Hepatic fibrosis occurs when liver tissue becomes scarred from repetitive liver injury and inflammatory responses; it can progress to cirrhosis and eventually to hepatocellular carcinoma. Previously, we reported that neoagarooligosaccharides (NAOs), produced by the hydrolysis of agar by β-agarases, have hepatoprotective effects against acetaminophen overdose-induced acute liver injury. However, the effect of NAOs on chronic liver injury, including hepatic fibrosis, has not yet been elucidated. Therefore, we examined whether NAOs protect against fibrogenesis in vitro and in vivo. NAOs ameliorated PAI-1, α-SMA, CTGF and fibronectin protein expression and decreased mRNA levels of fibrogenic genes in TGF-β-treated LX-2 cells. Furthermore, downstream of TGF-β, the Smad signaling pathway was inhibited by NAOs in LX-2 cells. Treatment with NAOs diminished the severity of hepatic injury, as evidenced by reduction in serum alanine aminotransferase and aspartate aminotransferase levels, in carbon tetrachloride (CCl4)-induced liver fibrosis mouse models. Moreover, NAOs markedly blocked histopathological changes and collagen accumulation, as shown by H&E and Sirius red staining, respectively. Finally, NAOs antagonized the CCl4-induced upregulation of the protein and mRNA levels of fibrogenic genes in the liver. In conclusion, our findings suggest that NAOs may be a promising candidate for the prevention and treatment of chronic liver injury via inhibition of the TGF-β/Smad signaling pathway. 相似文献
The aim of this exploratory study has been to investigate the fire properties and environmental aspects of different upholstery material combinations, mainly for domestic applications. An analysis of the sustainability and circularity of selected textiles, along with lifecycle assessment, is used to qualitatively evaluate materials from an environmental perspective. The cone calorimeter was the primary tool used to screen 20 different material combinations from a fire performance perspective. It was found that textile covers of conventional fibres such as wool, cotton and polyester, can be improved by blending them with fire resistant speciality fibres. A new three‐dimensional web structure has been examined as an alternative padding material, showing preliminary promising fire properties with regard to ignition time, heat release rates and smoke production. 相似文献
Antimony triselenide (Sb2Se3) nanoflake-based nitrogen dioxide (NO2) sensors exhibit a progressive bifunctional gas-sensing performance, with a rapid alarm for hazardous highly concentrated gases, and an advanced memory-type function for low-concentration (<1 ppm) monitoring repeated under potentially fatal exposure. Rectangular and cuboid shaped Sb2Se3 nanoflakes, comprising van der Waals planes with large surface areas and covalent bond planes with small areas, can rapidly detect a wide range of NO2 gas concentrations from 0.1 to 100 ppm. These Sb2Se3 nanoflakes are found to be suitable for physisorption-based gas sensing owing to their anisotropic quasi-2D crystal structure with extremely enlarged van der Waals planes, where they are humidity-insensitive and consequently exhibit an extremely stable baseline current. The Sb2Se3 nanoflake sensor exhibits a room-temperature/low-voltage operation, which is noticeable owing to its low energy consumption and rapid response even under a NO2 gas flow of only 1 ppm. As a result, the Sb2Se3 nanoflake sensor is suitable for the development of a rapid alarm system. Furthermore, the persistent gas-sensing conductivity of the sensor with a slow decaying current can enable the development of a progressive memory-type sensor that retains the previous signal under irregular gas injection at low concentrations. 相似文献
Reconstructing gene regulatory networks (GRNs) plays an important role in identifying the complicated regulatory relationships, uncovering regulatory patterns in cells, and gaining a systematic view for biological processes. In order to reconstruct large-scale GRNs accurately, in this paper, we first use fuzzy cognitive maps (FCMs), which are a kind of cognition fuzzy influence graphs based on fuzzy logic and neural networks, to model GRNs. Then, a novel hybrid method is proposed to reconstruct GRNs from time series expression profiles using memetic algorithm (MA) combined with neural network (NN), which is labeled as MANNFCM-GRN. In MANNFCM-GRN, the MA is used to determine regulatory connections in GRNs and the NN is used to determine the interaction strength of the regulatory connections. In the experiments, the performance of MANNFCM-GRN is validated on both synthetic data and the benchmark dataset DREAM3 and DREAM4. The experimental results demonstrate the efficacy of MANNFCM-GRN and show that MANNFCM-GRN can reconstruct GRNs with high accuracy without expert knowledge. The comparison with existing algorithms also shows that MANNFCM-GRN outperforms ant colony optimization, non-linear Hebbian learning, and real-coded genetic algorithms.