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Objective:To elucidate the change of whole genome expression profile for the effect of melatonin on radiation-induced intestinal injury in mice.Methods:C57BL/6J male mice were administrated with melatonin at 10 mg/kg body weight by intraperitoneal injection once a day for five consecutive days before abdominal irradiation with 14 Gy of γ-rays. Small intestines were harvested 3 d after radiation. GO annotation and KEGG pathway of the differential genes involved in small intestine were explored by DNA microarray analysis.Results:Compared with the control group, 584 differential genes were up-regulated and 538 differential genes were down-regulated for administration group pre-irradiation. The overlapping differential genes were selected from the irradiated mice and the administrated mice pre-irradiation. There were 324 up-regulated genes and 246 down-regulated genes unique to the administrated mice pre-irradiation. GO annotation analysis of the differential genes indicated that the top 15 significantly enriched biological processes for the administrated mice pre-irradiation mainly included autophagosome assembly (GO: 0000045), autophagosome organization (GO: 1905037) and regulation of acute inflammatory response (GO: 0002673). The genes ATG12, ATG16L2 and AMBRA1 were involved in autophagosome assembly and autophagosome organization. The genes C3, CPN1, CD55, CFP, CNR1, C1QA, C2 and CREB3L3 were involved in the regulation of acute inflammation response. KEGG pathway analysis of the differential genes involved indicated that the top 15 significantly enriched pathways for the administrated mice pre-irradiation mainly included O-glycan biosynthesis (hsa00512), glycosphingolipid biosynthesis (hsa00603), ECM-receptor interaction (hsa04512) and biosynthesis of unsaturated fatty acids (hsa01040). qRT-PCR verification showed that the expressions of ATG12 and ATG16L2 genes involved in autophagy for the administrated mice pre-irradiation increased significantly compared with the irradiated mice ( t=2.40, 4.35, P<0.05). Conclusions:The differential genes related with the biological process of autophagy, acute inflammatory response and the pathway of unsaturated fatty acid biosynthesis might be involved in the effect of melatonin on radiation-induced intestinal injury.
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Objective:To investigate whether transplantation of gingival mesenchymal stem cells (GMSCs) can inhibit radiation-induced senescence of alveolar epithelial cells type Ⅱ (AECⅡ) and its role in the prevention of radiation-induced pulmonary fibrosis (RIPF).Methods:Mouse type Ⅱ alveolar epithelial cells (MLE12) were irradiated with 6 Gy X-rays and then co-cultured with GMSCs. The extent of cellular senescence of MLE12 cells was assessed by cell morphology, β-Gal staining, and senescence secretion-associated phenotype (SASP) assay. RIPF model was constructed by unilaterally irradiating the right chest of C57BL/6 mice with 17 Gy X-rays. GMSCs were transplanted 1 d after irradiation. At 180 d after irradiation, the pulmonary organ ratio, HE staining, and Masson staining were used to assess intra-pulmonary structure and interstitial collagen deposition in the lung. β-Gal immunohistochemistry and immunofluorescence co-localization with AECⅡ were measured to assess the degree of cellular senescence in the lung. The SASP expression changes in lung tissue were detected by qRT-PCR. The protein expressions in P53-P21 and P16 pathways were detected by Western blot assay. P21 expression in AECⅡ was detected by immunofluorescence co-localization assay.Results:GMSCs effectively inhibited radiation-induced senescence of MLE12 cells, reduced the ratio of radiation-elevated β-Gal positive cells by 11.8% ( t=6.72, P<0.05), and decreased the expressions of SASP (IL-6, IL-8, IL-1β) ( t=28.43, 28.43, 4.82, P<0.05). GMSCs transplantation improved the survival rate of irradiated mice, prevented radiation-induced alveolar structural collapse thickening and collagen deposition, reduced the number of senescent cells in the irradiated lung tissues by 23.9% ( t=21.83, P<0.05), and inhibited the expressions of SASP ( t=8.86, 20.63, P<0.05). GMSCs also inhibited the expression of P53-P21, P16-related proteins in MLE12 cells and lung tissues of mice after irradiation. Conclusions:GMSCs inhibit senescence-related P53-P21 and P16 pathways, prevent radiation-induced AECⅡ senescence, as well as the development of RIPF.
