BACKGROUND:Endoplasmic reticulum stress is closely associated with the occurrence and progression of osteoarthritis,but the key genes and regulatory mechanisms remain unclear.OBJECTIVE:Utilizing bioinformatics to identify crucial endoplasmic reticulum stress-related genes in osteoarthritis,followed by experimental validation in cell models,aiming to offer new strategies for the prevention and treatment of osteoarthritis from the perspective of endoplasmic reticulum stress.METHODS:Osteoarthritis-related dataset GSE55235 was downloaded from the GEO database.Differential genes in synovial tissue of osteoarthritis were obtained through WGCNA machine learning algorithm and intersected with endoplasmic reticulum stress-related genes from the GeneCard database to acquire differential endoplasmic reticulum stress-related genes in osteoarthritis(ERSDEGs).These genes underwent GO and KEGG enrichment analysis,construction of a protein-protein interaction network,and validation of diagnostic efficiency in external datasets.Human primary synovioblast model of osteoarthritis was constructed.The control group was not treated,and the experimental group received 20 ng/mL lipopolysaccharide to simulate osteoarthritic synoviocyte modeling.Real-time fluorescence quantitative PCR was then performed to validate the expression level of each differential gene followed by immune infiltration analysis.RESULTS AND CONCLUSION:A total of 27 key endoplasmic reticulum stress-related genes in osteoarthritis were identified.GO enrichment analysis revealed that these genes were mainly enriched in collagen metabolism,chemokine,antigen binding,and immunoglobulin receptor binding processes.KEGG analysis indicated that they were mainly enriched in pathways such as rheumatoid arthritis and relaxin signaling pathways.The protein-protein interaction network was constructed,and the top five genes with the highest scores were identified using the Degree algorithm in Cytoscape software,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,collagen type 1 alpha 1,and chemokine C-X-C motif ligand 12.Immune infiltration analysis showed that immune cells were mainly distributed in M2 macrophages,chemokine C-X-C motif ligand 12 showed a significant positive correlation with resting mast cells(r=0.70,P＜0.001)and a significant negative correlation with resting memory CD4+T cells(r=-0.72,P＜0.001).Matrix metallopeptidase 9 showed a significant positive correlation with MO macrophages(r=0.94,P＜0.001).Collagen type 1 alpha 1 was significantly positively correlated with resting NK cells(r=0.77,P＜0.001)and MO macrophages(r=0.76,P＜0.001).Receiver operator characteristic curve analysis in external datasets GSE77298 and GSE1919 showed that the five key genes had good disease prediction value.In vitro cell experiments demonstrated significant differences in the expression levels of matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12 in the osteoarthritic cell model compared to the control group.These results showed that the key genes related to endoplasmic reticulum stress in osteoarthritis,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12,influence the occurrence and development of osteoarthritis through the links of collagen degradation and immune regulation,which are expected to provide new insights into the targeted treatment of osteoarthritis.

Objective To investigate the effects of different contrast injection schemes on the image quality of triple-rule-out com-puted tomography angiography(TRO-CTA).Methods A total of 691 patients with acute chest pain who underwent TRO-CTA exami-nation from multiple centers were prospectively selected and randomly divided into mixed group and unmixed group according to dif-ferent contrast injection methods.The image quality of aorta,pulmonary artery and coronary artery in the two groups was evaluated subjectively and objectively and the radiation dose was calculated.Results There were no significant differences in subjective image quality scores,aorta and coronary CT values,signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)between the two groups(P>0.05),while there were significant differences in pulmo-nary CT values,SNR,CNR and radiation dose between the two groups(P<0.05).Conclusion The utilization of a mixed contrast injection scheme in TRO-CTA can satisfy diagnostic require-ments while ensuring a low proportional dosage and reduced radiation dose,which has clinical application value.

