939 resultados para Shrimps - Classification - Molecular aspects


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The mineral chalcosiderite with formula CuFe6(PO4)4(OH)8⋅4H2O has been studied by Raman spectroscopy and by infrared spectroscopy. A comparison of the chalcosiderite spectra is made with the spectra of turquoise. The spectra of the mineral samples are very similar in the 1200–900 cm−1 region but strong differences are observed in the 900–100 cm−1 region. The effect of substitution of Fe for Al in chalcosiderite shifts the bands to lower wave numbers. Factor group analysis (FGA) implies four OH stretching vibrations for both the water and hydroxyl units. Two bands ascribed to water are observed at 3276 and 3072 cm−1. Three hydroxyl stretching vibrations are observed. Calculations using a Libowitzky type formula show that the hydrogen bond distances of the water molecules are 2.745 and 2.812 Å which are considerably shorter than the values for the hydroxyl units 2.896, 2.917 and 2.978 Å. Two phosphate stretching vibrations at 1042 and 1062 cm−1 in line with the two independent phosphate units in the structure of chalcosiderite. Three bands are observed at 1102, 1159 and 1194 cm−1 assigned to the phosphate antisymmetric stretching vibrations. FGA predicts six bands but only three are observed due to accidental degeneracy. Both the ν2 and ν4 bending regions are complex. Four Raman bands observed at 536, 580, 598 and 636 cm−1 are assigned to the ν4 bending modes. Raman bands at 415, 420, 475 and 484 cm−1are assigned to the phosphate ν2 bending modes. Vibrational spectroscopy enables aspects of the molecular structure of chalcosiderite to be assessed.

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Next Generation Sequencing (NGS) has revolutionised molec- ular biology, allowing routine clinical sequencing. NGS data consists of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. The common bacterium Staphylococcus aureus may cause severe and life-threatening infections in humans, with some strains exhibiting antibiotic resistance. Here we apply an SVM classifier to the important problem of distinguishing S. aureus sequencing projects from other pathogens, including closely related Staphylococci. Using a sequence k-mer representation, we achieve precision and recall above 95%, implicating features with important functional associations.

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The mineral natrodufrénite a secondary pegmatite phosphate mineral from Minas Gerais, Brazil, has been studied by a combination of scanning electron microscopy and vibrational spectroscopic techniques. Electron probe analysis shows the formula of the studied mineral as (Na0.88Ca0.12)∑1.00(Mn0.11Mg0.08Ca0.04Zr0.01Cu0.01)∑0.97(Al0.02)∑4.91(PO4)3.96(OH6.15F0.07)6.22⋅2.05(H2O). Raman spectroscopy identifies an intense peak at 1003 cm−1 assigned to the ν1 symmetric stretching mode. Raman bands are observed at 1059 and 1118 cm−1 and are attributed to the ν3 antisymmetric stretching vibrations. A comparison is made with the spectral data of other hydrate hydroxy phosphate minerals including cyrilovite and wardite. Raman bands at 560, 582, 619 and 668 cm−1 are assigned to the ν4 bending modes and Raman bands at 425, 444, 477 and 507 cm−1 are due to the ν2 bending modes. Raman bands in the 2600–3800 cm−1 spectral range are attributed to water and OH stretching vibrations. Vibrational spectroscopy enables aspects of the molecular structure of natrodufrénite to be assessed.

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In this paper, problems are described which are related to the ergonomic assessment of vehicle package design in vehicle systems engineering. The traditional approach, using questionnaire techniques for a subjective assessment of comfort related to package design, is compared to a biomechanical approach. An example is given for ingress design. The biomechanical approach is based upon objective postural data. The experimental setup for the study is described and methods used for the biomechanical analysis are explained. Because the biomechanic assessment requires not only a complex experimental setup but also time consuming data processing, a systematic reduction and preparation of biomechanic data for classification with an Artificial Neural Network significantly improves the economy of the biomechanical method.

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Cardiomyopathies represent a group of diseases of the myocardium of the heart and include diseases both primarily of the cardiac muscle and systemic diseases leading to adverse effects on the heart muscle size, shape, and function. Traditionally cardiomyopathies were defined according to phenotypical appearance. Now, as our understanding of the pathophysiology of the different entities classified under each of the different phenotypes improves and our knowledge of the molecular and genetic basis for these entities progresses, the traditional classifications seem oversimplistic and do not reflect current understanding of this myriad of diseases and disease processes. Although our knowledge of the exact basis of many of the disease processes of cardiomyopathies is still in its infancy, it is important to have a classification system that has the ability to incorporate the coming tide of molecular and genetic information. This paper discusses how the traditional classification of cardiomyopathies based on morphology has evolved due to rapid advances in our understanding of the genetic and molecular basis for many of these clinical entities.

