Evaluation of Biostimulation and Bioaugmentation To Stimulate Hexahydro-1,3,5-trinitro-1,3,5,-triazine Degradation in an Aerobic Groundwater Aquifer.

Hexahydro-1,3,5-trinitro-1,3,5,-triazine (RDX) is a toxic and mobile groundwater contaminant common to military sites. This study compared in situ RDX degradation rates following bioaugmentation with Gordonia sp. strain KTR9 (henceforth KTR9) to rates under biostimulation conditions in an RDX-contaminated aquifer in Umatilla, OR. Bioaugmentation was achieved by injecting site groundwater (6000 L) amended with KTR9 cells (10(8) cells mL(-1)) and low carbon substrate concentrations (<1 mM fructose) into site wells. Biostimulation (no added cells) was performed by injecting groundwater amended with low (<1 mM fructose) or high (>15 mM fructose) carbon substrate concentrations in an effort to stimulate aerobic or anaerobic microbial activity, respectively. Single-well push-pull tests were conducted to measure RDX degradation rates for each treatment. Average rate coefficients were 1.2 day(-1) for bioaugmentation and 0.7 day(-1) for high carbon biostimulation; rate coefficients for low carbon biostimulation were not significantly different from zero (p values ≥0.060). Our results suggest that bioaugmentation with KTR9 is a feasible strategy for in situ biodegradation of RDX and, at this site, is capable of achieving RDX concentration reductions comparable to those obtained by high carbon biostimulation while requiring ~97% less fructose. Bioaugmentation has potential to minimize substrate quantities and associated costs, as well as secondary groundwater quality impacts associated with anaerobic biostimulation processes (e.g., hydrogen sulfide, methane production) during full-scale RDX remediation.

Use of hidden correlations in short oligonucleotide array data are insufficient for accurate quantification of nucleic acid targets in complex target mixtures.

Nonspecific target binding (i.e., cross-hybridization) is a major challenge for interpreting oligonucleotide microarray results because it is difficult to determine what portion of the signal is due to binding of complementary (specific) targets to a probe versus that due to binding of nonspecific targets. Solving this challenge would be a major accomplishment in microarray research potentially allowing quantification of targets in biological samples. Marcelino et al. recently described a new approach that reportedly solves this challenge by iteratively deconvoluting 'true' specific signal from raw signal, and quantifying ribosomal (rRNA) sequences in artificial and natural communities (i.e., "Accurately quantifying low-abundant targets amid similar sequences by revealing hidden correlations in oligonucleotide microarray data", Proc. Natl. Acad. Sci. 103, 13629-13634). We evaluated their approach using high-density oligonucleotide microarrays and Latin-square designed experiments consisting of 6 and 8 rRNA targets in 16 different artificial mixtures. Our results show that contrary to the claims in the article, the hidden correlations in the microarray data are insufficient for accurate quantification of nucleic acid targets in complex artificial target mixtures.

Concentration dependency of nonequilibrium thermal dissociation curves in complex target samples.

The nonequilibrium thermal dissociation (NTD) methodology has been proposed to provide a superior discrimination between specific and nonspecific hybridizations than the commonly used array techniques involving hybridization followed by a single stringent wash. Multiple studies have used this method on gel-pad, planar, and nylon membrane arrays to identify specific microbial targets in complex target mixtures. A recent physicochemical study revealed several problems, particularly when the method was used to examine complex target samples. In the present study, we investigated the effect of target concentration on NTD of complex target samples obtained from an anaerobic bioreactor. Our purpose was to experimentally demonstrate that variation in the concentrations of both specific and nonspecific targets determines the course of dissociation, which was not evaluated in initial microbiological studies. We also present an approach for analyzing the dissociation curves that is less error prone compared to those used in the previous studies. Our results show that: (i) a specific target in a mixture, at a certain concentration, may have a higher dissociation temperature/time than that of the same pure target, and (ii) the concentration dependence of the dissociation precludes usage of reference curves for identifying a target. Contrary to the previous studies, an explicit calibration is required, which makes the NTD approach impractical for high throughput analysis.

The use of discriminant function analysis to predict student success on the NCLEX-RN.

Predicting whether a student will be successful on the National Council Licensure Examination for Registered Nurses (NCLEX-RN) has been an important endeavor for faculty in schools of nursing for the past 2 decades. Extensive documentation exists in the literature concerning research aimed at exploring the academic and nonacademic predictors of success on the NCLEX-RN. Reviews of the findings of these studies indicate that various factors emerge as academic predictors of success. The results of this study suggest that first-time success on the NCLEX-RN can be predicted with a high level of accuracy using existing student data. The findings also support the belief that it is possible to identify students who may be at risk for unsuccessful first time performance on the NCLEX-RN. Early identification of at-risk students will promote timely intervention strategies to optimize the students' potential for success.