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Diabetic nephropathy (DN), characterized by glomerular injury, is a common complication of both type 1 and type 2 diabetes, accompanied by massive proteinuria. Podocytes are reported to play pivotal roles in maintaining the glomerular filtration barrier. In addition, the expression of long non-coding RNAs (lncRNAs) ANRIL was upregulated in type 2 diabetes patients. Hence, the aim of this study was to investigate the underlying mechanisms implicated the role of LncRNA ANRIL in podocyte injury in DN. The concentration of inflammatory cytokines was quantified by the corresponding enzyme-linked immunosorbent assay (ELISA) kits. The mRNA levels of the target gene were determined by reverse transcription and real-time quantitative PCR (RT-qPCR). The expressions of proteins were evaluated by Western blot. The activities of lactate dehydrogenase (LDH), superoxide dismutase (SOD), and malondialdehyde (MDA) level were measured by corresponding commercial kits. Finally, the apoptosis of podocytes was analyzed by TUNEL assay. In our study, LncRNA ANRIL was highly expressed in high glucose (HG)-induced podocytes. Moreover, LncRNA ANRIL silencing attenuated HG-induced inflammation, oxidative stress, and apoptosis and induced MME overexpression in podocytes. Interestingly, MME knockdown abolished the suppressive effect of LncRNA ANRIL silencing on HG-induced inflammation, oxidative stress, and apoptosis in podocytes. LncRNA ANRIL silencing alleviates HG-induced inflammation, oxidative stress, and apoptosis via upregulation of MME in podocytes. Hence, LncRNA ANRIL may be a novel and effective target to ameliorate podocyte injury in DN.

Risk recognition and fast-start performance are critical to fish survival when faced with predators. Many fish species have been shown to recognize risks associated with chemical cues released by injured conspecifics. However, little is known about the ontogeny of “risk” recognition via damage-released chemical alarm cues and fast-start performance in prey fishes. The objectives of this study were to determine whether risk recognition and fast-start performance in guppies (Poecilia reticulata) exhibit ontogenetic variation, and whether there is a trade-off between risk recognition and fast-start performance. To achieve these objectives, individual guppies from replicate groups were assayed on one of the 1st, 7th, 14th, 21st, or 28th day after their birth. We found that both the risk recognition and fast-start performance in guppies exhibited ontogenetic variation, as on days 1 and 7, fish did not exhibit risk recognition when exposed to alarm cues from conspecifics, but by day 14, such recognition was evident. Noticeable increases in maximum linear velocity (Vmax), maximum linear acceleration (Amax), and escape distance (S120 ms) were concurrent with progressive ontogenetic stage, and no significant correlations were found between risk recognition and fast-start performance at any ontogenetic stage. Our findings reveal ontogenetic variation in damage-released chemical cue recognition and fast-start performance in guppies.

With the increasing popularity of the social tagging systems, tags can be effectively utilized to enhance Collaborative Filtering (CF) algorithms. Tags not only reflect users' preference, but also are a cue to describe the semantics of items. This paper formulates the problem of collaborative filtering as random walks over the user-item-tag tripartite graph. In order to alleviate the sparsity of tags, a lasso logistic regression model is conducted to accomplish tag expansion, i.e., adding relevant tags and removing irrelevant tags for each item. Experimental results on MovieLens dataset demonstrate the superiority of the proposed algorithms over several existing CF algorithms in terms of ranking performance measure F1 and Macro DOA.