CD68+ cells of monocyte/macrophage lineage in the environment of AIDS-associated and classic-sporadic Kaposi sarcoma are singly or doubly infected with human herpesviruses 7 and 6B

Earlier studies have shown that Kaposi sarcomas contain cells infected with human herpesvirus (HHV) 6B, and in current studies we report that both AIDS-associated and classic-sporadic Kaposi sarcoma contain HHV-7 genome sequences detectable by PCR. To determine the distribution of HHV-7-infected cells relative to those infected with HHV-6, sections from paraffin-embedded tissues were allowed to react with antibodies to HHV-7 virion tegument phosphoprotein pp85 and to HHV-6B protein p101. The antibodies are specific for HHV-7 and HHV-6B, respectively, and they retained reactivity for antigens contained in formalin-fixed, paraffin-embedded tissue samples. We report that (i) HHV-7 pp85 was present in 9 of 32 AIDS-associated Kaposi sarcomas, and in 1 of 7 classical-sporadic HIV-negative Kaposi sarcomas; (ii) HHV-7 pp85 was detected primarily in cells bearing the CD68 marker characteristic of the monocyte/macrophage lineage present in or surrounding the Kaposi sarcoma lesions; and (iii) in a number of Kaposi sarcoma specimens, tumor-associated CD68+ monocytes/macrophages expressed simultaneously antigens from both HHV-7 and HHV-6B, and therefore appeared to be doubly infected with the two viruses. CD68+ monocytes/macrophages infected with HHV-7 were readily detectable in Kaposi sarcoma, but virtually absent from other normal or pathological tissues that harbor macrophages. Because all of the available data indicate that HHV-7 infects CD4+ T lymphocytes, these results suggest that the environment of the Kaposi sarcoma (i) attracts circulating peripheral lymphocytes and monocytes, triggers the replication of latent viruses, and thereby increases the local concentration of viruses, (ii) renders CD68+ monocytes/macrophages susceptible to infection with HHV-7, and (iii) the combination of both events enables double infections of cells with both HHV-6B and HHV-7.

Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations

We present statistical methods for analyzing replicated cDNA microarray expression data and report the results of a controlled experiment. The study was conducted to investigate inherent variability in gene expression data and the extent to which replication in an experiment produces more consistent and reliable findings. We introduce a statistical model to describe the probability that mRNA is contained in the target sample tissue, converted to probe, and ultimately detected on the slide. We also introduce a method to analyze the combined data from all replicates. Of the 288 genes considered in this controlled experiment, 32 would be expected to produce strong hybridization signals because of the known presence of repetitive sequences within them. Results based on individual replicates, however, show that there are 55, 36, and 58 highly expressed genes in replicates 1, 2, and 3, respectively. On the other hand, an analysis by using the combined data from all 3 replicates reveals that only 2 of the 288 genes are incorrectly classified as expressed. Our experiment shows that any single microarray output is subject to substantial variability. By pooling data from replicates, we can provide a more reliable analysis of gene expression data. Therefore, we conclude that designing experiments with replications will greatly reduce misclassification rates. We recommend that at least three replicates be used in designing experiments by using cDNA microarrays, particularly when gene expression data from single specimens are being analyzed.

Phrase-based statistical machine translation: explanation of its processes and statistical models and evaluation of the English to Spanish translations produced

Statistical machine translation (SMT) is an approach to Machine Translation (MT) that uses statistical models whose parameter estimation is based on the analysis of existing human translations (contained in bilingual corpora). From a translation student’s standpoint, this dissertation aims to explain how a phrase-based SMT system works, to determine the role of the statistical models it uses in the translation process and to assess the quality of the translations provided that system is trained with in-domain goodquality corpora. To that end, a phrase-based SMT system based on Moses has been trained and subsequently used for the English to Spanish translation of two texts related in topic to the training data. Finally, the quality of this output texts produced by the system has been assessed through a quantitative evaluation carried out with three different automatic evaluation measures and a qualitative evaluation based on the Multidimensional Quality Metrics (MQM).