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As one of the most induced genes in activated macrophages, immune-responsive gene 1 (IRG1) encodes a mitochondrial metabolic enzyme catalysing the production of itaconic acid (ITA). Although ITA has an anti-inflammatory property, the underlying mechanisms are not fully understood. Here we show that ITA is a potent inhibitor of the TET-family DNA dioxygenases. ITA binds to the same site on TET2 as the co-substrate α-ketoglutarate, inhibiting TET2 catalytic activity. Lipopolysaccharide treatment, which induces Irg1 expression and ITA accumulation, inhibits Tet activity in macrophages. Transcriptome analysis reveals that TET2 is a major target of ITA in suppressing lipopolysaccharide-induced genes, including those regulated by the NF-κB and STAT signalling pathways. In vivo, ITA decreases the levels of 5-hydroxymethylcytosine, reduces lipopolysaccharide-induced acute pulmonary oedema as well as lung and liver injury, and protects mice against lethal endotoxaemia, depending on the catalytic activity of Tet2. Our study thus identifies ITA as an immune modulatory metabolite that selectively inhibits TET enzymes to dampen the inflammatory responses.

Characterizing percolation patterns in unsaturated zones has posed a greater challenge to numerical modeling investigations than comparable saturated zone studies, because of the heterogeneous nature of unsaturated media as well as the great number of variables impacting unsaturated zone flow. This paper presents an integrated modeling methodology for quantitatively characterizing percolation patterns in the unsaturated zone of Yucca Mountain, Nevada, a proposed underground repository site for storing high-level radioactive waste. It takes into account the multiple coupled processes of air, water, heat flow and chemical isotopic transport in Yucca Mountain s highly heterogeneous, unsaturated fractured tuffs. The modeling approach integrates a wide variety of moisture, pneumatic, thermal, and isotopic geochemical field data into a comprehensive three-dimensional numerical model for modeling analyses. Modeling results are examined against different types of field-measured data and then used to evaluate different hydrogeological conceptual models and their results of flow patterns in the unsaturated zone. In particular, this integration model provides a much clearer understanding of percolation patterns and flow behavior through the unsaturated zone, both crucial issues in assessing repository performance. The integrated approach for quantifying Yucca Mountain s flow system is also demonstrated to provide a comprehensive modeling tool for characterizing flow and transport processes in complex subsurface systems.

Two biodegradation models are developed to represent natural attenuation of fuel-hydrocarbon contaminants as observed in a comprehensive natural-gradient tracer test in a heterogeneous aquifer on the Columbus Air Force Base in Mississippi, USA. The first, a first-order mass loss model, describes the irreversible losses of BTEX and its individual components, i.e., benzene (B), toluene (T), ethyl benzene (E), and xylene (X). The second, a reactive pathway model, describes sequential degradation pathways for BTEX utilizing multiple electron acceptors, including oxygen, nitrate, iron and sulfate, and via methanogenesis. The heterogeneous aquifer is represented by multiple hydraulic conductivity (K) zones delineated on the basis of numerous flowmeter K measurements. A direct propagation artificial neural network (DPN) is used as an inverse modeling tool to estimate the biodegradation rate constants associated with each of the K zones. In both the mass loss model and the reactive pathway model, the biodegradation rate constants show an increasing trend with the hydraulic conductivity. The finding of correlation between biodegradation kinetics and hydraulic conductivity distributions is of general interest and relevance to characterization and modeling of natural attenuation of hydrocarbons in other petroleum-product contaminated sites.

This paper presents a large-scale modeling study characterizing fluid flow and tracer transport in the unsaturated zone of Yucca Mountain, Nevada, the proposed underground repository site for storing high-level radioactive waste. The modeling study is conducted using a three-dimensional numerical model, which incorporates a wide variety of field data and takes into account the coupled processes of flow and transport in Yucca Mountain's highly heterogeneous, unsaturated, fractured porous rock. The modeling approach is based on a dual-continuum formulation. Using different conceptual models of unsaturated flow, various scenarios of current and future climate conditions and their effects on the unsaturated zone are evaluated to aid in the assessment of the repository's system performance. These models are calibrated against field-measured data. Model-predicted flow and transport processes under current and future climates are discussed.