150 resultados para correlation theory
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Our paper aims to give a thorough description of the infra-ophiolitic melanges associated with the Mersin ophiolite. We propose new regional correlations of the Mersin melanges with other melange-like units or similar series, located both in southern Turkey and adjacent regions. The palaeotectonic implications of the correlations are also discussed. The main results may be summarized as follows: the infra-ophiolitic melange is subdivided into two units, the Upper Cretaceous Sorgun ophiolitic melange and the Ladinian-Carnian Hacialani melange. The Mersin melanges, together with the Antalya and Mamonia domains, are represented by a series of exotic units now found south of the main Taurus range, and are characteristic of the South-Taurides Exotic Units. These melanges clearly show the mixed origin of the different blocks and broken formations. Some components have a Palaeotethyan origin and are characterized by Pennsylvanian and Lower to Middle Permian pelagic and slope deposits. These Palaeotethyan remnants, found exclusively in the Hacialani melange, were reworked as major olistostromes in the Neotethys basin during the Eo-Cimmerian orogenic event. Neotethyan elements are represented by Middle Triassic seamounts and by broken formations containing typical Neotethyan conodont faunas such as Metapolygnathus mersinensis Kozur & Moix and M. primitius s. s., both present in the latest Carnian interval, as well as the occurrence of the middle Norian Epigondolella praeslovakensis Kozur, Masset & Moix. Other elements are clearly derived from the former north Anatolian passive margin and are represented by Huglu-type series including the Upper Triassic syn-rift volcanic event. These sequences attributed to the Huglu-Pindos back-arc ocean were displaced southward during the Late Cretaceous obduction event. The Tauric elements are represented by Eo-Cimmerian flysch-like and molasse sequences intercalated in Neotethyan series. Additionally, some shallow-water blocks might be derived from the Bolkardag para-autochthonous and the Taurus-Beydaglari marginal sequences.
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We survey the population genetic basis of social evolution, using a logically consistent set of arguments to cover a wide range of biological scenarios. We start by reconsidering Hamilton's (Hamilton 1964 J. Theoret. Biol. 7, 1-16 (doi:10.1016/0022-5193(64)90038-4)) results for selection on a social trait under the assumptions of additive gene action, weak selection and constant environment and demography. This yields a prediction for the direction of allele frequency change in terms of phenotypic costs and benefits and genealogical concepts of relatedness, which holds for any frequency of the trait in the population, and provides the foundation for further developments and extensions. We then allow for any type of gene interaction within and between individuals, strong selection and fluctuating environments and demography, which may depend on the evolving trait itself. We reach three conclusions pertaining to selection on social behaviours under broad conditions. (i) Selection can be understood by focusing on a one-generation change in mean allele frequency, a computation which underpins the utility of reproductive value weights; (ii) in large populations under the assumptions of additive gene action and weak selection, this change is of constant sign for any allele frequency and is predicted by a phenotypic selection gradient; (iii) under the assumptions of trait substitution sequences, such phenotypic selection gradients suffice to characterize long-term multi-dimensional stochastic evolution, with almost no knowledge about the genetic details underlying the coevolving traits. Having such simple results about the effect of selection regardless of population structure and type of social interactions can help to delineate the common features of distinct biological processes. Finally, we clarify some persistent divergences within social evolution theory, with respect to exactness, synergies, maximization, dynamic sufficiency and the role of genetic arguments.
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Cannabis use among adolescents and young adults has become a major public health challenge. Several European countries are currently developing short screening instruments to identify 'problematic' forms of cannabis use in general population surveys. One such instrument is the Cannabis Use Disorders Identification Test (CUDIT), a 10-item questionnaire based on the Alcohol Use Disorders Identification Test. Previous research found that some CUDIT items did not perform well psychometrically. In the interests of improving the psychometric properties of the CUDIT, this study replaces the poorly performing items with new items that specifically address cannabis use. Analyses are based on a sub-sample of 558 recent cannabis users from a representative population sample of 5722 individuals (aged 13-32) who were surveyed in the 2007 Swiss Cannabis Monitoring Study. Four new items were added to the original CUDIT. Psychometric properties of all 14 items, as well as the dimensionality of the supplemented CUDIT were then examined using Item Response Theory. Results indicate the unidimensionality of CUDIT and an improvement in its psychometric performance when three original items (usual hours being stoned; injuries; guilt) are replaced by new ones (motives for using cannabis; missing out leisure time activities; difficulties at work/school). However, improvements were limited to cannabis users with a high problem score. For epidemiological purposes, any further revision of CUDIT should therefore include a greater number of 'easier' items.
