This study investigated a metabolic network (MN) from Mycobacterium vanbaalenii PYR-1 for polycyclic aromatic hydrocarbons (PAHs) from the perspective of structure, behavior, and evolution, in which multilayer omics data are integrated. Initially, we utilized a high-throughput proteomic analysis to assess the protein expression response of M. vanbaalenii PYR-1 to seven different aromatic compounds. A total of 3,431 proteins (57.38% of the genome-predicted proteins) were identified, which included 160 proteins that seemed to be involved in the degradation of aromatic hydrocarbons. Based on the proteomic data and the previous metabolic, biochemical, physiological, and genomic information, we reconstructed an experiment-based system-level PAH-MN. The structure of PAH-MN, with 183 metabolic compounds and 224 chemical reactions, has a typical scale-free nature. The behavior and evolution of the PAH-MN reveals a hierarchical modularity with funnel effects in structure/function and intimate association with evolutionary modules of the functional modules, which are the ring cleavage process (RCP), side chain process (SCP), and central aromatic process (CAP). The 189 commonly upregulated proteins in all aromatic hydrocarbon treatments provide insights into the global adaptation to facilitate the PAH metabolism. Taken together, the findings of our study provide the hierarchical viewpoint from genes/proteins/metabolites to the network via functional modules of the PAH-MN equipped with the engineering-driven approaches of modularization and rationalization, which may expand our understanding of the metabolic potential of M. vanbaalenii PYR-1 for bioremediation applications.With the 2010 Deepwater Horizon BP oil spill in the Gulf of Mexico (http://www.epa.gov/BPSpill), concerns have been raised regarding the effect of polycyclic aromatic hydrocarbons (PAHs) on the environment. PAHs are a diverse class of organic compounds with two or more fused benzene rings (4). These compounds are highly hydrophobic and not easily bioavailable to microorganisms for degradation, and they pose a significant toxicological risk to human and environmental health (4). Microbial activities represent one of the primary processes by which PAHs are eliminated from the environment (4).Mycobacterium vanbaalenii PYR-1, originally isolated from oilcontaminated estuarine sediment, was the first bacterium reported to degrade high-molecular-weight (HMW) PAHs with four or more fused benzene rings (10, 18). Since it has the ability to mineralize or degrade various kinds of PAHs, such as phenanthrene, anthracene, fluoranthene, pyrene, benzo[a]pyrene, benz [a]anthracene, and 7,12-dimethylbenz[a]anthracene (10, 11, 15-17, 24, 34-38), strain PYR-1 has been studied extensively as a prototype organism to elucidate pathways (19) and has been used to remediate PAH-contaminated soils (31). Recently, with the completion of the genome sequence of M. vanbaalenii PYR-1, efforts to elucidate the molecular background for the metabolism of PAHs have been initiated (21,22,26...

The Experience Sampling Method (ESM) is an ecologically valid, time-sampling of self-reports developed to study the dynamic process of person-environment interactions. ESM with digital wristwatch and booklets (paper-based ESM; ESMp) has been used extensively to study schizophrenia. The present study is designed to test the feasibility and validity of using Computerized ESM (ESMc) among individuals with schizophrenia. ESMc is advantageous in allowing for recording of precise time-stamps of responses. We used PDAs ("Personal Digital Assistant"; Palm handheld computers) to collect data on momentary psychotic symptoms, mood, and thoughts over a one day period among 10 hospitalized schizophrenia patients and 10 healthy controls. ESMc was equally acceptable to both groups, with similar ratings of comfort carrying the PDAs and operating them, interference with daily activities, as well as response rates. The schizophrenia patients reported significantly higher ratings of auditory and visual hallucinations, suspiciousness, sense of unreality, lack of thought control, fear of losing control, difficulty expressing thoughts, as well as depression/sadness, loneliness and less cheerfulness. Significant inverse relationships were found among both groups between ratings of feeling cheerful and being stressed, irritated, and sad/depressed. Among the schizophrenia subjects, the correlation between ratings of suspiciousness on ESMc and Scale for Assessment of Positive Symptoms (SAPS) approached significance, as well as the link between suspiciousness and stress. Our results support the feasibility and validity of using ESMc for assessment of momentary psychotic symptoms, mood, and experiences among individuals with schizophrenia. The authors discuss the potential applications of combining ESMc with ambulatory physiological measures.

