Opportunistic pathogens represent a unique challenge because they establish and grow within drinking water systems, yet the factors stimulating their proliferation are largely unknown. The purpose of this study was to examine the influence of pipe materials, disinfectant type, and water age on occurrence and persistence of three opportunistic pathogens (Legionella pneumophila, Mycobacterium avium, and Pseudomonas aeruginosa), broader genera (Legionella and mycobacteria), and two amoeba hosts (Acanthamoeba spp. and Hartmanella vermiformis). Triplicate simulated distribution systems (SDSs) compared iron, cement, and PVC pipe materials fed either chlorinated or chloraminated tap water and were sampled at water ages ranging from 1 day to 5.7 days. Quantitative polymerase chain reaction quantified gene copies of target microorganisms in both biofilm and bulk water. Legionella, mycobacteria, P. aeruginosa, and both amoebas naturally colonized the six SDSs, but L. pneumophila and M. avium were not detected. Disinfectant type and dose was observed to have the strongest influence on the microbiota. Disinfectant decay was noted with water age, particularly in chloraminated SDSs (due to nitrification), generally resulting in increased microbial detection frequencies and densities with water age. The influence of pipe material became apparent at water ages corresponding to low disinfectant residual. Each target microbe appeared to display a distinct response to disinfectant type, pipe materials, water age, and their interactions. Differences between the first and the second samplings (e.g., appearance of Legionella, reduction in P. aeruginosa and Acanthamoeba) suggest a temporally dynamic drinking water microbial community.

Researchers collaborate on scientific projects that are often measured by both the quantity and the quality of the resultant peerreviewed publications. However, not all collaborators contribute to these publications equally, making metrics such as the total number of publications and the H-index insufficient measurements of individual scientific impact. To remedy this, we use an axiomatic approach to assign relative credits to the coauthors of a given paper, referred to as the A-index for its axiomatic foundation. In this paper, we use the A-index to compute the weighted sums of peer-reviewed publications and journal impact factors, denoted as the C-and P-indexes for collaboration and productivity, respectively. We perform an in-depth analysis of bibliometric data for 186 biomedical engineering faculty members and from extensive simulation. It is found that these axiomatically weighted indexes better capture a researcher's scientific caliber than do the total number of publications and the H-index, allowing for fairer and sharper evaluation of researchers with diverse collaborative behaviors.

Nuclear phosphoinositides, especially phosphatidylinositol 4,5-bisphosphate, fluctuate throughout the cell cycle and are linked to proliferation and differentiation. Here we report that phospholipase C-␦ 1 accumulates in the nucleus at the G 1 /S boundary and in G 0 phases of the cell cycle. Furthermore, as wild-type protein accumulated in the nucleus, nuclear phosphatidylinositol 4,5-bisphosphate levels were elevated 3-5-fold, whereas total levels were decreased compared with asynchronous cultures. To test whether phosphatidylinositol 4,5-bisphosphate binding is important during this process, we introduced a R40D point mutation within the pleckstrin homology domain of phospholipase C-␦ 1 , which disables high affinity phosphatidylinositol 4,5-bisphosphate binding, and found that nuclear translocation was significantly reduced at G 1 /S and in G 0 . These results demonstrate a cell cycle-dependent compartmentalization of phospholipase C-␦ 1 and support the idea that relative levels of phosphoinositides modulate the portioning of phosphoinositide-binding proteins between the nucleus and other compartments.A distinct phosphoinositide cycle is present in nucleus, and growing evidence suggests its metabolism is important for DNA repair, mRNA export, and gene transcription (1-5). Moreover, changes in nuclear phosphoinositide levels are correlated to cell cycle progression and independently regulated from the phosphoinositide cycle at the plasma membrane (6, 7). Because phospholipase C (PLC) 1 is a key regulator of phosphoinositide metabolism at the plasma membrane, understanding what controls the localization of this enzyme to the nucleus and how its activity there affects nuclear phosphoinositide metabolism is important.In mammals, PLC is a 13-member family of phosphodiesterases (␤, ␥, ␦, ⑀, and subtypes) essential to a wide range of cellular responses, including exocytosis, endocytosis, gene transcription, cytoskeletal remodeling, and membrane trafficking (8 -11). PLC-mediated hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP 2 ) generates inositol 1,4,5-trisphosphate and diacylglycerol critical second messengers that mobilize cellular calcium and activate protein kinase C, respectively (8). PLC␦ 1 has been shown to be activated by capacitative calcium entry (12), transglutaminase II (13), a form of Rho GTPase-activating protein (14), free fatty acids such as arachidonic acid (15), and phosphatidylserine (16). Upon activation, PLC␦ 1 binds the inositol head group of PIP 2 with high affinity and specificity through its non-catalytic PH domain (17)(18)(19). This interaction facilitates association with the plasma membrane, particularly with ruffles, where PIP 2 is enriched (20). When a point mutation in the PH domain (R40D) is introduced, however, the ability of PLC␦ 1 to target the plasma membrane is greatly reduced, resulting in a higher cytosolic concentration (18).Several PLC isoforms are detected in the nuclear compartment, primarily due to alternative spliced variation (21). PLC␦ 1 , however, is the only...

