related to morphological productivity and type richness. In particular, we study the use of the suffixes -ity and -ness in the 17th-century part of the Corpus of Early English Correspondence within the framework of historical sociolinguistics. Our hypothesis is that the productivity of -ity, as measured by type counts, is significantly low in letters written by women. To test such hypotheses, and to facilitate exploratory data analysis, we take the approach of computing accumulation curves for types and hapax legomena. We have developed an open source computer program which uses Monte Carlo sampling to compute the upper and lower bounds of these curves for one or more levels of statistical significance. By comparing the type accumulation from women’s letters with the bounds, we are able to confirm our hypothesis.

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An a priori error analysis of discontinuous Galerkin methods for a general elliptic problem is derived under a mild elliptic regularity assumption on the solution. This is accomplished by using some techniques from a posteriori error analysis. The model problem is assumed to satisfy a GAyenrding type inequality. Optimal order L (2) norm a priori error estimates are derived for an adjoint consistent interior penalty method.

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Background: This study examined the association of -866G/A, Ala55Val, 45bpI/D, and -55C/T polymorphisms at the uncoupling protein (UCP) 3-2 loci with type 2 diabetes in Asian Indians. Methods: A case-control study was performed among 1,406 unrelated subjects (487 with type 2 diabetes and 919 normal glucose-tolerant NGT]), chosen from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in Southern India. The polymorphisms were genotyped using polymerase chain reaction-restriction fragment length polymorphism and direct sequencing. Haplotype frequencies were estimated using an expectation-maximization algorithm. Linkage disequilibrium was estimated from the estimates of haplotypic frequencies. Results: The genotype (P = 0.00006) and the allele (P = 0.00007) frequencies of Ala55Val of the UCP2 gene showed a significant protective effect against the development of type 2 diabetes. The odds ratios (adjusted for age, sex, and body mass index) for diabetes for individuals carrying Ala/Val was 0.72, and that for individuals carrying Val/Val was 0.37. Homeostasis insulin resistance model assessment and 2-h plasma glucose were significantly lower among Val-allele carriers compared to the Ala/Ala genotype within the NGT group. The genotype (P = 0.02) and the allele (P = 0.002) frequencies of -55C/T of the UCP3 gene showed a significant protective effect against the development of diabetes. The odds ratio for diabetes for individuals carrying CT was 0.79, and that for individuals carrying TT was 0.61. The haplotype analyses further confirmed the association of Ala55Val with diabetes, where the haplotypes carrying the Ala allele were significantly higher in the cases compared to controls. Conclusions: Ala55Val and -55C/T polymorphisms at the UCP3-2 loci are associated with a significantly reduced risk of developing type 2 diabetes in Asian Indians.

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NDDO-based (AM1) configuration interaction (CI) calculations have been used to calculate the wavelength and oscillator strengths of electronic absorptions in organic molecules and the results used in a sum-over-states treatment to calculate second-order-hyperpolarizabilities. The results for both spectra and hyperpolarizabilities are of acceptable quality as long as a suitable CI-expansion is used. We have found that using an active space of eight electrons in eight orbitals and including all single and pair-double excitations in the CI leads to results that agree well with experiment and that do not change significantly with increasing active space for most organic molecules. Calculated second-order hyperpolarizabilities using this type of CI within a sum-over-states calculation appear to be of useful accuracy.

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We develop a model of the solar dynamo in which, on the one hand, we follow the Babcock-Leighton approach to include surface processes, such as the production of poloidal field from the decay of active regions, and, on the other hand, we attempt to develop a mean field theory that can be studied in quantitative detail. One of the main challenges in developing such models is to treat the buoyant rise of the toroidal field and the production of poloidal field from it near the surface. A previous paper by Choudhuri, Schüssler, & Dikpati in 1995 did not incorporate buoyancy. We extend this model by two contrasting methods. In one method, we incorporate the generation of the poloidal field near the solar surface by Durney's procedure of double-ring eruption. In the second method, the poloidal field generation is treated by a positive α-effect concentrated near the solar surface coupled with an algorithm for handling buoyancy. The two methods are found to give qualitatively similar results.

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Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K-nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue-type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright (C) 2011 John Wiley & Sons, Ltd.

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Most HIV-1 broadly neutralizing antibodies are directed against the gp120 subunit of the env surface protein. Native env consists of a trimer of gp120-gp41 heterodimers, and in contrast to monomeric gp120, preferentially binds CD4 binding site (CD4bs)-directed neutralizing antibodies over non-neutralizing ones. Some cryo-electron tomography studies have suggested that the V1V2 loop regions of gp120 are located close to the trimer interface. We have therefore designed cyclically permuted variants of gp120 with and without the h-CMP and SUMO2a trimerization domains inserted into the V1V2 loop. h-CMP-V1cyc is one such variant in which residues 153 and 142 are the N- and C-terminal residues, respectively, of cyclically permuted gp120 and h-CMP is fused to the N-terminus. This molecule forms a trimer under native conditions and binds CD4 and the neutralizing CD4bs antibodies b12 with significantly higher affinity than wild-type gp120. It binds non-neutralizing CD4bs antibody F105 with lower affinity than gp120. A similar derivative, h-CMP-V1cycl, bound the V1V2 loop-directed broadly neutralizing antibodies PG9 and PG16 with similar to 20-fold higher affinity than wild-type JRCSF gp120. These cyclic permutants of gp120 are properly folded and are potential immunogens. The data also support env models in which the V1V2 loops are proximal to the trimer interface.

