SIRT1 and ZNF350 as novel biomarkers for osteoporosis: a bioinformatics analysis and experimental validation.

BACKGROUND: Osteoporosis (OP) is characterized by bone mass decrease and bone tissue microarchitectural deterioration in bone tissue. This study identified potential biomarkers for early diagnosis of OP and elucidated the mechanism of OP. METHODS: Gene expression profiles were downloaded from Gene Expression Omnibus (GEO) for the GSE56814 dataset. A gene co-expression network was constructed using weighted gene co-expression network analysis (WGCNA) to identify key modules associated with healthy and OP samples. Functional enrichment analysis was conducted using the R clusterProfiler package for modules to construct the transcriptional regulatory factor networks. We used the "ggpubr" package in R to screen for differentially expressed genes between the two samples. Gene set variation analysis (GSVA) was employed to further validate hub gene expression levels between normal and OP samples using RT-PCR and immunofluorescence to evaluate the potential biological changes in various samples. RESULTS: There was a distinction between the normal and OP conditions based on the preserved significant module. A total of 100 genes with the highest MM scores were considered key genes. Functional enrichment analysis suggested that the top 10 biological processes, cellular component and molecular functions were enriched. The Toll-like receptor signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, osteoclast differentiation, JAK-STAT signaling pathway, and chemokine signaling pathway were identified by Kyoto Encyclopedia of Genes and Genomes pathway analysis. SIRT1 and ZNF350 were identified by Wilcoxon algorithm as hub differentially expressed transcriptional regulatory factors that promote OP progression by affecting oxidative phosphorylation, apoptosis, PI3K-Akt-mTOR signaling, and p53 pathway. According to RT-PCR and immunostaining results, SIRT1 and ZNF350 levels were significantly higher in OP samples than in normal samples. CONCLUSION: SIRT1 and ZNF350 are important transcriptional regulatory factors for the pathogenesis of OP and may be novel biomarkers for OP treatment.

Multi-omics reveals Dengzhan Shengmai formulation ameliorates cognitive impairments in D-galactose-induced aging mouse model by regulating CXCL12/CXCR4 and gut microbiota.

Dengzhan Shengmai (DZSM), a traditional Chinese medicine formulation, has been administered extensively to elderly individuals with cognitive impairment (CI). However, the underlying mechanisms by which Dengzhan Shengmai improves cognitive impairment remains unknown. This study aimed to elucidate the underlying mechanism of the effect of Dengzhan Shengmai on aging-associated cognitive impairment via a comprehensive combination of transcriptomics and microbiota assessment. Dengzhan Shengmai was orally administered to a D-galactose-induced aging mouse model, and evaluation with an open field task (OFT), Morris water maze (MWM), and histopathological staining was performed. Transcriptomics and 16S rDNA sequencing were applied to elucidate the mechanism of Dengzhan Shengmai in alleviating cognitive deficits, and enzyme-linked immunosorbent assay (ELISA), quantitative real-time polymerase chain reaction (PCR), and immunofluorescence were employed to verify the results. The results first confirmed the therapeutic effects of Dengzhan Shengmai against cognitive defects; specifically, Dengzhan Shengmai improved learning and impairment, suppressed neuro loss, and increased Nissl body morphology repair. Comprehensive integrated transcriptomics and microbiota analysis indicated that chemokine CXC motif receptor 4 (CXCR4) and its ligand CXC chemokine ligand 12 (CXCL12) were targets for improving cognitive impairments with Dengzhan Shengmai and also indirectly suppressed the intestinal flora composition. Furthermore, in vivo results confirmed that Dengzhan Shengmai suppressed the expression of CXC motif receptor 4, CXC chemokine ligand 12, and inflammatory cytokines. This suggested that Dengzhan Shengmai inhibited CXC chemokine ligand 12/CXC motif receptor 4 expression and modulated intestinal microbiome composition by influencing inflammatory factors. Thus, Dengzhan Shengmai improves aging-related cognitive impairment effects via decreased CXC chemokine ligand 12/CXC motif receptor 4 and inflammatory factor modulation to improve gut microbiota composition.

