Applicability of machine learning models for the assessment of long-term pollutant leaching from solid waste materials.

Column leaching tests are a common approach for evaluating the leaching behavior of contaminated soil and waste materials, which are often reused for various construction purposes. Standardized up-flow column leaching tests typically require about 7 days of laboratory work to evaluate long-term leaching behavior accurately. To reduce testing time, we developed linear and ensemble models based on parametric and non-parametric Machine Learning (ML) techniques. These models predict leachate concentrations of relevant chemical compounds at different Liquid-to-Solid ratios (LS) based on measurements at lower LS values. The ML models were trained using 82 column leaching test samples for Construction and Demolition Waste materials collected in Germany during the last two decades. R-Squared values measuring models' performance are as follows: Sulfate = 0.94, Vanadium = 0.97, Chromium = 0.82, Copper = 0.92, group of 15 (US-EPA) PAHs = 0.98 (values averaged over predictive models for LS 2 and 4). Sensitivity analysis utilizing the Shapley Additive Explanation value indicates that in addition to the concentrations of the considered compound at LS<=1, electrical conductivity and pH are the most critical features of each model, while concentrations of other compounds also play a minor role.

A Fractional-order dual-continuum model to capture non-Fickian solute transport in a regional-scale fractured aquifer.

Contaminant transport in fractured media exhibits complex dynamics, including multiple peaks in breakthrough curves (BTCs) and non-Fickian diffusion, thereby posing significant challenges to the application of traditional transport models. Here we undertook a detailed study of a natural-gradient tracer test conducted in a regional-scale fractured carbonate aquifer situated in southwestern Germany, where the observed BTCs contained both dual peaks and positive skewness. These BTCs were used to optimize parameters and interpret their physical meanings for several transport models, including the dual-continuum model (DCM) and the fractional derivative equation (FDE) model. Tracer concentration distributions were simulated in both single- and dual-continuum media employing the DCM and FDE models. Our results demonstrated that while the DCM model could reasonably replicate the bimodal BTC, the FDE (which accounts for solute retention) outperformed in capturing the heavy-tailed BTC. This was attributed to the limitations of grid-based numerical models that assume Fickian diffusion and fail to map small-scale medium heterogeneity exhaustively. In contrast, a parsimonious model like the FDE, with upscaled parameters, was found to be more effective in capturing regional-scale non-Fickian transport. To further characterize the multiple BTC peaks the standard FDE missed, we proposed a fractional derivative dual-continuum model (fDCM). This model was found to be adept at capturing both the multi-peak and late-time heavy tail in the BTC. Our study thus opens an alternate pathway for modeling solute transport in regional-scale fractured to partially karstified aquifers.

Legacy pollutants in fractured aquifers: Analytical approximations for back diffusion to predict atrazine concentrations under uncertainty.

We present novel analytical approximations for the estimation of travel distance and relative height of solute concentration peaks within a single fracture system for pollutants that have been temporarily applied at a constant rate in the past. These approximations are used to investigate the spatiotemporal evolution of the concentration of atrazine, as an example for many other so-called legacy compounds that are still found in the groundwater of fractured rock aquifers even decades after their application has stopped. This is done in a stochastic framework to account for the uncertainty in relevant parameters, focusing on probabilities of exceeding the given legal concentration limit and the expected length of the recovery period. We specifically consider the properties of the Muschelkalk limestone aquifer in the Ammer river catchment in SW Germany, and the three major types of carbonate rock facies: Shoal, Tempestite, and Basinal limestones. Atrazine sorption parameters have been determined in laboratory experiments. The simulations confirm that diffusion-limited sorption and desorption may cause considerable atrazine levels long after application stop. For the properties of the considered rock facies types, and corresponding parameter ranges, atrazine concentration above the legal limit is supposed to be limited to locations referring to only a few years of travel time. If the concentration exceeds the legal limit by the year 2022, it will take decades to centuries until recovery.

First order approximation for coupled film and intraparticle pore diffusion to model sorption/desorption batch experiments.

