Vicksburg, MS, United States
Vicksburg, MS, United States

Time filter

Source Type

Pavuk M.,SpecPro Inc. | Pavuk M.,Agency for Toxic Substances and Disease Registry | Patterson D.G.,EnviroSolutions Consulting | Turner W.E.,Centers for Disease Control and Prevention
Chemosphere | Year: 2014

We measured serum concentrations of seven dibenzo-p-dioxin congeners (PCDDs), ten dibenzofurans (PCDFs), four non-ortho polychlorinated biphenyls (noPCBs) and six mono-ortho polychlorinated biphenyls (moPCBs) in 1950 veterans of the Vietnam War. The veterans were participants in the Air Force Health Study (AFHS) who attended the final medical examination in 2002. Blood samples were collected from 777 Ranch Hands involved in the aerial spraying of herbicides in Vietnam and a comparison group of 1173 veterans ("Comparisons") who served in Southeast Asia during the same time period. Results for moPCBs were based on a random subsample of 800 veterans.The median 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) concentrations in 2002 were 5.0pgg-1 lipid in Ranch Hands and 2.2pgg-1 lipid in Comparisons. No substantial differences were found in measured concentrations of other PCDDs, PCDFs, and noPCBs. Similarly, no substantial differences were found for moPCBs in the subsample. The median total dioxin toxic equivalent (TEQ) in Ranch Hands was 18.7pgg-1 lipid for PCDDs, 3.4pgg-1 lipid for PCDFs, and 3.2pgg-1 lipid for noPCBs. Median TEQs in Comparisons were 14.4pgg-1 lipid for PCDDs, 3.5pgg-1 lipid for PCDFs, and 3.3pgg-1 lipid for noPCBs. These TEQs, with the exception of PCDD TEQ in Ranch Hands (primarily due to elevated TCDD), were similar to or lower than those reported for similar age and gender groups in the 2001-2002 National Health and Nutrition Examination Survey (NHANES). These findings support the assumption that the Ranch Hand veterans were not more highly exposed to dioxin-like compounds other than TCDD than were Comparison veterans or the general US population. © 2013.


Tang J.,Alcorn State University | Guo S.,Alcorn State University | Sun Q.,University of Southern Mississippi | Deng Y.,SpecPro Inc | Zhou D.,The Fifth Hospital of Harbin
BMC Genomics | Year: 2010

Background: Ultrasound imaging technology has wide applications in cattle reproduction and has been used to monitor individual follicles and determine the patterns of follicular development. However, the speckles in ultrasound images affect the post-processing, such as follicle segmentation and finally affect the measurement of the follicles. In order to reduce the effect of speckles, a bilateral filter is developed in this paper.Results: We develop a new bilateral filter for speckle reduction in ultrasound images for follicle segmentation and measurement. Different from the previous bilateral filters, the proposed bilateral filter uses normalized difference in the computation of the Gaussian intensity difference. We also present the results of follicle segmentation after speckle reduction. Experimental results on both synthetic images and real ultrasound images demonstrate the effectiveness of the proposed filter.Conclusions: Compared with the previous bilateral filters, the proposed bilateral filter can reduce speckles in both high-intensity regions and low intensity regions in ultrasound images. The segmentation of the follicles in the speckle reduced images by the proposed method has higher performance than the segmentation in the original ultrasound image, and the images filtered by Gaussian filter, the conventional bilateral filter respectively. © 2010 Tang et al; licensee BioMed Central Ltd.