BACKGROUND:Endoplasmic reticulum stress is closely associated with the occurrence and progression of osteoarthritis,but the key genes and regulatory mechanisms remain unclear.OBJECTIVE:Utilizing bioinformatics to identify crucial endoplasmic reticulum stress-related genes in osteoarthritis,followed by experimental validation in cell models,aiming to offer new strategies for the prevention and treatment of osteoarthritis from the perspective of endoplasmic reticulum stress.METHODS:Osteoarthritis-related dataset GSE55235 was downloaded from the GEO database.Differential genes in synovial tissue of osteoarthritis were obtained through WGCNA machine learning algorithm and intersected with endoplasmic reticulum stress-related genes from the GeneCard database to acquire differential endoplasmic reticulum stress-related genes in osteoarthritis(ERSDEGs).These genes underwent GO and KEGG enrichment analysis,construction of a protein-protein interaction network,and validation of diagnostic efficiency in external datasets.Human primary synovioblast model of osteoarthritis was constructed.The control group was not treated,and the experimental group received 20 ng/mL lipopolysaccharide to simulate osteoarthritic synoviocyte modeling.Real-time fluorescence quantitative PCR was then performed to validate the expression level of each differential gene followed by immune infiltration analysis.RESULTS AND CONCLUSION:A total of 27 key endoplasmic reticulum stress-related genes in osteoarthritis were identified.GO enrichment analysis revealed that these genes were mainly enriched in collagen metabolism,chemokine,antigen binding,and immunoglobulin receptor binding processes.KEGG analysis indicated that they were mainly enriched in pathways such as rheumatoid arthritis and relaxin signaling pathways.The protein-protein interaction network was constructed,and the top five genes with the highest scores were identified using the Degree algorithm in Cytoscape software,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,collagen type 1 alpha 1,and chemokine C-X-C motif ligand 12.Immune infiltration analysis showed that immune cells were mainly distributed in M2 macrophages,chemokine C-X-C motif ligand 12 showed a significant positive correlation with resting mast cells(r=0.70,P＜0.001)and a significant negative correlation with resting memory CD4+T cells(r=-0.72,P＜0.001).Matrix metallopeptidase 9 showed a significant positive correlation with MO macrophages(r=0.94,P＜0.001).Collagen type 1 alpha 1 was significantly positively correlated with resting NK cells(r=0.77,P＜0.001)and MO macrophages(r=0.76,P＜0.001).Receiver operator characteristic curve analysis in external datasets GSE77298 and GSE1919 showed that the five key genes had good disease prediction value.In vitro cell experiments demonstrated significant differences in the expression levels of matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12 in the osteoarthritic cell model compared to the control group.These results showed that the key genes related to endoplasmic reticulum stress in osteoarthritis,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12,influence the occurrence and development of osteoarthritis through the links of collagen degradation and immune regulation,which are expected to provide new insights into the targeted treatment of osteoarthritis.

Objective To investigate the effects of different contrast injection schemes on the image quality of triple-rule-out com-puted tomography angiography(TRO-CTA).Methods A total of 691 patients with acute chest pain who underwent TRO-CTA exami-nation from multiple centers were prospectively selected and randomly divided into mixed group and unmixed group according to dif-ferent contrast injection methods.The image quality of aorta,pulmonary artery and coronary artery in the two groups was evaluated subjectively and objectively and the radiation dose was calculated.Results There were no significant differences in subjective image quality scores,aorta and coronary CT values,signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)between the two groups(P>0.05),while there were significant differences in pulmo-nary CT values,SNR,CNR and radiation dose between the two groups(P<0.05).Conclusion The utilization of a mixed contrast injection scheme in TRO-CTA can satisfy diagnostic require-ments while ensuring a low proportional dosage and reduced radiation dose,which has clinical application value.

