Central role of Prominin-1 in lipid rafts during liver regeneration.

Prominin-1, a lipid raft protein, is required for maintaining cancer stem cell properties in hepatocarcinoma cell lines, but its physiological roles in the liver have not been well studied. Here, we investigate the role of Prominin-1 in lipid rafts during liver regeneration and show that expression of Prominin-1 increases after 2/3 partial hepatectomy or CCl4 injection. Hepatocyte proliferation and liver regeneration are attenuated in liver-specific Prominin-1 knockout mice compared to wild-type mice. Detailed mechanistic studies reveal that Prominin-1 interacts with the interleukin-6 signal transducer glycoprotein 130, confining it to lipid rafts so that STAT3 signaling by IL-6 is effectively activated. The overexpression of the glycosylphosphatidylinsositol-anchored first extracellular domain of Prominin-1, which is the domain that binds to GP130, rescued the proliferation of hepatocytes and liver regeneration in liver-specific Prominin-1 knockout mice. In summary, Prominin-1 is upregulated in hepatocytes during liver regeneration where it recruits GP130 into lipid rafts and activates the IL6-GP130-STAT3 axis, suggesting that Prominin-1 might be a promising target for therapeutic applications in liver transplantation.

Combined effect of bisphosphonate and recombinant human bone morphogenetic protein 2 on bone healing of rat calvarial defects.

BACKGROUND: This study aimed to investigate new bone formation using recombinant human bone morphogenetic protein 2 (rhBMP-2) and locally applied bisphosphonate in rat calvarial defects. METHODS: Thirty-six rats were studied. Two circular 5 mm diameter bony defect were formed in the calvaria using a trephine bur. The bony defect were grafted with Bio-Oss® only (group 1, n = 9), Bio-Oss® wetted with rhBMP-2 (group 2, n = 9), Bio-Oss® wetted with rhBMP-2 and 1 mM alendronate (group 3, n = 9) and Bio-Oss® wetted with rhBMP-2 and 10 mM alendronate (group 4, n = 9). In each group, three animals were euthanized at 2, 4 and 8 weeks after surgery, respectively. The specimens were then analyzed by histology, histomorphometry and immunohistochemistry analysis. RESULTS: There were significant decrease of bone formation area (p < 0.05) between group 4 and group 2, 3. Group 3 showed increase of new bone formation compared to group 2. In immunohistochemistry, collagen type I and osteoprotegerin (OPG) didn't show any difference. However, receptor activator of nuclear factor κB ligand (RANKL) decreased with time dependent except group 4. CONCLUSION: Low concentration bisphosphonate and rhBMP-2 have synergic effect on bone regeneration and this is result from the decreased activity of RANKL of osteoblast.

Decrease of the electroacupuncture-induced analgesic effects in nuclear factor-kappa B1 knockout mice.

To investigate the involvement of nuclear factor kappa B1 (NF-kappaB1; p50/p105) in electroacupuncture (EA)-induced analgesia, 2 and 100 Hz EA stimulations were applied at acupoint ST36 (Zusanli) in NF-kappaB1 knockout mice. EA was performed for 30 min and tail-flick latencies (TFLs) were evaluated every 15 min for 1 h. Wild-type mice displayed a 63.3% increase in TFLs compared to baseline after 2 Hz EA, whereas NF-kappaB1+/- mice exhibited a 41.8% increase and NF-kappaB1-/- mice showed only a 3.9% increase of TFLs. The TFLs of 100 Hz EA showed similar trends: a 72.6% increase of TFLs in wild-type, a 38.6% increase in NF-kappaB1+/- and a 9.3% increase in NF-kappaB1-/- mice. The present findings suggest that NF-kappaB1 may play a crucial role in both low and high frequency EA-induced analgesic effects.

Resolving the initial contour problem of GVF snake in the sequential images.

GVF algorithm has been studied actively and it will be able to apply to quite many applications. This paper presents GVF algorithm for the segmentation of a sequence of images. Traditional GVF algorithm can extract contour of object in an image. However, in the video sequence images or CT images traditional GVF algorithm had some problems. We can treat these problems under motion tracking using Motion Estimation using Mean Square Error (MSE). Initial point problem is very important in GVF algorithm. We applied extracted initial point of first image to the second image. In other word, previous initial contour can be used to the next initial contour.