The effect of gastric bypass surgery on cognitive function of Alzheimer's disease and the role of GLP1-SGLT1 pathway.

OBJECTIVE: Gastric bypass surgery has been shown to improve metabolic profiles via GLP1, which may also have cognitive benefits for Alzheimer's disease (AD) patients. However, the exact mechanism requires further investigation. METHODS: Roux-en-Y gastric bypass or sham surgery was performed on APP/PS1/Tau triple transgenic mice (an AD mice model) or wild type C57BL/6 mice. Morris Water Maze (MWM) test was used to evaluate the cognitive function of mice and animal tissue samples were obtained for measurements two months after the surgery. Additionally, STC-1 intestine cells were treated with siTAS1R2 and siSGLT1, and HT22 nerve cells were treated with Aß, siGLP1R, GLP1 and siSGLT1 in vitro to explore the role of GLP1-SGLT1 related signaling pathway in cognitive function. RESULTS: The MWM test showed that bypass surgery significantly improved cognitive function in AD mice as measured by navigation and spatial probe tests. Moreover, bypass surgery reversed neurodegeneration, down-regulated hyperphosphorylation of Tau protein and Aß deposition, improved glucose metabolism, and up-regulated the expression of GLP1, SGLT1, and TAS1R2/3 in the hippocampus. Furthermore, GLP1R silencing down-regulated SGLT1 expression, whereas SGLT1 silencing increased Tau protein deposition and exacerbated dysregulated of glucose metabolism in HT22 cells. However, RYGB did not alter the level of GLP1 secretion in the brainstem (where central GLP1 is mainly produced). Additionally, GLP1 expression was upregulated by RYGB via TAS1R2/3-SGLT1 activation sequentially in the small intestine. CONCLUSION: RYGB surgery could improve cognition function in AD mice through facilitating glucose metabolism and reducing Tau phosphorylation and Aß deposition in the hippocampus, mediated by peripheral serum GLP1 activation of SGLT1 in the brain. Furthermore, RYGB increased GLP1 expression through sequential activation of TAS1R2/TAS1R3 and SGLT1 in the small intestine.

The role of lactate metabolism-related LncRNAs in the prognosis, mutation, and tumor microenvironment of papillary thyroid cancer.

Background: Lactate, a byproduct of glucose metabolism, is primarily utilized for gluconeogenesis and numerous cellular and organismal life processes. Interestingly, many studies have demonstrated a correlation between lactate metabolism and tumor development. However, the relationship between long non-coding RNAs (lncRNAs) and lactate metabolism in papillary thyroid cancer (PTC) remains to be explored. Methods: Lactate metabolism-related lncRNAs (LRLs) were obtained by differential expression and correlation analyses, and the risk model was further constructed by least absolute shrinkage and selection operator analysis (Lasso) and Cox analysis. Clinical, immune, tumor mutation, and enrichment analyses were performed based on the risk model. The expression level of six LRLs was tested using RT-PCR. Results: This study found several lncRNAs linked to lactate metabolism in both The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets. Using Cox regression analysis, 303 lactate LRLs were found to be substantially associated with prognosis. Lasso was done on the TCGA cohort. Six LRLs were identified as independent predictive indicators for the development of a PTC prognostic risk model. The cohort was separated into two groups based on the median risk score (0.39717 -0.39771). Subsequently, Kaplan-Meier survival analysis and multivariate Cox regression analysis revealed that the high-risk group had a lower survival probability and that the risk score was an independent predictive factor of prognosis. In addition, a nomogram that can easily predict the 1-, 3-, and 5-year survival rates of PTC patients was established. Furthermore, the association between PTC prognostic factors and tumor microenvironment (TME), immune escape, as well as tumor somatic mutation status was investigated in high- and low-risk groups. Lastly, gene expression analysis was used to confirm the differential expression levels of the six LRLs. Conclusion: In conclusion, we have constructed a prognostic model that can predict the prognosis, mutation status, and TME of PTC patients. The model may have great clinical significance in the comprehensive evaluation of PTC patients.