Construction of rice supply chain supervision model driven by blockchain smart contract.

The outbreak of the COVID-19 and the Russia Ukraine war has had a great impact on the rice supply chain. Compared with other grain supply chains, rice supply chain has more complex structure and data. Using digital means to realize the dynamic supervision of rice supply chain is helpful to ensure the quality and safety of rice. This study aimed to build a dynamic supervision model suited to the circulation characteristics of the rice supply chain and implement contractualization, analysis, and verification. First, based on an analysis of key information in the supervision of the rice supply chain, we built a dynamic supervision model framework based on blockchain and smart contracts. Second, under the logical framework of a regulatory model, we custom designed three types of smart contracts: initialization smart contract, model-verification smart contract, and credit-evaluation smart contract. To implement the model, we combined an asymmetric encryption algorithm, virtual regret minimization algorithm, and multisource heterogeneous fusion algorithm. We then analyzed the feasibility of the algorithm and the model operation process. Finally, based on the dynamic supervision model and smart contract, a prototype system is designed for example verification. The results showed that the dynamic supervision model and prototype system could achieve the real-time management of the rice supply chain in terms of business information, hazard information, and personnel information. It could also achieve dynamic and credible supervision of the rice supply chain's entire life cycle at the information level. This new research is to apply information technology to the digital management of grain supply chain. It can strengthen the digital supervision of the agricultural product industry.

Suppression of ACE2 SUMOylation protects against SARS-CoV-2 infection through TOLLIP-mediated selective autophagy.

In addition to investigating the virology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), discovering the host-virus dependencies are essential to identify and design effective antiviral therapy strategy. Here, we report that the SARS-CoV-2 entry receptor, ACE2, conjugates with small ubiquitin-like modifier 3 (SUMO3) and provide evidence indicating that prevention of ACE2 SUMOylation can block SARS-CoV-2 infection. E3 SUMO ligase PIAS4 prompts the SUMOylation and stabilization of ACE2, whereas deSUMOylation enzyme SENP3 reverses this process. Conjugation of SUMO3 with ACE2 at lysine (K) 187 hampers the K48-linked ubiquitination of ACE2, thus suppressing its subsequent cargo receptor TOLLIP-dependent autophagic degradation. TOLLIP deficiency results in the stabilization of ACE2 and elevated SARS-CoV-2 infection. In conclusion, our findings suggest selective autophagic degradation of ACE2 orchestrated by SUMOylation and ubiquitination as a potential way to combat SARS-CoV-2 infection.

Research on the Cross-Chain Model of Rice Supply Chain Supervision Based on Parallel Blockchain and Smart Contracts

Rice is one of the three major staple foods in the world, and the quality and safety of rice are related to the development of human beings. The new crown epidemic, pesticide residues, insect pests, and heavy metal pollution have a certain security impact on the food supply chain. The rice supply chain is characterized by a long life cycle;complex roles in the main links;many types of hazards;and multidimensional, multisource, and heterogeneous information. To strengthen the rice supply chain’s supervision ability under the epidemic situation, a supervision cross-chain model suitable for the complicated data of the rice supply chain based on parallel blockchain theory and smart contract technology was built. Firstly, the data collected in the rice supply chain and different types of data stored in different parallel blockchains were analyzed. Secondly, based on data analysis, a collection/supervision cross-chain mechanism based on “hash lock + smart contract + relay chain”, a concurrency mechanism based on the K-means algorithm and a Bloom filter, and a consensus mechanism suitable for multichain consensus named the Supervision Practical Byzantine Fault Tolerance (SPBFT) were proposed. Furthermore, a cross-chain model of rice supply chain supervision was constructed. Finally, theoretical verification and simulation experiments were used to analyze the operation process, safety, cross-chain efficiency, and scalability of the model. The results showed that the application of parallel blockchains and smart contracts to supervision of rice supply chain information improved the convenience and security of information interaction between various links in the rice supply chain, the storage cost of supply chain data and the high latency of interaction was reduced, and the refined management of the rice supply chain data and personnel was realized. This research applied new information technology to the coordination and resource sharing of the food supply chain, and provides ideas for the digital transformation of the food industry.

RNA-induced liquid phase separation of SARS-CoV-2 nucleocapsid protein facilitates NF-κB hyper-activation and inflammation.

The ongoing 2019 novel coronavirus disease (COVID-19) caused by SARS-CoV-2 has posed a worldwide pandemic and a major global public health threat. The severity and mortality of COVID-19 are associated with virus-induced dysfunctional inflammatory responses and cytokine storms. However, the interplay between host inflammatory responses and SARS-CoV-2 infection remains largely unknown. Here, we demonstrate that SARS-CoV-2 nucleocapsid (N) protein, the major structural protein of the virion, promotes the virus-triggered activation of NF-κB signaling. After binding to viral RNA, N protein robustly undergoes liquid-liquid phase separation (LLPS), which recruits TAK1 and IKK complex, the key kinases of NF-κB signaling, to enhance NF-κB activation. Moreover, 1,6-hexanediol, the inhibitor of LLPS, can attenuate the phase separation of N protein and restrict its regulatory functions in NF-κB activation. These results suggest that LLPS of N protein provides a platform to induce NF-κB hyper-activation, which could be a potential therapeutic target against COVID-19 severe pneumonia.