Abstract:Objective: To investigate the effects of benzo[b]fluoranthene (BbF) intervention on renal inflammation and the advanced glycation end products/receptor for advanced glycation end products (AGE/RAGE) signaling pathway in rats with chronic kidney disease (CKD). Methods: A total of 53 specific pathogen-free (SPF) male Sprague-Dawley (SD) rats were used. Fourteen rats were randomly selected as the control group, and the remaining 39 rats were used to establish a CKD model. Among them, 36 rats were successfully modeled and randomly divided into three groups: the model group (14 rats), the BbF group (11 rats), and the BbF + FPS-ZM1 group (11 rats). The body weight changes of rats in each group were compared before and after gavage. After 4 weeks of gavage, a balance was used to measure the weight of both kidneys and the kidney index; hematoxylin-eosin (HE) staining was used to detect pathological changes in renal tissue. Tail vein blood was collected after 4 weeks of gavage, and a biochemical analyzer was used to detect renal function indicators [serum creatinine (Scr), blood urea nitrogen (BUN), uric acid (UA)]. Renal tissue was collected after 4 weeks of gavage; enzyme-linked immunosorbent assay (ELISA) was used to detect the content of inflammatory factors [C-reactive protein (CRP), interleukin-6 (IL-6), interleukin-8 (IL-8), tumor necrosis factor-α (TNF-α)] and the levels of oxidative stress [superoxide dismutase (SOD), malondialdehyde (MDA), glutathione peroxidase (GSH-Px)]; flow cytometry was used to detect the expression levels of macrophage-related markers [CD11c+, CD206+, CD11c+/CD206+]; Western blotting (Wb) was used to detect the levels of the AGE/RAGE signaling pathway. Results: With the extension of gavage time, the body weight of rats in the control group showed a gradual increase trend, while the body weight of rats in the model group, BbF group, and BbF + FPS-ZM1 group all showed a decreasing trend, with a significant decrease in the BbF group (P<0.05). In addition, the pathological changes in the BbF group were obvious. Compared with the control group, model group, and BbF+FPS-ZM1 group, the BbF group had significantly increased levels of kidney weight, kidney index, UA, BUN, Scr, IL-6, CRP, TNF-α, IL-8, MDA, CD11c+/CD206+, CD11c+, RAGE mRNA, and AGE mRNA, while the levels of GSH-Px, SOD, and CD206+ were significantly decreased, with statistically significant differences (P<0.05). Conclusion: BbF can promote the development of inflammation in CKD rats, accelerate the progression of the disease by activating the AGE/RAGE signaling pathway, and at the same time have adverse effects on oxidative stress, renal function, and macrophages.
[1] 陆蕾,朱慧敏,秦旭阳,等.复肾泄浊汤治疗慢性肾脏病脾肾两虚证大鼠的实验研究[J].新疆医科大学学报,2024,47(10):1418-1424. [2] Kidney disease: improving global outcomes (KDIGO) CKD work group.KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease[J].Kidney Int,2024,105(4):117-314. [3] 覃丽虹,陈静,向涯碟,等.1990年至2021年我国慢性肾脏病疾病负担及其危险因素分析[J].医学新知,2024,34(9):957-969. [4] Canha N,Diapouli E,Almeida SM.Integrated human exposure to air pollution[J].Int Environ Res Public Health,2021,18(5):2233. [5] Lin CC,Chiu CC,Lee PY,et al.The adverse effects of air pollution on the eye: a review[J].Int Environ Res Public Health,2022,19(3):1186. [6] Snelson M,Lucut E,Coughlan MT.The role of AGE-RAGE signalling as a modulator of gut permeability in diabetes[J].Int Mol Sci,2022,23(3):1766. [7] Molinari P,Caldiroli L,Dozio E,et al.Association of autofluorescent advanced glycation end products (AGEs) with frailty components in chronic kidney disease (CKD): data from a single-center cohort study[J].Cells,2023,12(3):438. [8] 张雪,王家瑞,陈康寅.甘草酸对慢性肾脏病大鼠心肌HMGB1/TLR4/NF-κB/HIF-1α信号通路的影响[J].天津医药,2023,51(2):155-160. [9] Tong R,Cao L,Yang X,et al.Health damage to housewives by contaminants emitted from coal combustion in the Chinese countryside: focusing on day-to-day cooking[J].Int Arch Occup Environ Health,2021,94(8):1917-1929. [10] Hsu CT,Hsu SC,Huang SK,et al.Air quality in a hospital dental department[J].Dent Sci,2022,17(3):1350-1355. [11] Onuk S,Sipahiolu H,Karahan S,et al.Cytokine levels and severity of illness scoring systems to predict mortality in COVID-19 infection[J].Healthcare (Basel),2023,11(3):387.