Bacteriophage materials have the potential to revolutionize medicine, energy production and storage, agriculture, solar cells, optics and many other fields. To fulfill these needs, this study examined critical process parameters during phage propagation to increase phage production capability. A representative scale-down system was created in tube spin reactors to allow parallel experimentation with single- and multi-variable analysis. Temperature, harvest time, media composition, feed regime, bacteriophage, and bacteria concentration were analyzed in the scale-down system. Temperature, media composition, and feeding regimens were found to affect phage production more than other factors. Temperature affected bacterial growth and phage production inversely. Multi-variate analysis identified an optimal parameter space which provided a significant improvement over the base line method. This method should be useful in scaled production of bacteriophage for biotechnology.

Insensitive munitions offer increased safety because of their "insensitivity" to unintended detonation relative to historically used formulations such as 2,4,6-trinitrotoluene (TNT). Dinitroanisole (DNAN) is an insensitive munition constituent, and its solubility and stability warrant investigations of potential toxicological hazard related to manufacturing discharges and training ranges. Although ecotoxicology data are available for other insensitive munition constituents, few data are available for DNAN. In the present study, acute and chronic exposures of a fish (Pimephales promelas) and 2 cladocerans (Ceriodaphnia dubia, Daphnia pulex) were conducted. The 50% lethal concentration (LC50) values of DNAN ranged from 14.2 mg/L to 42.0 mg/L, depending on species. In chronic exposures, fish survival (LC50 = 10.0 mg/L) was more sensitive than cladoceran survival (LC50 = 13.7 to >24.2 mg/L). However, cladoceran reproduction was equally or more sensitive to DNAN (50% inhibition values 2.7-10.6 mg/L, depending on species) than fish endpoints. Daphnia pulex was the most sensitive species, with only slight differences between the 3 populations tested. Although the aquatic toxicity of DNAN was lower than previously reported in the literature for TNT, future research is needed to determine the potential synergistic toxicity of all the constituents in insensitive munition mixtures and the implications of photo-oxidation.

Soil contamination near munitions plants and testing grounds is a serious environmental concern that can result in the formation of tissue chemical residue in exposed animals. Quantitative prediction of tissue residue still represents a challenging task despite long-term interest and pursuit, as tissue residue formation is the result of many dynamic processes including uptake, transformation, and assimilation. The availability of high-dimensional microarray gene expression data presents a new opportunity for computational predictive modeling of tissue residue from changes in expression profile. Here we analyzed a 240-sample data set with measurements of transcriptomic-wide gene expression and tissue residue of two chemicals, 2,4,6-trinitrotoluene (TNT) and 1,3,5-trinitro-1,3,5-triazacyclohexane (RDX), in the earthworm Eisenia fetida. We applied two different computational approaches, LASSO (Least Absolute Shrinkage and Selection Operator) and RF (Random Forest), to identify predictor genes and built predictive models. Each approach was tested alone and in combination with a prior variable selection procedure that involved the Wilcoxon rank-sum test and HOPACH (Hierarchical Ordered Partitioning And Collapsing Hybrid). Model evaluation results suggest that LASSO was the best performer of minimum complexity on the TNT data set, whereas the combined Wilcoxon-HOPACH-RF approach achieved the highest prediction accuracy on the RDX data set. Our models separately identified two small sets of ca. 30 predictor genes for RDX and TNT. We have demonstrated that both LASSO and RF are powerful tools for quantitative prediction of tissue residue. They also leave more unknown than explained, however, allowing room for improvement with other computational methods and extension to mixture contamination scenarios.

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