Expression levels of vascular endothelial growth factors A and C in patients with peptic ulcers and gastric cancer

Purpose: Vascular endothelial growth factor (VEGF) is one of the most important growth factors for metastatic tumors. To clarify the role of VEGF-A and C in patients with peptic ulcer disease (PUD) or gastric cancer (GC), we evaluated the expression levels of these two molecules. We also analyzed the effect of Helicobacter pylori infection on VEGF-A and C expression levels

Increased expression of two alternative spliced variants of CD1d molecule in human gastric cancer

Background: CD1d presents glycolipid antigens to invariant natural killer T (iNKT) cells. The role of CD1d in the development of peptic ulcer and gastric cancer has not been revealed, yet. Objective: To clarify the expression of alternatively spliced variants of CD1d in peptic ulcer and gastric cancer. Methods: Patients with dyspepsia were selected and divided into three groups of non-ulcer dyspepsia (NUD), peptic ulcer disease (PUD), and gastric cancer (GC), according to their endoscopic and histopathological examinations. H. pylori infection was diagnosed by rapid urease test and histopathology. The expression levels of V2, V4, and V5 spliced variants of CD1d molecule were determined by quantitative Reverse Transcriptase PCR. Results: Relative gene expression levels of V4 were higher in GC patients (n=37) than those in NUD (n=49) and PUD (n=51) groups (p<0.05 and p<0.01, respectively). Moreover, GC patients showed higher expression levels of V5 compared to NUD and PUD groups (p<0.001 and p<0.001, respectively). Positive correlation coefficients were attained between V4 and V5 expression in patients with PUD (r=0.734, p<0.0001) and GC (r=0.423, p<0.01), but not in patients with NUD. Among NUD patients, the expression levels of V4, but not V5, were higher in H. pylori-positive patients than in H. pylori-negative ones (p<0.01). Conclusion: Collectively, both membrane-bound (V4) and soluble (V5) isoforms of CD1d were over-expressed in gastric tumor tissues, suggesting that they are involved in anti-tumor immune responses. © 2015, Shiraz University of Medical Sciences. All rights reserved

Role of morphine preconditioning and nitric oxide following brain ischemia reperfusion injury in mice

Objective(s): Morphine dependence (MD) potently protects heart against ischemia reperfusion (IR) injury through specific signaling mechanisms, which are different from the pathways involved in acute morphine treatment or classical preconditioning. Since opioid receptor density changes post cerebral ischemia strongly correlated with brain histological damage, in the present study, we tried to elucidate the possible role of opioid receptors in IR injury among morphine-dependent mice. Materials and Methods: Accordingly, incremental doses (10 mg/kg/day to 30 mg/kg/day) of morphine sulphate were subcutaneously administered for 5 days before global brain ischemia induction through bilateral common carotid artery occlusion. Animals were received naloxone (5 mg/kg) or L-NAME (20 mg/kg) 30 min after the last morphine dose. Twenty four hr after the ischemia induction, Retention trial of passive avoidance test and western blot analysis were done. histological analysis (TUNEL and NISSL staining) performed 72 hr after ischemia. Results: MD improved post ischemia memory performance (P<0.01) and neuronal survival (P<0.001) and decreased apoptosis (P<0.05) in region I of hippocampus (CA1 region) in mouse. Treatment with naloxone or L-NAME abolished all MD aforementioned effects. Conclusion: Results of the present study suggested that opioid receptors activation in the early hr post ischemia is crucial for MD-induced hippocampus tolerance against IR injury. Opioid receptor-dependent balance of NO production was another key factor in MD-induced protection. Further studies are required to determine the effect of MD on opioid receptor changes after ischemia and its correlation with MD-induced protection. © 2015, Mashhad University of Medical Sciences. All rights reserved

Improvement of tissue survival of skin flaps by 5α-reductase inhibitors: Possible involvement of nitric oxide and inducible nitric oxide synthase

Background: Skin flap grafting is a popular approach for reconstruction of critical skin and underlying soft tissue injuries. In a previous study, we demonstrated the beneficial effects of two 5α-reductase inhibitors, azelaic acid and finasteride, on tissue survival in a rat model of skin flap grafting. In the current study, we investigated the involvement of nitric oxide and inducible nitric oxide synthase (iNOS) in graft survival mediated by these agents. Methods: A number of 42 male rats were randomly allocated into six groups: 1, normal saline topical application; 2, azelaic acid (100 mg/flap); 3, finasteride (1 mg/flap); 4, injection of L-NG-nitroarginine methyl ester (L-NAME) (i.p., 20 mg/kg); 5, L-NAME (20 mg/kg, i.p.) + azelaic acid (100 mg/flap, topical); 6, L-NAME (20 mg/kg, i.p.) + finasteride (1 mg/flap, topical). Tissue survival, level of nitric oxide, and iNOS expression in groups were measured. Results: Our data revealed that azelaic acid and finasteride significantly increased the expression of iNOS protein and nitric oxide (NO) levels in graft tissue (P &lt; 0.05). These increases in iNOS expression and NO level were associated with higher survival of the graft tissue. Conclusion: It appears that alterations of the NO metabolism are implicated in the azelaic acid- and finasteride-mediated survival of the skin flaps. © 2015, Pasteur Institute of Iran. All rights reserved

An Integrated Hydrologic Bayesian Multi-Model Combination Framework: Confronting Input, parameter and model structural uncertainty in Hydrologic Prediction