Chaitankar V.,University of Southern Mississippi | Ghosh P.,University of Southern Mississippi | Perkins E.J.,U.S. Army | Gong P.,SpecPro Inc. | Zhang C.,University of Southern Mississippi
BMC Bioinformatics | Year: 2010

Background: A number of models and algorithms have been proposed in the past for gene regulatory network (GRN) inference; however, none of them address the effects of the size of time-series microarray expression data in terms of the number of time-points. In this paper, we study this problem by analyzing the behaviour of three algorithms based on information theory and dynamic Bayesian network (DBN) models. These algorithms were implemented on different sizes of data generated by synthetic networks. Experiments show that the inference accuracy of these algorithms reaches a saturation point after a specific data size brought about by a saturation in the pair-wise mutual information (MI) metric; hence there is a theoretical limit on the inference accuracy of information theory based schemes that depends on the number of time points of micro-array data used to infer GRNs. This illustrates the fact that MI might not be the best metric to use for GRN inference algorithms. To circumvent the limitations of the MI metric, we introduce a new method of computing time lags between any pair of genes and present the pair-wise time lagged Mutual Information (TLMI) and time lagged Conditional Mutual Information (TLCMI) metrics. Next we use these new metrics to propose novel GRN inference schemes which provides higher inference accuracy based on the precision and recall parameters.Results: It was observed that beyond a certain number of time-points (i.e., a specific size) of micro-array data, the performance of the algorithms measured in terms of the recall-to-precision ratio saturated due to the saturation in the calculated pair-wise MI metric with increasing data size. The proposed algorithms were compared to existing approaches on four different biological networks. The resulting networks were evaluated based on the benchmark precision and recall metrics and the results favour our approach.Conclusions: To alleviate the effects of data size on information theory based GRN inference algorithms, novel time lag based information theoretic approaches to infer gene regulatory networks have been proposed. The results show that the time lags of regulatory effects between any pair of genes play an important role in GRN inference schemes. © 2010 Zhang et al; licensee BioMed Central Ltd.


Chaitankar V.,University of Southern Mississippi | Ghosh P.,University of Southern Mississippi | Perkins E.J.,U.S. Army | Gong P.,SpecPro Inc. | And 2 more authors.
BMC Systems Biology | Year: 2010

Background: Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold which defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we proposed a new inference algorithm which incorporated mutual information (MI), conditional mutual information (CMI) and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter.Results: The performance of the proposed algorithm was evaluated using both synthetic time series data sets and a biological time series data set for the yeast Saccharomyces cerevisiae. The benchmark quantities precision and recall were used as performance measures. The results show that the proposed algorithm produced less false edges and significantly improved the precision, as compared to the existing algorithm. For further analysis the performance of the algorithms was observed over different sizes of data.Conclusions: We have proposed a new algorithm that implements the PMDL principle for inferring gene regulatory networks from time series DNA microarray data that eliminates the need of a fine tuning parameter. The evaluation results obtained from both synthetic and actual biological data sets show that the PMDL principle is effective in determining the MI threshold and the developed algorithm improves precision of gene regulatory network inference. Based on the sensitivity analysis of all tested cases, an optimal CMI threshold value has been identified. Finally it was observed that the performance of the algorithms saturates at a certain threshold of data size. © 2010 Zhang et al; licensee BioMed Central Ltd.


Li Y.,University of Southern Mississippi | Wang N.,University of Southern Mississippi | Perkins E.J.,U.S. Army | Zhang C.,University of Southern Mississippi | Gong P.,SpecPro Inc.
PLoS ONE | Year: 2010

Monitoring, assessment and prediction of environmental risks that chemicals pose demand rapid and accurate diagnostic assays. A variety of toxicological effects have been associated with explosive compounds TNT and RDX. One important goal of microarray experiments is to discover novel biomarkers for toxicity evaluation. We have developed an earthworm microarray containing 15,208 unique oligo probes and have used it to profile gene expression in 248 earthworms exposed to TNT, RDX or neither. We assembled a new machine learning pipeline consisting of several well-established feature filtering/selection and classification techniques to analyze the 248-array dataset in order to construct classifier models that can separate earthworm samples into three groups: control, TNT-treated, and RDX-treated. First, a total of 869 genes differentially expressed in response to TNT or RDX exposure were identified using a univariate statistical algorithm of class comparison. Then, decision tree-based algorithms were applied to select a subset of 354 classifier genes, which were ranked by their overall weight of significance. A multiclass support vector machine (MC-SVM) method and an unsupervised K-mean clustering method were applied to independently refine the classifier, producing a smaller subset of 39 and 30 classifier genes, separately, with 11 common genes being potential biomarkers. The combined 58 genes were considered the refine dsubset and used to build MC-SVM and clustering models with classification accuracy of 83.5% and 56.9%, respectively. This study demonstrates that the machine learning approach can be used to identify and optimize a small subset of classifier/ biomarker genes from high dimensional datasets and generate classification models of acceptable precision for multiple classes.


