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T B Tang

Publications and source records attributed to T B Tang.

2 recordsLinked to original sources

N-3 fatty acids inhibit vascular calcification via the p38-mitogen-activated protein kinase and peroxisome proliferator-activated receptor-gamma pathways.

Fish oil supplementation is associated with lower risk of coronary artery disease in humans, and it has been shown to reduce ectopic calcification in an animal model. However, whether N-3 fatty acids, active ingredients of fish oil, have direct effects on calcification of vascular cells is not clear. In this report, we investigated the effects of eicosapentaenoic acid and docosahexaenoic acid (DHA) on osteoblastic differentiation and mineralization of calcifying vascular cells (CVCs), a subpopulation of bovine aortic medial cells that undergo osteoblastic differentiation and form calcified matrix in vitro. Results showed that N-3 fatty acids inhibited alkaline phosphatase (ALP) activity and mineralization of vascular cells, suggesting that they directly affect osteoblastic differentiation in vascular cells. By Western blot analysis, DHA activated p38-mitogen-activated protein kinase (MAPK) but not extracellular-regulated kinase (ERK) or Akt. An inhibitor of p38-MAPK partially reversed the inhibitory effects of DHA on osteoblastic differentiation and mineralization. Transient transfection experiments showed that DHA also activated peroxisome proliferator-activated receptor-gamma (PPAR-gamma). Both p38-MAPK activator and PPAR-gamma agonists reproduced the inhibitory effects of DHA on CVC mineralization. Pretreatment with DHA also inhibited interleukin-6-induced ALP activity and mineralization. Together, these results suggest that N-3 fatty acids directly inhibit vascular calcification, and that the inhibitory effects are mediated by the p38-MAPK and PPAR-gamma pathways.

Animals↗

Adaptive, integrated sensor processing to compensate for drift and uncertainty: a stochastic 'neural' approach.

An adaptive stochastic classifier based on a simple, novel neural architecture--the Continuous Restricted Boltzmann Machine (CRBM) is demonstrated. Together with sensors and signal conditioning circuits, the classifier is capable of measuring and classifying (with high accuracy) the H+ ion concentration, in the presence of both random noise and sensor drift. Training on-line, the stochastic classifier is able to overcome significant drift of real incomplete sensor data dynamically. As analogue hardware, this signal-level sensor fusion scheme is therefore suitable for real-time analysis in a miniaturised multisensor microsystem such as a Lab-in-a-Pill (LIAP).

Journal Article↗