Multiple inherent molecular interactions of natural polyphenols enable the assembly of quaternary ordered superstructures.

Groutability determination is a very important task in grouting quality control. There is little research on the groutability of cement-based grout in a fractured rock mass, and the prediction is hampered by a small number of samples along with multidimensional and nonlinear problems. This study proposes an intelligent predictive model that integrates hybrid grey wolf optimization (HGWO) and a support vector machine (SVM) to predict the groutability. The model was built in three steps: HGWO was embedded in a SVM to search for the best hyperparameters ($C$ , $g$ ); crossvalidation and error analysis were introduced into the HGWO-SVM model to ensure the generalization performance and prediction accuracy; and the classification and regression prediction of groutability with cement-based grout in a fractured rock mass were predicted by the established HGWO-SVM intelligent prediction method. Taking a curtain grouting project as a case, the applicability of the method was verified. The performance of the proposed prediction model is improved compared with other methods, and the prediction accuracy meets engineering needs. The results show that this method can accurately and conveniently predict the groutability of cement-based grout in a fractured rock mass and provide practical assistance to field projects.

Extracellular vesicles (EVs) are important cell-to-cell communication mediators. This paper focuses on the regulatory role of tumor-derived EVs on macrophages. It aims to investigate the causes of tumor progression and therapeutic directions. Tumor-derived EVs can cause macrophages to shift to M1 or M2 phenotypes. This indicates they can alter the M1/M2 cell ratio and have pro-tumor and anti-inflammatory effects. This paper discusses several key points: first, the factors that stimulate macrophage polarization and the cytokines released as a result; second, an overview of EVs and the methods used to isolate them; third, how EVs from various cancer cell sources, such as hepatocellular carcinoma, colorectal carcinoma, lung carcinoma, breast carcinoma, and glioblastoma cell sources carcinoma, promote tumor development by inducing M2 polarization in macrophages; and fourth, how EVs from breast carcinoma, pancreatic carcinoma, lungs carcinoma, and glioblastoma cell sources carcinoma also contribute to tumor development by promoting M2 polarization in macrophages. Modified or sourced EVs from breast, pancreatic, and colorectal cancer can repolarize M2 to M1 macrophages. This exhibits anti-tumor activities and offers novel approaches for tumor treatment. Therefore, we discovered that macrophage polarization to either M1 or M2 phenotypes can regulate tumor development. This is based on the description of altering macrophage phenotypes by vesicle contents.