Network pharmacology integrated with experimental validation revealed the anti-inflammatory effects of Andrographis paniculata.

Inflammation is a key factor in the development and complications of various diseases because it has a complex pathogenesis. Andrographis paniculate (Burm. f.) Nees (Chuan Xinlian) is a well-known form of Traditional Chinese Medicine (TCM) applied in clearing heat and detoxification. Also, it is rich in bioactive lactones, with various anti-inflammatory activities. Here, network pharmacology combined with molecular biology experimental approach was used to predict and verify the potential molecular mechanism of Chuan Xinlian in treating inflammation. The bioactive ingredients of Chuan Xinlian were obtained from the TCMSP database and literature. Besides, the targets of Chuan Xinlian and inflammation were collected based on the multi-source databases and used to generate the PPI network. Network topology analysis and functional enrichment analysis were used to screen hub genes and their mechanisms. Molecular docking simulation was performed to evaluate the binding activity between the predicted hub genes and the bioactive ingredients. Additionally, LPS-induced NO production in RAW264.7 cell inflammatory response, RT-PCR and Western blot were used to validate the efficacy of the Chuan Xinlian in the treatment of inflammation. Network analysis outcomes indicated that five targets (IL-6, VEGFA, PTGST2, TNF-α, and MMP-9) were identified as the key targets of Chuan Xinlian in the treatment of inflammation. Further, molecular docking findings revealed that the majority of the bioactive ingredients exhibited a strong binding efficacy towards the predicted hub genes. Functional analysis results showed that the potential mechanisms were primarily concentrated in key pathways including cancer, immunology, and inflammation process. Moreover, RT-PCR and Western blot analysis indicated that Chuan Xinlian extract suppressed the production of inflammatory mediators with anti-inflammatory effects. Our study shows that Chuan Xinlian potentially exerts an anti-inflammatory effect via key pathways including cancer, immunology, and inflammation process. This suggests that Chuan Xinlian has a potential anti-inflammatory action, thereby providing a scientific reference for clinical studies.

Molecular mechanism of the anti-inflammatory effects of Sophorae Flavescentis Aiton identified by network pharmacology.

Inflammation, a protective response against infection and injury, involves a variety of biological processes. Sophorae Flavescentis (Kushen) is a promising Traditional Chinese Medicine (TCM) for treating inflammation, but the pharmacological mechanism of Kushen's anti-inflammatory effect has not been fully elucidated. The bioactive compounds, predicted targets, and inflammation-related targets of Kushen were obtained from open source databases. The "Component-Target" network and protein-protein interaction (PPI) network were constructed, and hub genes were screened out by topological analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on genes in the PPI network. Furthermore, nitric oxide (NO) production analysis, RT-PCR, and western blot were performed to detect the mRNA and protein expression of hub genes in LPS-induced RAW264.7 cells. An immunofluorescence assay found that NF-κB p65 is translocated. A total of 24 bioactive compounds, 465 predicted targets, and 433 inflammation-related targets were identified and used to construct "Component-Targets" and PPI networks. Then, the five hub genes with the highest values-IL-6, IL-1ß, VEGFA, TNF-α, and PTGS2 (COX-2)- were screened out. Enrichment analysis results suggested mainly involved in the NF-κB signaling pathway. Moreover, experiments were performed to verify the predicted results. Kushen may mediate inflammation mainly through the IL-6, IL-1ß, VEGFA, TNF-α, and PTGS2 (COX-2), and the NF-κB signaling pathways. This finding will provide clinical guidance for further research on the use of Kushen to treat inflammation.

Assessing immune infiltration and the tumor microenvironment for the diagnosis and prognosis of sarcoma.