Gong P.,SpecPro Inc | Pirooznia M.,Johns Hopkins University | Guan X.,SpecPro Inc | Perkins E.J.,U.S. Army
PLoS ONE | Year: 2010

High density oligonucleotide probe arrays have increasingly become an important tool in genomics studies. In organisms with incomplete genome sequence, one strategy for oligo probe design is to reduce the number of unique probes that target every non-redundant transcript through bioinformatic analysis and experimental testing. Here we adopted this strategy in making oligo probes for the earthworm Eisenia fetida, a species for which we have sequenced transcriptomescale expressed sequence tags (ESTs). Our objectives were to identify unique transcripts as targets, to select an optimal and non-redundant oligo probe for each of these target ESTs, and to annotate the selected target sequences. We developed a streamlined and easy-to-follow approach to the design, validation and annotation of species-specific array probes. Four 244K-formatted oligo arrays were designed using eArray and were hybridized to a pooled E. fetida cRNA sample. We identified 63,541 probes with unsaturated signal intensities consistently above the background level. Target transcripts of these probes were annotated using several sequence alignment algorithms. Significant hits were obtained for 37,439 (59%) probed targets. We validated and made publicly available 63.5K oligo probes so the earthworm research community can use them to pursue ecological, toxicological, and other functional genomics questions. Our approach is efficient, costeffective and robust because it (1) does not require a major genomics core facility; (2) allows new probes to be easily added and old probes modified or eliminated when new sequence information becomes available, (3) is not bioinformaticsintensive upfront but does provide opportunities for more in-depth annotation of biological functions for target genes; and (4) if desired, EST orthologs to the UniGene clusters of a reference genome can be identified and selected in order to improve the target gene specificity of designed probes. This approach is particularly applicable to organisms with a wealth of EST sequences but unfinished genome.


Zubatyuk R.I.,Ukrainian Academy of Sciences | Gorb L.,SpecPro Inc. | Shishkin O.V.,Ukrainian Academy of Sciences | Qasim M.O.,SpecPro Inc. | And 2 more authors.
Journal of Computational Chemistry | Year: 2010

Performance of the set of density functional approaches for calculation of one-electron reduction potentials of nitroaromatic compounds was investigated. To select the most precise and affordable method, we selected a set of model molecules and investigated effects of basis set, density functional, and solvation model on the calculation of reduction potentials. It was found that the mPWB1K/TZVP method provides the most accurate gas phase electron affinity values (RMS error is 0.1 eV). This method in conjunction with the PCM (Bondi) method yields also the most accurate difference in solvation energies of neutral oxidized form and anion-radical reduced form. The final E0 values were calculated with RMS error of 0.10 V, compared with experimental values. © 2009 Wiley Periodicals, Inc.


Johnson D.R.,U.S. Army | Ang C.,SpecPro Inc. | Bednar A.J.,U.S. Army | Inouye L.S.,U.S. Army
Toxicological Sciences | Year: 2010

