Activation of Pregnane X Receptor by Pregnenolone 16 α-carbonitrile Prevents High-Fat Diet-Induced Obesity in AKR/J Mice

Pregnane X receptor (PXR) is known to function as a xenobiotic sensor to regulate xenobiotic metabolism through selective transcription of genes responsible for maintaining physiological homeostasis. Here we report that the activation of PXR by pregnenolone 16α-carbonitrile (PCN) in AKR/J mice can prevent the development of high-fat diet-induced obesity and insulin resistance. The beneficial effects of PCN treatment are seen with reduced lipogenesis and gluconeogenesis in the liver, and lack of hepatic accumulation of lipid and lipid storage in the adipose tissues. RT-PCR analysis of genes involved in gluconeogenesis, lipid metabolism and energy homeostasis reveal that PCN treatment on high-fat diet-fed mice reduces expression in the liver of G6Pase, Pepck, Cyp7a1, Cd36, L-Fabp, Srebp, and Fas genes and slightly enhances expression of Cyp27a1 and Abca1 genes. RT-PCR analysis of genes involved in adipocyte differentiation and lipid metabolism in white adipose tissue show that PCN treatment reduces expression of Pparγ2, Acc1, Cd36, but increases expression of Cpt1b and Pparα genes in mice fed with high-fat diet. Similarly, PCN treatment of animals on high-fat diet increases expression in brown adipose tissue of Pparα, Hsl, Cpt1b, and Cd36 genes, but reduces expression of Acc1 and Scd-1 genes. PXR activation by PCN in high-fat diet fed mice also increases expression of genes involved in thermogenesis in brown adipose tissue including Dio2, Pgc-1α, Pgc-1β, Cidea, and Ucp-3. These results verify the important function of PXR in lipid and energy metabolism and suggest that PXR represents a novel therapeutic target for prevention and treatment of obesity and insulin resistance

Advances in Quantitative Hepcidin Measurements by Time-of-Flight Mass Spectrometry

Assays for the detection of the iron regulatory hormone hepcidin in plasma or urine have not yet been widely available, whereas quantitative comparisons between hepcidin levels in these different matrices were thus far even impossible due to technical restrictions. To circumvent these limitations, we here describe several advances in time-of flight mass spectrometry (TOF MS), the most important of which concerned spiking of a synthetic hepcidin analogue as internal standard into serum and urine samples. This serves both as a control for experimental variation, such as recovery and matrix-dependent ionization and ion suppression, and at the same time allows value assignment to the measured hepcidin peak intensities. The assay improvements were clinically evaluated using samples from various patients groups and its relevance was further underscored by the significant correlation of serum hepcidin levels with serum iron indices in healthy individuals. Most importantly, this approach allowed kinetic studies as illustrated by the paired analyses of serum and urine samples, showing that more than 97% of the freely filtered serum hepcidin can be reabsorbed in the kidney. Thus, the here reported advances in TOF MS-based hepcidin measurements represent critical steps in the accurate quantification of hepcidin in various body fluids and pave the way for clinical studies on the kinetic behavior of hepcidin in both healthy and diseased states

Identification of S100A8-correlated genes for prediction of disease progression in non-muscle invasive bladder cancer