A simple first order approximation was derived to model sorption/desorption kinetics of hazardous compounds in batch experiments based on a coupled film and intraparticle diffusion model. The solution is accurate enough to replace infinite series expansions needed in analytical solution for intraparticle diffusion and it accounts for the mass transfer shift from diffusion in the external aqueous boundary layer to the intraparticle pore space. With increasing distribution coefficient (Kd) and intraparticle particle porosity (ε) or decreasing Sherwood number (Sh) this mass transfer shift from film diffusion to intraparticle pore diffusion is delayed. The simple first order approximation equation allows analyses of mass transfer resistances and calculation of characteristic times which is relevant for the planning of batch experiments. The proposed solution is verified by a semi-analytical solution in Laplace space for fractional mass uptakes in the solid phase at equilibrium ranging from 50% to 91%, representing scenarios typically encountered in batch experiments.

Mass Transfer Principles in Column Percolation Tests: Initial Conditions and Tailing in Heterogeneous Materials.

Initial conditions (pre-equilibrium or after the first flooding of the column), mass transfer mechanisms and sample composition (heterogeneity) have a strong impact on leaching of less and strongly sorbing compounds in column percolation tests. Mechanistic models as used in this study provide the necessary insight to understand the complexity of column leaching tests especially when heterogeneous samples are concerned. By means of numerical experiments, we illustrate the initial concentration distribution inside the column after the first flooding and how this impacts leaching concentrations. Steep concentration gradients close to the outlet of the column have to be expected for small distribution coefficients (Kd<1 L kg-1) and longitudinal dispersion leads to smaller initial concentrations than expected under equilibrium conditions. In order to elucidate the impact of different mass transfer mechanisms, film diffusion across an external aqueous boundary layer (first order kinetics, FD) and intraparticle pore diffusion (IPD) are considered. The results show that IPD results in slow desorption kinetics due to retarded transport within the tortuous intragranular pores. Non-linear sorption has not much of an effect if compared to Kd values calculated for the appropriate concentration range (e.g., the initial equilibrium concentration). Sample heterogeneity in terms of grain size and different fractions of sorptive particles in the sample have a strong impact on leaching curves. A small fraction (<1%) of strongly sorbing particles (high Kd) carrying the contaminant may lead to very slow desorption rates (because of less surface area)-especially if mass release is limited by IPD-and thus non-equilibrium. In contrast, mixtures of less sorbing fine material ("labile" contamination with low Kd), with a small fraction of coarse particles carrying the contaminant leads to leaching close to or at equilibrium showing a step-wise concentration decline in the column effluent.

Impact of pre-equilibration and diffusion limited release kinetics on effluent concentration in column leaching tests: Insights from numerical simulations.

Column leaching tests have become a standard method for assessing leaching of pollutants from materials used, e.g., for road and railway constructions and in landscaping measures. Column tests showed to be practical in laboratories yielding robust and reproducible results. However, considerable uncertainty still exists related particularly to the degree of equilibration of the pore water with the solids during preparation (pre-equilibration) and percolation of the column. We analyse equilibration time scales and sensitivity of concentrations in column leachate with respect to initial conditions in a series of numerical experiments covering a broad spectrum of material and solute properties. Slow release of pollutants from solid materials is described by a spherical diffusion model of kinetic sorption accounting for multiple grain size fractions and sorption capacities. Results show that the cumulative concentrations are rather independent of the pre-equilibration level for a broad spectrum of parameter settings, e.g. if intra-particle porosity is high, grain size is small, or if the sorption coefficient is large. Sensitivity increases with decreasing liquid solid ratios and contact time during percolation. Significant variations with initial column conditions are to be expected for material and compound properties leading to slow release kinetics. In these cases, sensitivity to initial conditions may have to be considered.

Exposure-time based modeling of nonlinear reactive transport in porous media subject to physical and geochemical heterogeneity.

