No abstract

BackgroundA newly isolated L. acidophilus strain has been reported to have potential anti-inflammatory activities against lipopolysaccharide (LPS) challenge in piglet, while the details of the related inflammatory responses are limited. Here we aimed to analysis the ability of L. acidophilus to regulate inflammatory responses and to elucidate the mechanisms involved in its anti-inflammatory activity.ResultsThe ETEC (enterotoxigenic Escherichia coli) K88-induced up-regulations of IL-1β, IL-8 and TNF-α were obviously inhibited by L. acidophilus while IL-10 was significantly increased. Moreover, L. acidophilus down-regulated pattern recognition receptors TLR (Toll-like receptor) 2 and TLR4 expression in both spleen and mesenteric lymph nodes of ETEC-challenged piglets, in accompanied with the reduced phosphorylation levels of nuclear factor kappa B (NF-κB) p65 and mitogen-activated protein kinase (MAPK) p38 as well in spleen of ETEC-infected piglets. Furthermore, L.acidophilus significantly increased the expression of the negative regulators of TLRs signaling, including Tollip, IRAK-M, A20 and Bcl-3 in spleen of ETEC-challenged piglets.ConclusionsOur findings suggested that L. acidophilus regulated inflammatory response to ETEC via impairing both NF-κB and MAPK signaling pathways in piglets.

Using the widely available DMSO as the formylation reagent under oxidative conditions, an efficient Cu-catalyzed C3-formylation reaction of imidazo[1,2-a]pyridine C-H bonds to directly generate structurally sophisticated 3-formyl imidazo[1,2-a]pyridine derivatives has been developed. The reaction proceeded to generate products in good yields, and used the environmentally friendly molecular oxygen as the oxidant.

In this paper, we propose a framework to semi-automatically annotate faces in family photo albums. The core of the framework is the features used to define face similarity and this results in the learning algorithm used to refine automatic face annotation. We have adopted similarity based search and relevance feedback ideas developed for content-based image retrieval and a set of simple yet effective color and texture based features, in addition to the traditional face recognition features, in performing candidate annotation search. The experimental evaluation of the proposed approach has been conducted with a family album of 1707 photos and the results show that the proposed approach is an effective and efficient one for semi-automatic family photo album annotation.