967 resultados para 2-MERCAPTO-3-N-OCTYLTHIOPHENE


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In this issue...Butte, Anaconda, Silver Lake, Montana, Wilson Chemical Company, Seattle, Washington, Co-Ed Club, Professor Koenig, First-Year student course

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In this issue...Oredigger football, American Chemical Society, Student Union Building, Virginia City, Butte, Montana, Tom Minette, Professor Ruggles

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The HIV-1 RT inhibitory activity of 2-(2,6-dihalophenyl)-3-(substituted pyridin-2-yl)-thiazolidin-4-ones has been analyzed with different topological descriptors obtained from DRAGON software. Here, simple topological descriptors (TOPO), Galvez topological charge indices (GVZ) and 2D autocorrelation descriptors (2DAUTO) have been found to yield good predictive models for the activity of these compounds. The correlations obtained from the TOPO class descriptors suggest that less extended or compact saturated structural templates would be better for the activity. The participating GVZ class descriptors suggest that they have same degree of influence on the activity. In 2DAUTO class, the large participation of descriptors of lags seven and three indicate the association of activity information with the seven and three centered structural fragments of these compounds. The physicochemical weighting components of these descriptors suggest homogeneous influence of mass, volume, electronegativity and/ or polarizability on the activity.

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Objective. To investigate the association of the three major genetic groups of Mycobacterium tuberculosis with pulmonary and extra-pulmonary tuberculosis in clustered and non-clustered TB cases in the Houston area. ^ Study design. Secondary analysis of an ambi-directional study. ^ Study population. Three hundred fifty-eight confirmed cases of tuberculosis in the Houston that occurred between October 1995 and May 1997, who had been interviewed by the Houston T13 Initiative staff at Baylor College of Medicine, and whose isolates have had their DNA fingerprint and genetic group determined. ^ Exclusions. Individuals whose mycobacterial genotype was unknown, or whose data variables were unavailable. ^ Source of data. Laboratory results, patient interviews, and medical records at clinics and hospitals of the study population. ^ Results. In clustered cases, the majority of both, pulmonary and extra-pulmonary TB cases were caused by genetic group 1. Independent factors were assessed to determine the interactions that may influence the site of infection or increase the risk for one site or another. HIV negative males were protected against extra-pulmonary TB compared to HIV negative females. Individuals ages 1–14 years were at higher risk of having extra-pulmonary TB. Group 3 organisms were found less frequently in the total population in general, especially in extra-pulmonary disease. This supports the evidence in previous studies that this group is the least virulent and genetically distinct from the other two groups. Group 1 was found more frequently among African Americans than other ethnic groups, a trend for future investigations. ^ Among the non-clustered cases, group 2 organisms were the majority of the organisms found in both sites. They were also the majority of organisms found in African Americans, Caucasians, and Hispanics causing the majority of the infections at both sites. However, group 1 organisms were the overwhelming majority found in Asian/Pacific Islander individuals, which may indicate these organisms are either endemic to that area, or that there is an ethnic biological factor involved. This may also be due to a systematic bias, since isolates from individuals from that geographic region lack adequate copies of the insertion sequence IS6110, which leads to their placement in the non-clustered population. ^ The three genetic groups of Mycobacterium tuberculosis were not found equally distributed between sites of infection in both clustered and non-clustered cases. Furthermore, these groups were not distributed in the same patterns among the clustered and non-clustered cases, but rather in distinct patterns. ^

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The comparison of radiotherapy techniques regarding secondary cancer risk has yielded contradictory results possibly stemming from the many different approaches used to estimate risk. The purpose of this study was to make a comprehensive evaluation of different available risk models applied to detailed whole-body dose distributions computed by Monte Carlo for various breast radiotherapy techniques including conventional open tangents, 3D conformal wedged tangents and hybrid intensity modulated radiation therapy (IMRT). First, organ-specific linear risk models developed by the International Commission on Radiological Protection (ICRP) and the Biological Effects of Ionizing Radiation (BEIR) VII committee were applied to mean doses for remote organs only and all solid organs. Then, different general non-linear risk models were applied to the whole body dose distribution. Finally, organ-specific non-linear risk models for the lung and breast were used to assess the secondary cancer risk for these two specific organs. A total of 32 different calculated absolute risks resulted in a broad range of values (between 0.1% and 48.5%) underlying the large uncertainties in absolute risk calculation. The ratio of risk between two techniques has often been proposed as a more robust assessment of risk than the absolute risk. We found that the ratio of risk between two techniques could also vary substantially considering the different approaches to risk estimation. Sometimes the ratio of risk between two techniques would range between values smaller and larger than one, which then translates into inconsistent results on the potential higher risk of one technique compared to another. We found however that the hybrid IMRT technique resulted in a systematic reduction of risk compared to the other techniques investigated even though the magnitude of this reduction varied substantially with the different approaches investigated. Based on the epidemiological data available, a reasonable approach to risk estimation would be to use organ-specific non-linear risk models applied to the dose distributions of organs within or near the treatment fields (lungs and contralateral breast in the case of breast radiotherapy) as the majority of radiation-induced secondary cancers are found in the beam-bordering regions.