Irreversible electroporation (IRE) is a non-thermal focal ablation technique that uses a series of brief but intense electric pulses delivered into a targeted region of tissue, killing the cells by irrecoverably disrupting cellular membrane integrity. This study investigates if there is an improved local anti-tumor response in immunocompetent (IC) BALB/c versus immunodeficient (ID) nude mice, including the potential for a systemic protective effect against rechallenge. Subcutaneous murine renal carcinoma tumors were treated with an IRE pulsing protocol that used 60% of the predicted voltage required to invoke complete regressions in the ID mice. Tumors were followed for 34 days following treatment for 11 treated mice from each strain, and 7 controls from each strain. Mouse survival based on tumor burden and the progression-free disease period was substantially longer in the treated IC mice relative to the treated ID mice and sham controls for both strains. Treated IC mice were rechallenged with the same cell line 18 days after treatment, where growth of the second tumors was shown to be significantly reduced or prevented entirely. There was robust CD3+ cell infiltration in some treated BALB/C mice, with immunocytes focused at the transition between viable and dead tumor. There was no difference in the low immunocyte presence for untreated tumors, nude mice, and matrigel-only injections in both strains. These findings suggest IRE therapy may have greater therapeutic efficacy in immunocompetent patients than what has been suggested by immunodeficient models, and that IRE may invoke a systemic response beyond the targeted ablation region.

BackgroundHeat illness is a debilitating and potentially life-threatening condition. Limited data are available to identify individuals with heat illness at greatest risk for organ damage. We recently described the transcriptomic and proteomic responses to heat injury and recovery in multiple organs in an in vivo model of conscious rats heated to a maximum core temperature of 41.8°C (Tc,Max). In this study, we examined changes in plasma metabolic networks at Tc,Max, 24, or 48 hours after the heat stress stimulus.ResultsCirculating metabolites were identified by gas chromatography/mass spectrometry and liquid chromatography/tandem mass spectrometry. Bioinformatics analysis of the metabolomic data corroborated proteomics and transcriptomics data in the tissue at the pathway level, supporting modulations in metabolic networks including cell death or catabolism (pyrimidine and purine degradation, acetylation, sulfation, redox alterations and glutathione metabolism, and the urea cycle/creatinine metabolism), energetics (stasis in glycolysis and tricarboxylic acid cycle, β-oxidation), cholesterol and nitric oxide metabolism, and bile acids. Hierarchical clustering identified 15 biochemicals that differentiated animals with histopathological evidence of cardiac injury at 48 hours from uninjured animals. The metabolic networks perturbed in the plasma corroborated the tissue proteomics and transcriptomics pathway data, supporting a model of irreversible cell death and decrements in energetics as key indicators of cardiac damage in response to heat stress.ConclusionsIntegrating plasma metabolomics with tissue proteomics and transcriptomics supports a diagnostic approach to assessing individual susceptibility to organ injury and predicting recovery after heat stress.Electronic supplementary materialThe online version of this article (doi:10.1186/s12899-014-0014-0) contains supplementary material, which is available to authorized users.