The findings support the feasibility and validity of our methodology in individuals with psychosis. The methodology offers a novel way to study in high time resolution the concurrent, "real-world" interactions between stress, arousal, and psychosis. The authors discuss the methodology's potential applications and future research directions.

The healing of skeletal fractures is essentially a replay of bone development, involving the closely regulated, interdependent processes of chondrogenesis and osteogenesis. Using a rat femur model of bone healing to determine the degree of transcriptional complexity of these processes, suppressive subtractive hybridization (SSH) was performed between RNA isolated from intact bone to that of callus from post-fracture (PF) days 3, 5, 7, and 10 as a means of identifying up-regulated genes in the regenerative process. Analysis of 3,635 cDNA clones revealed 588 known genes (65.8%, 2392 clones) and 821 expressed sequence tags (ESTs) (31%, 1,127). The remaining 116 cDNAs (3.2%) yielded no homology and presumably represent novel genes. Microarrays were then constructed to confirm induction of expression and determine the temporal profile of all isolated cDNAs during fracture healing. These experiments confirmed that ϳ90 and ϳ80% of the subtracted known genes and ESTs are up-regulated (>2.5-fold) during the repair process, respectively. Clustering analysis revealed subsets of genes, both known and unknown, that exhibited distinct expression patterns over 21 days (PF), indicating distinct roles in the healing process. Additionally, this transcriptional profiling of bone repair revealed a host of activated signaling molecules and even pathways (i.e. Wnt). In summary, the data demonstrate, for the fist time, that the healing process is exceedingly complex, involves thousands of activated genes, and indicates that groups of genes rather than individual molecules should be considered if the regeneration of bone is to be accelerated exogenously.

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Physiologically based pharmacokinetic (PBPK) models need the correct organ/tissue weights to match various total body weights in order to be applied to children and the obese individual. Baseline data from Reference Man for the growth of human organs (adrenals, brain, heart, kidneys, liver, lungs, pancreas, spleen, thymus, and thyroid) were augmented with autopsy data to extend the describing polynomials to include the morbidly obese individual (up to 250 kg). Additional literature data similarly extends the growth curves for blood volume, muscle, skin, and adipose tissue. Collectively these polynomials were used to calculate blood/organ/tissue weights for males and females from birth to 250 kg, which can be directly used to help parameterize PBPK models. In contrast to other black/white anthropomorphic measurements, the data demonstrated no observable or statistical difference in weights for any organ/tissue between individuals identified as black or white in the autopsy reports.

Standard classification algorithms are generally designed to maximize the number of correct predictions (concordance). The criterion of maximizing the concordance may not be appropriate in certain applications. In practice, some applications may emphasize high sensitivity (e.g., clinical diagnostic tests) and others may emphasize high specificity (e.g., epidemiology screening studies). This paper considers effects of the decision threshold on sensitivity, specificity, and concordance for four classification methods: logistic regression, classification tree, Fisher's linear discriminant analysis, and a weighted k-nearest neighbor. We investigated the use of decision threshold adjustment to improve performance of either sensitivity or specificity of a classifier under specific conditions. We conducted a Monte Carlo simulation showing that as the decision threshold increases, the sensitivity decreases and the specificity increases; but, the concordance values in an interval around the maximum concordance are similar. For specified sensitivity and specificity levels, an optimal decision threshold might be determined in an interval around the maximum concordance that meets the specified requirement. Three example data sets were analyzed for illustrations.