Objective To investigate the role and possible molecular mechanism of Krüppel-like factor 7 (KLF7) in the TLR4/NF-κB/IL-6 inflammatory signaling pathway activated by free fatty acids (FFA). Methods The mRNA and protein expression levels of KLF7 and the factors of TLR4/NF-κB/IL-6 inflammatory signal pathways were detected by qRT-PCR and Western blotting after cell culture with different concentrations of palmitic acid (PA). The expression of KLF7 or TLR4 in adipocytes was upregulated or downregulated; after that, the mRNA and protein expression levels of these key factors were detected. KLF7 expression was downregulated while PA stimulated adipocytes, and then the mRNA and protein expressions of KLF7/p65 and downstream inflammatory cytokine IL-6 were detected. The luciferase reporter assay was used to determine whether KLF7 had a transcriptional activation effect on IL-6. Results (1) High concentration of PA can promote the expression of TLR4, KLF7, and IL-6 in adipocytes. (2) TLR4 positively regulates KLF7 expression in adipocytes. (3) KLF7 positively regulates IL-6 expression in adipocytes. (4) PA promotes IL-6 expression via KLF7 in adipocytes. (5) KLF7 has a transcriptional activation on IL-6. Conclusion PA promotes the expression of the inflammatory cytokine IL-6 by activating the TLR4/KLF7/NF-κB inflammatory signaling pathway. In addition, KLF7 may directly bind to the IL-6 promoter region and thus activate IL-6.

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Background: Han and Uygur are the two main nationalities living in Xinjiang, China. There are significant differences in the incidence of metabolic diseases for two nationalities, but the specific reasons are not clear. Obesity is an important risk factor for the development of metabolic syndrome, which may be closely related to the increase of serum free fatty acids (FFAs) content. This study aims to use metabolomics to compare the changes of serum FFAs profiles between normal weight (NW) and obese (OB) individuals of two nationalities, screening out the differential FFAs, predicting and evaluating their relationship with diseases. Methods: Thirty-four kinds of FFAs in serum were detected by ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) and distinctions in FFAs profiles were evaluated using a metabolomics method while Receiver operating characteristics (ROC) and logistic regression models were used to explore FFAs significant for diagnosing obesity and obesity-associated comorbidities.

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