Background and purpose:The MEG3 gene is a imprinted gene, whose loss may be associated with the pathogenesis and progression of several tumor types. This study was done to investigate the transcription of MEG3 mRNA in human mammary cancer cell line MCF7 and cell proliferation, in order to explore the effect of the methylation inhibitor, 5-aza-2'-deoxycytidine (5-aza-CdR) on MEG3 gene expression and proliferation in MCF7. Methods:MCF7 was treated with 5 ?mol/L 5-aza-CdR for 2, 4, 6 days, then the alteration of MEG3 gene expression was detected by RT-PCR and Northern blot technology and the proliferation difference in cell growth of MCF7 was observed by MTT. Results:After treated with 5-aza-CdR, the transcription of MEG3 mRNA in MCF7 was increased and the growth of MCF7 was reduced. MCF7 was treated with 5 ?mol/L 5-aza-CdR for 2, 4, 6 days, the inhibitory rates were (23.16?3.93), (49.39?2.38), (64.73?2.24), there were signifi cant differences between them. Conclusion:The growth of MCF7 was possibly inhibited by MEG3 gene, and the downregulation of MEG3 gene might result from the methylation, which was involved in the mammary cancer pathogenesis.

Sixty-two patients with type 2 diabetes were treated with acarbose combined intensive insulin therapy( combined intensive group)or intensive insulin therapy alone (simple intensive group).As the blood glucose control reached the target,the mean amplitude of glycaemic excursion (MAGE),the absolute difference between the mean of daily differences ( MODD ),and standard deviation of blood glucose (SDBG) in combined intensive group were lower than those in simple intensive group [ ( 3.76 ± 1.47 vs 6.52 ± 1.57 ) mmol/L,( 0.57 ±0.49 vs 1.10 ±0.69 )mmol/L,( 1.44±0.60 vs 2.42±0.92 ) mmol/L,all P＜0.01 ].Daily mean blood glucose (MBG) of the former group was better than that of the latter group [ (7.08±0.69 vs 8.27 ± 1.31 ) mmol/L,P＜0.01 ].By the end of treatment,HbA1c [ 6.77％ ± 0.57％ vs 7.21％ ±0.83％,P＜0.05 ],incidence of hypoglycemia( 29％ vs 48％,P＜0.01 ),and body mass index[ (24.14±2.7 vs 27.63±3.41 ) kg/m2,P＜0.01 ] in combined intensive group were statistically improved more than those in the simple intensive group.

Magnetic resonance imaging (MRI) simulator (MRI-Sim) can provide superior images for radiotherapy.Due to the complexity of MRI technology and the safety problem caused by strong magnetic field, the acquisition and implementation of MRI simulation is more complicated than CT simulation.In order to ensure the introduction of MRI-Sim, this paper reviews the selection, installation, and acceptance test of MRI-Sim, including the selection of host and auxiliary equipment, installation site preparation, and safety precautions,as well as MRI-Sim acceptance test and commissioning.

Objective We propose a low-dose CT reconstruction method using partial differential equation (PDE) denoising under high-dimensional constraints. Methods The projection data were mapped into a high-dimensional space to construct a high-dimensional representation of the data, which were updated by moving the points in the high-dimensional space. The data were denoised using partial differential equations and the CT image was reconstructed using the FBP algorithm. Results Compared with those by FBP, PWLS-QM and TGV-WLS methods, the relative root mean square error of the Shepp-Logan image reconstructed by the proposed method were reduced by 68.87％, 50.15％ and 27.36％, the structural similarity values were increased by 23.50％, 8.83％ and 1.62％, and the feature similarity values were increased by 17.30％, 2.71％ and 2.82％, respectively. For clinical image reconstruction, the proposed method, as compared with FBP, PWLS-QM and TGV-WLS methods, resulted in reduction of the relative root mean square error by 42.09％, 31.04％and 21.93％, increased the structural similarity values by 18.33％, 13.45％ and 4.63％, and increased the feature similarity values by 3.13％, 1.46％ and 1.10％, respectively. Conclusion The new method can effectively reduce the streak artifacts and noises while maintaining the spatial resolution in reconstructed low-dose CT images.

Objective We propose a low-dose CT reconstruction method using partial differential equation (PDE) denoising under high-dimensional constraints. Methods The projection data were mapped into a high-dimensional space to construct a high-dimensional representation of the data, which were updated by moving the points in the high-dimensional space. The data were denoised using partial differential equations and the CT image was reconstructed using the FBP algorithm. Results Compared with those by FBP, PWLS-QM and TGV-WLS methods, the relative root mean square error of the Shepp-Logan image reconstructed by the proposed method were reduced by 68.87％, 50.15％ and 27.36％, the structural similarity values were increased by 23.50％, 8.83％ and 1.62％, and the feature similarity values were increased by 17.30％, 2.71％ and 2.82％, respectively. For clinical image reconstruction, the proposed method, as compared with FBP, PWLS-QM and TGV-WLS methods, resulted in reduction of the relative root mean square error by 42.09％, 31.04％and 21.93％, increased the structural similarity values by 18.33％, 13.45％ and 4.63％, and increased the feature similarity values by 3.13％, 1.46％ and 1.10％, respectively. Conclusion The new method can effectively reduce the streak artifacts and noises while maintaining the spatial resolution in reconstructed low-dose CT images.