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In this paper we study the problem of designing SVM classifiers when the kernel matrix, K, is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the problem using the Robust Optimization methodology. This reduces the uncertain SVM problem into a deterministic conic quadratic problem which can be solved in principle by a polynomial time Interior Point (IP) algorithm. However, for large-scale classification problems, IP methods become intractable and one has to resort to first-order gradient type methods. The strategy we use here is to reformulate the robust counterpart of the uncertain SVM problem as a saddle point problem and employ a special gradient scheme which works directly on the convex-concave saddle function. The algorithm is a simplified version of a general scheme due to Juditski and Nemirovski (2011). It achieves an O(1/T-2) reduction of the initial error after T iterations. A comprehensive empirical study on both synthetic data and real-world protein structure data sets show that the proposed formulations achieve the desired robustness, and the saddle point based algorithm outperforms the IP method significantly.

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Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]

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The solution structure of the monomeric glutamine amidotransferase (GATase) subunit of the Methanocaldococcus janaschii (Mj) guanosine monophosphate synthetase (GMPS) has been determined using high-resolution nuclear magnetic resonance methods. Gel filtration chromatography and N-15 backbone relaxation studies have shown that the Mj GATase subunit is present in solution as a 21 kDa (188-residue) monomer. The ensemble of 20 lowest-energy structures showed root-mean-square deviations of 0.35 +/- 0.06 angstrom for backbone atoms and 0.8 +/- 0.06 angstrom for all heavy atoms. Furthermore, 99.4% of the backbone dihedral angles are present in the allowed region of the Ramachandran map, indicating the stereochemical quality of the structure. The core of the tertiary structure of the GATase is composed of a seven-stranded mixed beta-sheet that is fenced by five alpha-helices. The Mj GATase is similar in structure to the Pyrococcus horikoshi (Ph) GATase subunit. Nuclear magnetic resonance (NMR) chemical shift perturbations and changes in line width were monitored to identify residues on GATase that were responsible for interaction with magnesium and the ATPPase subunit, respectively. These interaction studies showed that a common surface exists for the metal ion binding as well as for the protein-protein interaction. The dissociation constant for the GATase-Mg2+ interaction has been found to be similar to 1 mM, which implies that interaction is very weak and falls in the fast chemical exchange regime. The GATase-ATPPase interaction, on the other hand, falls in the intermediate chemical exchange regime on the NMR time scale. The implication of this interaction in terms of the regulation of the GATase activity of holo GMPS is discussed.

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In this article, we study the thermal performance of phase-change material (PCM)-based heat sinks under cyclic heat load and subjected to melt convection. Plate fin type heat sinks made of aluminum and filled with PCM are considered in this study. The heat sink is heated from the bottom. For a prescribed value of heat flux, design of such a heat sink can be optimized with respect to its geometry, with the objective of minimizing the temperature rise during heating and ensuring complete solidification of PCM at the end of the cooling period for a given cycle. For given length and base plate thickness of a heat sink, a genetic algorithm (GA)-based optimization is carried out with respect to geometrical variables such as fin thickness, fin height, and the number of fins. The thermal performance of the heat sink for a given set of parameters is evaluated using an enthalpy-based heat transfer model, which provides the necessary data for the optimization algorithm. The effect of melt convection is studied by taking two cases, one without melt convection (conduction regime) and the other with convection. The results show that melt convection alters the results of geometrical optimization.

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Staphylococcus aureus is a commensal gram positive bacteria which causes severe and non severe infections in humans and livestock. In India, ST772 is a dominant and ST672 is an emerging clone of Staphylococcus aureus. Both cause serious human diseases, and carry type V SCCmec elements. The objective of this study was to characterize SCCmec type V elements of ST772 and ST672 because the usual PCR methods did not amplify all primers specific to the type. Whole genome sequencing analysis of seven ST772 and one ST672 S. aureus isolates revealed that the SCCmec elements of six of the ST772 isolates were the smallest of the extant type V elements and in addition have several other novel features. Only one ST772 isolate and the ST672 isolate carried bigger SCCmec cassettes which were composites carrying multiple ccrC genes. These cassettes had some similarities to type V SCCmec element from M013 isolate (ST59) from Taiwan in certain aspects. SCCmec elements of all Indian isolates had an inversion of the mec complex, similar to the bovine SCCmec type X. This study reveals that six out of seven ST772 S. aureus isolates have a novel type V (5C2) SCCmec element while one each of ST772 and ST672 isolates have a composite SCCmec type V element (5C2&5) formed by the integration of type V SCCmec into a MSSA carrying a SCC element, in addition to the mec gene complex inversions and extensive recombinations.