Cell‐based immunotherapy, for example, chimeric antigen receptor T (CAR‐T) cell immunotherapy, has revolutionized cancer treatment, particularly for blood cancers. However, factors such as insufficient T cell tracking, tumour heterogeneity, inhibitory tumour microenvironment (TME) and T cell exhaustion limit the broad application of CAR‐based immunotherapy for solid tumours. In particular, the TME is a complex and evolving entity, which is composed of cells of different types (e.g., cancer cells, immune cells and stromal cells), vasculature, soluble factors and extracellular matrix (ECM), with each component playing a critical role in CAR‐T immunotherapy. Thus, developing approaches to mitigate the inhibitory TME factors is critical for future success in applying CAR‐T cells for solid tumour treatment. Accordingly, understanding the bilateral interaction of CAR‐T cells with the TME is in pressing need to pave the way for more efficient therapeutics. In the following review, we will discuss TME‐associated aspects with an emphasis on T cell trafficking, ECM barriers, abnormal vasculature, solid tumour heterogenicity and immune suppressive microenvironment. We will then summarize current engineering strategies to overcome the challenges posed by the TME‐associated factors. Lastly, the future directions for engineering efficient CAR‐T cells for solid tumour therapy will be discussed.

Abstract. This essay legally restrains the illegal content based on the e-commerce directive and introduces that the European countries detect and notify illegal content through the instructions of competent authorities, notification of credible flaggers, user reports and technical tools. The illegal content should be deleted through the service terms and transparency report basing on prevent excessive deletions system. At the same time, use filters to detect and filter to against the recurrence of illegal content. By analyzing the advantages of China under the environment of cracking down on illegal content, this essay concludes that the success of China in cracking down on illegal content lies in all-round collaborative management model of countries, governments, enterprises and individuals. At the end of the essay, one is to build a training corpus that can automatically update the ability to identify the illegal content. And it proposes an optimization scheme that establish a complete set of address resolution procedures and classify IP address data according to big data analysis and DNS protection module to prevent hackers from spreading illegal content by tampering with DNS segments.

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Regarding the practicality of the quality evaluation model, the lack of quantitative experimental evaluation affects the effective use of the quality model, and also a lack of effective guidance for choosing the model. Aiming at this problem, based on the sensitivity of the quality evaluation model to code defects, a machine learningbased quality evaluation attribute validity verification method is proposed. This method conducts comparative experiments by controlling variables. First, extract the basic metric elements; then, convert them into quality attributes of the software; finally, to verify the quality evaluation model and the effectiveness of medium quality attributes, this paper compares machine learning methods based on quality attributes with those based on text features, and conducts experimental evaluation in two data sets. The result shows that the effectiveness of quality attributes under control variables is better, and leads by 15% in AdaBoostClassifier; when the text feature extraction method is increased to 50 -150 dimensions, the performance of the text feature in the four machine learning algorithms overtakes the quality attributes; but when the peak is reached, quality attributes are more stable. This also provides a direction for the optimization of the quality model and the use of quality assessment in different situations.