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Litopenaeus vannamei easily blackens during cold storage. To inhibit blackening and improve the storage quality of prawns, in this study, konjac glucomman (KGM)-epigallocatechin gallate (EGCG) topological microgel was formed and used for storage and preservation of prawns to improve their antioxidant properties. The effect of KGM-EGCG topological microgel on inhibiting shrimp blackening was studied by measuring the sensory evaluation score, pH value, TVB-N value, K value, PPO activity, and the effect of changes in the total number of bacteria of KGM-EGCG-treated prawns during storage. SEM and FTIR results showed that during the KGM-EGCG binding process, the number of hydrogen bond connections and the intermolecular force increased. Results also showed that the KGM microgel can effectively embed EGCG and enhance its stability to achieve a better controlled release effect. Compared with the EGCG group and untreated group, KGM-EGCG microgel has better anti-PPO activity and can better maintain the organoleptic quality and inhibit bacterial growth of Litopenaeus vannamei. Therefore, the KGM-EGCG microgel could slow down the increase in pH value, the production of volatile base nitrogen, and the increase in K value, and effectively extend the shelf life of Litopenaeus vannamei from 3 d to 6 d, providing a theoretical basis for the research of KGM functional gel and a reference for the deep processing and value enhancement of green tea and shrimp. [ABSTRACT FROM AUTHOR]

Spatial prediction is essential for obtaining the spatial distribution of geographic variables and selecting appropriate covariates for this process can be challenging, especially for non-expert users. For easing the burden of selecting the appropriate covariates, two case-based reasoning strategies, namely the most-similar-case and covariate-classification strategies, have been proposed for automated covariate selection. The former may suggest nonessential covariates due to its case-level reasoning way. And the latter with covariate-level reasoning may overlook related covariates and recommend fewer covariates than the case-level reasoning. In this study, we propose a new strategy of integrating case-level and covariate-level reasoning to effectively leverage the strengths of both previous strategies while also addressing their limitations. The proposed strategy is validated through a case study of automatically selecting covariates for digital soil mapping under reasoning with a case base containing 189 cases. The leave-one-out evaluation demonstrated that our proposed strategy outperformed the previous two strategies. [ABSTRACT FROM AUTHOR]

Existing GIS software mainly target at expert users and do not sufficiently integrate resources for efficient computing. They are difficult for non-experts to use and are often slow in completing the complicated geographic analysis. To address these problems, future generation of GIS software must be 'easy'. By 'easy' we mean 'easy to use' and 'easy to compute'. 'Easy to use' means that software system should be goal-oriented, rather than the currently procedure-oriented doctrine. The goal-oriented will relieve users, particularly novice users, the burden of knowing the exact commands and their sequences to perform for achieving the goal they want to achieve. 'Easy to compute' means that implementation of GIS analytical functionality should be able to utilize the high-performance computing infrastructures for complicated geographic analysis. Two case studies, one in digital soil mapping and the other in digital terrain analysis, are presented to illustrate the meaning of 'easy'. We believe that the future generations of GIS platforms should be goal-driven, intelligent, high-performance computing enabled, easily accessible, and participatory. It allows anyone to participate in geo-computation at anywhere and anytime. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer but has shown limited success to date in the treatment of advanced stage. Recruitment of T cells for cancer treatment is a rapidly growing strategy in immunotherapy such as chimeric antigen receptor T cells and bispecific antibodies. However, unwanted aggregations, structural instability or short serum half-life are major challenges of bispecific antibodies. Here, we developed a new format of T cell-redirecting antibody that is bispecific for membrane proteoglycans GPC3 of HCC and the T-cell-specific antigen CD3, which demonstrated to be favorable stability and productivity. Cross-linking of T cells with GPC3 positive tumor cells by the anti-GPC3/CD3 bispecific antibody-mediated potent GPC3-dependent and concentration-dependent cytotoxicity in vitro. Administration of the bispecific antibody with different concentrations in murine xenograft models of human HCC significantly inhibited tumor growth. In addition, no effects on tumor growth were observed in the absence of human effector cells or the bispecific antibody. Taken together, the anti-GPC3/CD3 bispecific antibody might be a potential therapeutic treatment for HCC. [ABSTRACT FROM AUTHOR]