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Migraine is a common neurological disorder with a strong genetic basis. However, the complex nature of the disorder has meant that few genes or susceptibility loci have been identified and replicated consistently to confirm their involvement in migraine. Approaches to genetic studies of the disorder have included analysis of the rare migraine subtype, familial hemiplegic migraine with several causal genes identified for this severe subtype. However, the exact genetic contributors to the more common migraine subtypes are still to be deciphered. Genome-wide studies such as genome-wide association studies and linkage analysis as well as candidate genes studies have been employed to investigate genes involved in common migraine. Neurological, hormonal and vascular genes are all considered key factors in the pathophysiology of migraine and are a focus of many of these studies. It is clear that the influence of individual genes on the expression of this disorder will vary. Furthermore, the disorder may be dependent on gene–gene and gene–environment interactions that have not yet been considered. In addition, identifying susceptibility genes may require phenotyping methods outside of the International Classification of Headache Disorders II criteria, such as trait component analysis and latent class analysis to better define the ambit of migraine expression.

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Natural single-crystal specimens of barbosalite from Brazil, with general formula Fe2+Fe3+ 2 (PO4)2(OH)2 were investigated by Raman and infrared spectroscopy. The mineral occurs as secondary products in granitic pegmatites. The Raman spectrum of barbosalite is characterized by bands at 1020, 1033 and 1044 cm−1 cm−1, assigned to ν1 symmetric stretching mode of the HOPO3- 3 and PO3- 4 units. Raman bands at around 1067, 1083 and 1138 cm−1 are attributed to both the HOP and PO antisymmetric stretching vibrations. The set of Raman bands observed at 575, 589 and 606 cm−1 are assigned to the ν4 out of plane bending modes of the PO4 and H2PO4 units. Raman bands at 439, 461, 475 and 503 cm−1 are attributed to the ν2 PO4 and H2PO4 bending modes. Strong Raman bands observed at 312, 346 cm−1 with shoulder bands at 361, 381 and 398 cm−1 are assigned to FeO stretching vibrations. No bands which are attributable to water vibrations were found. Vibrational spectroscopy enables aspects of the molecular structure of barbosalite to be assessed.

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Natural single-crystal specimens of althausite from Brazil, with general formula Mg2(PO4)(OH,F,O) were investigated by Raman and infrared spectroscopy. The mineral occurs as a secondary product in granitic pegmatites. The Raman spectrum of althausite is characterized by bands at 1020, 1033 and 1044 cm-1, assigned to ν1 symmetric stretching modes of the HOPO33- and PO43- units. Raman bands at around 1067, 1083 and 1138 cm-1 are attributed to both the HOP and PO antisymmetric stretching vibrations. The set of Raman bands observed at 575, 589 and 606 cm-1 are assigned to the ν4 out of plane bending modes of the PO4 and H2PO4 units. Raman bands at 439, 461, 475 and 503 cm-1 are attributed to the ν2 PO4 and H2PO4 bending modes. Strong Raman bands observed at 312, 346 cm-1 with shoulder bands at 361, 381 and 398 cm-1 are assigned to MgO stretching vibrations. No bands which are attributable to water were found. Vibrational spectroscopy enables aspects of the molecular structure of althausite to be assessed.

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The detection and correction of defects remains among the most time consuming and expensive aspects of software development. Extensive automated testing and code inspections may mitigate their effect, but some code fragments are necessarily more likely to be faulty than others, and automated identification of fault prone modules helps to focus testing and inspections, thus limiting wasted effort and potentially improving detection rates. However, software metrics data is often extremely noisy, with enormous imbalances in the size of the positive and negative classes. In this work, we present a new approach to predictive modelling of fault proneness in software modules, introducing a new feature representation to overcome some of these issues. This rank sum representation offers improved or at worst comparable performance to earlier approaches for standard data sets, and readily allows the user to choose an appropriate trade-off between precision and recall to optimise inspection effort to suit different testing environments. The method is evaluated using the NASA Metrics Data Program (MDP) data sets, and performance is compared with existing studies based on the Support Vector Machine (SVM) and Naïve Bayes (NB) Classifiers, and with our own comprehensive evaluation of these methods.