Transport of reactive solutes in groundwater is affected by physical and chemical heterogeneity of the porous medium, leading to complex spatio-temporal patterns of concentrations and reaction rates. For certain cases of bioreactive transport, it could be shown that the concentrations of reactive constituents in multi-dimensional domains are approximately aligned with isochrones, that is, lines of identical travel time, provided that the chemical properties of the matrix are uniform. We extend this concept to combined physical and chemical heterogeneity by additionally considering the time that a water parcel has been exposed to reactive materials, the so-called exposure time. We simulate bioreactive transport in a one-dimensional domain as function of time and exposure time, rather than space. Subsequently, we map the concentrations to multi-dimensional heterogeneous domains by means of the mean exposure time at each location in the multi-dimensional domain. Differences in travel and exposure time at a given location are accounted for as time difference. This approximation simplifies reactive-transport simulations significantly under conditions of steady-state flow when reactions are restricted to specific locations. It is not expected to be exact in realistic applications because the underlying assumption, such as neglecting transverse mixing altogether, may not hold. We quantify the error introduced by the approximation for the hypothetical case of a two-dimensional, binary aquifer made of highly-permeable, non-reactive and low-permeable, reactive materials releasing dissolved organic matter acting as electron donor for aerobic respiration and denitrification. The kinetically controlled reactions are catalyzed by two non-competitive bacteria populations, enabling microbial growth. Even though the initial biomass concentrations were uniform, the interplay between transport, non-uniform electron-donor supply, and bio-reactions led to distinct spatial patterns of the two types of biomass at late times. Results obtained by mapping the exposure-time based results to the two-dimensional domain are compared with simulations based on the two-dimensional, spatially explicit advection-dispersion-reaction equation. Once quasi-steady state has been reached, we find a good agreement in terms of the chemical-compound concentrations between the two approaches inside the reactive zones, whereas the exposure-time based model is not able to capture reactions occurring in the zones with zero electron-donor release. We conclude that exposure-time models provide good approximations of nonlinear bio-reactive transport when transverse mixing is not the overall controlling process and all reactions are essentially restricted to distinct reactive zones.

1D-¹H-nuclear magnetic resonance metabolomics reveals age-related changes in metabolites associated with experimental venous thrombosis.

OBJECTIVE: Age is a significant risk factor for the development of venous thrombosis (VT), but the mechanism(s) that underlie this risk remain(s) undefined and poorly understood. Aging is known to adversely influence inflammation and affect metabolism. Untargeted metabolomics permits an agnostic assessment of the physiological landscape and lends insight into the mechanistic underpinnings of clinical phenotypes. The objective of this exploratory study was to test the feasibility of a metabolomics approach for identifying potential metabolic mechanisms of age-related VT. METHODS: We subjected whole blood samples collected from young and old nonthrombosed controls and VT mice 2 days after thrombus induction using the electrolytic inferior vena cava, to a methanol:chloroform extraction and assayed the resulting aqueous fractions using 1D-(1)H- nuclear magnetic resonance. Normalized mouse metabolite data were compared across groups using analysis of variance (ANOVA) with Holm-Sidak post-testing. In addition, associations between metabolite concentrations and parameters of thrombosis such as thrombus and vein wall weights, and markers of inflammation, vein wall P- and E-selectin levels, were assessed using linear regression. The relatedness of the found significant metabolites was visually assessed using a bioinformatics tool, Metscape, which generates compound-reaction-enzyme-gene networks to aid in the interpretation of metabolomics data. RESULTS: Old mice with VT had a greater mean vein wall weight compared with young mice with VT (P < .05). Clot weight differences between old and young mice followed the same trend as vein wall weight (0.011 ± 0.04 g vs 0.008 ± 0.003 g; P = not significant). Glutamine (ANOVA, P < .01), proline (ANOVA, P < .01), and phenylalanine (ANOVA, P < .05) levels were increased in old VT mice compared with age-matched controls and young VT mice. Betaine and/or trimethylamine N-oxide levels were increased in aged mice compared with young animals. Vein wall weight was strongly associated with glutamine (P < .05), and phenylalanine (P < .01) concentrations and there was a trend toward an association with proline (P = .09) concentration. Vein wall P-selectin, but not E-selectin levels, were increased in old VT mice and were associated with the three found metabolites of age-related VT. Collectively, with the addition of glutamate, these metabolites form a single compound-reaction-enzyme-gene network that was generated by Metscape. CONCLUSIONS: We used 1D-(1)H-nuclear magnetic resonance-metabolite profiling to identify, for the first time, in an experimental model, three potential metabolites, glutamine, phenylalanine, and proline, associated with age-related VT. These metabolites are metabolically related and their levels are associated with vein wall weight and P-selectin concentrations. In aggregate, these findings provide a "roadmap" of pathways that could be interrogated in future studies, which could include provocation of the glutamine, phenylalanine, and proline pathways in the vein wall. This study introduces metabolomics as a new approach to furthering knowledge about the mechanisms of age-related VT.

