MDR1 is highly expressed in MDR A2780DX5 ovarian cancer cells, MDR SGC7901R gastric cancer cells and recurrent tumours. It pumps cytoplasmic agents out of cells, leading to decreased drug accumulation in cells and making cancer cells susceptible to multidrug resistance. Here, we identified that miR‐495 was predicted to target ABCB1, which encodes protein MDR1. To reduce the drug efflux and reverse MDR in cancer cells, we overexpressed a miR‐495 mimic in SGC7901R and A2780DX cells and in transplanted MDR ovarian tumours in vivo. The results indicated that the expression of MDR1 in the above cells or tumours was suppressed and that subsequently the drug accumulation in the MDR cells was decreased, cell death was increased, and tumour growth was inhibited after treatment with taxol‐doxorubicin, demonstrating increased drug sensitivity. This study suggests that pre‐treatment with miR‐495 before chemotherapy could improve the curative effect on MDR1‐based MDR cancer.

In order to improve the performance of the cladding layer, this study used the Taguchi orthogonal design to investigate the influence of laser power, scanning speed, gas flow, and SiC powder ratio on the micro-hardness and wear volume of the cladding layer. The results indicate that the SiC powder ratio was the major factor that had the main impact on the micro-hardness and wear volume of the cladding layer. The contribution of SiC powder ratio on the micro-hardness and wear volume are 92.08% and 79.39%, respectively. Through signal to noise ratio conversion and combining grey relational analysis, the multiple objectives optimization was attained. With the target of maximizing the micro-hardness and minimizing the wear volume simultaneously, grey relational analysis was applied to obtain the optimal processing parameters set and predict the corresponding grey relational grade. The error rate was 5.3% between the prediction and experimental validation. This study provides the guidance for optimizing multiple goals at the same time using grey relational analysis about the coating properties deposited by laser cladding in actual industrial applications. It provided theoretical basis for the processing parameters optimization with targeting the micro-hardness and wear resistance.

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The influence of processing parameters in laser engineered net shaping (LENS) on the properties of 316L stainless steel and titanium carbide (TiC) composite coating was studied. The key processing parameters were laser power, scanning speed, TiC powder ratio, and powder feed rate. Mathematical models were developed to investigate the micro-hardness, wear volume, and defect area of the coating. The accuracy of the models was examined by analysis of variance and experimental validation. Results showed that micro-hardness was positively correlated with TiC powder ratio. Increasing TiC powder ratio could reduce the wear volume. In addition, the wear volume displayed an increase then decrease with increasing laser power and decreasing scanning speed. Both scanning speed and TiC powder ratio showed a recognizable impact on the defect area. Reducing the scanning speed and TiC powder ratio can effectively reduce the defect area. The targets for the processing parameters optimization were set to maximize micro-hardness, minimize wear volume, and defect area. The difference between the model prediction value and experimental validation result for micro-hardness, wear volume, and defect area were 0.46%, 4.54%, and 8.82%, respectively. These results provide guidance for the LENS processing parameters optimization in controlling and predicting of 316L/TiC composite coating properties.

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