Loss of Guanylyl Cyclase C (GCC) Signaling Leads to Dysfunctional Intestinal Barrier

Guanylyl Cyclase C (GCC) signaling via uroguanylin (UGN) and guanylin activation is a critical mediator of intestinal fluid homeostasis, intestinal cell proliferation/apoptosis, and tumorigenesis. As a mechanism for some of these effects, we hypothesized that GCC signaling mediates regulation of intestinal barrier function.Paracellular permeability of intestinal segments was assessed in wild type (WT) and GCC deficient (GCC-/-) mice with and without lipopolysaccharide (LPS) challenge, as well as in UGN deficient (UGN-/-) mice. IFNγ and myosin light chain kinase (MLCK) levels were determined by real time PCR. Expression of tight junction proteins (TJPs), phosphorylation of myosin II regulatory light chain (MLC), and STAT1 activation were examined in intestinal epithelial cells (IECs) and intestinal mucosa. The permeability of Caco-2 and HT-29 IEC monolayers, grown on Transwell filters was determined in the absence and presence of GCC RNA interference (RNAi). We found that intestinal permeability was increased in GCC-/- and UGN-/- mice compared to WT, accompanied by increased IFNγ levels, MLCK and STAT1 activation in IECs. LPS challenge promotes greater IFNγ and STAT1 activation in IECs of GCC-/- mice compared to WT mice. Claudin-2 and JAM-A expression were reduced in GCC deficient intestine; the level of phosphorylated MLC in IECs was significantly increased in GCC-/- and UGN-/- mice compared to WT. GCC knockdown induced MLC phosphorylation, increased permeability in IEC monolayers under basal conditions, and enhanced TNFα and IFNγ-induced monolayer hyperpermeability.GCC signaling plays a protective role in the integrity of the intestinal mucosal barrier by regulating MLCK activation and TJ disassembly. GCC signaling activation may therefore represent a novel mechanism in maintaining the small bowel barrier in response to injury

Vegetative Ecological Characteristics of Restored Reed (Phragmites australis) Wetlands in the Yellow River Delta, China

In this study, we compared ecological characteristics of wetland vegetation in a series of restoration projects that were carried out in the wetlands of Yellow River Delta. The investigated characteristics include plant composition structure, species diversity and community similarity in three kinds of Phragmites australis wetlands, i.e. restored P. australis wetlands (R1, R2, R3 and R4: restored in 2002, 2005, 2007 and 2009, respectively), natural P. australis wetland (N) and degraded P. australis wetland (D) to assess the process of wetlands restoration. The coverage of the R1 was 99%, which was similar to natural wetland. Among all studied wetlands, the highest and lowest stem density was observed in R1 and R2, respectively, Plant height and stem diameter show the same trend as N > R2 > R1 > R3 > D > R4. Species diversity of restored P. australis wetlands became closed to natural wetland. Both species richness and Shannon–Wiener index had similar tendency: increased first and then decreased with restored time. The highest species richness and species diversity were observed in R2, while the lowest values of those parameters were found in natural P. australis wetland. Similarity indexes between restored wetlands and natural wetland increased with the restoration time, but they were still less than 50%. The results indicate that the vegetation of P. australis wetlands has experienced a great improvement after several years’ restoration, and it is feasible to restored degraded P. australis wetlands by pouring fresh water into those wetlands in the Yellow River Delta. However, it is notable that costal degraded P. australis wetland in this region may take years to decades to reach the status of natural wetland

An improved empirical dynamic control system model of global mean sea level rise and surface temperature change

10.1007/s00704-017-2039-3Theoretical and Applied Climatology1321-Feb375-38

Quercetin and Allopurinol Ameliorate Kidney Injury in STZ-Treated Rats with Regulation of Renal NLRP3 Inflammasome Activation and Lipid Accumulation

Hyperuricemia, hyperlipidemia and inflammation are associated with diabetic nephropathy. The NLRP3 inflammasome-mediated inflammation is recently recognized in the development of kidney injury. Urate and lipid are considered as danger signals in the NLRP3 inflammasome activation. Although dietary flavonoid quercetin and allopurinol alleviate hyperuricemia, dyslipidmia and inflammation, their nephroprotective effects are currently unknown. In this study, we used streptozotocin (STZ)-induced diabetic nephropathy model with hyperuricemia and dyslipidemia in rats, and found over-expression of renal inflammasome components NLRP3, apoptosis-associated speck-like protein and Caspase-1, resulting in elevation of IL-1β and IL-18, with subsequently deteriorated renal injury. These findings demonstrated the possible association between renal NLRP3 inflammasome activation and lipid accumulation to superimpose causes of nephrotoxicity in STZ-treated rats. The treatment of quercetin and allopurinol regulated renal urate transport-related proteins to reduce hyperuricemia, and lipid metabolism-related genes to alleviate kidney lipid accumulation in STZ-treated rats. Furthermore, quercetin and allopurinol were found to suppress renal NLRP3 inflammasome activation, at least partly, via their anti-hyperuricemic and anti-dyslipidemic effects, resulting in the amelioration of STZ-induced the superimposed nephrotoxicity in rats. These results may provide a basis for the prevention of diabetes-associated nephrotoxicity with urate-lowering agents such as quercetin and allopurinol

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe

A gas chromatographic analysis of light hydrocarbons on a column packed with modified silica gel

A one-meter long column packed with silica gel is used to separate light hydrocarbons. The silica gel has been modified with several kinds of gas chromatography stationary phases. Among these, PEG 2000 shows fairly good effect when using 80-100 meshes silica gel for the separation of mixture of methane, ethane, ethylene, acetylene, propane, propylene and n-, i-butane. The different behavior of silica gel between batch to batch is also found. When silica gel is coated with a small amount of Al2O3 prepared with sol-gel method, better resolution has been observed on a 2-meter column compared with the non-modified silica gel