Relevance of the Myeloid Differentiation Factor 88 (MyD88) on RANKL, OPG, and Nod Expressions Induced by TLR and IL-1R Signaling in Bone Marrow Stromal Cells

The myeloid differentiation factor 88 (MyD88) plays a pivotal role in Toll-like receptor (TLR)- and interleukin-1 receptor (IL-1R)-induced osteoclastogenesis. We examined the role of MyD88 on p38 mitogen-activated protein kinase (MAPK) and nuclear factor kappa-light-chain-enhancer of activated B cell (NF-κB) activation and nucleotide-binding oligomerization domain (Nod) induction by lipopolysaccharide (LPS) and IL-1 beta, and their effect on receptor activator of NF-κB ligand (RANKL) and osteoprotegerin (OPG) production in bone marrow stromal cell (BMSC). RANKL, Nod1, Nod2, NF-κB, and p38 protein levels were determined by Western blot. Nod2 was stimulated with muramyl dipeptide (MDP) prior to TLR4 stimulation with LPS. MyD88 deficiency markedly inhibited RANKL expression after LPS stimulation and increased OPG messenger RNA (mRNA) production. Also, MyD88 was necessary for NF-κB and p38 MAPK activation. MDP alone did not induce RANKL and OPG expressions; however, when combined with LPS, their expressions were significantly increased (p < 0.05). Our results support that MyD88 signaling has a pivotal role in osteoclastogenesis thought NF-κB and p38 activation. Nod2 and especially Nod1 levels were influenced by MyD88.

Relevance of the Myeloid Differentiation Factor 88 (MyD88) on RANKL, OPG, and Nod Expressions Induced by TLR and IL-1R Signaling in Bone Marrow Stromal Cells

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Semi-supervised learning for relevance feedback on image retrieval tasks

Relevance feedback approaches have been established as an important tool for interactive search, enabling users to express their needs. However, in view of the growth of multimedia collections available, the user efforts required by these methods tend to increase as well, demanding approaches for reducing the need of user interactions. In this context, this paper proposes a semi-supervised learning algorithm for relevance feedback to be used in image retrieval tasks. The proposed semi-supervised algorithm aims at using both supervised and unsupervised approaches simultaneously. While a supervised step is performed using the information collected from the user feedback, an unsupervised step exploits the intrinsic dataset structure, which is represented in terms of ranked lists of images. Several experiments were conducted for different image retrieval tasks involving shape, color, and texture descriptors and different datasets. The proposed approach was also evaluated on multimodal retrieval tasks, considering visual and textual descriptors. Experimental results demonstrate the effectiveness of the proposed approach.

Cardiac remodeling induced by smoking: concepts, relevance, and potential mechanisms

Cardiac or ventricular remodeling is characterized by molecular, cellular, and interstitial alterations that lead to changes in heart size, mass, geometry and function in response to a given insult. Currently, tobacco smoke exposure is recognized as one of these insults. Indeed, tobacco smoke exposure induces the enlargement of the left-sided cardiac chambers, myocardial hypertrophy, and ventricular dysfunction. Potential mechanisms for these alterations include hemodynamic and neurohormonal changes, oxidative stress, inflammation, nitric oxide bioavailability, matrix metalloproteinases and mitogen-activated protein kinase activation. This review will focus on the concepts, relevance, and potential mechanisms of cardiac remodeling induced by tobacco smoke.