Modulating neuroinflammation and cognitive function in postoperative cognitive dysfunction via CCR5-GPCRs-Ras-MAPK pathway targeting with microglial EVs.

AIMS: Postoperative cognitive dysfunction (POCD) is prevalent among the elderly, characterized primarily by cognitive decline after surgery. This study aims to explore how extracellular vesicles (EVs) derived from BV2 microglial cells, with and without the C-C chemokine receptor type 5 (CCR5), affect neuroinflammation, neuronal integrity, and cognitive function in a POCD mouse model. METHODS: We collected EVs from LPS-stimulated BV2 cells expressing CCR5 (EVsM1) and from BV2 cells with CCR5 knockdown (EVsM1-CCR5). These were administered to POCD-induced mice. Protein interactions between CCR5, G-protein-coupled receptors (GPCRs), and Ras were analyzed using structure-based docking and co-immunoprecipitation (Co-IP). We assessed the phosphorylation of p38 and Erk, the expression of synaptic proteins PSD95 and MAP2, and conducted Morris Water Maze tests to evaluate cognitive function. RESULTS: Structure-based docking and Co-IP confirmed interactions between CCR5, GPR, and Ras, suggesting a CCR5-GPCRs-Ras-MAPK pathway involvement in neuroinflammation. EVsM1 heightened neuroinflammation, reduced synaptic integrity, and impaired cognitive function in POCD mice. In contrast, EVsM1-CCR5 reduced neuroinflammatory markers, preserved synaptic proteins, enhanced dendritic spine structure, and improved cognitive outcomes. CONCLUSION: EVsM1 induced neuroinflammation via the CCR5-GPCRs-Ras-MAPK pathway, with EVsM1-CCR5 showing protective effects on POCD progression, suggesting a new therapeutic strategy for POCD management via targeted modification of microglial EVs.

Predicting the transmission dynamics of novel coronavirus infection in Shanxi province after the implementation of the "Class B infectious disease Class B management" policy.

Background: China managed coronavirus disease 2019 (COVID-19) with measures against Class B infectious diseases, instead of Class A infectious diseases, in a major shift of its epidemic response policies. We aimed to generate robust information on the transmission dynamics of novel coronavirus infection in Shanxi, a province located in northern China, after the implementation of the "Class B infectious disease Class B management" policy. Methods: We consolidated infection data in Shanxi province from December 6, 2022 to January 14, 2023 through a network questionnaire survey and sentinel surveillance. A dynamics model of the SEIQHCVR was developed to track the infection curves and effective reproduction number (Rt). Results: Our model was effective in estimating the trends of novel coronavirus infection, with the coefficient of determination (R2) above 90% in infections, inpatients, and critically ill patients. The number of infections in Shanxi province as well as in urban and rural areas peaked on December 20, 2022, with the peak of inpatients and critically ill patients occurring 2 to 3 weeks after the peak of infections. By the end of January 2023, 87.72% of the Shanxi residents were predicted to be infected, and the outbreak subsequently subsided. A small wave of COVID-19 infections may re-emerge at the end of April. In less than a month, the Rt values of positive infections, inpatients and critically ill patients were all below 1.0. Conclusion: The outbreak in Shanxi province is currently at a low prevalence level. In the face of possible future waves of infection, there is a strong need to strengthen surveillance and early warning.

Perceived impact of the Covid-19 crisis on SMEs in different industry sectors: Evidence from Sichuan, China.

The outbreak of the novel coronavirus (Covid-19) has led to a global public health disaster and global economic crisis and significantly impacted industries across the world. As China was the first to feel the effects of the Covid-19 outbreak, it was also the first to overcome the effects and resume economic production. To understand the impact of the Covid-19 pandemic on SMEs in China and suggest public policies to deal with the negative effects, in February 2020, this paper examined the impacts on 3194 SMEs from primary, manufacturing, wholesale and retail trade, hospitality (accommodation and catering), and new economy industries in Sichuan, China using an online survey and follow-up interviews. It was found that the effects differed by industry sector: the primary industry sector by poor logistics; the manufacturing industry sector by supply chain management problems; the wholesale and retail trade industry sector by the need to accelerate their online services; the hospitality industry sector, the most severely affected sector, by cash flow pressure; and the new economy industry sector by short-term pressures. Short-term revenue declines and an inability to resume work and production were common problems faced by all surveyed SMEs. These findings from Sichuan, China provide some valuable references for global industry recovery.

Two new phragmalin-type limonoids from Chukrasia tabularis and their α-glucosidase inhibitory activity.

Phytochemical investigation on the stems of C. tabularis (Meliaceae) led to the isolation of two new phragmalin-type limonoids, named tabularisins S and T (1-2), along with five known ones (3-7). The structures of the new limonoids were established by spectroscopic methods including UV, IR, HRESIMS, and 1D and 2D NMR. All the compounds were evaluated for α-glucosidase inhibitory activity in vitro. Compounds 2 and 3 exhibited significant inhibitory activity against α-glucosidase with IC50 values of 0.15 and 0.03 mM, respectively (acarbose as positive control, IC50 0.95 mM).

New Phragmalin-Type Limonoids from Chukrasia tabularis and Their α-Glucosidase Inhibitory Activity.

Phytochemical investigation on the stems of C. tabularis led to the isolation of five new phragmalin-type limonoids and six known ones. The structures of the new compounds 1-5, named chukbularisins A-E, were elucidated by spectroscopic techniques (IR, HRESIMS, 1D and 2D NMR) and comparisons with published data. All the compounds were evaluated for in vitro α-glucosidase inhibitory activity. Compounds 2, 3, 4, 5, and 8 exhibited inhibitory activity against α-glucosidase with IC50 values of 0.06 ± 0.008, 0.04 ± 0.002, 0.52 ± 0.039, 1.09 ± 0.040, and 0.20 ± 0.057 mM, respectively (using acarbose as positive control, IC50 0.95 ± 0.092 mM).