Compared with traditional internal fixation devices, bone adhesives are expected to exhibit remarkable advantages, such as improved fixation of comminuted fractures and maintained spatial location of fractured scattered bone pieces in treating bone injuries. In this review, different bone adhesives are summarized from the aspects of bone tissue engineering, and the applications of bone adhesives are emphasized. The concepts of "liquid scaffold" and "liquid plate" are proposed to summarize two different research directions of bone adhesives. Furthermore, significant advances of bone adhesives in recent years in mechanical strength, osseointegration, osteoconductivity, and osteoinductivity are discussed. We conclude this topic by providing perspectives on the stateof-the-art research progress and future development trends of bone adhesives. We hope this review will provide a comprehensive summary of bone adhesives and inspire more extensive and in-depth research on this subject.

High-fat (HF) diet-induced neuroinflammation and cognitive decline in humans and animals have been associated with microbiota dysbiosis via the gut-brain axis. Our previous studies revealed that excretory-secretory products (ESPs) derived from the larval Echinococcus granulosus (E. granulosus) function as immunomodulators to reduce the inflammatory response, while the parasitic infection alleviates metabolic disorders in the host. However, whether ESPs can improve cognitive impairment under obese conditions remain unknown. This study aimed to investigate the effects of E. granulosus-derived ESPs on cognitive function and the microbiota-gut-brain axis in obese mice. We demonstrated that ESPs supplementation prevented HF diet-induced cognitive impairment, which was assessed behaviorally by nest building, object location, novel object recognition, temporal order memory, and Y-maze memory tests. In the hippocampus (HIP) and prefrontal cortex (PFC), ESPs suppressed neuroinflammation and HF diet-induced activation of the microglia and astrocytes. Moreover, ESPs supplementation improved the synaptic ultrastructural impairments and increased both pre- and postsynaptic protein levels in the HIP and PFC compared to the HF diet-treated group. In the colon, ESPs reversed the HF diet-induced gut barrier dysfunction, increased the thickness of colonic mucus, upregulated the expression of zonula occludens-1 (ZO-1), attenuated the translocation of bacterial endotoxins, and decreased the colon inflammation. Notably, ESPs supplementation alleviated the HF diet-induced microbiota dysbiosis. After clarifying the role of antibiotics in obese mice, we found that broad-spectrum antibiotic intervention abrogated the effects of ESPs on improving the gut microbiota dysbiosis and cognitive decline. Overall, the present study revealed for the first time that the parasite-derived ESPs alleviate gut microbiota dysbiosis and improve cognitive impairment induced by a high-fat diet. This finding suggests that parasite-derived molecules may be used to explore novel drug candidates against obesity-associated neurodegenerative diseases.

The current global water environment has been seriously damaged. The prediction of water quality parameters can provide effective reference materials for future water conditions and water quality improvement. In order to further improve the accuracy of water quality prediction and the stability and generalization ability of the model, we propose a new comprehensive deep learning water quality prediction algorithm. Firstly, the water quality data are cleaned and pretreated by isolation forest, the Lagrange interpolation method, sliding window average, and principal component analysis (PCA). Then, one-dimensional residual convolutional neural networks (1-DRCNN) and bi-directional gated recurrent units (BiGRU) are used to extract the potential local features among water quality parameters and integrate information before and after time series. Finally, a full connection layer is used to obtain the final prediction results of total nitrogen (TN), total phosphorus (TP), and potassium permanganate index (COD-Mn). Our prediction experiment was carried out according to the actual water quality data of Daheiting Reservoir, Luanxian Bridge, and Jianggezhuang at the three control sections of the Luan River in Tangshan City, Hebei Province, from 5 July 2018 to 26 March 2019. The minimum mean absolute percentage error (MAPE) of this method was 2.4866, and the coefficient of determination (R2) was able to reach 0.9431. The experimental results showed that the model proposed in this paper has higher prediction accuracy and generalization than the existing LSTM, GRU, and BiGRU models.