<p>Abstract</p> <p>Background</p> <p><it>S100 calcium binding protein A8 </it>(<it>S100A8</it>) has been implicated as a prognostic indicator in several types of cancer. However, previous studies are limited in their ability to predict the clinical behavior of the cancer. Here, we sought to identify a molecular signature based on <it>S100A8 </it>expression and to assess its usefulness as a prognostic indicator of disease progression in non-muscle invasive bladder cancer (NMIBC).</p> <p>Methods</p> <p>We used 103 primary NMIBC specimens for microarray gene expression profiling. The median follow-up period for all patients was 57.6 months (range: 3.2 to 137.0 months). Various statistical methods, including the leave-one-out cross validation method, were applied to identify a gene expression signature able to predict the likelihood of progression. The prognostic value of the gene expression signature was validated in an independent cohort (n = 302).</p> <p>Results</p> <p>Kaplan-Meier estimates revealed significant differences in disease progression associated with the expression signature of <it>S100A8</it>-correlated genes (log-rank test, <it>P </it>< 0.001). Multivariate Cox regression analysis revealed that the expression signature of <it>S100A8</it>-correlated genes was a strong predictor of disease progression (hazard ratio = 15.225, 95% confidence interval = 1.746 to 133.52, <it>P </it>= 0.014). We validated our results in an independent cohort and confirmed that this signature produced consistent prediction patterns. Finally, gene network analyses of the signature revealed that <it>S100A8</it>, <it>IL1B</it>, and <it>S100A9 </it>could be important mediators of the progression of NMIBC.</p> <p>Conclusions</p> <p>The prognostic molecular signature defined by <it>S100A8</it>-correlated genes represents a promising diagnostic tool for the identification of NMIBC patients that have a high risk of progression to muscle invasive bladder cancer.</p

A First-Time-in-Human Study of GSK2636771, a Phosphoinositide 3 Kinase Beta-Selective Inhibitor, in Patients with Advanced Solid Tumors.

Background: The PI3K/protein kinase B (AKT) pathway is commonly activated in several tumor types. Selective targeting of p110β could result in successful pathway inhibition while avoiding the on- and off-target effects of pan-PI3K inhibitors. GSK2636771 is a potent, orally bioavailable, adenosine triphosphate-competitive, selective inhibitor of PI3Kβ.Methods: We evaluated the safety, pharmacokinetics, pharmacodynamics and antitumor activity of GSK2636771 to define the recommended phase II dose (RP2D). During the dose-selection and dose-escalation stages (parts 1 and 2), patients with PTEN-deficient advanced solid tumors received escalating doses of GSK2636771 (25-500 mg once daily) using a modified 3+3 design to determine the RP2D; tumor type-specific expansion cohorts (part 3) were implemented to further assess tumor responses at the RP2D.Results: A total of 65 patients were enrolled; dose-limiting toxicities were hypophosphatemia and hypocalcemia. Adverse events included diarrhea (48%), nausea (40%), and vomiting (31%). Single- and repeat-dose exposure increased generally dose proportionally. GSK2636771 400 mg once daily was the RP2D. Phospho/total AKT ratio decreased with GSK2636771 in tumor and surrogate tissue. A castrate-resistant prostate cancer (CRPC) patient harboring PIK3CB amplification had a partial response for over a year; an additional 10 patients derived durable (≥24 weeks) clinical benefit, including two other patients with CRPC with PIK3CB alterations (≥34 weeks). GSK2636771 400 mg once daily orally induced sufficient exposure and target inhibition with a manageable safety profile.Conclusions: Genomic aberrations of PIK3CB may be associated with clinical benefit from GSK2636771. Clin Cancer Res; 23(19); 5981-92. ©2017 AACR

Informational entropy : a failure tolerance and reliability surrogate for water distribution networks

Evolutionary algorithms are used widely in optimization studies on water distribution networks. The optimization algorithms use simulation models that analyse the networks under various operating conditions. The solution process typically involves cost minimization along with reliability constraints that ensure reasonably satisfactory performance under abnormal operating conditions also. Flow entropy has been employed previously as a surrogate reliability measure. While a body of work exists for a single operating condition under steady state conditions, the effectiveness of flow entropy for systems with multiple operating conditions has received very little attention. This paper describes a multi-objective genetic algorithm that maximizes the flow entropy under multiple operating conditions for any given network. The new methodology proposed is consistent with the maximum entropy formalism that requires active consideration of all the relevant information. Furthermore, an alternative but equivalent flow entropy model that emphasizes the relative uniformity of the nodal demands is described. The flow entropy of water distribution networks under multiple operating conditions is discussed with reference to the joint entropy of multiple probability spaces, which provides the theoretical foundation for the optimization methodology proposed. Besides the rationale, results are included that show that the most robust or failure-tolerant solutions are achieved by maximizing the sum of the entropies