Direct Cr (VI) bio-reduction with organics as electron donor by anaerobic sludge

Industrial activities produce lots of Cr (VI)-containing wastewater. This study presented a detailed work on direct Cr (VI) bio-reduction (i.e. Cr (VI) is reduced with organics as electron donor directly) by anaerobic sludge through both batch and long-term experiments. Effects of pH and initial Cr (VI) concentrations on direct Cr (VI) bio-reduction activity were evaluated. The highest direct Cr (VI) bio-reduction rate was achieved at pH 8.0 at 104\ua0mg Cr (VI)/g MLVSS/d (MLVSS: mixed liquor volatile suspended solids), corresponding to the highest protein release (124\ua0mg/g MLVSS) and cell viability (71%). In contrast, the direct Cr (VI) bio-reduction rates were 46, 70 and 82\ua0mg Cr (VI)/g MLVSS/d, respectively, at pH 6.0, 7.0 and 9.0. Also, the direct Cr (VI) bio-reduction activity decreased by 74% when initial Cr (VI) concentration increased from 10\ua0mg/L to 50\ua0mg/L. The contribution of chemical adsorption to Cr (VI) removal was found to be negligible, whereas biosorption played a role in Cr (VI) removal although its role was insignificant. Indirect Cr (VI) bio-reduction (i.e. Cr (VI) is chemically reduced by sulfide produced from biological sulfate reduction) rate (990\ua0mg Cr (VI)/g MLVSS/d) was faster than that (210\ua0mg Cr (VI)/g MLVSS/d) of direct Cr (VI) bio-reduction, indicating that indirect Cr (VI) bio-reduction would dominate the Cr (VI) bio-reduction pathway if both Cr (VI) and sulfate were present. The direct Cr (VI) bio-reduction was then successfully demonstrated in an up-flow anaerobic sludge bed (UASB) reactor, where the Cr (VI) was completely removed with a Cr (VI) removal rate of 1.0\ua0mg Cr (VI)/L/h. 454 pyrosequencing results revealed that direct Cr (VI) bio-reduction related genera were Desulfovibrio, Ochrobactrum and Anaerovorax

Urine-Derived Stem Cells: The Present and the Future

Stem cell research provides promising strategies in improving healthcare for human beings. As a noninvasively obtained and easy-to-culture cell resource with relatively low expense, urine-derived stem cells have special advantages. They have been extensively studied on its proliferation ability and differentiation potential and were being reprogrammed to model diseases during the last decade. In this review, we intend to summarize the latest progress on the research of urine-derived stem cells for its broad application mainly in regenerative medicine and disease modeling, as well as in what is challenging currently. This minireview will highlight the potential application of urine-derived stem cells and provides possible direction of further research in the future

Detection of Pine Nut Allergen in Three Kinds of Food by Ultra-high Performance Liquid Chromatography-Tandem Mass Spectrometry

An ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was established for the detection of pine nut allergen Pin k 2 in food matrices. Pine nuts were ground, degreased, and enzymatically extracted and the hydrolysate was separated and analyzed by using an Easy-nLC 1000-QExecutive high-resolution mass spectrometer, and the mass spectral data obtained were processed using Protein Pilot TM software and the Uniprot protein database. The specificity was verified by Basic Local Alignment Search Tool (BLAST), and three pine nut-specific peptides were selected finally. The developed method exhibited a good linear relationship in the concentration range of 0.001–50 mg/mL, and the limit of quantification was 1 mg/kg. The average recoveries for blank biscuit, chocolate and beverage were 88.50%–107.57%, with a relative standard deviation (RSD) not exceeding 6.08%, and the matrix effect was 89.77%–96.13%. This method has the advantages of high sensitivity and good specificity, and can be applied to the detection of pine nut allergens in food samples such as biscuits, chocolate, and beverages, which provides technical support for the authentication of food labels and the detection of latent allergens in foods

Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy

Somatic SF3B1 hotspot mutation in prolactinomas.

The genetic basis and corresponding clinical relevance of prolactinomas remain poorly understood. Here, we perform whole genome sequencing (WGS) on 21 patients with prolactinomas to detect somatic mutations and then validate the mutations with digital polymerase chain reaction (PCR) analysis of tissue samples from 227 prolactinomas. We identify the same hotspot somatic mutation in splicing factor 3 subunit B1 (SF3B1R625H) in 19.8% of prolactinomas. These patients with mutant prolactinomas display higher prolactin (PRL) levels (p = 0.02) and shorter progression-free survival (PFS) (p = 0.02) compared to patients without the mutation. Moreover, we identify that the SF3B1R625H mutation causes aberrant splicing of estrogen related receptor gamma (ESRRG), which results in stronger binding of pituitary-specific positive transcription factor 1 (Pit-1), leading to excessive PRL secretion. Thus our study validates an important mutation and elucidates a potential mechanism underlying the pathogenesis of prolactinomas that may lead to the development of targeted therapeutics

Fusarium pseudograminearum biomass and toxin accumulation in wheat tissues with and without Fusarium crown rot symptoms

