Discernment of possible mechanisms of hepatotoxicity via biological processes over-represented by co-expressed genes

<p>Abstract</p> <p>Background</p> <p>Hepatotoxicity is a form of liver injury caused by exposure to stressors. Genomic-based approaches have been used to detect changes in transcription in response to hepatotoxicants. However, there are no straightforward ways of using co-expressed genes anchored to a phenotype or constrained by the experimental design for discerning mechanisms of a biological response.</p> <p>Results</p> <p>Through the analysis of a gene expression dataset containing 318 liver samples from rats exposed to hepatotoxicants and leveraging alanine aminotransferase (ALT), a serum enzyme indicative of liver injury as the phenotypic marker, we identified biological processes and molecular pathways that may be associated with mechanisms of hepatotoxicity. Our analysis used an approach called Coherent Co-expression Biclustering (cc-Biclustering) for clustering a subset of genes through a coherent (consistency) measure within each group of samples representing a subset of experimental conditions. Supervised biclustering identified 87 genes co-expressed and correlated with ALT in all the samples exposed to the chemicals. None of the over-represented pathways related to liver injury. However, biclusters with subsets of samples exposed to one of the 7 hepatotoxicants, but not to a non-toxic isomer, contained co-expressed genes that represented pathways related to a stress response. Unsupervised biclustering of the data resulted in 1) four to five times more genes within the bicluster containing all the samples exposed to the chemicals, 2) biclusters with co-expression of genes that discerned 1,4 dichlorobenzene (a non-toxic isomer at low and mid doses) from the other chemicals, pathways and biological processes that underlie liver injury and 3) a bicluster with genes up-regulated in an early response to toxic exposure.</p> <p>Conclusion</p> <p>We obtained clusters of co-expressed genes that over-represented biological processes and molecular pathways related to hepatotoxicity in the rat. The mechanisms involved in the response of the liver to the exposure to 1,4-dichlorobenzene suggest non-genotoxicity whereas the exposure to the hepatotoxicants could be DNA damaging leading to overall genomic instability and activation of cell cycle check point signaling. In addition, key pathways and biological processes representative of an inflammatory response, energy production and apoptosis were impacted by the hepatotoxicant exposures that manifested liver injury in the rat.</p

The economic impacts of green product development

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1994.Includes bibliographical references (leaves 85-89).by Jeff Yen-Chou Chen.M.S

Spiral Antenna with Reconfigurable HIS using Liquid Crystals for Monopulse Radar Application

Combined meta-intersections between two algorithms SOM and k-means. This Excel file contains final 23 meta-intersections as described in Results section. Each intersection is in separate tab, which also contains gene-annotation enrichment analysis results. (XLSX 721 kb

Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV) or ionizing radiation (IR)-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying biological processes affected by IR- and/or UV- induced DNA damage. Conclusion EPIG competed with CLICK and performed better than CAST in extracting patterns from simulated data. EPIG extracted more biological informative patterns and co-expressed genes from both C. elegans and IR/UV-treated human fibroblasts. Using Gene Ontology analysis of the genes in the patterns extracted by EPIG, several key biological categories related to p53-dependent cell cycle control were revealed from the IR/UV data. Among them were mitotic cell cycle, DNA replication, DNA repair, cell cycle checkpoint, and G0-like status transition. EPIG can be applied to data sets from a variety of experimental designs

Identification of Genes Implicated in Methapyrilene-Induced Hepatotoxicity by Comparing Differential Gene Expression in Target and Nontarget Tissue

