Oleanolic acid mitigates interleukin-1ß-induced chondrocyte dysfunction by regulating miR-148-3p-modulated FGF2 expression.

BACKGROUND: microRNA (miR)-mediated post-transcriptional repression has been reported in the process of chondrocyte dysfunction. The present study aimed to investigate the molecular mechanisms underlying in oleanolic acid (OLA)-prevented interleukin (IL)-1ß-induced chondrocyte dysfunction via the miR-148-3p/fibroblast growth factor-2 (FGF-2) signaling pathway. METHODS: Candidate miRs were filtrated using miR microarray assays in chondrocytes with or without IL-1ß stimulation. Gene expression of candidate miRs and protein expression of FGF2 were analyzed using a quantitative reverse transcriptase-polymerase chain reaction and western blotting, respectively. Cell growth was evaluated using cell counting kit-8 assays. Cell apoptosis was detected using Annexin V-fluorescein isothiocyanate double staining. RESULTS: Treatment with OLA counteracted IL-1ß-evoked chondrocyte growth inhibition, apoptosis, caspase3 production, and release of malondialdehyde (MDA) and 8-hydroxy-2'-deoxyguanosine. Additionally, FGF2 protein expression levels elevated by IL-1ß were down-regulated by OLA and transfection with miR-148-3p mimics. IL-1ß-induced down-regulation of miR-148-3p in chondrocytes was evaluated by OLA administration. Bioinformatics algorithms and experimental measurements indicated that FGF2 might be a direct target of miR-148-3p. miR-148-3p mimics exhibited equal authenticity of OLA to protect against IL-1ß-induced chondrocyte dysfunction. CONCLUSIONS: Our present findings highlight a protective effect of OLA on IL-1ß-induced chondrocyte dysfunction, and a novel signal cascade comprising the miR-148-3p/FGF2 signaling pathway might be a potential therapeutic target of OLA with respect to preventing the progression of osteoarthritis.

Molecular Cavity Topological Representation for Pattern Analysis: A NLP Analogy-Based Word2Vec Method.

Cavity analysis in molecular dynamics is important for understanding molecular function. However, analyzing the dynamic pattern of molecular cavities remains a difficult task. In this paper, we propose a novel method to topologically represent molecular cavities by vectorization. First, a characterization of cavities is established through Word2Vec model, based on an analogy between the cavities and natural language processing (NLP) terms. Then, we use some techniques such as dimension reduction and clustering to conduct an exploratory analysis of the vectorized molecular cavity. On a real data set, we demonstrate that our approach is applicable to maintain the topological characteristics of the cavity and can find the change patterns from a large number of cavities.

Ellipsoidal Abstract and Illustrative Representations of Molecular Surfaces.

Molecular visualization is often challenged with rendering of large molecular structures in real time. The key to LOD (level-of-detail), a classical technology, lies in designing a series of hierarchical abstractions of protein. In the paper, we improved the smoothness of transition for these abstractions by constructing a complete binary tree of a protein. In order to reduce the degree of expansion of the geometric model corresponding to the high level of abstraction, we introduced minimum ellipsoidal enveloping and some post-processing techniques. At the same time, a simple, ellipsoid drawing method based on graphics processing unit (GPU) is used that can guarantee that the drawing speed is not lower than the existing sphere-drawing method. Finally, we evaluated the rendering performance and effect on series of molecules with different scales. The post-processing techniques applied, diffuse shading and contours, further conceal the expansion problem and highlight the surface details.

Prediction of Enzyme Function Based on Three Parallel Deep CNN and Amino Acid Mutation.

