ALBERT

Description: Background. HER-2 is a key molecule serving as the therapeutic target, prognostic biomarker, and classification marker in breast cancer. Accurate microRNA profilings had not been conducted in purified tumor cells of HER-2-negative and HER-2-positive tissue specimens obtained from breast cancer patients. Methods. (i) Differential expression microRNA discovery using laser capture microdissection- (LCM-) assisted specimen preparation and microRNA array chips on HER-2 overexpressing and triple-negative breast carcinoma (TNBC) subtype tissues, (ii) differential expression microRNA validation by quantitative real-time PCR, and (iii) independent validation on tissue microarray. Results. Five microRNAs (miR-20a-5p, miR-221-3p, miR-362-5p, miR-502-3p, and miR-222-3p) were screened and validated as upregulated microRNAs in TNBC cells comparing to HER-2 overexpressing cells using a microRNA array (5 cases in each group) and quantitative real-time PCR (20 cases in each group). The expression difference of miR-362-5p had the most significant statistical significance (p=0.0016) among the five microRNAs. The expression of miR-362-5p and its target gene Sema3A was further analyzed using in situ hybridization (ISH) and immunohistochemistry on standard tissue sections (n=150). 70.8% of HER-2-negative cells showed moderate expression of miR-362-5p whereas 20.4% HER-2-negative cells correlated with strong expression of miR-362-5p (p

Description: Tool geometric parameters have a huge impact on tool wear. Up to now, there are only a few researches on tool geometric parameters and optimization, and the single objective function of parameter optimization used by researchers during high-speed machining (HSM) mainly is the minimum cutting force. However, the elevated cutting temperature also greatly affects tool wear due to the numerous cutting heat generation. Thus, to reduce tool wear, it is the most fundamental approach to taking into account the comprehensive control of the cutting force and cutting temperature because they are the two most important physical quantities in metal cutting processes. This work proposes a new optimization idea of the cutting-tool’s multi geometric parameters (three main parameters: rake angle, clearance angle, and cutting edge radius) with two objective functions (the cutting force and the temperature). Based on the response surface method (RSM), we have established the modified functional relation models of the influence of tool geometric parameters on the cutting force and temperature according to the finite element simulation results in high-speed cutting of Ti6Al4V. Then the models are solved by using a genetic algorithm, and the optimal tool geometric parameters values that can concurrently control the two objectives in their minimum values are obtained. The advantages lie in the strategy of the separate models of the cutting force and cutting temperature owing to their different dimensions and the solution of the models through giving the cutting force and cutting temperature different weight coefficients. The optimal results are verified by experiments, which shows that the optimal tool geometric parameters are very effective and vital for ensuring both the cutting force and the cutting temperature not too high. This work is of great significance to the cutting tool design theory and its manufacturing for reducing tool wear.