Effect of liver histopathology on islet cell engraftment in the model mimicking autologous islet cell transplantation

Background: The inflammatory milieu in the liver as determined by histopathology is different in individual patients undergoing autologous islet cell transplantation. We hypothesized that inflammation related to fatty-liver adversely impacts islet survival. To test this hypothesis, we used a mouse model of fatty-liver to determine the outcome of syngeneic islet transplantation after chemical pancreatectomy. Methods: Mice (C57BL/6) were fed a high-fat-diet from 6 weeks of age until attaining a weight of ≥28 grams (6–8 weeks) to produce a fatty liver (histologically > 30% fat);steatosis was confirmed with lipidomic profile of liver tissue. Islets were infused via the intra-portal route in fatty-liver and control mice after streptozotocin induction of diabetes. Outcomes were assessed by the rate of euglycemia, liver histopathology, evaluation of liver inflammation by measuring tissue cytokines IL-1β and TNF-α by RT-PCR and CD31 expression by immunohistochemistry. Results: The difference in the euglycemic fraction between the normal liver group (90%, 9/10) and the fatty-liver group (37.5%, 3/8) was statistically significant at the 18th day post- transplant and was maintained to the end of the study (day 28) (p = 0.019, X2 = 5.51). Levels of TNF–α and IL-1β were elevated in fatty-liver mice (p = 0.042, p = 0.037). Compared to controls cytokine levels were elevated after islet cell transplantation and in transplanted fatty-liver mice as compared to either fatty- or islet transplant group alone (p = NS). A difference in the histochemical pattern of CD31 could not be determined. Conclusion: Fatty-liver creates an inflammatory state which adversely affects the outcome of autologous islet cell transplantation

Investigation of the failure mechanism and theoretical model of bolt-reinforced shallow tunnel faces with different bolt lengths

Using fiberglass bolts to reinforce a tunnel face is a practical auxiliary technology for ensuring tunnel face stability in soft ground. The reinforcing effect and the economics of this technology are significantly affected by bolt length. However, to date, the failure mechanism of bolt-reinforced tunnel faces with different bolt lengths has rarely been investigated. To reveal the failure mechanism of bolt-reinforced shallow tunnel faces, in this study, the stability of bolt-reinforced tunnel faces with different bolt lengths was investigated by using laboratory tests and numerical simulations, and a simplified theoretical model for practical engineering was proposed. The face support pressure and failure pattern for different bolt lengths during the face collapse process were obtained, and the influence of bolt length on face stability was clearly revealed. More specifically, the results show that face stability increases with increasing bolt length, and the reinforcing effect of face bolts is governed by the shear failure at the soil-grout interface first in the stable zone of the tunnel face and then in the failure zone. Once the bolt length in the stable zone is larger than that in the failure zone, face stability will not be improved with increasing bolt length; thus, this bolt length is referred to as the optimal bolt length Lopt. The Lopt value is slightly larger than the initial failure range (in the unreinforced condition) and can be approximately calculated by Lopt = (1 − 0.0133φ)D (φ is the friction angle of the soil, and D is the tunnel diameter) in practical engineering. Finally, a simplified theoretical model was established to analyse the stability of reinforced tunnel faces, and the results are in good agreement with both laboratory tests and numerical simulations. The proposed model can be used as an efficient tool for the design of face bolts

UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation

Global transcriptomic and proteomic profiling platforms have yielded important insights into the complex response to ionizing radiation (IR). Nonetheless, little is known about the ways in which small cellular metabolite concentrations change in response to IR. Here, a metabolomics approach using ultraperformance liquid chromatography coupled with electrospray time-of-flight mass spectrometry was used to profile, over time, the hydrophilic metabolome of TK6 cells exposed to IR doses ranging from 0.5 to 8.0 Gy. Multivariate data analysis of the positive ions revealed dose- and time-dependent clustering of the irradiated cells and identified certain constituents of the water-soluble metabolome as being significantly depleted as early as 1 h after IR. Tandem mass spectrometry was used to confirm metabolite identity. Many of the depleted metabolites are associated with oxidative stress and DNA repair pathways. Included are reduced glutathione, adenosine monophosphate, nicotinamide adenine dinucleotide, and spermine. Similar measurements were performed with a transformed fibroblast cell line, BJ, and it was found that a subset of the identified TK6 metabolites were effective in IR dose discrimination. The GEDI (Gene Expression Dynamics Inspector) algorithm, which is based on self-organizing maps, was used to visualize dynamic global changes in the TK6 metabolome that resulted from IR. It revealed dose-dependent clustering of ions sharing the same trends in concentration change across radiation doses. "Radiation metabolomics," the application of metabolomic analysis to the field of radiobiology, promises to increase our understanding of cellular responses to stressors such as radiation

Identification of noninvasive biomarkers for alcohol-induced liver disease using urinary metabolomics and the Ppara-null mouse

Alcohol-induced liver disease (ALD) is a leading cause of nonaccident-related deaths in the United States. Although liver damage caused by ALD is reversible when discovered at the earlier stages, current risk assessment tools are relatively nonspecific. Identification of an early specific signature of ALD would aid in therapeutic intervention and recovery. In this study, the metabolic changes associated with ALD were examined using alcohol-fed male Ppara-null mouse as a model of ALD. Principal components analysis of the mass spectrometry-based urinary metabolic profile showed that alcohol-treated wild-type and Ppara-null mice could be distinguished from control animals without information on history of alcohol consumption. The urinary excretion of ethyl-sulfate, ethyl-beta-d-glucuronide, 4-hydroxyphenylacetic acid, and 4-hydroxyphenylacetic acid sulfate was elevated and that of the 2-hydroxyphenylacetic acid, adipic acid, and pimelic acid was depleted during alcohol treatment in both wild-type and the Ppara-null mice albeit to different extents. However, indole-3-lactic acid was exclusively elevated by alcohol exposure in Ppara-null mice. The elevation of indole-3-lactic acid is mechanistically related to the molecular events associated with development of ALD in alcohol-treated Ppara-null mice. This study demonstrated the ability of a metabolomics approach to identify early, noninvasive biomarkers of ALD pathogenesis in Ppara-null mouse model

The Human Toxome Project

The Human Toxome Project, funded as an NIH Transformative Research grant 2011-2016, is focused on developing the concepts and the means for deducing, validating and sharing molecular pathways of toxicity (PoT). Using the test case of estrogenic endocrine disruption, the responses of MCF-7 human breast cancer cells are being phenotyped by transcriptomics and mass-spectrometry-based metabolomics. The bioinformatics tools for PoT deduction represent a core deliverable. A number of challenges for quality and standardization of cell systems, omics technologies and bioinformatics are being addressed. In parallel, concepts for annotation, validation and sharing of PoT information, as well as their link to adverse outcomes, are being developed. A reasonably comprehensive public database of PoT, the Human Toxome Knowledge-base, could become a point of reference for toxicological research and regulatory test strategies