Adverse Effects of Trichothiodystrophy DNA Repair and Transcription Gene Abnormalities on Human Fetal Development

The effects of DNA repair and transcription genes in human prenatal life have never been studied. Trichothiodystrophy (TTD) is a rare (affected frequency of 10^-6^) recessive disorder caused by mutations in genes involved in the nucleotide excision repair (NER) pathway and in transcription. Based on our clinical observations, we conducted a genetic epidemiologic study to investigate gestational outcomes associated with TTD. We compared pregnancies resulting in TTD-affected offspring (N=24) with respect to abnormalities in their antenatal and neonatal periods to pregnancies resulting in their unaffected siblings (N=18), accounting for correlation, and to population reference values. Significantly higher incidence of several severe gestational complications was noted in TTD-affected pregnancies. Gestational complications were noted in nearly all pregnancies resulting in TTD-affected offspring with _XPD_ and _TTDN1_, but not _TTD-A_, gene mutations. Abnormal placental development may explain the constellation of observed complications; therefore, we hypothesize that some TTD genes play an important role in normal placental and fetal development. We investigated this hypothesis by analyzing the expression patterns of TTD genes. Expression of _TTDA_ was strongly negatively correlated (r=-0.7,P<0.0001) with gestational age, while _XPD, XPB_ and _TTDN1_ were consistently expressed from 14 to 40 weeks gestation. *Conclusion:* Our results indicate an important role for _XPD, XPB_ and _TTDN1_ gene products during normal human placental and fetal development

Modelling Energy Consumption based on Resource Utilization

Power management is an expensive and important issue for large computational infrastructures such as datacenters, large clusters, and computational grids. However, measuring energy consumption of scalable systems may be impractical due to both cost and complexity for deploying power metering devices on a large number of machines. In this paper, we propose the use of information about resource utilization (e.g. processor, memory, disk operations, and network traffic) as proxies for estimating power consumption. We employ machine learning techniques to estimate power consumption using such information which are provided by common operating systems. Experiments with linear regression, regression tree, and multilayer perceptron on data from different hardware resulted into a model with 99.94\% of accuracy and 6.32 watts of error in the best case.Comment: Submitted to Journal of Supercomputing on 14th June, 201

Early transcriptome changes associated with western diet induced NASH in Ldlr−/− mice points to activation of hepatic macrophages and an acute phase response

BackgroundNonalcoholic fatty liver disease (NAFLD) is a global health problem. Identifying early gene indicators contributing to the onset and progression of NAFLD has the potential to develop novel targets for early therapeutic intervention. We report on the early and late transcriptomic signatures of western diet (WD)-induced nonalcoholic steatohepatitis (NASH) in female and male Ldlr−/− mice, with time-points at 1 week and 40 weeks on the WD. Control Ldlr−/− mice were maintained on a low-fat diet (LFD) for 1 and 40 weeks.MethodsThe approach included quantitation of anthropometric and hepatic histology markers of disease as well as the hepatic transcriptome.ResultsOnly mice fed the WD for 40 weeks revealed evidence of NASH, i.e., hepatic steatosis and fibrosis. RNASeq transcriptome analysis, however, revealed multiple cell-specific changes in gene expression after 1 week that persisted to 40 weeks on the WD. These early markers of disease include induction of acute phase response (Saa1-2, Orm2), fibrosis (Col1A1, Col1A2, TGFβ) and NASH associated macrophage (NAM, i.e., Trem2 high, Mmp12 low). We also noted the induction of transcripts associated with metabolic syndrome, including Mmp12, Trem2, Gpnmb, Lgals3 and Lpl. Finally, 1 week of WD feeding was sufficient to significantly induce TNFα, a cytokine involved in both hepatic and systemic inflammation.ConclusionThis study revealed early onset changes in the hepatic transcriptome that develop well before any anthropometric or histological evidence of NALFD or NASH and pointed to cell-specific targeting for the prevention of disease progression

Interaction between the microbiome and TP53 in human lung cancer.

BACKGROUND: Lung cancer is the leading cancer diagnosis worldwide and the number one cause of cancer deaths. Exposure to cigarette smoke, the primary risk factor in lung cancer, reduces epithelial barrier integrity and increases susceptibility to infections. Herein, we hypothesize that somatic mutations together with cigarette smoke generate a dysbiotic microbiota that is associated with lung carcinogenesis. Using lung tissue from 33 controls and 143 cancer cases, we conduct 16S ribosomal RNA (rRNA) bacterial gene sequencing, with RNA-sequencing data from lung cancer cases in The Cancer Genome Atlas serving as the validation cohort. RESULTS: Overall, we demonstrate a lower alpha diversity in normal lung as compared to non-tumor adjacent or tumor tissue. In squamous cell carcinoma specifically, a separate group of taxa are identified, in which Acidovorax is enriched in smokers. Acidovorax temporans is identified within tumor sections by fluorescent in situ hybridization and confirmed by two separate 16S rRNA strategies. Further, these taxa, including Acidovorax, exhibit higher abundance among the subset of squamous cell carcinoma cases with TP53 mutations, an association not seen in adenocarcinomas. CONCLUSIONS: The results of this comprehensive study show both microbiome-gene and microbiome-exposure interactions in squamous cell carcinoma lung cancer tissue. Specifically, tumors harboring TP53 mutations, which can impair epithelial function, have a unique bacterial consortium that is higher in relative abundance in smoking-associated tumors of this type. Given the significant need for clinical diagnostic tools in lung cancer, this study may provide novel biomarkers for early detection

Estimation of low frequency antigen-presenting cells with a novel RELISPOT assay

Adequate presentation of self and foreign antigens is a key factor for efficient T-cell immunosurveillance against pathogens and tumors. Cells presenting foreign antigens usually comprise a rare population and are difficult to detect even at the peak of infection. Here we demonstrate a CD8(+) T-cell-based approach that allows detection of specific antigen-presenting cells (APC) at a frequency of less than 0.0005%. When T cells are in excess, they form rosettes with rare APCs, which appear as single spots in an IFN-gamma ELISPOT assay. Using this RELISPOT (Rosette ELISPOT) method we demonstrate the dynamic interplay between CD8 T cells and professional and non-professional APCs following virus challenge