Using travel times to simulate multi-dimensional bioreactive transport in time-periodic flows.

In travel-time models, the spatially explicit description of reactive transport is replaced by associating reactive-species concentrations with the travel time or groundwater age at all locations. These models have been shown adequate for reactive transport in river-bank filtration under steady-state flow conditions. Dynamic hydrological conditions, however, can lead to fluctuations of infiltration velocities, putting the validity of travel-time models into question. In transient flow, the local travel-time distributions change with time. We show that a modified version of travel-time based reactive transport models is valid if only the magnitude of the velocity fluctuates, whereas its spatial orientation remains constant. We simulate nonlinear, one-dimensional, bioreactive transport involving oxygen, nitrate, dissolved organic carbon, aerobic and denitrifying bacteria, considering periodic fluctuations of velocity. These fluctuations make the bioreactive system pulsate: The aerobic zone decreases at times of low velocity and increases at those of high velocity. For the case of diurnal fluctuations, the biomass concentrations cannot follow the hydrological fluctuations and a transition zone containing both aerobic and obligatory denitrifying bacteria is established, whereas a clear separation of the two types of bacteria prevails in the case of seasonal velocity fluctuations. We map the 1-D results to a heterogeneous, two-dimensional domain by means of the mean groundwater age for steady-state flow in both domains. The mapped results are compared to simulation results of spatially explicit, two-dimensional, advective-dispersive-bioreactive transport subject to the same relative fluctuations of velocity as in the one-dimensional model. The agreement between the mapped 1-D and the explicit 2-D results is excellent. We conclude that travel-time models of nonlinear bioreactive transport are adequate in systems of time-periodic flow if the flow direction does not change.

Whole Blood Reveals More Metabolic Detail of the Human Metabolome than Serum as Measured by 1H-NMR Spectroscopy: Implications for Sepsis Metabolomics.

Serum is a common sample of convenience for metabolomics studies. Its processing time can be lengthy and may result in the loss of metabolites including those of red blood cells (RBCs). Unlike serum, whole blood (WB) is quickly processed, minimizing the influence of variable hemolysis while including RBC metabolites. To determine differences between serum and WB metabolomes, both sample types, collected from healthy volunteers, were assayed by H-NMR (proton nuclear magnetic resonance) spectroscopy. A total of 34 and 50 aqueous metabolites were quantified from serum and WB, respectively. Free hemoglobin (Hgb) levels in serum were measured, and the correlation between Hgb and metabolite concentrations was determined. Most metabolites detected in serum were at higher concentrations in WB with the exception of acetoacetate and propylene glycol. The 18 unique metabolites of WB included adenosine, AMP, ADP, and ATP, which are associated with RBC metabolism. The use of serum results in the underrepresentation of a number of metabolic pathways including branched-chain amino acid degradation and glycolysis and gluconeogenesis. The range of free Hgb in serum was 0.03 to 0.01 g/dL, and eight metabolites were associated (P ≤ 0.05) with free Hgb. The range of free Hgb in serum samples from 18 sepsis patients was 0.02 to 0.46 g/dL. Whole blood and serum have unique aqueous metabolite profiles, but the use of serum may introduce potential pathway bias. Use of WB for metabolomics may be particularly important for studies in diseases such as sepsis in which RBC metabolism is altered, and mechanical and sepsis-induced hemolysis contributes to variance in the metabolome.

On the validity of travel-time based nonlinear bioreactive transport models in steady-state flow.

