PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-3 (3)
 

Clipboard (0)
None
Journals
Authors
more »
Year of Publication
Document Types
1.  Glucose Restriction Inhibits Skeletal Myoblast Differentiation by Activating SIRT1 through AMPK-Mediated Regulation of Nampt 
Developmental cell  2008;14(5):661-673.
SUMMARY
It is intuitive to speculate that nutrient availability may influence differentiation of mammalian cells. Nonetheless, a comprehensive complement of the molecular determinants involved in this process has not been elucidated yet. Here, we have investigated how nutrients (glucose) affect skeletal myogenesis. Glucose restriction (GR) impaired differentiation of skeletal myoblasts and was associated with activation of the AMP-activated protein kinase (AMPK). Activated AMPK was required to promote GR-induced transcription of the NAD+ biosynthetic enzyme Nampt. Indeed, GR augmented the Nampt activity, which consequently modified the intracellular [NAD+]/[NADH] ratio and nicotinamide levels, and mediated inhibition of skeletal myogenesis. Skeletal myoblasts derived from SIRT1+/− heterozygous mice were resistant to the effects of either GR or AMPK activation. These experiments reveal that AMPK, Nampt, and SIRT1 are the molecular components of a functional signaling pathway that allows skeletal muscle cells to sense and react to nutrient availability.
doi:10.1016/j.devcel.2008.02.004
PMCID: PMC2431467  PMID: 18477450
2.  Aberrant Expression of ID2 protein and its correlation with EBV-LMP1 and P16(INK4A) in Classical Hodgkin Lymphoma in China 
BMC Cancer  2008;8:379.
Background
The relationships between the expression of ID2, EBV-LMP1 and P16(INK4A) in Chinese classical Hodgkin lymphoma are unknown and need exploring.
Methods
Samples of classical Hodgkin lymphoma from 60 Chinese patients were analyzed for the expression of ID2, EBV-LMP1 and p16(INK4A) proteins by immunohistochemistry.
Results
ID2 protein was expressed in 83.3% of this group of classical Hodgkin lymphoma, staining strongly in both cytoplasm and nucleus of the Hodgkin and Reed-Sternberg (HRS) cells. EBV-LMP1 and P16(INK4A) were overexpressed in 85.0% and 71.7% of Hodgkin lymphoma, respectively. EBV-LMP1 was noted in the cytoplasm, membrane and nucleus of HRS cells; P16(INK4A) was in the nucleus and cytoplasm. Microscopically, ID2, EBV-LMP1 and P16(INK4A) staining distinguished the HRS cells from the complex background of lymphocytes. ID2 was positively correlated with EBV-LMP1(P < 0.01), but P16(INK4A) was inversely related to EBV-LMP1 (P < 0.05).
Conclusion
It is suggested that ID2, EBV-LMP1 and P16(INK4A) could play an important role in the evolution of classical Hodgkin lymphoma, and be considered as potential adjunct markers to identify HRS cells in diagnosis.
doi:10.1186/1471-2407-8-379
PMCID: PMC2625365  PMID: 19099554
3.  Motif-directed network component analysis for regulatory network inference 
BMC Bioinformatics  2008;9(Suppl 1):S21.
Background
Network Component Analysis (NCA) has shown its effectiveness in discovering regulators and inferring transcription factor activities (TFAs) when both microarray data and ChIP-on-chip data are available. However, a NCA scheme is not applicable to many biological studies due to limited topology information available, such as lack of ChIP-on-chip data. We propose a new approach, motif-directed NCA (mNCA), to integrate motif information and gene expression data to infer regulatory networks.
Results
We develop motif-directed NCA (mNCA) to incorporate motif information into NCA for regulatory network inference. While motif information is readily available from knowledge databases, it is a "noisy" source of network topology information consisting of many false positives. To overcome this problem, we develop a stability analysis procedure embedded in mNCA to resolve the inconsistency between motif information and gene expression data, and to enable the identification of stable TFAs. The mNCA approach has been applied to a time course microarray data set of muscle regeneration. The experimental results show that the inferred TFAs are not only numerically stable but also biologically relevant to muscle differentiation process. In particular, several inferred TFAs like those of MyoD, myogenin and YY1 are well supported by biological experiments.
Conclusion
A novel computational approach, mNCA, has been developed to integrate motif information and gene expression data for regulatory network reconstruction. Specifically, motif analysis is used to obtain initial network topology, and stability analysis is developed and applied with mNCA to extract stable TFAs. Experimental results on muscle regeneration microarray data have demonstrated that mNCA is a practical and reliable computational method for regulatory network inference and pathway discovery.
doi:10.1186/1471-2105-9-S1-S21
PMCID: PMC2259422  PMID: 18315853

Results 1-3 (3)