BACKGROUND:Glucose metabolism plays a crucial role in maintaining the normal physiological function of the body.Glucose metabolism disorder can lead to a range of health problems.At present,the molecular mechanism of glucose metabolism and potential gene targets in osteoarthritis need to be further studied.OBJECTIVE:To analyze the genes related to glucose metabolism in osteoarthritis by bioinformatics methods,and to verify them by cell experiments in vitro,so as to provide new ideas for prevention and treatment of osteoarthritis from the perspective of glucose metabolism.METHODS:Differentially expressed genes and glucose metabolism related genes were screened out from GEO database and GeneCards database.The genes related to both osteoarthritis and glucose metabolism were obtained.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were used to screen the functions and pathways of these genes.To further investigate the interactions between these genes,a protein-protein interaction network was constructed and computational methods using Cytoscape software were utilized to identify key genes(Hub genes)for osteoarthritis glucose metabolism.In addition,CIBERSORT algorithm was used to analyze immune cell infiltration in GSE98918 data set.Finally,the expression of Hub gene was verified by cell experiment in vitro.RESULTS AND CONCLUSION:A total of 134 osteoarthritis glucose metabolism-related genes were obtained.GO enrichment analysis showed that GO was mainly involved in the reaction of toxic substances,the positive regulation of inflammatory reaction,the reaction of lipopolysaccharide and so on.KEGG enrichment analysis showed that it was closely related to PI3K-Akt signaling pathway,interleukin-17 signaling pathway,and AGE-RAGE signaling pathway in diabetic complications.Macrophages,monocytes,resting natural killer cells,regulatory T cells,and CD8+T cells were the main infiltrating cells obtained by immune infiltration analysis.In vitro cell experiments showed that the expression of Hub genes SERPINF1,TAC1,GLUL,APOE,and TMEM176A in the experimental group was significantly different from that in the control group.The mRNA expression of HLA-DRA was not statistically significant.The results show that SERPINF1,TAC1,Glul,APOE,and TMEM176A may be the key genes of glucose metabolism in osteoarthritis,and may be potential new targets for the prevention and treatment of osteoarthritis.

BACKGROUND:Glucose metabolism plays a crucial role in maintaining the normal physiological function of the body.Glucose metabolism disorder can lead to a range of health problems.At present,the molecular mechanism of glucose metabolism and potential gene targets in osteoarthritis need to be further studied.OBJECTIVE:To analyze the genes related to glucose metabolism in osteoarthritis by bioinformatics methods,and to verify them by cell experiments in vitro,so as to provide new ideas for prevention and treatment of osteoarthritis from the perspective of glucose metabolism.METHODS:Differentially expressed genes and glucose metabolism related genes were screened out from GEO database and GeneCards database.The genes related to both osteoarthritis and glucose metabolism were obtained.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were used to screen the functions and pathways of these genes.To further investigate the interactions between these genes,a protein-protein interaction network was constructed and computational methods using Cytoscape software were utilized to identify key genes(Hub genes)for osteoarthritis glucose metabolism.In addition,CIBERSORT algorithm was used to analyze immune cell infiltration in GSE98918 data set.Finally,the expression of Hub gene was verified by cell experiment in vitro.RESULTS AND CONCLUSION:A total of 134 osteoarthritis glucose metabolism-related genes were obtained.GO enrichment analysis showed that GO was mainly involved in the reaction of toxic substances,the positive regulation of inflammatory reaction,the reaction of lipopolysaccharide and so on.KEGG enrichment analysis showed that it was closely related to PI3K-Akt signaling pathway,interleukin-17 signaling pathway,and AGE-RAGE signaling pathway in diabetic complications.Macrophages,monocytes,resting natural killer cells,regulatory T cells,and CD8+T cells were the main infiltrating cells obtained by immune infiltration analysis.In vitro cell experiments showed that the expression of Hub genes SERPINF1,TAC1,GLUL,APOE,and TMEM176A in the experimental group was significantly different from that in the control group.The mRNA expression of HLA-DRA was not statistically significant.The results show that SERPINF1,TAC1,Glul,APOE,and TMEM176A may be the key genes of glucose metabolism in osteoarthritis,and may be potential new targets for the prevention and treatment of osteoarthritis.

