Liver fatty acid composition in mice with or without nonalcoholic fatty liver disease

<p>Abstract</p> <p>Background</p> <p>Nonalcoholic fatty liver disease (NAFLD) is one of the most frequent causes of abnormal liver function. Because fatty acids can damage biological membranes, fatty acid accumulation in the liver may be partially responsible for the functional and morphological changes that are observed in nonalcoholic liver disease. The aim of this study was to use gas chromatography-mass spectrometry to evaluate the fatty acid composition of an experimental mouse model of NAFLD induced by high-fat feed and CCl₄and to assess the association between liver fatty acid accumulation and NAFLD. C57BL/6J mice were given high-fat feed for six consecutive weeks to develop experimental NAFLD. Meanwhile, these mice were given subcutaneous injections of a 40% CCl₄-vegetable oil mixture twice per week.</p> <p>Results</p> <p>A pathological examination found that NAFLD had developed in the C57BL/6J mice. High-fat feed and CCl₄led to significant increases in C14:0, C16:0, C18:0 and C20:3 (P < 0.01), and decreases in C15:0, C18:1, C18:2 and C18:3 (P < 0.01) in the mouse liver. The treatment also led to an increase in SFA and decreases in other fatty acids (UFA, PUFA and MUFA). An increase in the ratio of product/precursor n-6 (C20:4/C18:2) and n-3 ([C20:5+C22:6]/C18:3) and a decrease in the ratio of n-6/n-3 (C20:4/[C20:5+C22:6]) were also observed.</p> <p>Conclusion</p> <p>These data are consistent with the hypothesis that fatty acids are deranged in mice with non-alcoholic fatty liver injury induced by high-fat feed and CCl₄, which may be involved in its pathogenesis and/or progression via an unclear mechanism.</p

Content Popularity Prediction in Fog-RANs : A Bayesian Learning Approach

AbstractIn this paper, the content popularity prediction problem in cache-enabled fog radio access networks (F-RANs) is investigated. In order to predict the content popularity with high accuracy and low complexity, we propose a Gaussian process based Poisson regressor to model the content request pattern. Firstly, the relationship between content features and popularity is captured by our developed model. Then, we utilize Bayesian learning to learn the model parameters, which are robust to over-fitting. However, Bayesian methods are usually unable to find a closed-form expression of the posterior distribution. To tackle this issue, we apply a Stochastic Variance Reduced Gradient Hamiltonian Monte Carlo (SVRG-HMC) to approximate the posterior distribution. Two types of predictive content popularity are formulated for the requests of existing contents and newly-added contents. Simulation results show that the performance of our proposed policy outperforms the policy based on other Monte Carlo based method.Abstract In this paper, the content popularity prediction problem in cache-enabled fog radio access networks (F-RANs) is investigated. In order to predict the content popularity with high accuracy and low complexity, we propose a Gaussian process based Poisson regressor to model the content request pattern. Firstly, the relationship between content features and popularity is captured by our developed model. Then, we utilize Bayesian learning to learn the model parameters, which are robust to over-fitting. However, Bayesian methods are usually unable to find a closed-form expression of the posterior distribution. To tackle this issue, we apply a Stochastic Variance Reduced Gradient Hamiltonian Monte Carlo (SVRG-HMC) to approximate the posterior distribution. Two types of predictive content popularity are formulated for the requests of existing contents and newly-added contents. Simulation results show that the performance of our proposed policy outperforms the policy based on other Monte Carlo based method

STABILITY ANALYSIS OF DEFECT AROUND PARTICLES IN EUTECTIC COMPOSITE CERAMIC

The defect arising from the thermal coefficient mismatch of different phases was an important factor of reducing strength in eutectic composite ceramic. Based on the equivalent inclusion method and the interaction direct derivative（ IDD）estimate,stress intensity factor of annular defect under residual stress field and applied loading was calculated,and annular defect stability was analyzed. And the influence of particle stiffness,shape and volume fraction was investigated. Results indicated that,the crack nucleation was most easily produced in the oblate particle; stiff particles caused average applied stress reduced in matrix,and it reduced greater when the stiff particle was prolate elliptic,while the soft particle had the contrary effect. Stress intensity factor of defect was controlled by residual stress as the defect extension was small while it was controlled by applied stress for large defect extension. Prolate elliptic particle was beneficial to improve strength

Changes in Heat and Energy During Depressurization-Induced Natural Gas Hydrate Dissociation in Porous Media

Natural gas hydrates (shortened as hydrates) are expected to be a prospective alternative to traditional fossil energies. The main strategy of exploring hydrates is achieved by dissociating solid hydrates into gas and water with the depressurization method. However, we have little knowledge on the changes in heat and energy, which are implicit essences compared with explicit temperature. Thus, this study for the first time investigates the evolutionary patterns of heat and energy during hydrate dissociation, by fully coupled thermal&ndash;hydraulic&ndash;mechanical&ndash;chemical modelling. A novel numerical technique (physics-based constrained conditions) is proposed to guarantee the stability and precision of the numerical computation. The classic Masuda&rsquo;s experiment is used as a case study. Results show that the cumulative conduction heat tends to increase first and then decrease during the dissociation of hydrate, while the cumulative advection heat has the tendency to increase monotonically. External heat sources increase the energy, while phase change has a reduction effect on the change in energy. The role of conduction heat is minor, but the contribution of advection heat is considerable for the change in energy. Additionally, two implications are given for lab-scale experiments and in situ engineering from the perspective of energy. Our findings provide new insights into the mechanism of hydrate dissociation and are beneficial to the real-world engineering of hydrate exploration in terms of cost evaluation

Dioscin Protects against Cisplatin-Induced Acute Kidney Injury by Reducing Ferroptosis and Apoptosis through Activating Nrf2/HO-1 Signaling

Acute kidney injury (AKI) is a clinical syndrome with high morbidity and mortality worldwide, and there is currently no effective means to prevent it. Dioscin is naturally present in the dioscoreaceae plants and has antioxidant and anti-inflammatory effects. Here, we found that dioscin is protective against cisplatin-induced AKI. Pathological and ultrastructural observations revealed that dioscin reduced renal tissue lesions and mitochondrial damage. Furthermore, dioscin markedly suppressed reactive oxygen species and malondialdehyde levels in the kidneys of AKI rats and increased the contents of glutathione and catalase. In addition, dioscin dramatically reduced the number of apoptotic cells and the expression of pro-apoptotic proteins in rat kidneys and human renal tubular epithelial cells (HK2). Conversely, the protein levels of anti-ferroptosis including GPX4 and FSP1 in vivo and in vitro were significantly enhanced after dioscin treatment. Mechanistically, dioscin promotes the entry of Nrf2 into the nucleus and regulates the expression of downstream HO-1 to exert renal protection. However, the nephroprotective effect of dioscin was weakened after inhibiting Nrf2 in vitro and in vivo. In conclusion, dioscin exerts a reno-protective effect by decreasing renal oxidative injury, apoptosis and ferroptosis through the Nrf2/HO-1 signaling pathway, providing a new insight into AKI prevention