986 resultados para Miollis, Charles François Bienvenu de, bp. of Digne, 1753-1843.
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An exact copy, except for a few corrections, of the original manuscript which is in the Museum of comparative zoology of Harvard university; now published for the first time.
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Mode of access: Internet.
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Mode of access: Internet.
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On t.-p. of v. 7: 1843-79.
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Includes index.
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Mode of access: Internet.
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Mode of access: Internet.
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Two snapshot surveys to establish the diversity and ecological preferences of mosquitoes (Diptera: Culicidae) in the terra firme primary rain forest surrounding the Tiputini Biodiversity Station in the UNESCO Yasuní Biosphere Reserve of eastern Amazonian Ecuador were carried out in November 1998 and May 1999. The mosquito fauna of this region is poorly known; the focus of this study was to obtain high quality link-reared specimens that could be used to unequivocally confirm species level diversity through integrated systematic study of all life stages and DNA sequences. A total of 2,284 specimens were preserved; 1,671 specimens were link-reared with associated immature exuviae, all but 108 of which are slide mounted. This study identified 68 unique taxa belonging to 17 genera and 27 subgenera. Of these, 12 are new to science and 37 comprise new country records. DNA barcodes [658-bp of the mtDNA cytochrome c oxidase ( COI ) I gene] are presented for 58 individuals representing 20 species and nine genera. DNA barcoding proved useful in uncovering and confirming new species and we advocate an integrated systematics approach to biodiversity studies in future. Associated bionomics of all species collected are discussed. An updated systematic checklist of the mosquitoes of Ecuador (n = 179) is presented for the first time in 60 years.
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The high Km glucose transporter GLUT2 is a membrane protein expressed in tissues involved in maintaining glucose homeostasis, and in cells where glucose-sensing is necessary. In many experimental models of diabetes, GLUT2 gene expression is decreased in pancreatic beta-cells, which could lead to a loss of glucose-induced insulin secretion. In order to identify factors involved in pancreatic beta-cell specific expression of GLUT2, we have recently cloned the murine GLUT2 promoter and identified cis-elements within the 338-bp of the proximal promoter capable of binding islet-specific trans-acting factors. Furthermore, in transient transfection studies, this 338-bp fragment could efficiently drive the expression of the chloramphenicol acetyl transferase (CAT) gene in cell lines derived from the endocrine pancreas, but displayed no promoter activity in non-pancreatic cells. In this report, we tested the cell-specific expression of a CAT reporter gene driven by a short (338 bp) and a larger (1311 bp) fragment of the GLUT2 promoter in transgenic mice. We generated ten transgenic lines that integrated one of the constructs. CAT mRNA expression in transgenic tissues was assessed using the RNAse protection assay and the quantitative reverse transcribed polymerase chain reaction (RT-PCR). Overall CAT mRNA expression for both constructs was low compared to endogenous GLUT2 mRNA levels but the reporter transcript could be detected in all animals in the pancreatic islets and the liver, and in a few transgenic lines in the kidney and the small intestine. The CAT protein was also present in Langerhans islets and in the liver for both constructs by immunocytochemistry. These findings suggest that the proximal 338 bp of the murine GLUT2 promoter contain cis-elements required for the islet-specific expression of GLUT2.
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Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.
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Several clinical studies have reported that EEG synchrony is affected by Alzheimer’s disease (AD). In this paper a frequency band analysis of AD EEG signals is presented, with the aim of improving the diagnosis of AD using EEG signals. In this paper, multiple synchrony measures are assessed through statistical tests (Mann–Whitney U test), including correlation, phase synchrony and Granger causality measures. Moreover, linear discriminant analysis (LDA) is conducted with those synchrony measures as features. For the data set at hand, the frequency range (5-6Hz) yields the best accuracy for diagnosing AD, which lies within the classical theta band (4-8Hz). The corresponding classification error is 4.88% for directed transfer function (DTF) Granger causality measure. Interestingly, results show that EEG of AD patients is more synchronous than in healthy subjects within the optimized range 5-6Hz, which is in sharp contrast with the loss of synchrony in AD EEG reported in many earlier studies. This new finding may provide new insights about the neurophysiology of AD. Additional testing on larger AD datasets is required to verify the effectiveness of the proposed approach.
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Does Independent Component Analysis (ICA) denature EEG signals? We applied ICA to two groups of subjects (mild Alzheimer patients and control subjects). The aim of this study was to examine whether or not the ICA method can reduce both group di®erences and within-subject variability. We found that ICA diminished Leave-One- Out root mean square error (RMSE) of validation (from 0.32 to 0.28), indicative of the reduction of group di®erence. More interestingly, ICA reduced the inter-subject variability within each group (¾ = 2:54 in the ± range before ICA, ¾ = 1:56 after, Bartlett p = 0.046 after Bonfer- roni correction). Additionally, we present a method to limit the impact of human error (' 13:8%, with 75.6% inter-cleaner agreement) during ICA cleaning, and reduce human bias. These ¯ndings suggests the novel usefulness of ICA in clinical EEG in Alzheimer's disease for reduction of subject variability.
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A motion that the case not be tried in Suffolk County, on the grounds that the judges and jurors were residents of the colony. Pratt was attorney to Paxton, an attorney and commissioner of customs, who had incurred a debt to the Colony.
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Mode of access: Internet.
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Mode of access: Internet.