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OBJECTIVE: To study the correlation between the bacteriological and histopathological findings in placentas from women with suspected or proven chorioamnionitis (CA). METHODS: Over a 1-year period, 376 placentas were prospectively collected and processed for bacteriological and pathological studies in cases of confirmed or suspected maternal or neonatal infection. RESULTS: Histological CA was diagnosed in 26.9% of placentas (101/376), and 27.7% (28/101) of these placentas had positive bacteriological cultures. A monomicrobial culture, mainly represented by Gram-positive cocci and Gram-negative bacilli, was identified in 27% of the positive bacterial cultures. The proportion of positive cultures was higher (p=0.03) when CA was associated with funisitis, as compared with placental samples with early CA. In placentas without histological CA, bacteriological cultures were mostly negative (230/275), although pathogenic bacteria were identified in 16.3% of them (45/275). CONCLUSIONS: The histological and bacteriological results were concordant in about 70% of the examined placentas, with 61.1% negative cases (CA absent and negative bacterial cultures), and only 7.4% placentas with positive histological and bacteriological results. Discordant results (positive histology with negative bacteriology) were obtained in placentas with early CA documented by histology although possibly in relation with antibiotic prophylaxis and the presence of fastidious bacteria. Conversely, negative histology with positive bacteriology could be explained by the presence of an early-stage bacterial infection that has not yet led to detectable microscopic lesions.
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Previous work has shown that aggregating fetal brain cell cultures are able to attain a highly differentiated state, and that their development is greatly enhanced by growth and/or differentiation factors such as epidermal growth factor (EGF), basic fibroblast growth factor (bFGF), and the protein kinase C-activating tumor promoter mezerein. The present study shows that in these 3-dimensional cultures the peptide growth factors EGF and bFGF as well as mezerein are able to induce the expression of the proto-oncogene c-fos. This induction was rapid and transient, in good agreement with observations reported from a wide variety of cell types in vitro. The maximal levels of c-fos mRNA found after stimulation were low in immature cultures and increased greatly as maturation progressed. Of the three factors tested, mezerein was the most potent inducer of c-fos. In contrast to the peptide growth factors EGF and bFGF which were found to induce c-fos only in glial cells, mezerein was stimulatory in glial cells as well as in neurons. A similar cell type specificity has been observed previously for the maturation-enhancing response in immature aggregate cultures. However, in the present study no correlation was found between the degree of c-fos induction and the extent of the maturation-enhancing stimulation. Immature cultures known to be most sensitive and responsive to these maturation-enhancing agents required relatively high doses of peptide growth factors for the induction of c-fos, and the maximal levels of c-fos mRNA elicited were much lower than those in differentiated cultures which did not show any long-term response to these stimuli.(ABSTRACT TRUNCATED AT 250 WORDS)
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This article builds on the recent policy diffusion literature and attempts to overcome one of its major problems, namely the lack of a coherent theoretical framework. The literature defines policy diffusion as a process where policy choices are interdependent, and identifies several diffusion mechanisms that specify the link between the policy choices of the various actors. As these mechanisms are grounded in different theories, theoretical accounts of diffusion currently have little internal coherence. In this article we put forward an expected-utility model of policy change that is able to subsume all the diffusion mechanisms. We argue that the expected utility of a policy depends on both its effectiveness and the payoffs it yields, and we show that the various diffusion mechanisms operate by altering these two parameters. Each mechanism affects one of the two parameters, and does so in distinct ways. To account for aggregate patterns of diffusion, we embed our model in a simple threshold model of diffusion. Given the high complexity of the process that results, strong analytical conclusions on aggregate patterns cannot be drawn without more extensive analysis which is beyond the scope of this article. However, preliminary considerations indicate that a wide range of diffusion processes may exist and that convergence is only one possible outcome.
