2 resultados para nuclear densities and introduced new imaginary potential component


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Some sites of extrapulmonary tuberculosis and focal complications of brucellosis are very difficult to differentiate clinically, radiologically, and even histopathologically. Conventional microbiological methods for the diagnosis of extrapulmonary tuberculosis and complicated brucellosis not only lack adequate sensitivity, they are also time consuming, which could lead to an unfavourable prognosis. The aim of this work was to develop a multiplex real-time PCR assay based on SYBR Green I to simultaneously detect Brucella spp and Mycobacterium tuberculosis complex and evaluate the efficacy of the technique with different candidate genes. The IS711, bcsp31 and omp2a genes were used for the identification of Brucella spp and the IS6110, senX3-regX3 and cfp31 genes were targeted for the detection of the M. tuberculosis complex. As a result of the different combinations of primers, nine different reactions were evaluated. A test was defined as positive only when the gene combinations were capable of co-amplifying both pathogens in a single reaction tube and showed distinguishable melting temperatures for each microorganism. According to the melting analysis, only three combinations of amplicons (senX3-regX3+bcsp31, senX3-regX3+IS711 and IS6110+IS711) were visible. Detection limits of senX3-regX3+bcsp31 and senX3-regX3+IS711 were of 2 and 3 genome equivalents for M. tuberculosis complex and Brucella while for IS6110+IS711 they were of 200 and 300 genome equivalents, respectively. The three assays correctly identified all the samples, showing negative results for the control patients. The presence of multicopy elements and GC content were the components most influencing the efficiency of the test; this should be taken into account when designing a multiplex-based SYBR Green I assay. In conclusion, multiplex real time PCR assays based on the targets senX3-regX3+bcsp31 and senX3-regX3+IS711 using SYBR Green I are highly sensitive and reproducible. This may therefore be a practical approach for the rapid differential diagnosis between extrapulmonary tuberculosis and complicated brucellosis.

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BACKGROUND & AIMS Hy's Law, which states that hepatocellular drug-induced liver injury (DILI) with jaundice indicates a serious reaction, is used widely to determine risk for acute liver failure (ALF). We aimed to optimize the definition of Hy's Law and to develop a model for predicting ALF in patients with DILI. METHODS We collected data from 771 patients with DILI (805 episodes) from the Spanish DILI registry, from April 1994 through August 2012. We analyzed data collected at DILI recognition and at the time of peak levels of alanine aminotransferase (ALT) and total bilirubin (TBL). RESULTS Of the 771 patients with DILI, 32 developed ALF. Hepatocellular injury, female sex, high levels of TBL, and a high ratio of aspartate aminotransferase (AST):ALT were independent risk factors for ALF. We compared 3 ways to use Hy's Law to predict which patients would develop ALF; all included TBL greater than 2-fold the upper limit of normal (×ULN) and either ALT level greater than 3 × ULN, a ratio (R) value (ALT × ULN/alkaline phosphatase × ULN) of 5 or greater, or a new ratio (nR) value (ALT or AST, whichever produced the highest ×ULN/ alkaline phosphatase × ULN value) of 5 or greater. At recognition of DILI, the R- and nR-based models identified patients who developed ALF with 67% and 63% specificity, respectively, whereas use of only ALT level identified them with 44% specificity. However, the level of ALT and the nR model each identified patients who developed ALF with 90% sensitivity, whereas the R criteria identified them with 83% sensitivity. An equal number of patients who did and did not develop ALF had alkaline phosphatase levels greater than 2 × ULN. An algorithm based on AST level greater than 17.3 × ULN, TBL greater than 6.6 × ULN, and AST:ALT greater than 1.5 identified patients who developed ALF with 82% specificity and 80% sensitivity. CONCLUSIONS When applied at DILI recognition, the nR criteria for Hy's Law provides the best balance of sensitivity and specificity whereas our new composite algorithm provides additional specificity in predicting the ultimate development of ALF.