BACKGROUND: Sarcomas, cancers originating from mesenchymal cells, are comprehensive tumors with poor prognoses, yet their tumorigenic mechanisms are largely unknown. In this study, we characterize infiltrating immune cells and analyze immune scores to identify the molecular mechanism of immunologic response to sarcomas. METHOD: The "CIBERSORT" algorithm was used to calculate the amount of L22 immune cell infiltration in sarcomas. Then, the "ESTIMATE" algorithm was used to assess the "Estimate," "Immune," and "Stromal" scores. Weighted gene co-expression network analysis (WGCNA) was utilized to identify the significant module related to the immune therapeutic target. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the "clusterProfiler" package in R for annotation and visualization. RESULTS: Macrophages were the most common immune cells infiltrating sarcomas. The number of CD8 T cells was negatively associated with that of M0 and M2 macrophages, and positively associated with M macrophages in sarcomas samples. The clinical parameters (disease type, gender) significantly increased with higher Estimate, Immune, and Stromal scores, and with a better prognosis. The blue module was significantly associated with CD8 T cells. Functional enrichment analysis showed that the blue module was mainly involved in chemokine signaling and the PI3K-Akt signaling pathway. CD48, P2RY10 and RASAL3 were identified and validated at the protein level. CONCLUSION: Based on the immune cell infiltration and immune microenvironment, three key genes were identified, thus presenting novel molecular mechanisms of sarcoma metastasis.

Co-expression network analysis identifies a gene signature as a predictive biomarker for energy metabolism in osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is a common malignant bone tumor originating in the interstitial tissues and occurring mostly in adolescents and young adults. Energy metabolism is a prerequisite for cancer cell growth, proliferation, invasion, and metastasis. However, the gene signatures associated with energy metabolism and their underlying molecular mechanisms that drive them are unknown. METHODS: Energy metabolism-related genes were obtained from the TARGET database. We applied the "NFM" algorithm to classify putative signature gene into subtypes based on energy metabolism. Key genes related to progression were identified by weighted co-expression network analysis (WGCNA). Based on least absolute shrinkage and selection operator (LASSO) Cox proportional regression hazards model analyses, a gene signature for the predication of OS progression and prognosis was established. Robustness and estimation evaluations and comparison against other models were used to evaluate the prognostic performance of our model. RESULTS: Two subtypes associated with energy metabolism was determined using the "NFM" algorithm, and significant modules related to energy metabolism were identified by WGCNA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) suggested that the genes in the significant modules were enriched in kinase, immune metabolism processes, and metabolism-related pathways. We constructed a seven-gene signature consisting of SLC18B1, RBMXL1, DOK3, HS3ST2, ATP6V0D1, CCAR1, and C1QTNF1 to be used for OS progression and prognosis. Upregulation of CCAR1, and C1QTNF1 was associated with augmented OS risk, whereas, increases in the expression SCL18B1, RBMXL1, DOK3, HS3ST2, and ATP6VOD1 was correlated with a diminished risk of OS. We confirmed that the seven-gene signature was robust, and was superior to the earlier models evaluated; therefore, it may be used for timely OS diagnosis, treatment, and prognosis. CONCLUSIONS: The seven-gene signature related to OS energy metabolism developed here could be used in the early diagnosis, treatment, and prognosis of OS.

Exploring the mechanism of action Xianlingubao Prescription in the treatment of osteoporosis by network pharmacology.

In this study, the network pharmacology analysis method was used to explore the bioactive components and targets of Xianlinggubao (XLGB) and further elucidate its potential biological mechanisms of action in the treatment of osteoporosis (OP). The bioactive compounds and predictive targets of XLGB were collected from the traditional Chinese medicine systems pharmacology databases and analysis platform(TCMSP), the Encyclopeida of traditional Chinese medicine (ETCM), traditional Chinese medicine Databse@Taiwan, ChEMBL, STITCH, and SymMap database. The targets corresponding to OP were obtained by using Online Mendelian Inheritance in Man® (OMIM), GeneCards, the National Center for Biotechnology Information-Gene database. The XLGB-OP targets were obtained by intersecting with the targets of XLGB and OP. Protien-Protien interaciton (PPI) network was constructed using STRING online database and analyzed using Cytoscape 3.7.0 software to screen out hub genes. Gene ontology (GO) and KEGG enrichment analysis of the target in the PPI network was conducted using the ClusterProfiler package in R with adjusted p-value<0.05. A total of 65 XLGB bioactive compounds were screened corresponding to 776 XLGB targets and 2556 OP targets. The GO analysis and KEGG enrichment analyses suggested XLGB played a therapeutic roles in OP treatment via the interleukin-17 signaling pathway, hypoxia-inducible factor-1 signaling pathway, insulin resistance, Th-17 signaling pathway, etc. Five hub genes (AKT1, MAPK1, MAPK8, TP53, and STAT3) were screened using the degree algorithm, and molecular docking stimulation results showed that most bioactive compounds of XLGB had strong binding efficiency with hub genes. Overall, this study laid the foundation for further in vivo and in vitro experimental research and expanded the clinical applications of XLGB.