Fusarium crown rot (FCR) is an important and devastating disease of wheat (Triticum aestivum) caused by the fungus Fusarium pseudograminearum and related pathogens. Using two distinct susceptible cultivars, we investigated the isolation frequencies of F. pseudograminearum and quantified its biomass accumulation and the levels of the associated toxins deoxynivalenol (DON) and DON-3-glucoside (D3G) in inoculated field-grown wheat plants. We detected F. pseudograminearum in stem, peduncle, rachis, and husk tissues, but not in grains, whereas DON and D3G accumulated in stem, rachis, husk, and grain tissues. Disease severity was positively correlated with the frequency of pathogen isolation, F. pseudograminearum biomass, and mycotoxin levels. The amount of F. pseudograminearum biomass and mycotoxin contents in asymptomatic tissue of diseased plants were associated with the distance of the tissue from the diseased internode and the disease severity of the plant. Thus, apparently healthy tissue may harbor F. pseudograminearum and contain associated mycotoxins. This research helps clarify the relationship between F. pseudograminearum occurrence, F. pseudograminearum biomass, and mycotoxin accumulation in tissues of susceptible wheat cultivars with or without disease symptoms, providing information that can lead to more effective control measures

HbA1C and Cancer Risk in Patients with Type 2 Diabetes – A Nationwide Population-Based Prospective Cohort Study in Sweden

Background: Diabetes is associated with increased cancer risk. The underlying mechanisms remain unclear. Hyperglycemia might be one risk factor. HbA1c is an indicator of the blood glucose level over the latest 1 to 3 months. This study aimed to investigate association between HbA1c level and cancer risks in patients with type 2 diabetes based on real life situations. Methods: This is a cohort study on 25,476 patients with type 2 diabetes registered in the Swedish National Diabetes Register from 1997-1999 and followed until 2009. Follow-up for cancer was accomplished through register linkage. We calculated incidences of and hazard ratios (HR) for cancer in groups categorized by HbA1c <= 58 mmol/mol (7.5%) versus >58 mmol/mol, by quartiles of HbA1c, and by HbA1c continuously at Cox regression, with covariance adjustment for age, sex, diabetes duration, smoking and insulin treatment, or adjusting with a propensity score. Results: Comparing HbA1c >58 mmol/mol with <= 58 mmol/mol, adjusted HR for all cancer was 1.02 [95% CI 0.95-1.10] using baseline HbA1c, and 1.04 [95% CI 0.97-1.12] using updated mean HbA1c, and HRs were all non-significant for specific cancers of gastrointestinal, kidney and urinary organs, respiratory organs, female genital organs, breast or prostate. Similarly, no increased risks of all cancer or the specific types of cancer were found with higher quartiles of baseline or updated mean HbA1c, compared to the lowest quartile. HR for all cancer was 1.01 [0.98-1.04] per 1%-unit increase in HbA1c used as a continuous variable, with non-significant HRs also for the specific types of cancer per unit increase in HbA1c. Conclusions: In this study there were no associations between HbA1c and risks for all cancers or specific types of cancer in patients with type 2 diabetes

Analysis of Common and Specific Mechanisms of Liver Function Affected by Nitrotoluene Compounds

BACKGROUND: Nitrotoluenes are widely used chemical manufacturing and munitions applications. This group of chemicals has been shown to cause a range of effects from anemia and hypercholesterolemia to testicular atrophy. We have examined the molecular and functional effects of five different, but structurally related, nitrotoluenes on using an integrative systems biology approach to gain insight into common and disparate mechanisms underlying effects caused by these chemicals. METHODOLOGY/PRINCIPAL FINDINGS: Sprague-Dawley female rats were exposed via gavage to one of five concentrations of one of five nitrotoluenes [2,4,6-trinitrotoluene (TNT), 2-amino-4,6-dinitrotoluene (2ADNT) 4-amino-2,6-dinitrotoulene (4ADNT), 2,4-dinitrotoluene (2,4DNT) and 2,6-dinitrotoluene (2,6DNT)] with necropsy and tissue collection at 24 or 48 h. Gene expression profile results correlated well with clinical data and liver histopathology that lead to the concept that hematotoxicity was followed by hepatotoxicity. Overall, 2,4DNT, 2,6DNT and TNT had stronger effects than 2ADNT and 4ADNT. Common functional terms, gene expression patterns, pathways and networks were regulated across all nitrotoluenes. These pathways included NRF2-mediated oxidative stress response, aryl hydrocarbon receptor signaling, LPS/IL-1 mediated inhibition of RXR function, xenobiotic metabolism signaling and metabolism of xenobiotics by cytochrome P450. One biological process common to all compounds, lipid metabolism, was found to be impacted both at the transcriptional and lipid production level. CONCLUSIONS/SIGNIFICANCE: A systems biology strategy was used to identify biochemical pathways affected by five nitroaromatic compounds and to integrate data that tie biochemical alterations to pathological changes. An integrative graphical network model was constructed by combining genomic, gene pathway, lipidomic, and physiological endpoint results to better understand mechanisms of liver toxicity and physiological endpoints affected by these compounds

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe