Summary Chromolaena odorata is one of the world's worst tropical weeds, and it can be found in Guangdong, Guangxi, Hainan and Yunnan provinces in China. Genetic variation of 27 C. odorata populations sampled from across its invasive range in China was investigated using inter‐simple sequence repeats (ISSR) analysis. All populations exhibited low levels of genetic variation. On average, 2.35% of the ISSR loci were polymorphic, total genetic diversity (HT) was 0.0406 and Shannon's information index (Hsp) was 0.0623. High genetic identities (I) between populations (0.9687 ± 0.01204) indicated low genetic differentiation. A frequent founder effect was interpreted as the main cause of the genetic structure observed in C. odorata.

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Research on quantitatively controlling the ligand density on the surface of nanocarriers is in the frontier and becomes a technical difficulty for targeted delivery system designing. In this study, we developed an improved pre-conjugation (Imp) strategy, in which herceptin as a ligand was pre-conjugated with DSPE-PEG2000-Mal via chemical cross-linking, followed by conjugation onto the surface of pre-prepared paclitaxel-loaded PLGA/DODMA nanoparticles (PDNs) through hydrophobic interaction and electrostatic attraction for paclitaxel delivery. Compared with the post-conjugation (Pos) strategy, in which the ligand was conjugated onto the nanoparticle surface after the preparation of the nanoparticles, it realized a precise control targeting effect via adjustment of the herceptin density on the surface of the nanoparticles. Within the range of 0-20% of DSPE-PEG2000-herceptin in the blend, it showed a linear relation with the ligand density on the surface of the nanoparticles. The Imp strategy protected the bioactivity of the ligand during the preparation of nanoparticles. At the same time it avoided the waste of an excess amount of herceptin to drive the conjugation reaction in comparison with the post-conjugation (Pos) strategy. The nanoparticles from the Imp strategy showed much better cytotoxicity (p< 0.001), tumor targeting and cellular uptake efficiency (p < 0.001) than that of the other strategies in BT474 cells, in which BT474 cells were HER2 receptor over-expression breast cancer cell lines. A significant reduction in cellular uptake of the nanoparticles from the Imp strategy was observed in the presence of sucrose and cytochalasin D, indicating that clathrin-mediated and caveolae-dependent endocytosis was as a primary mechanism of cellular entry for these antibody-modified nanoparticles.

Electrical capacitance tomography (ECT) is an attractive visualization measurement method, in which the acquisition of high-quality images is beneficial for the understanding of the underlying physical or chemical mechanisms of the dynamic behaviors of the measurement objects. In real-world measurement environments, imaging objects are often in a dynamic process, and the exploitation of the spatial-temporal correlations related to the dynamic nature will contribute to improving the imaging quality. Different from existing imaging methods that are often used in ECT measurements, in this paper a dynamic image sequence is stacked into a third-order tensor that consists of a low rank tensor and a sparse tensor within the framework of the multiple measurement vectors model and the multi-way data analysis method. The low rank tensor models the similar spatial distribution information among frames, which is slowly changing over time, and the sparse tensor captures the perturbations or differences introduced in each frame, which is rapidly changing over time. With the assistance of the Tikhonov regularization theory and the tensor-based multi-way data analysis method, a new cost function, with the considerations of the multi-frames measurement data, the dynamic evolution information of a time-varying imaging object and the characteristics of the low rank tensor and the sparse tensor, is proposed to convert the imaging task in the ECT measurement into a reconstruction problem of a third-order image tensor. An effective algorithm is developed to search for the optimal solution of the proposed cost function, and the images are reconstructed via a batching pattern. The feasibility and effectiveness of the developed reconstruction method are numerically validated.

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