In vitro suppression of the MMP-3 gene in normal and cytokine-treated human chondrosarcoma using small interfering RNA

<p>Abstract</p> <p>Background</p> <p>Matrix metalloproteinase (MMPs) synthesized and secreted from connective tissue cells have been thought to participate in degradation of the extracellular matrix. Increased MMPs activities that degrade proteoglycans have been measured in osteoarthritis cartilage. This study aims to suppress the expression of the <it>MMP-3 </it>gene in <it>in vitro </it>human chondrosarcoma using siRNA.</p> <p>Methods</p> <p>Cells were categorized into four groups: control (G.1); transfection solution treated (G.2); negative control siRNA treated (G.3); and <it>MMP-3 </it>siRNA treated (G.4). All four groups were further subdivided into two groups - treated and non-treated with IL-1β- following culture for 48 and 72 h. We observed the effects of gene suppression according to cell morphology, glycosaminoglycan (GAG) and hyaluronan (HA) production, and gene expression by using real-time polymerase chain reaction (PCR).</p> <p>Results</p> <p>In IL-1β treated cells the apoptosis rate in G.4 was found to be lower than in all other groups, while viability and mitotic rate were higher than in all other groups (<it>p </it>< 0.05). The production of GAG and HA in G.4 was significantly higher than the control group (<it>p </it>< 0.05). <it>MMP-3 </it>gene expression was downregulated significantly (<it>p </it>< 0.05).</p> <p>Conclusion</p> <p><it>MMP-3 </it>specific siRNA can inhibit the expression of <it>MMP-3 </it>in chondrosarcoma. This suggests that <it>MMP-3 </it>siRNA has the potential to be a useful preventive and therapeutic agent for osteoarthritis.</p

A posteriori error estimates for the virtual element method

An a posteriori error analysis for the virtual element method (VEM) applied to general elliptic problems is presented. The resulting error estimator is of residual-type and applies on very general polygonal/polyhedral meshes. The estimator is fully computable as it relies only on quantities available from the VEM solution, namely its degrees of freedom and element-wise polynomial projection. Upper and lower bounds of the error estimator with respect to the VEM approximation error are proven. The error estimator is used to drive adaptive mesh refinement in a number of test problems. Mesh adaptation is particularly simple to implement since elements with consecutive co-planar edges/faces are allowed and, therefore, locally adapted meshes do not require any local mesh post-processing

Damped Response of a Cantilever Sensor Embedded in Passive Muscle under Impact

在生活中，容易因為外物的碰撞使得體內之微懸臂梁感測器的量測失準。為了排除因撞擊而產生的位移量，並準確地偵測CRP蛋白質濃度，我們從文獻中蒐集生物軟組織(皮膚、肌肉)的單軸拉伸實驗曲線和鬆弛試驗曲線，並以曲線擬合的方式擬合出超彈性(hyperelastic) (以Ogden form表示)和黏彈性(viscoelastic)(以Prony級數表示)的材料常數。 　　在計算微懸臂梁的位移量時會因為充斥感測器內的液體(即血液)產生的剪力和正向壓力，使得梁不會很迅速地回到原來的位置，而類似於阻尼的效果。其間的過程在於固液耦合的物理現象，在每個時間點固體結構的變形和液體的流速互相影響。經由有限元素法的分析，可以得到微懸臂梁上產生最大位移的地方(梁末端)衰減所需要的時間。梁末端位移衰減至因衝擊造成最大位移的10%所需要的時間，經由二維以及三維分析得到的結果分別為11.5秒和6.2秒。目錄 摘要 i 目錄 ii 圖目錄 v 表目錄 viii 第一章、導論 1 1.1、研究動機 1 1.2、文獻回顧 2 1.3、研究方法 8 1.4、論文架構 10 第二章、理論與數值方法 11 2.1、黏彈性之本構律(viscoelasticity) 11 2.1.1、積分形式的應力應變關係 11 2.1.2、微分形式的應力應變關係 15 2.1.3、模型理論 16 2.2、大應變時的本構關係(超彈性(hyperelastic)) 20 2.3、幾何非線性(大變形之情況) 21 2.3.1、大變形下的應變 22 2.3.2、大變形下的應力 23 2.4、流場統御域方程式 24 2.5、懸臂梁變形理論 25 第三章、模擬結果與分析(2D) 27 3.1、第一階段 28 3.1.1、建立模型 28 3.1.2、網格生成 28 3.1.3、材料屬性 29 3.1.4、邊界條件和接觸條件 34 3.1.5、模擬結果 35 3.1.6、結果分析 39 3.2、第二階段 41 3.2.1、建立模型 41 3.2.2、網格生成 42 3.2.3、材料屬性 42 3.2.4、邊界條件 43 3.2.5、求解與數值結果 43 3.2.6、結果分析 47 3.3、不同位置下的變形情況 52 3.3.1、第一階段 52 3.3.2、第二階段 54 3.3.3、結果分析 55 第四章、模擬結果與分析(3D) 56 4.1、第一階段 56 4.1.1、模型建立 56 4.1.2、網格生成 57 4.1.3、材料屬性 57 4.1.4、邊界條件 57 4.1.5、模擬結果 58 4.1.6、結果分析 60 4.2、第二階段 61 4.2.1、模型建立 61 4.2.2、網格生成、材料屬性、邊界條件 61 4.2.3、模擬結果 61 4.2.4、結果分析 62 第五章、結論與未來展望 64 5.1、結論 64 5.2、未來展望 65 參考文獻 66 附錄A、數值模擬中使用的材料參數 6

Primer of adaptive finite element methods

Adaptive finite element methods (AFEM) are a fundamental numerical instrument in science and engineering to approximate partial differential equations. In the 1980s and 1990s a great deal of effort was devoted to the design of a posteriori error estimators, following the pioneering work of Babuska. These are computable quantities, depending on the discrete solution(s) and data, that can be used to assess the approximation quality and improve it adaptively. Despite their practical success, adaptive processes have been shown to converge, and to exhibit optimal cardinality, only recently for dimension d > 1 and for linear elliptic PDE. These series of lectures presents an up-to-date discussion of AFEM encompassing the derivation of upper and lower a posteriori error bounds for residual-type estimators, including a critical look at the role of oscillation, the design of AFEM and its basic properties, as well as a complete discussion of convergence, contraction property and quasi-optimal cardinality of AFEM