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Objectives: Atractylenolide III (ATL III) is the major bioactive component found in Atractylodes macrocephala, which has shown a range of benefits in pharmacological studies, including neuroprotection, anti-neuroinflammatory properties, antioxidant effects, anti-allergic effects, anti-cancer properties and antifibrotic abilities. Here, we investigated the therapeutic potential and underlying mechanisms of ATL III in the treatment of post-traumatic joint contracture (PTJC) in rat knees., Methods: The rat PTJC model and TGF-β1-induced a primary synovial fibroblast model were used to observe several fibrotic markers (α-SMA、TGF-β1、FGF2、COL1A1and COL3A1) using histological staining, immunofluorescence and western blot. Additionally, the effects of ATL III on synovial fibroblasts in vitro were evaluated through CCK-8 assays and migration assays to ascertain both cell viability and migratory behaviors. Furthermore, molecular docking studies were performed to elucidate the potential binding affinity of ATL III for Silent information regulator of transcription 1 (Sirt1), thereby providing insights into the underlying molecular mechanisms implicated in fibrosis modulation., Results: ATL III treatment was observed to reduce proliferating cells, inflammatory cells and collagen accumulation in a rat model of traumatic rat knee fibrosis. In vitro, ATL III treatment was found to significantly reduce fibrosis and collagen-associated protein expression and inhibit synovial fibroblast proliferation and migration. Molecular docking identified Sirt1 as a potential target of ATL III. Interestingly, Sirt1 and Smad3 can interact and act to deacetylate Smad3, and in vitro and in vivo ATL III treatment significantly reduced Smad3 acetylation levels., Conclusion: ATL III produces a therapeutic effect on knee fibrosis probably because Sirt1 deacetylates Smad3 and thus relieves knee fibrosis in rats., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier Inc. All rights reserved.)

Lysine β-hydroxybutyrylation (Kbhb) is newly discovered β-hydroxybutyrylate-derived histone modification which has been associated with the pathogenesis of many human diseases. To further elucidate the biological significance and molecular mechanism of Kbhb, it is necessary to accurately identify the Kbhb sites from protein sequences. In this study, a novel computational model named iBhb-Lys is developed for the identification of Kbhb sites. Four types of features are combined to encode each Kbhb site as a 3266-dimensional feature vector. And the autoencoder network is used to reduce the dimensionality of feature space, due to the high dimensionality of the combined features. In addition, to effectively reduce the influence of noise and outlier on classification, a new fuzzy support vector machine algorithm is proposed by incorporating the density around the sample into the fuzzy membership function. As illustrated by independent test, the AUC value of iBhb-Lys has increased by 2.22 % compared to the existing predictor KbhbXG. Feature analysis shows that some amino acid composition features, such as the occurrence frequency of leucine and histidine residues around Kbhb sites, contribute profoundly to the identification of Kbhb sites. The conclusions drawn in this study may provide useful reference for studying the molecular mechanism of Kbhb., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)