Objective To investigate the molecular mechanism of Shema Zhichuan Liquid in the treatment of neutrophilic asthma(NA)based on network pharmacology and in vivo experiments.Methods(1)The TCMSP,literature search and Swiss ADME and Swiss Target Prediction databases were used to search and screen the active components and their targets of Shema Zhichuan Liquid.OMIM,GeneCards,DisGeNET and DrugBank databases were used to search and screen NA disease-related targets.The intersection of the active components and NA disease-related targets of Shema Zhichuan Liquid was obtained through the microbiology platform to obtain the potential targets of Shema Zhichuan Liquid for the treatment of NA(common targets).Cytoscape 3.8 software was used to construct the network of"Chinese medicinals-active components-potential targets".The PPI network of potential targets was established by STRING database,and the core targets were obtained by analysing the built-in Mcode plug-in.The Metascape platform was used to enrich the gene ontology(GO),Kyoto Encyclopaedia of Genes and Genomes(KEGG)pathways for the potential targets.(2)BALB/C mice were acclimatised and fed for 1 week and randomly divided into a blank group,NA model group,low-dose group(2.5 g·kg-1)and high-dose group of Shema Zhichuan Liquid(10 g·kg-1),and control group of Dexamethasone(1 mg·kg-1);the NA mouse model was replicated by intraperitoneal injection of sensitizer(OVA+CFA)and nebulized inhalation excitation.OVA/CFA(20 μg OVA+75 μg CFA,0.3 mL)was injected intraperitoneally to sensitize on days 0,7 and 14 respectively,and 5%OVA suspension was nebulized on days 21-30(8 mL each time,40 minutes each time,once a day);1 hour before nebulisation,each group was administered by gastric gavage,and the Dexamethasone control group was administered by intraperitoneal injection once a day.The pathological changes of mouse lung tissue were observed by HE staining;IL-8 content in alveolar lavage fluid was detected by ELISA;mRNA expression levels of NLRP3 and CXCR2 were detected by RT-qPCR;and p-mTOR protein expression levels was detected by immunohistochemistry.Results(1)A total of 826 active component targets and 154 NA disease-related targets were obtained,and 51 potential targets(common targets)for the treatment of NA were obtained from the intersection of the active component and the NA disease-related targets of Shema Zhichuan Liquid.Through the network analysis of"Chinese medicinals-active components-potential targets",quercetin,lignocerotoxin,kaempferol,stigmasterol,naringenin and other key active components were obtained.The PPI network analysis of potential targets yielded 29 core targets,including AKT1,IL6,TNF,EGFR,NLRP3,RELA,MIF,CXCR2,VEGFA,etc..The GO functional enrichment analysis yielded 882 biological process entries,33 cellular component entries,and 61 molecular function entries;KEGG analysis yielded 142 signaling pathways,mainly involving TNF signaling pathway,influenza A signaling pathway,Toll-like receptor pathway,MAPK signaling pathway,mTOR signaling pathway and so on.(2)Results of animal experiments:compared with the blank group,mice in the NA model group showed obvious damage to the airway mucosa,structural disorders,a large number of inflammatory cells infiltration,mucosal congestion,oedema,obvious thickening of the alveolar wall,and narrowing of the alveolar lumen;the level of the inflammatory factor IL-8 in the alveolar lavage fluid was significantly elevated(P＜0.05);the mRNA expressions of NLRP3 and CXCR2 in the lung tissues of the mice were significantly up-regulated(P＜0.01),and the protein expression of p-mTOR was significantly increased.Compared with the NA model group,the structural arrangement of bronchial epithelial cells in the mice in the low-and high-dose groups of Shema Zhichuan Liquid was slightly disordered,with a small amount of inflammatory cell infiltration around the airways and blood vessels,and the congestion and edema of the bronchial mucosa were significantly reduced;the mRNA expression of CXCR2 in the lung tissues of the mice was significantly down-regulated(P＜0.01),and the level of expression of p-mTOR protein was significantly reduced.The IL-8 level in the vesicular lavage fluid of mice in the high-dose group was significantly reduced(P＜0.05);the mRNA expression of NLRP3 in the lung tissue of mice in the low-dose group was significantly down-regulated(P＜0.05).Conclusion The therapeutic effect of Shema Zhichuan Liquid on NA may be achieved through the key active components,such as quercetin,lignocerol and kaempferol,acting on the core targets,such as NLRP3 and CXCR2,and regulating the key signaling pathways,such as the TNF signaling pathway,the MAPK signaling pathway,the Toll-like signaling pathway,and the mTOR pathway.

