Baicalin is a flavonoid compound extracted from Scutellaria roots that has been reported to possess antibacterial, anti-inflammatory, and antiviral activities. However, the antiviral effect of baicalin on enterovirus 71 (EV71) is still unknown. In this study, we found that baicalin showed inhibitory activity on EV71 infection and was independent of direct virucidal or prophylactic effect and inhibitory viral absorption. The expressions of EV71/3D mRNA and polymerase were significantly blocked by baicalin treatment at early stages of EV71 infection. In addition, baicalin could decrease the expressions of FasL and caspase-3, as well as inhibit the apoptosis of EV71-infected human embryonal rhabdomyosarcoma (RD) cells. Altogether, these results indicate that baicalin exhibits potent antiviral effect on EV71 infection, probably through inhibiting EV71/3D polymerase expression and Fas/FasL signaling pathways.

In recent years, sodium butyrate has gained increased attention for its numerous beneficial properties. However, whether sodium butyrate could alleviate inflammatory damage by macrophage activation and its underlying mechanism remains unclear. The present study used an advanced glycosylation products- (AGEs-) induced inflammatory damage model to study whether sodium butyrate could alleviate oxidative stress, inflammation, and metabolic dysfunction of human monocyte-macrophage originated THP-1 cells in a PI3K-dependent autophagy pathway. The results indicated that sodium butyrate alleviated the AGEs-induced oxidative stress, decreased the level of reactive oxygen species (ROS), increased malondialdehyde (MDA) and mRNA expression of pro-inflammatory cytokines of interleukin (IL)-1β and tumor necrosis factor (TNF)-α, and increased the content of superoxide dismutase (SOD). Sodium butyrate reduced the protein expression of the NLR family, pyrin domain-containing protein 3 (NLRP3) and Caspase-1, and decreased the nucleus expression of nuclear factor-kappaB (NF-κB). Sodium butyrate decreased the expression of light-chain-associated protein B (LC3B) and Beclin-1, and inhibited autophagy. Moreover, sodium butyrate inhibited the activation of the PI3K/Akt pathway in AGEs-induced THP-1 cells. In addition, the metabolomics analysis showed that sodium butyrate could affect the production of phosphatidylcholine, L-glutamic acid, UDP-N-acetylmuraminate, biotinyl-5’-AMP, and other metabolites. In summary, these results revealed that sodium butyrate inhibited autophagy and NLRP3 inflammasome activation by blocking the PI3K/Akt/NF-κB pathway, thereby alleviating oxidative stress, inflammation, and metabolic disorder induced by AGEs.

Diabetes mellitus (DM) is associated with an elevated risk of cognitive decline, though trajectories are heterogeneous. This study investigated whether a novel, clinically applicable measure of brain network integrity, the Morphometric Inverse Divergence (MIND) network, could differentiate and predict cognitive progression in DM. We retrospectively analyzed 101 DM participants (41 cognitively normal, 60 with mild cognitive impairment) from the Alzheimer's Disease Neuroimaging Initiative, classifying them into stable (DM_S, n = 64) or decline (DM_D, n = 37) group based on longitudinal diagnostic conversion. MIND networks were constructed from multiple cortical morphological features derived from T1-weighted MRI and graph theory measurements were further analyzed. Using network-based statistics (NBS) and its extension NBS-predict, we tested whether subject-level connectomes were associated with long-term DM-related cognitive worsening. At baseline, DM_D individuals exhibited significantly lower cognitive scores and a focal subnetwork of disrupted morphometric similarity, primarily involving temporal regions. Longitudinally, DM_D individuals showed a more targeted pattern of network change that significantly altered global efficiency, local efficiency, and path length exclusively, while stable individuals, the brain underwent more widespread changes. Crucially, baseline MIND networks significantly predicted long-term cognitive progression status (accuracy = 63.1%, p = 0.034). The predictive subnetwork was rich in transmodal connections involving the temporoparietal, default mode, and limbic networks. These findings indicate that cognitive decline in DM is preceded by specific disruptions in the brain's structural connectome. The MIND method shows promise as a network-based biomarker for identifying at-risk individuals and predicting cognitive trajectory, potentially driving advanced network analyses toward real-world applicability.