Paeonol

Moutan Cortex (MC), recognized as a traditional Chinese medicinal herb, possesses significant therapeutic properties. The existing quality assessment method only measures the content of one component in MC, which is obviously not comprehensive enough. Besides, the determination process is time-consuming and laborious.Thus, this article presents a novel approach for the rapid, precise, and efficient quality assessment of MC based on near-infrared spectroscopy (NIR) technology in combination with the bionic swarm intelligent optimization algorithms. First, MC samples were collected and acquired with the NIR spectra in diffuse reflectance mode. Second, the content of paeonol, paeoniflorin, and gallic acid in MC was determined by high-performance liquid chromatography, and the content of total flavonoids and phenols was determined by UV-visible spectrophotometry. Afterward, all the measured content was analyzed in correlation with the NIR spectra of MC, and the partial least squares regression method was utilized to build the models. Especially, to improve the models' performance, five famous bionic swarm intelligent optimization algorithms were investigated to perform the wavelength selection. As a result, the models' performance was significantly enhanced. The coefficient of determination (R²) > 0.9 and residual prediction deviation (RPD) > 3 were observed on the calibration set and the prediction set. Thus, we believe that bionic swarm intelligent optimization algorithms have the potential to enhance the performance of quantitative models considerably, which offers substantial support for the quality assessment of MC and shows promising applications in the domain of NIR analysis.

Diabetic nephropathy (DN) is a significant clinical and public health burden worldwide whose magnitude underscores the urgent need for more effective treatment options. Excessive lipid accumulation in renal tubular cells leads to their injury and dysfunction, thereby contributing to DN progression, suggesting that the alleviation of renal tubular lipid accumulation is a potential strategy for treating DN.

The effects of paeonol (PAE), a natural phenolic compound, on renal tubular lipid accumulation were evaluated using a glucolipotoxicity-treated HK-2 cell line and C57BL/6 J mice treated with streptozotocin (STZ) injection combined with a high-fat diet (HFD). Autophagic flux and lipophagy were assessed through immunofluorescence, adenoviral mRFP-GFP-LC3 transfection, and western blotting. Small interfering RNA (siRNA) was used for in vitro experiments to silence Tfeb in HK-2 cells, while a Cre-loxP system was employed to induce Tfeb knockout specifically in renal tubules in vivo, to validate the therapeutic target of PAE. RNA sequencing, pulldown assays, surface plasmon resonance (SPR), and molecular docking were utilized to further explore the specific molecular mechanisms involved.

We found that PAE dose-dependently alleviated renal tubular lipid accumulation in glucolipotoxicity-treated HK-2 cells and the DN mouse model. Mechanistically, PAE directly binds to RHEB, functioning as an mTOR suppressor, thereby activating TFEB to promote lysosome biogenesis and lipophagy, subsequently alleviating renal tubular lipid accumulation and DN progression.

Per our findings, PAE holds promise as a therapeutic agent for DN, with the unique mechanism of activating renal TFEB-mediated lipophagy.