Objective:To develop and validate a liquid chromatography-tandem mass spectrometry method for determining levofloxacin in plasma sample from pediatric patients.Method:This is a prospective, observational study. The clinical residual plasma samples from healthy individuals for physical examination in Children's Hospital Affiliated to Zhengzhou University were collected as blank matrix. Plasma samples from five pediatric patients who did not receive levofloxacin or ciprofloxacin in the department of Respiration were collected for methodological evaluation. In addition, 34 clinical plasma samples from 22 pediatric patients (9 males and 13 females; mean age (8.1±3.7) years) using levofloxacin was collected, and their plasma concentrations were determined. Using ciprofloxacin as the internal standard, levofloxacin in plasma samples was quantified by liquid chromatography-tandem mass spectrometry following protein precipitation using acetonitrile. A C18 column (Shim-pac GIST-HP C18, 2.1 mm×100 mm, 3 μm) and mobile phase composed of water (containing 0.1% formic acid) and acetonitrile (containing 0.1% formic acid) with gradient elution at a flow rate of 0.4 ml/min were used to separate levofloxacin. The column temperature was 40 ℃, injection volume was 1 μl and the total analysis time was 9 min. Levofloxacin and ciprofloxacin were ionized with an ESI source in positive ion mode and detected in multiple reaction monitoring (MRM) mode. The detected ions of levofloxacin and ciprofloxacin were m/z 362.10→318.1 and 332.15→231.05, respectively. The method′s specificity, sensitivity, linearity, precision, accuracy, recovery rate, stability, matrix effect, and carry-over were validated. All statistical analyses were performed with SPSS statistical software (version 17.0). The normality of the data was detected by the K-S test. A P<0.05 was considered statistically significant for two tailed tests. Results:The LC-MS/MS method showed a good linearity within the range of 0.062 5-20 mg/L, with the lower detection limit of levofloxacin of 0.062 5 mg/L. The calibration curve for levofloxacin was Y=0.093X+0.010 ( R2>0.99). Under different quality control levels, the accuracy ranged from 92.57% to 104.39%, and the intra-day and inter-day imprecision ranged from 2.32% to 9.35%. These values were not affected by the normal matrix, 5% hemolysis matrix and 15% hyperlipidemia matrix. Furthermore, the levofloxacin plasma samples were stable in the short term. A total of 34 plasma samples from 22 patients were collected and analyzed. Only 2 plasma samples were below the lower limit of quantification, while the other plasma concentrations of levofloxacin were ranged from 0.091 to 6.755 mg/L. Cmax was (5.52 ± 1.09) mg/L. Conclusion:The LC-MS/MS method meets the requirements of the reference method and requires a small sample size (50 μl), making it suitable for the determination of levofloxacin in plasma from pediatric patients.

Objective: To investigate the role of long non-coding RNA double homeobox A pseudogene 9 (DUXAP9) in head and neck squamous cell carcinoma (HNSCC) and to evaluate the expression level, molecular function and mechanism of DUXAP9 in HNSCC cells. Methods: Differential expression of lncRNAs between normal and tumor tissues in HNSCC tissues were screened using lncRNA microarray, the expression level of DUXAP9 in HNSCC tissues and its relationship with prognosis were analyzed in the TCGA database. The expression levels of DUXAP9 in HNSCC tissues and cell lines were detected using qRT-PCR. The function in HNSCC cells after DUXAP9 silencing was evaluated using the CCK-8 assay, wound healing assay, Transwell migration assay and subcutaneous xenograft assay in nude mice. Changes in the transcription and translation of epithelial-mesenchymal transition (EMT)-related proteins in head and neck squamous cell carcinoma cells after DUXAP9 silencing were detected using qRT-PCR and Western blot. Results: lncRNA microarray results showed that, compared to adjacent normal tissues, DUXAP9 was abnormally upregulated in HNSCC tissues. Analysis from TCGA database showed that, compared to HNSCC patients with low DUXAP9 expression, HNSCC patients with high DUXAP9 expression had poorer survival. The relative expression of DUXAP9 in HNSCC tissues and 4 HNSCC cell lines increased compared to paired adjacent normal tissues as detected using qRT-PCR. Silencing DUXAP9 significantly inhibited the proliferation, migration and expression of EMT-related genes in HNSCC cells. The silencing of DUXAP9 significantly inhibited subcutaneous tumorigenesis of the HNSCC cell line CAL27 in nude mice. Conclusion Silencing DUXAP9 significantly inhibited the proliferation of HNSCC cells and subcutaneous xenografts in nude mice. DUXAP9 may mediate the migration of head and neck squamous cell carcinoma cells via the EMT pathway.