Travel-time based models simplify the description of reactive transport by replacing the spatial coordinates with the groundwater travel time, posing a quasi one-dimensional (1-D) problem and potentially rendering the determination of multidimensional parameter fields unnecessary. While the approach is exact for strictly advective transport in steady-state flow if the reactive properties of the porous medium are uniform, its validity is unclear when local-scale mixing affects the reactive behavior. We compare a two-dimensional (2-D), spatially explicit, bioreactive, advective-dispersive transport model, considered as "virtual truth", with three 1-D travel-time based models which differ in the conceptualization of longitudinal dispersion: (i) neglecting dispersive mixing altogether, (ii) introducing a local-scale longitudinal dispersivity constant in time and space, and (iii) using an effective longitudinal dispersivity that increases linearly with distance. The reactive system considers biodegradation of dissolved organic carbon, which is introduced into a hydraulically heterogeneous domain together with oxygen and nitrate. Aerobic and denitrifying bacteria use the energy of the microbial transformations for growth. We analyze six scenarios differing in the variance of log-hydraulic conductivity and in the inflow boundary conditions (constant versus time-varying concentration). The concentrations of the 1-D models are mapped to the 2-D domain by means of the kinematic (for case i), and mean groundwater age (for cases ii & iii), respectively. The comparison between concentrations of the "virtual truth" and the 1-D approaches indicates extremely good agreement when using an effective, linearly increasing longitudinal dispersivity in the majority of the scenarios, while the other two 1-D approaches reproduce at least the concentration tendencies well. At late times, all 1-D models give valid approximations of two-dimensional transport. We conclude that the conceptualization of nonlinear bioreactive transport in complex multidimensional domains by quasi 1-D travel-time models is valid for steady-state flow fields if the reactants are introduced over a wide cross-section, flow is at quasi steady state, and dispersive mixing is adequately parametrized.

Machado-Joseph disease in a Nigerian family: mutational origin and review of the literature.

Machado-Joseph disease (MJD) has been described in Africans, but no cases have been reported from Nigeria. Current MJD global distribution results from both the ancestral populations-of-origin and the founder effects of mutations, some as a consequence of the Portuguese sea travels in the 15th to 16th century. Two main ancestral haplotypes have been identified: the Machado lineage, which is more recent, predominant in families of Portuguese extraction, and the Joseph lineage, which is much older and worldwide spread, postulated to have an Asian origin. We report a Nigerian family with MJD from Calabar, once settled by Portuguese slave traders, and assessed its mutational origin. The proband was a 33-year-old man with progressive unsteady gait, weakness of all limbs, dysphagia, dysarthria, urinary frequency and diaphoresis. He had end-of-gaze nystagmus, spastic quadriparesis and atrophic small muscles of the hand. He showed fibrillation potentials on EMG, and nerve conduction studies suggested a central axonopathy without demyelination. This family bears the Joseph haplotype, which has a founder effect in the island of Flores, in the Azores (and their descendants in North-America), but is also the most common in non-Portuguese populations worldwide, with an estimated mutation age of around 7000 years.

Pharmacometabolomics of l-carnitine treatment response phenotypes in patients with septic shock.

RATIONALE: Sepsis therapeutics have a poor history of success in clinical trials, due in part to the heterogeneity of enrolled patients. Pharmacometabolomics could differentiate drug response phenotypes and permit a precision medicine approach to sepsis. OBJECTIVES: To use existing serum samples from the phase 1 clinical trial of l-carnitine treatment for severe sepsis to metabolically phenotype l-carnitine responders and nonresponders. METHODS: Serum samples collected before (T0) and after completion of the infusion (T24, T48) from patients randomized to either l-carnitine (12 g) or placebo for the treatment of vasopressor-dependent septic shock were assayed by untargeted (1)H-nuclear magnetic resonance metabolomics. The normalized, quantified metabolite data sets of l-carnitine- and placebo-treated patients at each time point were compared by analysis of variance with post-hoc testing for multiple comparisons. Pathway analysis was performed to statistically rank metabolic networks. MEASUREMENTS AND MAIN RESULTS: Thirty-eight metabolites were identified in all samples. Concentrations of 3-hydroxybutyrate, acetoacetate, and 3-hydroxyisovalerate were different at T0 and over time in l-carnitine-treated survivors versus nonsurvivors. Pathway analysis of pretreatment metabolites revealed that synthesis and degradation of ketone bodies had the greatest impact in differentiating l-carnitine treatment response. Analysis of all patients based on pretreatment 3-hydroxybutyrate concentration yielded distinct phenotypes. Using the T0 median 3-hydroxybutyrate level (153 µM), patients were categorized as either high or low ketone. l-Carnitine-treated low-ketone patients had greater use of carnitine as evidenced by lower post-treatment l-carnitine levels. The l-carnitine responders also had faster resolution of vasopressor requirement and a trend toward a greater improvement in mortality at 1 year (P = 0.038) compared with patients with higher 3-hydroxybutyrate. CONCLUSIONS: The results of this preliminary study, which were not readily apparent from the parent clinical trial, show a unique metabolite profile of l-carnitine responders and introduce pharmacometabolomics as a viable strategy for informing l-carnitine responsiveness. The approach taken in this study represents a concrete example for the application of precision medicine to sepsis therapeutics that warrants further study.