During the past decade, due to the number of proteins in PDB database being increased gradually, traditional methods cannot better understand the function of newly discovered enzymes in chemical reactions. Computational models and protein feature representation for predicting enzymatic function are more important. Most of existing methods for predicting enzymatic function have used protein geometric structure or protein sequence alone. In this paper, the functions of enzymes are predicted from many-sided biological information including sequence information and structure information. Firstly, we extract the mutation information from amino acids sequence by the position scoring matrix and express structure information with amino acids distance and angle. Then, we use histogram to show the extracted sequence and structural features respectively. Meanwhile, we establish a network model of three parallel Deep Convolutional Neural Networks (DCNN) to learn three features of enzyme for function prediction simultaneously, and the outputs are fused through two different architectures. Finally, The proposed model was investigated on a large dataset of 43,843 enzymes from the PDB and achieved 92.34% correct classification when sequence information is considered, demonstrating an improvement compared with the previous result.

P-15 promotes chondrocyte proliferation in osteoarthritis by regulating SFPQ to target the Akt-RUNX2 axis.

BACKGROUND: The disruption of chondrocyte proliferation and differentiation is a critical event during the process of joint injury in osteoarthritis (OA). P-15 peptides could bind to integrin receptors on various precursor cells, promote cell adhesion, release growth factors, and promote the differentiation of osteoblast precursor cells. However, the role of P-15 in OA, particularly in chondrocyte proliferation, is not fully understood. METHODS: The activity of SFPQ and RUNX2 in the bone tissue of patients with osteoarthritis was analyzed using quantitative real-time polymerase chain reaction (qRT-PCR). Interleukin-1ß (IL-1ß) inducer was performed to establish an in vitro model of OA. Cell proliferation was measured by CCK-8 assay. The expressions of COL2a1, ACAN, COMP, SOX9, and BMP2 related to cartilage differentiation were detected using qRT-PCR. In addition, the expression levels of SFPQ, AKT, p-AKT, and RUNX2 were detected using Western blotting. RESULTS: The results showed that the expression of SFPQ was significantly decreased and the expression of RUNX2 was significantly increased in osteoarthritis cartilage tissue. P-15 peptide reversed IL-1ß-induced cell proliferation obstruction and alleviated chondrocyte damage. Furthermore, P-15 polypeptide increased the expression levels of cartilage differentiation genes COL2a1, ACAN, and BMP2, while decreasing the expression of COMP and SOX9 in an inverse dose-dependent manner. Then specific interfering RNA proved that P-15 maintains chondrocyte stability and is associated with the SFPQ gene. Finally, we confirmed that P-15 inhibited the Akt-RUNX2 pathway, which is regulated in the expression of SFPQ. CONCLUSIONS: P-15 can mitigate chondrocyte damage and osteoarthritis progression by inhibiting cell death and modulating SFPQ-Akt-RUNX2 pathway, offering an opportunity to develop new strategies for the treatment of osteoarthritis.

Circ-Sirt1 promotes osteoblast differentiation by activating Sirt1 and Wnt/ß-catenin pathway.

Osteoporosis, a bone disease common in the elderly, results in bone loss and damage to bone microstructure. Sirtuin 1 (Sirt1), belongs to Sirtuin family, is involved in regulating bone quality. Circ-Sirt1 is one of the transcripts of Sirt1 host gene. Here, the involvement of circ-Sirt1 was determined in bone disease for the first time, proposing that circ-Sirt1 can activate the Wnt/ß-catenin pathway to promote osteogenesis differentiation. This study was aimed to elucidate the potential function of Circ-Sirt1 and Sirt1 regulatory loop in the differentiation of bone marrow mesenchymal stem cells (BMSCs). The differentiation of bone marrow mesenchymal stem cells was detected by ALP, alizarin red staining and qPCR. The dual luciferase reporter assay was applied to reveal the interaction between RNAs. The result showed that Sirt1 promoted osteogenic differentiation of BMSCs. Circ-Sirt1, derived from Sirt1, acted as miR-132 and miR-212 sponge, and up-regulated the expression of Sirt1. Furthermore, Sirt1-mediated circ-Sirt1 promoted osteogenic differentiation. Finally, we unveiled that Circ-Sirt1 facilitates osteogenic differentiation by activating the Wnt/ß-catenin pathway. In conclusion, our data suggested that Circ-Sirt1 elevates osteogenic differentiation via miR-132/212/Sirt1 and Wnt/ß-catenin pathway.