Mechanism-Driven Technology Development for Solving the Intracellular Delivery Problem of Hard-To-Transfect Cells.

The so-called "hard-to-transfect cells" are well-known to present great challenges to intracellular delivery, but detailed understandings of the delivery behaviors are lacking. Recently, we discovered that vesicle trapping is a likely bottleneck of delivery into a type of hard-to-transfect cells, namely, bone-marrow-derived mesenchymal stem cells (BMSCs). Driven by this insight, herein, we screened various vesicle trapping-reducing methods on BMSCs. Most of these methods failed in BMSCs, although they worked well in HeLa cells. In stark contrast, coating nanoparticles with a specific form of poly(disulfide) (called PDS1) nearly completely circumvented vesicle trapping in BMSCs, by direct cell membrane penetration mediated by thiol-disulfide exchange. Further, in BMSCs, PDS1-coated nanoparticles dramatically enhanced the transfection efficiency of plasmids of fluorescent proteins and substantially improved osteoblastic differentiation. In addition, mechanistic studies suggested that higher cholesterol content in plasma membranes of BMSCs might be a molecular-level reason for the greater difficulty of vesicle escape in BMSCs.

Food Fraud Vulnerability Assessment in the Chinese Baijiu Supply Chain.

As a representative of Chinese alcoholic drinks, baijiu has developed into a mass-consumption commodity. Its simple industrial chain makes it a suitable target for fraudsters. In order to understand the differences and potential factors of fraud vulnerability among groups at various levels, this study constructed a food fraud vulnerability assessment system for the Chinese baijiu supply chain based on routine activities theory. We examined the fraud vulnerability in the baijiu supply chain with data from 243 producers and 45 retailers by using the safe supply of affordable food everywhere (SSAFE) food fraud vulnerability assessment (FFVA) tool. The results indicate that fraud factors related to opportunities have an overall medium vulnerability, while those related to motivations and control measures have an overall medium-low vulnerability. In addition, there are significant differences in the perceived vulnerability of fraud factors across the supply chain. Moreover, retailers have overall higher fraud vulnerability in terms of opportunities and control measures than producers. The main reasons for the frequent occurrence of fraud in the baijiu industry are numerous technical opportunities, strong economic drivers, and insufficient control measures.

Drivers of Farmers' Intention to Use the Digital Agricultural Management System: Integrating Theory of Planned Behavior and Behavioral Economics.

China's fishery industry has national and international relevance whose aquaculture production accounts for more than 60 percent of the world's total aquaculture production. But the average amount of pesticides used per hectare in China is roughly five times of the world average. The abuse of chemical fertilizers and drugs has brought chronic, long-term, and cumulative harm to both human beings and environment. The digital agricultural management system should be adopted to reduce non-negligible environment pollution and the quality and safety risks of aquatic products. So, it is essential to understand the factors that may influence the adopting intention of this digital management approaches. The present study aimed to examine the adopting intention of farmers toward the digital agricultural management system using two theories-the theory of planned behavior (TPB) and the behavioral economics-as the research framework. The population was composed of farmers in the provinces of Guangdong province in south China of whom 219 farmers were sampled with stratified random sampling technique. Structural equation modeling was used to analyze the data, and it was revealed that this research framework could potentially predict intention. And we observed that the two biased belief of availability bias and loss aversion bias can be the main predictive influence factors of responsible behaviors in adopting the digital agriculture management system, which highlights the importance of framing recommendations in terms of losses rather than gain may be more effective to increase farmers' intention to adopt the digital system on their farms.