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Objective:To study the non-target metabolomics analysis and to analyze the metabolomic changesof cerebrospinal fluid (CSF) in patients with tuberculous meningitis.Methods:Case-control study. From July 2018 to July 2019, 20 cerebrospinal fluid specimens of diagnosed patients with tuberculous meningitis were collectedin the department of neurology from the first medical center of the PLA general hospital and the eighth medical center of the PLA general hospital and 20 CSF without tuberculous meningitis as the control. Among them, there were 12 males and 8 femalesin the tuberculous meningitis group, aged (37.9±16.1) years; there were 13 males and 7 femalesin the control group, aged (34.7±14.8) years. Using ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) technology with three different mode, namely reverse phase chromatography positive ion mode, reverse phase chromatography negative ion mode and hydrophilic chromatography positive ion mode,to detectthe metabolic fingerprints of patients′CSF and analyzed by SIMCA software for orthogonal partial least squares discriminant analysis (OPLS-DA). The variable importance projection value of OPLS-DA model (threshold value>1) plus the P value of t-test (P<0.05) was applied to find the differential metabolites in the cerebrospinal fluid of the two groups of patients.Results:Ten differential metabolites were found in CSF, including L-isoleucine, L-phenylalanine, L-kynurenine, L-methionine, L-tyrosine acid, dimethylglycine, L-alanine, L-threonine, L-histidine and L-lysine, and all of them were up-regulated in the tuberculous meningitis group.Conclusion:Changesof the amino acid metabolism found in the cerebrospinal fluid of tuberculous meningitis patients can provide basis for differential diagnosis and basic molecular research of tuberculous meningitis.
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Objective:To investigate the omics mechanism of SARS-related immune injury and predict targeted therapeutic drugs through clinical bioinformatics analysis of the transcriptome data of SARS virus in order to provide reference for clinical treatment of COVID-19.Methods:The transcriptome data of SARA virus were collected from the Gene Expression Oibus (GEO) and used to screen differential genes. Enrichment analysis and protein interaction analysis were performed to investigate the mechanism of immune damage associated with SARS. A platform of epigenetics in precision medicine (EpiMed) was established to predict potential therapeutic drugs.Results:The mechanism of SARS-related immune injury was complex, involving affecting the function of immune cells through signaling pathways such as Toll-like receptors, increasing cytokines in plasma through Th17 signaling pathway and inducing autoimmune responses after autoantibodies were generated by molecules such as IL-6, NF-κB, and TNF. Drugs such as Chuanqiong and Etanercept might have therapeutic effects on SARS-related immune damage.Conclusions:SARS virus could cause abnormal expression of many immune-related molecules and signaling pathways. Drugs such as Chuanqiong and Etanercept might have therapeutic effects on SARS-related immune damage. This study might provide reference for clinical treatment of COVID-19.
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Objective:To analyze the inflammatory mechanism and potential intervention drugs related to angiotensin converting enzyme 2 (ACE2) inhibitory mutations in order to provide reference for the treatment of corona virus disease 2019 (COVID-19).Methods:The data of lung adenocarcinoma with ACE2 mutations were screened from the cancer genome atlas (TCGA) database. The data were analyzed by R program language edgeR package and cluster Profiler package, gene ontology (GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Using String online analysis website for protein-protein interaction (PPI) network analysis, screening out the core genes, and finally using the Epigenomic Precision Medicine Prediction Platform (EpiMed) for multi-group association analysis of key genes, and drug candidates prediction.Results:A total of 1 005 differential genes were obtained, of which 91 were up-regulated and 914 down-regulated. A total of 71 GO were enriched, including 45 items related to biological processes, 16 items related to cell components, and 10 items related to molecular function. A total of 13 KEGG pathways were enriched, mainly in inflammatory pathways, various viral infectious diseases, transcriptional regulation, drug metabolism and protein digestion and absorption pathways. The differentially expressed genes were introduced into String online analysis website for PPI network analysis, a total of 252 proteins were obtained, and 10 core genes were H2A clustered histone 16(HIST1H2AL), H3 clustered histone 2 (HIST1H3B), H3 clustered histone 7 (HIST1H3F), H3 clustered histone 11 (HIST1H3I), H3 clustered histone 3 (HIST1H3C), H2B clustered histone 3 (HIST1H2BB), H2B clustered histone 6 (HIST1H2BI), H4 clustered histone 2 (HIST1H4B), H1-4 linker histone (HIST1H1E), H2A clustered histone 4 (HIST1H2AB). Interferon-α, resveratrol, celecoxib, heartleaf houttuynia herb, weeping forsythia capsule, dexamethasone, Chinese pulsatilla root, tumor necrosis factor-α inhibitors, liquorice root and famciclovir might be drugs for the treatment of ACE2 mutation-related inflammation.Conclusions:Inflammation associated with ACE2 inhibitory mutations is similar to the pathogenesis of COVID-19, which could lead to disease by promoting the activation of inflammatory pathways such as mitogen-activated protein kinase (MAPK), the Janus kinase signal transducer and activator of transcription (JAK/STAT), mammalian target of rapamycin (mTOR). Celecoxib, interferon and resveratrol may have the potential therapeutic effects on COVID-19.
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Objective Toinvestigatestatistically significant peptide peaks as biomarkersto diagnose osteoarticular tuberculosis, matrix-assisted laser desorption/ ionization time of flight mass spectrometry (MALDI-TOF MS) was applied to identify the characteristic fingerprint among the serum of patients with osteoarticular tuberculosis, rheumatoid arthritis and healthy adults.Methods Clinical Study. Serum samples of untreatedpatients with osteoarticular tuberculosis and rheumatoid arthritis were collected from August 2018 to December 2018, and serum samples of healthy adults from physical examination were collected as control. After analysis with MALDI-TOF MS, the serum peptide fingerprint datawas imported into software, and protein polypeptide peaks with obvious differences were screened to establish diagnostic models.Results Established the diagnostic model of osteoarticular tuberculosis and healthy adults with m/z 2943.9, 5929.6, 7615.4 and 9033.8 as differential protein polypeptides, the diagnostic model of osteoarticular tuberculosis and rheumatoid arthritis with m/z 4195.6, 5847.6, 5929.6 and 7748.6 as differential protein polypeptides. To these two models, the sensitivity were 95.00％ and 97.50％, respectively. The specificity were 85.71％ and 88.46％, respectively. The accuracy rates were 89.58％ and 92.39％, respectively. The AUC value of ROC curves were 0.8859 and 0.8709, respectively. Conclusions By mass spectrometry and software analysis, the serum protein polypeptides with statistical difference were found successfully. The related diagnostic modelsarealso established, which has certain reference value for auxiliary diagnosis of osteoarticular tuberculosis.
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Objective To explore the application of CT value in calculating the proton incident energy in proton treatment planning system. Methods Bethe-Block formula and the formula for calculating the proton range were analyzed to study the correlation of the range of proton beam ( 70-250 MeV ) between a variety of radiation equivalent material and water. Procedure of Monte Carlo SRIM2008 was used to verify the possibility of a constant proportional coefficient of range ( Ci ). The proportional coefficient ( Ci ) of range in radiation-equivalent material and the CT value were fitted by using Origin 8.0 software to study the functional relation of CT value and Ci. The actual range of proton was equivalent to a range of water and incident proton energy could be calculated. Results There was a constant range of Ci of proton beam (70-250 MeV) between a variety of radiation equivalent material and water. There was a functional relation between CT value and Ci ( r = 0.999). The actual range of proton in radiation equivalent material can be equivalent to a range of the water. Conclusions CT values and a range of proportional coefficient ( Ci ),and the actual required range of the tumor could be used to accurately calculate the water equivalent range,and the incident proton energy to the position of Bragg peak. A new exploration for using CT technology in proton treatment planning system could be obtained.