Signal intensities derived from different NMR probes and parameters contribute to variations in quantification of metabolites.

We discovered that serious issues could arise that may complicate interpretation of metabolomic data when identical samples are analyzed at more than one NMR facility, or using slightly different NMR parameters on the same instrument. This is important because cross-center validation metabolomics studies are essential for the reliable application of metabolomics to clinical biomarker discovery. To test the reproducibility of quantified metabolite data at multiple sites, technical replicates of urine samples were assayed by 1D-(1)H-NMR at the University of Alberta and the University of Michigan. Urine samples were obtained from healthy controls under a standard operating procedure for collection and processing. Subsequent analysis using standard statistical techniques revealed that quantitative data across sites can be achieved, but also that previously unrecognized NMR parameter differences can dramatically and widely perturb results. We present here a confirmed validation of NMR analysis at two sites, and report the range and magnitude that common NMR parameters involved in solvent suppression can have on quantitated metabolomics data. Specifically, saturation power levels greatly influenced peak height intensities in a frequency-dependent manner for a number of metabolites, which markedly impacted the quantification of metabolites. We also investigated other NMR parameters to determine their effects on further quantitative accuracy and precision. Collectively, these findings highlight the importance of and need for consistent use of NMR parameter settings within and across centers in order to generate reliable, reproducible quantified NMR metabolomics data.

Applying a multi-criteria genetic algorithm framework for brownfield reuse optimization: improving redevelopment options based on stakeholder preferences.

The reuse of underused or abandoned contaminated land, so-called brownfields, is increasingly seen as an important means for reducing the consumption of land and natural resources. Many existing decision support systems are not appropriate because they focus mainly on economic aspects, while neglecting sustainability issues. To fill this gap, we present a framework for spatially explicit, integrated planning and assessment of brownfield redevelopment options. A multi-criteria genetic algorithm allows us to determine optimal land use configurations with respect to assessment criteria and given constraints on the composition of land use classes, according to, e.g., stakeholder preferences. Assessment criteria include sustainability indicators as well as economic aspects, including remediation costs and land value. The framework is applied to a case study of a former military site near Potsdam, Germany. Emphasis is placed on the trade-off between possibly conflicting objectives (e.g., economic goals versus the need for sustainable development in the regional context of the brownfield site), which may represent different perspectives of involved stakeholders. The economic analysis reveals the trade-off between the increase in land value due to reuse and the costs for remediation required to make reuse possible. We identify various reuse options, which perform similarly well although they exhibit different land use patterns. High-cost high-value options dominated by residential land use and low-cost low-value options with less sensitive land use types may perform equally well economically. The results of the integrated analysis show that the quantitative integration of sustainability may change optimal land use patterns considerably.

Integrated planning and spatial evaluation of megasite remediation and reuse options.