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Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

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We provide the first molecular phylogeny of the clerid lineage (Coleoptera: Cleridae, Thanerocleridae) within the superfamily Cleroidea to examine the two most recently-proposed hypotheses of higher-level classification. Phylogenetic relationships of checkered beetles were inferred from approximately ~5,000nt of both nuclear and mitochondrial rDNA (28S, 16S, and 12S) and the mitochondrial protein-coding gene COI. A worldwide sample of ~70 genera representing almost a quarter of generic diversity of the clerid lineage was included and phylogenies were reconstructed using Bayesian and Maximum Likelihood approaches. Results support the monophyly of many proposed subfamilies but were not entirely congruent with either current classification system. The subfamilial relationships within the Cleridae are resolved with support for three main lineages. Tillinae are supported as the sister group to all other subfamilies within the Cleridae, whereas Thaneroclerinae, Korynetinae and a new subfamily formally described here, Epiclininae subf. n, form a sister group to Clerinae + Hydnocerinae.

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We have compared physical and genetic maps of the region around the legJ gene in pea. In this vicinity there are four B-type legumin genes, arranged as two close pairs. The detection of a recombination event within this gene cluster allows the orientation of this group of genes within the surrounding linkage group to be determined. The relationship between physical and genetic distances in this region is discussed, as are the implications of this for relating physical and genetic maps elsewhere in the pea genome.

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Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

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Marsupials exhibit great diversity in ecology and morphology. However, compared to their sister group, the placental mammals, our understanding of many aspects of marsupial evolution remains limited. We use 101 mitochondrial genomes and data from 26 nuclear loci to reconstruct a dated phylogeny including 97% of extant genera and 58% of modern marsupial species. This tree allows us to analyze the evolution of habitat preference and geographic distributions of marsupial species through time. We found a pattern of mesic-adapted lineages evolving to use more arid and open habitats, which is broadly consistent with regional climate and environmental change. However, contrary to the general trend, several lineages subsequently appear to have reverted from drier to more mesic habitats. Biogeographic reconstructions suggest that current views on the connectivity between Australia and New Guinea/Wallacea during the Miocene and Pliocene need to be revised. The antiquity of several endemic New Guinean clades strongly suggests a substantially older period of connection stretching back to the Middle Miocene, and implies that New Guinea was colonized by multiple clades almost immediately after its principal formation.

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Technical dinitrotoluene (DNT) is a mixture of 2,4- and 2,6-DNT. In humans, industrial or environmental exposure can occur orally, by inhalation, or by skin contact. The classification of DNT as an 'animal carcinogen' is based on the formation of malignant tumors in kidneys, liver, and mammary glands of rats and mice. Clear signs of toxic nephropathy were found in rats dosed with DNT, and the concept was derived of an interrelation between renal toxicity and carcinogenicity. Recent data point to the carcinogenicity of DNT on the urinary tract of exposed humans. Between 1984 and 1997, 6 cases of urothelial cancer and 14 cases of renal cell cancer were diagnosed in a group of 500 underground mining workers in the copper mining industry of the former GDR and having high exposures to explosives containing technical DNT. The incidences of both urothelial and renal cell tumors in this group were 4.5 and 14.3 times higher, respectively, than anticipated on the basis of the cancer registers of the GDR. The genotyping of all identified tumor patients for the polymorphic enzymes NAT2, GSTM1, and GSTT1 identified the urothelial tumor cases as exclusively 'slow acetylates'. A group of 161 miners highly exposed to DNT was investigated for signs of subclinical renal damage. The exposures were categorized semi-quantitatively into 'low', 'medium', 'high', and 'very high'. A straight dose-dependence of the excretion of urinary biomarker proteins with the ranking of exposure was seen. Biomarker excretion (alpha1-microglobulin, glutathione S-transferases alpha and pi) indicated that DNT-induced damage was directed toward the tubular system. New data on DNT-exposed humans appear consistent with the concept of cancer initiation by DNT isomers and the subsequent promotion of renal carcinogenesis by selective damage to the proximal tubule. The differential pathways of metabolic activation of DNT appear to apply to the proximal tubule of the kidney and to the urothelium of the renal pelvis and lower urinary tract as target tissues of carcinogenicity.