Identification of key genes and expression profiles in osteoarthritis by co-expressed network analysis.

BACKGROUND: The underlying molecular characteristics of osteoarthritis (OA), a common age-related joint disease, remains elusive. Here, we aimed to identify potential early diagnostic biomarkers and elucidate underlying mechanisms of OA using weighted gene co-expression network analysis (WGCNA). MATERIAL AND METHODS: We obtained the gene expression profile dataset GSE55235, GSE55457, and GSE55584, from the Gene Expression Omnibus. WGCNA was used to investigate the changes in co-expressed genes between normal and OA synovial membrane samples. Modules that were highly correlated to OA were subjected to functional enrichment analysis using the R clusterProfiler package. Differentially expressed genes (DEGs) between the two samples were screened using the "limma" package in R. A Venn diagram was constructed to intersect the genes in significant modules and DEGs. RT -PCR was used to further verify the hub gene expression levels between normal and OA samples. RESULTS: The preserved significant module was found to be highly associated with OA development and progression (P < 1e-200, correlation = 0.92). Functional enrichment analysis suggested that the antiquewhite4 module was highly correlated to FoxO signaling pathway, and the metabolism of fatty acids and 2-oxocarboxylic acid. A total of 13 hub genes were identified based on significant module network topology and DEG analysis, and RT-PCR confirmed that these genes were significantly increased in OA samples compared with that in normal samples. CONCLUSIONS: We identified 13 hub genes correlated to the development and progression of OA, which may provide new biomarkers and drug targets for OA.

Treatment of simple bone cysts of the humerus by intramedullary nailing and steroid injection.

BACKGROUND: Simple bone cysts (SBCs) are common benign lytic bone lesions in children. This study focused on exploring a clinical treatment method, minimally invasive intramedullary decompression and drainage with elastic stable intramedullary nailing (ESIN) combined with intralesional injections of steroids, and evaluated its effectiveness, complications and morbidity through functional and radiographic outcomes. METHODS: The postoperative recovery of 18 children who suffered from SBCs of humerus was evaluated (mean follow-up, 40 months) from January 2009 to December 2016. These patients (11 males, 7 females; 8 in the left, 10 in the right; mean age, 10.9 years old) were treated with minimally invasive intramedullary decompression and drainage with ESIN combined with intralesional injections of steroids. The diagnosis was based on not only pre-operative typical medical images (X-rays/CT/MRI) but also surgical findings and pathological diagnosis. Radiological and functional outcomes were evaluated according to Capanna and Musculoskeletal Tumor Society (MSTS) score. The interclass differences were analyzed by t-test. RESULTS: According to Capanna and MSTS criteria, after treatment, 14 patients made full recoveries which was presented by all the cysts filled with bone tissue, and 4 patients made partially recoveries, which were presented by cystic spaces partially filled with low density bone. All the cysts responded to treatment method, and there was no cyst recurrence. All except 2 patients had good functional results. One of the two patients had irritation of the end of the nail and one patient had a valgus deformity. CONCLUSIONS: Treatment for SBCs of humerus by minimally invasive intramedullary decompression and drainage with ESIN combined with intralesional injections of steroids is safe, effective and convenient. The clinical effect is satisfactory and worth popularizing.