BACKGROUND: Toxicogenomics experiments often reveal thousands of transcript alterations that are related to multiple processes, making it difficult to identify key gene changes that are related to the toxicity of interest. OBJECTIVES: The objective of this study was to compare gene expression changes in a nontarget tissue to the target tissue for toxicity to help identify toxicity-related genes. METHODS: Male rats were given the hepatotoxicant methapyrilene at two dose levels, with livers and kidneys removed 24 hr after one, three, and seven doses for gene expression analysis. To identify gene changes likely to be related to toxicity, we analyzed genes on the basis of their temporal pattern of change using a program developed at the National Institute of Environmental Health Sciences, termed “EPIG” (extracting gene expression patterns and identifying co-expressed genes). RESULTS: High-dose methapyrilene elicited hepatic damage that increased in severity with the number of doses, whereas no treatment-related lesions were observed in the kidney. High-dose methapyrilene elicited thousands of gene changes in the liver at each time point, whereas many fewer gene changes were observed in the kidney. EPIG analysis identified patterns of gene expression correlated to the observed toxicity, including genes associated with endoplasmic reticulum stress and the unfolded protein response. CONCLUSIONS: By factoring in dose level, number of doses, and tissue into the analysis of gene expression elicited by methapyrilene, we were able to identify genes likely to not be implicated in toxicity, thereby allowing us to focus on a subset of genes to identify toxicity-related processes

Taiwan Oscillation Network

The Taiwan Oscillation Network (TON) is a ground-based network to measure solar intensity oscillations to study the internal structure of the Sun. K-line full-disk images of 1000 pixels diameter are taken at a rate of one image per minute. Such data would provide information onp-modes withl as high as 1000. The TON will consist of six identical telescope systems at proper longitudes around the world. Three telescope systems have been installed at Teide Observatory (Tenerife), Huairou Solar Observing Station (near Beijing), and Big Bear Solar Observatory (California). The telescopes at these three sites have been taking data simultaneously since October of 1994. Anl – v diagram derived from 512 images is included to show the quality of the data

The hidden circumgalactic medium

The cycling of baryons in and out of galaxies is what ultimately drives galaxy formation and evolution. The circumgalactic medium (CGM) represents the interface between the interstellar medium and the cosmic web, hence its properties are directly shaped by the baryon cycle. Although traditionally the CGM is thought to consist of warm and hot gas, recent breakthroughs are presenting a new scenario according to which an important fraction of its mass may reside in the cold atomic and molecular phase. This would represent fuel that is readily available for star formation, with crucial implications for feeding and feedback processes in galaxies. However, such cold CGM, especially in local galaxies where its projected size on sky is expected to be of several arcminutes, cannot be imaged by ALMA due to interferometric spatial scale filtering of large-scale structures. We show that the only way to probe the multiphase CGM including its coldest component is through a large (e.g. 50-m) single dish (sub-)mm telescope.Comment: Science white paper submitted to the Astro2020 Decadal Surve

Intrinsic tumor resistance to CAR T cells is a dynamic transcriptional state that is exploitable with low-dose radiation

Chimeric antigen receptor (CAR) T-cell therapy represents a major advancement for hematologic malignancies, with some patients achieving long-term remission. However, the majority of treated patients still die of their disease. A consistent predictor of response is tumor quantity, wherein a higher disease burden before CAR T-cell therapy portends a worse prognosis. Focal radiation to bulky sites of the disease can decrease tumor quantity before CAR T-cell therapy, but whether this strategy improves survival is unknown. We find that substantially reducing systemic tumor quantity using high-dose radiation to areas of bulky disease, which is commonly done clinically, is less impactful on overall survival in mice achieved by CAR T cells than targeting all sites of disease with low-dose total tumor irradiation (TTI) before CAR T-cell therapy. This finding highlights another predictor of response, tumor quality, the intrinsic resistance of an individual patient\u27s tumor cells to CAR T-cell killing. Little is known about whether or how an individual tumor\u27s intrinsic resistance may change under different circumstances. We find a transcriptional death receptor score that reflects a tumor\u27s intrinsic sensitivity to CAR T cells can be temporarily increased by low-dose TTI, and the timing of this transcriptional change correlates with improved in vivo leukemia control by an otherwise limited number of CAR T cells. This suggests an actionable method for potentially improving outcomes in patients predicted to respond poorly to this promising therapy and highlights that intrinsic tumor attributes may be equally or more important predictors of CAR T-cell response as tumor burden