[First Extended Anaerobic Phase Enhanced Nitrogen and Phosphorus Removal by Aerobic Granular Sludge Under Intermittent Gradient Aeration].

In this study, a SBR reactor was selected to explore the effect of nitrogen and phosphorus removal by aerobic granular sludge under different initial anaerobic time using intermittent gradient aeration (decreasing dissolved oxygen concentration in each aeration section) and actual domestic wastewater with low C/N ratio as the influent matrix. The results showed that the initial anaerobic stage of intermittent gradient aeration increased from 50 min to 90 min, which increased the carbon source reserves in granular sludge. This improved delayed anaerobic condition led to the improvement of nitrogen and phosphorus removal efficiency of granular sludge. When delayed to 70 and 90 min, the removal efficiency of COD, TN, and TP reached 84.74%, 70.05%, and 89.7% and 86.65%, 78.81%, and 85.5%, respectively. However, after the first anaerobic phase time was increased to 110 min, the sludge loss was more severe owing to the disintegration of some cells, leading to a decrease in internal carbon source reserves by about 13.6%. Owing to this, the pollutant removal efficiency decreased. In the process of prolonging the first anaerobic phase time from 50 min to 90 min, the content of PS in LB-EPS changed minimally; when it was delayed to 110 min, the content of PS increased to about 7.18 mg·g-1, and the PN content increased to about 5.56 mg·g-1. The contents of PN and PS in TB-EPS were stable, which indicated that the effect of internal carbon storage on LB-EPS was greater than that of TB-EPS, and the decrease in sludge settling performance was closely related to the increase in PS content in LB-EPS. The proportion of DPAOs in granular sludge increased as the first anaerobic phase time increased, and the proportion of DPAOs reached 51.5% when the first anaerobic phase time was 70 min.

Puerarin alleviates streptozotocin (STZ)-induced osteoporosis in rats through suppressing inflammation and apoptosis via HDAC1/HDAC3 signaling.

Diabetic osteoporosis is a severe public health concern in the world. Puerarin (PU) is extensively attractive due to its superior bioactivities. In the study, we found that PU protected against streptozotocin (STZ)-induced osteoporotic changes in rats. PU treatment improved STZ-induced diabetes in rats, as evidenced by the reduced serum glucose and insulin levels. PU administration markedly attenuated bone loss and tartarate-resistant acid phosphatase (TRAP) activity in STZ-induced rats. Bone mineral density (BMD) was significantly decreased in diabetic rats, while being prevented by PU. STZ-induced impairments in microarchitecture of femoral tissues were markedly alleviated by PU treatment. In addition, bone-specific alkaline phosphatase (BALP), osteoprotegerin (OPG) and Runt-related transcription factor 2 (Runx2) levels in serum or tibia were improved by PU in STZ-injected rats; however, TRACP isoform 5b (TRACP-5b), carboxy-terminal collagen cross-links (ß-CTX) and receptor activator of nuclear factor-κB ligand (RANKL) levels were decreased. Further, PU treatment inhibited inflammation and apoptosis in STZ-treated rats. Additionally, STZ injection increased histone deacetylase (HDAC)-1 and -3 expressions in femoral heads of rats, which were relieved by PU treatment. Notably, both HDAC1 and HDAC3 could enhance osteoporosis in vitro, as proved by the decreased ALP and Runx2 levels and the increased TRAP expression. Inflammation and apoptosis were exacerbated by HDAC1/3 over-expression, which were markedly diminished by PU treatment. In contrast, suppressing HDAC1/3 significantly abrogated fructose (Fru)-elicited inflammation and apoptosis in cells. Collectively, our data illustrated that PU is a potential therapeutic option to prevent diabetic osteoporosis by inhibiting HDAC1/HDAC3 signaling.

Information Filtering via Heterogeneous Diffusion in Online Bipartite Networks.

The rapid expansion of Internet brings us overwhelming online information, which is impossible for an individual to go through all of it. Therefore, recommender systems were created to help people dig through this abundance of information. In networks composed by users and objects, recommender algorithms based on diffusion have been proven to be one of the best performing methods. Previous works considered the diffusion process from user to object, and from object to user to be equivalent. We show in this work that it is not the case and we improve the quality of the recommendation by taking into account the asymmetrical nature of this process. We apply this idea to modify the state-of-the-art recommendation methods. The simulation results show that the new methods can outperform these existing methods in both recommendation accuracy and diversity. Finally, this modification is checked to be able to improve the recommendation in a realistic case.