Redevelopment of large contaminated brownfields (megasites) is often hampered by a lack of communication and harmonization among diverse stakeholders with potentially conflicting interests. Decision support is required to provide integrative yet transparent evaluation of often complex spatial information to stakeholders with different areas of expertise. It is considered crucial for successful redevelopment to identify a shared vision of how the respective contaminated site could be remediated and redeveloped. We describe a framework of assessment methods and models that analyzes and visualizes site- and land use-specific spatial information at the screening level, with the aim to support the derivation of recommendable land use layouts and to initiate further and more detailed planning. The framework integrates a GIS-based identification of areas to be remediated, an estimation of associated clean-up costs, a spatially explicit market value appraisal, and an assessment of the planned future land use's contribution to sustainable urban and regional development. Case study results show that derived options are potentially favorable in both a sustainability and an economic sense and that iterative re-planning is facilitated by the evaluation and visualization of economic, ecological and socio-economic aspects. The framework supports an efficient early judgment about whether and how abandoned land may be assigned a sustainable and marketable land use.

Introduction of pro-interleukin-16 inhibits T-lymphoblastic leukemia growth in mice.

PURPOSE: Pro-interleukin-16 (pro-IL-16) is the precursor to mature interleukin-16 (IL-16) protein. Previous studies have demonstrated that pro-IL-16 can function as a regulator of cell cycle. A number of human T-cell leukemia and lymphoma cell lines are pro-IL-16 deficient. Intracellular expression of pro-IL-16 causes these cell lines to become quiescent, implicating loss of pro-IL-16 as a contributory step in T-cell malignancy. Therefore, we tested whether or not reintroduction of pro-IL-16 into solid tumors in mice could halt tumor growth. METHODS: MOLT-4 lymphoblastic leukemia cells were stably transfected with a dsRed-tomato virus and were injected subcutaneously into NOD/SCID/γ chain-knockout mice. Tumor growth was monitored with an in vivo imaging system. A pro-IL-16-GFP fusion virus or control GFP only virus was injected into the tumors, and mice were monitored for 1 week. RESULTS: Injection of the pro-IL-16-containing lentivirus inhibited growth of established MOLT-4 tumors in mice. Tumor explants exhibited diminished proliferative capacity. CONCLUSIONS: Our data support the concept that restoration of pro-IL-16 expression in malignant T cells may have therapeutic value.

Field scale characterization and modeling of contaminant release from a coal tar source zone.

A coal tar contaminated site was characterized using traditional and innovative investigation methods. A careful interpretation of hydrogeological and hydrogeochemical data allowed for the conceptualization of the heterogeneous coal tar distribution in the subsurface. Past and future contaminant release from the source zone was calculated using a modeling framework consisting of a three-dimensional steady-state groundwater flow model (MODFLOW) and two hydrogeochemical models (MIN3P). Computational time of long-term simulations was reduced by simplifying the coal tar composition using 3 composite and 2 individual constituents and sequential application of a 2D centerline model (for calibration and predictions) and a 3D model (only for predictions). Predictions were carried out for a period of 1000 years. The results reveal that contaminant mass flux is governed by the geometry of zones containing residual coal tar, amount of coal tar, its composition and the physicochemical properties of the constituents. The long-term predictions made using the 2D model show that even after 1000 years, source depletion will be small with respect to phenanthrene, 89% of initial mass will be still available, and for the moderately and sparingly soluble composite constituents, 60% and 98%, respectively.

Modelling the long-term performance of zero-valent iron using a spatio-temporal approach for iron aging.

Zero-valent iron (ZVI) permeable reactive barriers (PRBs) have become popular for the degradation of chlorinated ethenes (CEs) in groundwater. However, a knowledge gap exists pertaining to the longevity of ZVI. The present investigation addresses this situation by suggesting a numerical simulation model that is intended to be used in conjunction with field or column tests in order to describe long-term ZVI performance at individual sites. As ZVI aging processes are not yet completely understood and are still subject to research, we propose a phenomenological modelling technique instead of a common process-based approach. We describe ZVI aging by parameters that characterise the extent and rate of ZVI reactivity change depending on the propagation of the precipitation front through ZVI. We approximate degradation of CEs by pseudo-first order kinetics accounting for the formation of partially dechlorinated products, and describe ZVI reactivity change by scaling the degradation rate constants. Three independent modelling studies were carried out to test the suitability of the conceptual and numerical model to describe the observations of accelerated column tests. All three tests indicated that ZVI reactivity declined with an increasing number of exchanged pore volumes. Measured and modelled concentrations showed good agreement, thereby proving that resolving spatial as well as temporal changes in ZVI reactivity is reasonable.