A Process Model for the Production of Hydrogen Using High Temperature Electrolysis

High temperature electrolysis (HTE) involves the splitting of stream into hydrogen and oxygen at high temperatures. The primary advantage of HTE over conventional low temperature electrolysis is that considerably higher hydrogen production efficiencies can be achieved. Performing the electrolysis process at high temperatures results in more favorable thermodynamics for electrolysis, more efficient production of electricity, and allows direct use of process heat to generate steam. This paper presents the results of process analyses performed to evaluate the hydrogen production efficiencies of an HTE plant coupled to a 600 MWt Modular Helium Reactor (MHR) that supplies both the electricity and process heat needed to drive the process. The MHR operates with a coolant outlet temperature of 950 C. Approximately 87% of the high-temperature heat is used to generate electricity at high efficiency using a direct, Brayton-cycle power conversion system. The remaining high-temperature heat is used to generate a superheated steam / hydrogen mixture that is supplied to the electrolyzers. The analyses were performed using the HYSYS process modeling software. The model used to perform the analyses consisted of three loops; a primary high temperature helium loop, a secondary helium loop and the HTE process loop. The detailed model included realistic representations of all major components in the system, including pumps, compressors, heat exchange equipment, and the electrolysis stack. The design of the hydrogen production process loop also included a steam-sweep gas system to remove oxygen from the electrolysis stack so that it can be recovered and used for other applications. Results of the process analyses showed that hydrogen production efficiencies in the range of 45% to 50% are achievable with this system

The Effectiveness of Pharmacological and Non-Pharmacological Interventions for Improving Glycaemic Control in Adults with Severe Mental Illness: A Systematic Review and Meta-Analysis

People with severe mental illness (SMI) have reduced life expectancy compared with the general population, which can be explained partly by their increased risk of diabetes. We conducted a meta-analysis to determine the clinical effectiveness of pharmacological and non-pharmacological interventions for improving glycaemic control in people with SMI (PROSPERO registration: CRD42015015558). A systematic literature search was performed on 30/10/2015 to identify randomised controlled trials (RCTs) in adults with SMI, with or without a diagnosis of diabetes that measured fasting blood glucose or glycated haemoglobin (HbA1c). Screening and data extraction were carried out independently by two reviewers. We used random effects meta-analysis to estimate effectiveness, and subgroup analysis and univariate meta-regression to explore heterogeneity. The Cochrane Collaboration’s tool was used to assess risk of bias. We found 54 eligible RCTs in 4,392 adults (40 pharmacological, 13 behavioural, one mixed intervention). Data for meta-analysis were available from 48 RCTs (n = 4052). Both pharmacological (mean difference (MD), -0.11mmol/L; 95% confidence interval (CI), [-0.19, -0.02], p = 0.02, n = 2536) and behavioural interventions (MD, -0.28mmol//L; 95% CI, [-0.43, -0.12], p<0.001, n = 956) were effective in lowering fasting glucose, but not HbA1c (pharmacological MD, -0.03%; 95% CI, [-0.12, 0.06], p = 0.52, n = 1515; behavioural MD, 0.18%; 95% CI, [-0.07, 0.42], p = 0.16, n = 140) compared with usual care or placebo. In subgroup analysis of pharmacological interventions, metformin and antipsychotic switching strategies improved HbA1c. Behavioural interventions of longer duration and those including repeated physical activity had greater effects on fasting glucose than those without these characteristics. Baseline levels of fasting glucose explained some of the heterogeneity in behavioural interventions but not in pharmacological interventions. Although the strength of the evidence is limited by inadequate trial design and reporting and significant heterogeneity, there is some evidence that behavioural interventions, antipsychotic switching, and metformin can lead to clinically important improvements in glycaemic measurements in adults with SMI

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

BACKGROUND: Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. METHODS: In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. RESULTS: The most significant global associations for all genes in the pathway were seen in endometrioid (p = 0.082) and clear cell (p = 0.083), with the most significant gene level association seen with TGFBR2 (p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 (p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA (p = 0.035, endometrioid and mucinous), LGALS1 (p = 0.03, mucinous), STAT5B (p = 0.022, clear cell), TGFBR1 (p = 0.021 endometrioid) and TGFBR2 (p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). CONCLUSIONS: Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization

Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR=1.33, p=4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR=1.07, p=0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR=0.90, p=0.00033; rs927062, OR =0.94, p=0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations