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Desulfovibrio are sulfate-reducing anaerobic gram-negative rods that have been proposed as potential periodontopathogens. We investigated the capacity of Desulfovibrio to invade epithelial cells and induce cytokine secretion from these cells. Desulfovibrio strains were co-cultured with KB cells and counts of intracellular bacteria evaluated up to 3 days after infection. Desulfovibrio desulfuricans and Desulfovibrio fairfieldensis were able to survive within epithelial cells. Intracytoplasmic location of both bacterial species was confirmed by confocal laser scanning microscopy and transmission electron microscopy. Invasion was sensitive to nocodazole, an inhibitor of microtubule polymerization, but not to cytochalasin D, a microfilament inhibitor, suggesting that microtubule rearrangements were involved in the internalization of Desulfovibrio strains by KB cells. Infection by Desulfovibrio resulted in increased production of IL-6 and IL-8 by KB cells. The ability of D. desulfuricans and D. fairfieldensis to survive within oral epithelial cells and to modulate the epithelial immune response may contribute to the initiation and progression of periodontal diseases.

We present a new method for calibrating a classified 3D seismic volume. The classification process employs a Kohonen self-organizing map, a type of unsupervised artificial neural network; the subsequent calibration is performed using one or more suites of well logs. Kohonen self-organizing maps and other unsupervised clustering methods generate classes of data based on the identification of various discriminating features. These methods seek an organization in a dataset and form relational organized clusters. However, these clusters may or may not have any physical analogues in the real world. In order to relate them to the real world, we must develop a calibration method that not only defines the relationship between the clusters and real physical properties, but also provides an estimate of the validity of these relationships. With the development of this relationship, the whole dataset can then be calibrated. The clustering step reduces the multi-dimensional data into logically smaller groups. Each original data point defined by multiple attributes is reduced to a one- or two-dimensional relational group. This establishes some logical clustering and reduces the complexity of the classification problem. Furthermore, calibration should be more successful since it will have to consider less variability in the data. In this paper, we present a simple calibration method that employs Bayesian logic to provide the relationship between cluster centres and the real world. The output will give the most probable calibration between each self-organized map node and wellboremeasured parameters such as lithology, porosity and fluid saturation. The second part of the output comprises the calibration probability. The method is described in detail, and a case study is briefly presented using data acquired in the Orange River Basin, South Africa. The method shows promise as an alternative to current techniques for integrating seismic and log data during reservoir characterization.

The aim of this study was to assess the value of the measurement of os-placenta distance by translabial ultrasonography in the evaluation of placenta previa. This method was used in 40 women with suspected placenta previa to measure the distance between the placenta and internal cervical os. Sonographic diagnoses were compared to placental location determined at delivery. Translabial ultrasonography proved superior to the transabdominal route in both diagnosis and exclusion of placenta previa. Measurement of the os-placenta distance can be used as an adjunct to clinical assessment to predict the likelihood of safe vaginal delivery in cases of suspected placenta previa.

In refluxing diglyme, the title α-hydroxy imines 7 and 8 rearrange cleanly to amino ketones 9 and 10 substituted on the carbon α to nitrogen by an allyl or a propargyl group. In the case of α-hydroxy imine 9 , the migration of the allyl group occurs with an allylic transposition.