Toxic industrial chemicals induce liver injury, which is difficult to diagnose without invasive procedures. Identifying indicators of end organ injury can complement exposure-based assays and improve predictive power. A multiplexed approach was used to experimentally evaluate a panel of 67 genes predicted to be associated with the fibrosis pathology by computationally mining DrugMatrix, a publicly available repository of gene microarray data. Five-day oral gavage studies in male Sprague Dawley rats dosed with varying concentrations of 3 fibrogenic compounds (allyl alcohol, carbon tetrachloride, and 4,4'-methylenedianiline) and 2 nonfibrogenic compounds (bromobenzene and dexamethasone) were conducted. Fibrosis was definitively diagnosed by histopathology. The 67-plex gene panel accurately diagnosed fibrosis in both microarray and multiplexed-gene expression assays. Necrosis and inflammatory infiltration were comorbid with fibrosis. ANOVA with contrasts identified that 51 of the 67 predicted genes were significantly associated with the fibrosis phenotype, with 24 of these specific to fibrosis alone. The protein product of the gene most strongly correlated with the fibrosis phenotype PCOLCE (Procollagen C-Endopeptidase Enhancer) was dose-dependently elevated in plasma from animals administered fibrogenic chemicals (P < .05). Semiquantitative global mass spectrometry analysis of the plasma identified an additional 5 protein products of the gene panel which increased after fibrogenic toxicant administration: fibronectin, ceruloplasmin, vitronectin, insulin-like growth factor binding protein, and α2-macroglobulin. These results support the data mining approach for identifying gene and/or protein panels for assessing liver injury and may suggest bridging biomarkers for molecular mediators linked to histopathology.

Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules) specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1) known biochemical pathways associated with liver injuries and 2) clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20%) genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.

Toxic liver injury causes necrosis and fibrosis, which may lead to cirrhosis and liver failure. Despite recent progress in understanding the mechanism of liver fibrosis, our knowledge of the molecular-level details of this disease is still incomplete. The elucidation of networks and pathways associated with liver fibrosis can provide insight into the underlying molecular mechanisms of the disease, as well as identify potential diagnostic or prognostic biomarkers. Towards this end, we analyzed rat gene expression data from a range of chemical exposures that produced observable periportal liver fibrosis as documented in DrugMatrix, a publicly available toxicogenomics database. We identified genes relevant to liver fibrosis using standard differential expression and co-expression analyses, and then used these genes in pathway enrichment and protein-protein interaction (PPI) network analyses. We identified a PPI network module associated with liver fibrosis that includes known liver fibrosis-relevant genes, such as tissue inhibitor of metalloproteinase-1, galectin-3, connective tissue growth factor, and lipocalin-2. We also identified several new genes, such as perilipin-3, legumain, and myocilin, which were associated with liver fibrosis. We further analyzed the expression pattern of the genes in the PPI network module across a wide range of 640 chemical exposure conditions in DrugMatrix and identified early indications of liver fibrosis for carbon tetrachloride and lipopolysaccharide exposures. Although it is well known that carbon tetrachloride and lipopolysaccharide can cause liver fibrosis, our network analysis was able to link these compounds to potential fibrotic damage before histopathological changes associated with liver fibrosis appeared. These results demonstrated that our approach is capable of identifying early-stage indicators of liver fibrosis and underscore its potential to aid in predictive toxicity, biomarker identification, and to generally identify disease-relevant pathways.