This paper presents a new technique--Integrated Bayesian Uncertainty Estimator (IBUNE) to account for the major uncertainties of hydrologic rainfall-runoff predictions explicitly. The uncertainties from the input (forcing) data--mainly the precipitation observations and from the model parameters are reduced through a Monte Carlo Markov Chain (MCMC) scheme named Shuffled Complex Evolution Metropolis (SCEM) algorithm which has been extended to include a precipitation error model. Afterwards, the Bayesian Model Averaging (BMA) scheme is employed to further improve the prediction skill and uncertainty estimation using multiple model output. A series of case studies using three rainfall-runoff models to predict the streamflow in the Leaf River basin, Mississippi are used to examine the necessity and usefulness of this technique. The results suggests that ignoring either input forcings error or model structural uncertainty will lead to unrealistic model simulations and their associated uncertainty bounds which does not consistently capture and represent the real-world behavior of the watershed

Spatial links between subchondral bone architectural features and cartilage degeneration in osteoarthritic joints

Early diagnosis of osteoarthritis (OA), before the onset of irreversible changes is crucial for understanding the disease process and identifying potential disease-modifying treatments from the earliest stage. OA is a whole joint disease and affects both cartilage and the underlying subchondral bone. However, spatial relationships between cartilage lesion severity (CLS) and microstructural changes in subchondral plate and trabecular bone remain elusive. Herein, we collected femoral heads from hip arthroplasty for primary osteoarthritis (n = 7) and femoral neck fracture (n = 6; non-OA controls) cases. Samples were regionally assessed for cartilage lesions by visual inspection using Outerbridge classification and entire femoral heads were micro-CT scanned. Scans of each femoral head were divided into 4 quadrants followed by morphometric analysis of subchondral plate and trabecular bone in each quadrant. Principal component analysis (PCA), a data reduction method, was employed to assess differences between OA and non-OA samples, and spatial relationship between CLS and subchondral bone changes. Mapping of the trabecular bone microstructure in OA patients with low CLS revealed trabecular organisation resembling non-OA patients, whereas clear differences were identifiable in subchondral plate architecture. The OA-related changes in subchondral plate architecture were summarised in the first principle component (PC1) which correlated with CLS in all quadrants, whilst by comparison such associations in trabecular bone were most prominent in the higher weight-bearing regions of the femoral head. Greater articular cartilage deterioration in OA was regionally-linked with lower BV/TV, TMD and thickness, and greater BS/BV and porosity in the subchondral plate; and with thinner, less separated trabeculae with greater TMD and BS/BV in the trabecular bone. Our findings suggest that impairment of subchondral bone microstructure in early stage of OA is more readily discernible in the cortical plate and that morphological characterisation of the femoral head bone microstructure may allow for earlier OA diagnosis and monitoring of progression

How Might Recharge Change Under Projected Climate Change in the Western U.S.?

Although groundwater is a major water resource in the western U.S., little research has been done on the impacts of climate change on groundwater storage and recharge in the West. Here we assess the impact of projected changes in climate on groundwater recharge in the near (2021–2050) and far (2071–2100) future across the western U.S. Variable Infiltration Capacity model was run with RCP 6.0 forcing from 11 global climate models and “subsurface runoff” output was considered as recharge. Recharge is expected to decrease in the West (−5.8 ± 14.3%) and Southwest (−4.0 ± 6.7%) regions in the near future and in the South region (−9.5 ± 24.3%) in the far future. The Northern Rockies region is expected to get more recharge in the near (+5.3 ± 9.2%) and far (+11.8 ± 12.3%) future. Overall, southern portions of the western U.S. are expected to get less recharge in the future and northern portions will get more. Climate change interacts with land surface properties to affect the amount of recharge that occurs in the future. Effects on recharge due to change in vegetation response from projected changes in climate and CO2 concentration, though important, are not considered in this study.Key PointsClimate change interacts with land surface properties to affect the amount of recharge that occurs in the futureSouthern portions of the western U.S. are expected to get less and northern portions more recharge in the futureThe large variability in projected recharge across the GCMs is associated with variability in projected precipitationPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139906/1/grl56569.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139906/2/grl56569_am.pd

Multi-Model Combination Techniques for Hydrological Forecasting: Application to Distributed Model Intercomparison Project Results

This paper examines several multi-model combination techniques: the Simple Multimodel Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction

Towards a radiation free numerical modelling framework to predict spring assisted correction of scaphocephaly

Sagittal Craniosynostosis (SC) is a congenital craniofacial malformation, involving premature sagittal suture ossification; spring-assisted cranioplasty (SAC) – insertion of metallic distractors for skull reshaping – is an established method for treating SC. Surgical outcomes are predictable using numerical modelling, however published methods rely on computed tomography (CT) scans availability, which are not routinely performed. We investigated a simplified method, based on radiation-free 3D stereophotogrammetry scans.Eight SAC patients (age 5.1 ± 0.4 months) with preoperative CT and 3D stereophotogrammetry scans were included. Information on osteotomies, spring model and post-operative spring opening were recorded. For each patient, two preoperative models (PREOP) were created: i) CT model and ii) S model, created by processing patient specific 3D surface scans using population averaged skin and skull thickness and suture locations. Each model was imported into ANSYS Mechanical (Analysis System Inc., Canonsburg, PA) to simulate spring expansion. Spring expansion and cranial index (CI - skull width over length) at times equivalent to immediate postop (POSTOP) and follow up (FU) were extracted and compared with in-vivo measurements.Overall expansion patterns were very similar for the 2 models at both POSTOP and FU. Both models had comparable outcomes when predicting spring expansion. Spring induced CI increase was similar, with a difference of 1.2%±0.8% for POSTOP and 1.6%±0.6% for FU.This work shows that a simplified model created from the head surface shape yields acceptable results in terms of spring expansion prediction. Further modelling refinements will allow the use of this predictive tool during preoperative planning