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Resistance to alkylating agents via direct DNA repair by O(6)-methylguanine methyltransferase (MGMT) remains a significant barrier to the successful treatment of patients with malignant glioma. The relative expression of MGMT in the tumor may determine response to alkylating agents, and epigenetic silencing of the MGMT gene by promoter methylation plays an important role in regulating MGMT expression in gliomas. MGMT promoter methylation is correlated with improved progression-free and overall survival in patients treated with alkylating agents. Strategies to overcome MGMT-mediated chemoresistance are being actively investigated. These include treatment with nontoxic pseudosubstrate inhibitors of MGMT, such as O(6)-benzylguanine, or RNA interference-mediated gene silencing of MGMT. However, systemic application of MGMT inhibitors is limited by an increase in hematologic toxicity. Another strategy is to deplete MGMT activity in tumor tissue using a dose-dense temozolomide schedule. These alternative schedules are well tolerated; however, it remains unclear whether they are more effective than the standard dosing regimen or whether they effectively deplete MGMT activity in tumor tissue. Of note, not all patients with glioblastoma having MGMT promoter methylation respond to alkylating agents, and even those who respond will inevitably experience relapse. Herein we review the data supporting MGMT as a major mechanism of chemotherapy resistance in malignant gliomas and describe ongoing studies that are testing resistance-modulating strategies.
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In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).
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Introduction: Schizophrenia is associated with multiple neuropsychological dysfunctions, such as disturbances of attention, memory, perceptual functioning, concept formation and executive processes. These cognitive functions are reported to depend on the integrity of the prefrontal and thalamo-prefrontal circuits. Multiple lines of evidence suggest that schizophrenia is related to abnormalities in neural circuitry and impaired structural connectivity. Here, we report a preliminary case-control study that showed a correlation between thalamo-frontal connections and several cognitive functions known to be impaired in schizophrenia. Materials and Methods: We investigated 9 schizophrenic patients (DSM IV criteria, Diagnostic Interview for Genetic Studies) and 9 age and sex matched control subjects. We obtained from each volunteer a DT-MRI dataset (3 T, _ _ 1,000 s/mm2), and a high resolution anatomic T1. The thalamo- frontal tracts are simulated with DTI tractography on these dataset, a method allowing inference of the main neural fiber tracks from Diffusion MRI data. In order to see an eventual correlation with the thalamo-frontal connections, every subject performs a battery of neuropsychological tests including computerized tests of attention (sustained attention, selective attention and reaction time), working memory tests (Plane test and the working memory sub-tests of the Wechsler Adult Intelligence Scale), a executive functioning task (Tower of Hanoï) and a test of visual binding abilities. Results: In a pilot case-control study (patients: n _ 9; controls: n _ 9), we showed that this methodology is appropriate and giving results in the excepted range. Considering the relation of the connectivity density and the neuropsychological data, a correlation between the number of thalamo- frontal fibers and the performance in the Tower of Hanoï was observed in the patients (Pearson correlation, r _ 0.76, p _ 0.05) but not in control subjects. In the most difficult item of the test, the least number of fibers corresponds to the worst performance of the test (fig. 2, number of supplementary movements of the elements necessary to realize the right configuration). It's interesting to note here that in an independent study, we showed that schizophrenia patients (n _ 32) perform in the most difficult item of the Tower of Hanoï (Mann-Whitney, p _ 0.005) significantly worse than control subjects (n _ 29). This has been observed in several others neuropsychological studies. Discussion: This pilot study of schizophrenia patients shows a correlation between the number of thalam-frontal fibers and the performance in the Tower of Hanoï, which is a planning and goal oriented actions task known to be associated with frontal dysfonction. This observation is consistent with the proposed impaired connectivity in schizophrenia. We aim to pursue the study with a larger sample in order to determine if other neuropsychological tests may be associated with the connectivity density.