Tungsten, in the form of tungstate, polymerizes with phosphate, and as extensive polymerization occurs, cellular phosphorylation and dephosphorylation reactions may be disrupted, resulting in negative effects on cellular functions. A series of studies were conducted to evaluate the effect of tungsten on several phosphate-dependent intracellular functions, including energy cycling (ATP), regulation of enzyme activity (cytosolic protein tyrosine kinase [cytPTK] and tyrosine phosphatase), and intracellular secondary messengers (cyclic adenosine monophosphate [cAMP]). Rat non-cancerous hepatocyte (Clone-9), rat cancerous hepatocyte (H4IIE), and human cancerous hepatocyte (HepG2) cells were exposed to 1-1000 mg/l tungsten (in the form of sodium tungstate) for 24 h, lysed, and analyzed for the above biochemical parameters. Cellular ATP levels were not significantly affected in any cell line. After 4 h, tungsten significantly decreased cytPTK activity in Clone-9 cells at ≥ 18 mg/l, had no effect in H4IIE cells, and significantly increased cytPTK activity by 70% in HepG2 cells at ≥ 2 mg/l. CytPTK displayed a slight hormetic response to tungsten after 24-h exposure yet returned to normal after 48-h exposure. Tungsten significantly increased cAMP by over 60% in Clone-9 cells at ≥ 100 mg/l, significantly increased cAMP in H4IIE cells at only 100 mg/l, and significantly increased cAMP in HepG2 cells between 1-100 mg/l but at much more modest levels (8-20%). In conclusion, these data indicate that tungsten produces complex results that must be carefully interpreted in the context of their respective animal models, as well as the phenotype of the cell lines (i.e., normal vs. cancerous). © The Author 2010. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved.


Uchimiya M.,U.S. Army | Gorb L.,SpecPro Inc | Isayev O.,Case Western Reserve University | Qasim M.M.,U.S. Army | And 2 more authors.
Environmental Pollution | Year: 2010

Extensive studies have been conducted in the past decades to predict the environmental abiotic and biotic redox fate of nitroaromatic and nitramine explosives. However, surprisingly little information is available on one-electron standard reduction potentials (Eo(R-NO 2/R-NO2-)). The Eo(R-NO 2/R-NO2-) is an essential thermodynamic parameter for predicting the rate and extent of reductive transformation for energetic residues. In this study, experimental (linear free energy relationships) and theoretical (ab initio calculation) approaches were employed to determine Eo(R-NO2/R-NO2-) for nitroaromatic, (caged) cyclic nitramine, and nitroimino explosives that are found in military installations or are emerging contaminants. The results indicate a close agreement between experimental and theoretical E o(R-NO2/R-NO2-) and suggest a key trend: Eo(R-NO2/R-NO2-) value decreases from di- and tri-nitroaromatic (e.g., 2,4-dinitroanisole) to nitramine (e.g., RDX) to nitroimino compound (e.g., nitroguanidine). The observed trend in Eo(R-NO2/R-NO2-) agrees with reported rate trends for reductive degradation, suggesting a thermodynamic control on the reduction rate under anoxic/suboxic conditions. © 2010 Elsevier Ltd. All rights reserved.


Kholod Y.A.,Jackson State University | Gryn'ova G.,Jackson State University | Gorb L.,SpecPro Inc. | Hill F.C.,U.S. Army | And 2 more authors.
Chemosphere | Year: 2011

The solubility in pure and saline water at various temperatures was calculated for selected nitro compounds (nitrobenzene, 1,3,5-trinitrobenzene, 2-nitrotoluene, 3-nitrotoluene, 4-nitrotoluene, 2,4-dinitrotoluene, 2,6-dinitrotoluene, 2,3-dinitrotoluene, 3,4-dinitrotoluene, 2,4,6-trinitrotoluene) using the Conductor-like Screening model for Real Solvents (COSMO-RS). The results obtained were compared with experimental values. The COSMO-RS predictions have shown high accuracy in reproducing the trends of aqueous solubilities for both temperature and salinity. The proposed methodology was then applied to predict the aqueous solubilities of 19 nitro compounds in the temperature range of 5-50°C in saline solutions. The salting-out parameters of the Setschenow equation were also calculated. The predicted salting-out parameters were overestimated when compared to the measured values, but these parameters can still be used for qualitative estimation of the trends. © 2010 Elsevier Ltd.

Loading SpecPro Inc collaborators
Loading SpecPro Inc collaborators