Network Pharmacology Identifies the Mechanisms of Action of Shaoyao Gancao Decoction in the Treatment of Osteoarthritis.

BACKGROUND Osteoarthritis (OA) affects the health and wellbeing of the elderly. Shaoyao Gancao decoction (SGD) is used in traditional Chinese medicine (TCM) for the treatment of OA and has two active components, shaoyao (SY) and gancao (GC). This study aimed to undertake a network pharmacology analysis of the mechanism of the effects of SGD in OA. MATERIAL AND METHODS The active compounds and candidates of SGD were obtained from the Traditional Chinese Medicine (TCM) Databases@Taiwan, the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the STITCH database, the ChEMBL database, and PubChem. The network pharmacology approach involved network construction, target prediction, and module analysis. Significant signaling pathways of the cluster networks for SGD and OA were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. RESULTS Twenty-three bioactive compounds were identified, corresponding to 226 targets for SGD. Also, 187 genes were closely associated with OA, of which 161 overlapped with the targets of SGD and were considered to be therapeutically relevant. Functional enrichment analysis suggested that SGD exerted its pharmacological effects in OA by modulating multiple pathways, including cell cycle, cell apoptosis, drug metabolism, inflammation, and immune modulation. CONCLUSIONS A novel approach was developed to systematically identify the mechanisms of the TCM, SGD in OA using network pharmacology analysis.

Integrated analysis of a competing endogenous RNA network reveals key lncRNAs as potential prognostic biomarkers for human bladder cancer.

Human bladder cancer (BCa) is one of the most commonly diagnosed malignancies worldwide. It has high recurrence rates and low-grade malignancy, thus representing an important public health concern. An increasing number of studies suggest that long-noncoding RNAs (lncRNAs) play important roles in various biological processes and disease pathologies, including cancer.We analyzed the expression profiles of lncRNA, miRNA, and mRNA, along with the clinical information of BCa patients collected from the Cancer Genome Atlas database to identify lncRNA biomarkers for prognosis. We also constructed an lncRNA-miRNA-mRNA global triple network (competitive endogenous RNA network) by bioinformational approach.This BCa lncRNA-miRNA-mRNA network consisted of 23 miRNA nodes, 52 mRNA nodes, 59 lncRNA nodes, and 365 edges. Subsequent gene ontology (GO) and pathway analyses were performed using BinGO for Cytoscape and Database for Annotation, Visualization, and Integration Discovery, respectively, highlighting important GO terms and pathways that were enriched in the network. Subnetworks were created using 3 key lncRNAs (MAGI2-AS3, ADAMTS9-AS2, and LINC00330), revealing associations with BCa-linked mRNAs and miRNAs. Finally, an analysis of significantly differentiating RNAs found 6 DElncRNAs (AC112721.1, ADAMTS9-AS1, ADAMTS9-AS2, HCG22, MYO16-AS1, and SACS-AS1), 1 DEmiRNA (miRNA-195), and 6 DEmRNAs (CCNB1, FAM129A, MAP1B, TMEM100, AIFM3, and HOXB5) that correlated with BCa patient survival.Our results provide a novel perspective from which to study the lncRNA-related ceRNA network in BCa, contributing to the development of future diagnostic biomarkers and therapeutic targets.

Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis.

Rheumatoid arthritis (RA) and osteoarthritis (OA) comprise the most common forms of arthritis. The aim of this study was to identify differentially expressed genes (DEGs) and associated biological processes between RA and OA using a bioinformatics approach to elucidate their potential pathogenesis.The gene expression profiles of the GSE55457 datasets, originally produced through use of the high-throughput Affymetrix Human Genome U133A Array, were downloaded from the Gene Expression Omnibus (GEO) database. The GSE55457 dataset contains information from 33 samples, including 10 normal control (NC) samples, 13 RA samples, and 10 OA samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed to identify functional categories and associated molecular and biochemical pathways, respectively, for the identified DEGs, and a protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape software.GO and KEGG results suggested that several biological pathways (ie, "immune response," "inflammation," and "osteoclast differentiation") are commonly involved in the development of both RA and OA, whereas several other pathways (eg, "MAPK signaling pathway," and "ECM-receptor interaction") presented significant differences between these disorders.This study provides further insights into the underlying pathogenesis of RA and OA, which may facilitate the diagnosis and treatment of these diseases.

