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The regulation of glial cell activation is a critical step for the treatment or prevention of neuroinflammation‐based brain diseases. However, the development of therapeutic drugs that pass the blood–brain barrier (BBB) and inhibit the glia cell activation remains a significant challenge. Herein, an ultrasmall 2D vanadium carbide quantum dots (V2C QDs) that are capable of crossing the BBB are prepared, and the admirable anti‐neuroinflammatory effects are presented. The prepared 2D V2C QDs with an average size of 2.54 nm show good hydrophilicity, physiological stability, and effective BBB‐crossing ability. The biological effect of V2C QDs on inflammatory reactions demonstrates fascinating results in preventing the impairment of learning and memory in BALB/c mice stimulated by lipopolysaccharide. Investigation of molecular mechanism reveals that V2C QDs not only inhibit the toll‐like receptor 4/myeloid differentiation factor 88‐mediated nuclear factor kappa B and mitogen‐activated protein kinase pathways, but also prevent eukaryotic translation initiation factor 2α/activating transcription factor 4/C/EBP homologous protein‐signaling pathway and reduce oxidative stress via activating the NF‐E2‐related factor‐2/heme oxygenase‐1‐signaling pathway, leading to greatly inhibited activation of microglia and astrocytes and weakened production of inflammatory cytokines. In summary, V2C QDs exert potent anti‐inflammatory effects through multiple pathways, thus offer great potential for the treatment of neurodegenerative diseases.

With the rapid development of the economy, it is important to reasonably evaluate the development status of the regional manufacturing industry. Given this, this article expands the evaluation indicators of urban advanced manufacturing (UAM) from the perspective of the push–pull-mooring (PPM). Then, it uses a machine learning (ML) method to predict the evaluation results of other cities through a small amount of sample data. The results show that: (1) From the current development status of UAM in Guangdong Province (GD), cities in the Pearl River Delta region occupy a dominant position. However, cities in eastern, western, and mountainous regions have strong development potential and lead cities. Therefore, each region has cities with high levels of development and has a demonstrative role. (2) By comparison, it was found that the overall development level of UAM in GD is not significantly different from that of the Yangtze River Economic Belt. However, due to significant differences in their extreme values, the proportion of cities above the average in the overall population is relatively small. This indirectly proves that GD’s UAM not only has a phased nature, but also has a demonstrative role. (3) The prediction effect of the perceptron model is better than other methods. Although neural network models have better prediction performance than other machine learning models, they should not overly rely on complex network structure prediction data. By comparing the results, the reliability is verified. Finally, according to the life cycle theory, we propose a targeted development path for different UAM.