[Spatial relation study between the compressed spinal cord and the cervical pedicle].

OBJECTIVE: To study the relationship between cervical pedicle and compressed spinal cord. METHODS: One hundred and five patients (53 male,52 female,age from 29 to 80 years) with cervical spondylotic myelopathy who needed surgery were included from December 2011 to January 2013 in Shengjing Hospital. Plain MRI scan was used for cross section of C4 - C7 vertebral bodies parallel to the axis of bilateral pedicle, and the images were sent to the workstation. PACS system was applied to measure the anatomical parameters related to the security of cervical pedicle screw, including the shortest distance from medial left/right cervical pedicle to the cervical spinal cord (LH/RH), and the smallest angle between the longitudinal axis of left/right cervical pedicle and the screw which was assumed to just touch the cervical spinal cord (LSA/RSA). All these data in each segment were classified according to compression or not:with compression and without compression. Twelve cases were selected and measured by MRI and 3D cervical CT for spinal canal width D, namely the straight-line distance between the medial margins of cervical pedicle. And the results of two methods were compared to see whether there were statistical differences. RESULTS: At C4, LH was (7.2±1.3) mm, RH was (6.7±1.4) mm, and the average was (6.9±1.4) mm; at C5, LH was (7.7±1.4) mm, RH was (6.7±1.4) mm, and the average was (7.2±1.5) mm; at C6, LH was (8.2±1.5) mm, RH was (6.9±1.3) mm, and the average was (7.5±1.5) mm; at C7, LH was (8.2±1.4) mm, RH was (7.3±2.1) mm, and the average was (7.7±1.8) mm. At C4, LSA was 34.4°±4.2°, RSA was 34.4°±5.2° and the average angle was 34.4°±4.7°; at C5, LSA was 35.9°±5.2°, RSA was 34.6°±5.4° and the average angle was 35.3°±5.3°; at C6, LSA was 37.4°±4.8°, RSA was 34.8°±4.8° and the average angle was 36.1°±5.0°; at C7, LSA was 39.2°±5.8°, RSA was 37.1°±5.2° and the average angle was 38.1°±5.6°; There were no statistically significant differences between segments with and without compression in H, SA and D (all P>0.05). CONCLUSIONS: There is security space between the medial vertebral pedicle and compressed spinal cord. There is individual variation in security space. It is very necessary to identify security space before surgery by MRI, emphasize individual procedure and avoid spinal cord injury.

A rapid and sensitive LC-MS/MS method for quantification of 3,29-dibenzoyl rarounitriol in rat plasma: application to a pharmacokinetic study.

A rapid, sensitive and high-throughput liquid chromatography-tandem mass spectrometry was established and validated to assay the concentrations of 3,29-dibenzoyl rarounitriol in rat plasma. Plasma samples were processed by liquid-liquid extraction with ethyl acetate and separated on a Hypersil Gold C18 column (50 × 4.6 mm, 3 µm) at an isocratic flow rate of 0.5 mL/min using methanol-10 mm ammonium acetate-formic acid (90:10:0.1, v/v/v) as mobile phase. The total run time was 5 min for each sample. MS/MS detection was accomplished in selected reaction monitoring mode with positive electrospray ionization. The calibration curve was linear over the concentration range of 0.125-50 ng/mL with lower limit of quantification of 0.125 ng/mL. The intra- and inter-day precisions were <10.1% in terms of coefficient of variation, and the accuracy was within ±11.7% in terms of relative error. The developed method was successfully applied to a pharmacokinetic study of 3,29-dibenzoyl rarounitriol following intragastric administration of 3.65 mg/kg to Wistar rats.