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Objective To investigate the effects of Olaparib on cell proliferation and radiosensitization of human non-small cell lung cancer cells.Methods Non-small cell lung H460 and H1299 cell lines were cultured in vitro and the cells in logarithmic growth phase were selected for experiments.MTT and colony formation assays were used to determine cell proliferation and radiosensitization,respectively.Single cell gel electrophoresis assay (comet assay) was used to detect irradiation-induced DNA damage.Results The results of MTT assay showed that Olaparib inhibited the proliferation of H460 and H1299 cells in a dose-dependent pattern (all P＜0.05).H1299 cell line was more sensitive to Olaparib than H460 cells.The results of colony formation assay showed that Olaparib enhanced the radiosensitizition of H460 and H1299 cells (all P＜0.05).The results of comet assay showed that Olaparib increased γ ray-induced DNA damage.Conclusions Olapani can enhance the radiosensitization of human non-small cell lung cancer cells,and the radiosensitization effect of Olaparib may be associated with the inhibition of cell proliferation and induction of irradiation-induced DNA damage.
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As a newly-identified protein post-translational modification, malonylation is involved in a variety of biological functions. Recognizing malonylation sites in substrates represents an initial but crucial step in elucidating the molecular mechanisms underlying protein malonylation. In this study, we constructed a deep learning (DL) network classifier based on long short-term memory (LSTM) with word embedding (LSTM) for the prediction of mammalian malonylation sites. LSTM performs better than traditional classifiers developed with common pre-defined feature encodings or a DL classifier based on LSTM with a one-hot vector. The performance of LSTM is sensitive to the size of the training set, but this limitation can be overcome by integration with a traditional machine learning (ML) classifier. Accordingly, an integrated approach called LEMP was developed, which includes LSTM and the random forest classifier with a novel encoding of enhanced amino acid content. LEMP performs not only better than the individual classifiers but also superior to the currently-available malonylation predictors. Additionally, it demonstrates a promising performance with a low false positive rate, which is highly useful in the prediction application. Overall, LEMP is a useful tool for easily identifying malonylation sites with high confidence. LEMP is available at http://www.bioinfogo.org/lemp.
Subject(s)
Animals , Amino Acid Sequence , Genetics , Amino Acids , Deep Learning , Forecasting , Methods , Lysine , Chemistry , Machine Learning , Malonates , Chemistry , Protein Processing, Post-Translational , GeneticsABSTRACT
Objective To investigate the usefulness of Utstein template to guide the assessment and study of cardiopulmonary resuscitation (CPR) in our medical practice because it has been popularized in many countries since 1991.Methods A prospective observational study using Utstein CPR registry form to evaluate the epidemiological features and outcomes of 511 patients resuscitated in the emergency department.Results Of 511 CPR patients registered,higher cardiac arrest rates were observed in the group of patients aged 40- 70 years. In 511 CPR patients registered,preexisting chronic diseases were common including cardiovascular diseases ( 190,37.2％ ) cerebrovascular diseases (48,9.4％ ) and respiratory diseases (39,7.6％ ).Of them,173 cardiac arrest patients (33.9％) had underlying cardiac causes,such as acute myocardial infarction (AMI) found in 109 (21.3％) patients,and ventricular fibrillation witnessed during first cardiac monitoring in eighty ( 15.7％ ) patients.The restoration of spontaneous circulation (ROSC) rate and survival rate at discharge of in - hospital cardiac arrest (IHCA) patients were 47.0％ and 13.5％respectively,but 16.7％ and 4.7％ respectively in the out - hospital cardiac arrest (OHCA) patients (P ＜0.01,both ). Conclusions This study indicated that the cardiovascular diseases, cerebrovascular diseases,and respiratory diseases were the most common preexisting chronic diseases found in cardiac arrest patients.Myocardial infarct,stroke and trauma were the most common precipitation causes of cardiac arrest in the recruited patients.The rates of ROSC and survival at discharge were significantly higher in statistics in patients with IHCA than those in ones with OHCA.
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We developed a user-friendly, interactive program to simultaneously cluster and visualize omics data, such as DNA and protein array profiles. This program provides diverse algorithms for the hierarchical clustering of two-dimensional data. The clustering results can be interactively visualized and optimized on a heatmap. The present tool does not require any prior knowledge of scripting languages to carry out the data clustering and visualization. Furthermore, the heatmaps allow the selective display of data points satisfying user-defined criteria. For example, a clustered heatmap of experimental values can be differentially visualized based on statistical values, such as p-values. Including diverse menu-based display options, QCanvas provides a convenient graphical user interface for pattern analysis and visualization with high-quality graphics.
Subject(s)
DNA , Genomics , Protein Array AnalysisABSTRACT
Recent trends in generating multiple, large-scale datasets provide new challenges to manipulating the relationship of different types of components, such as gene expression and drug response data. Integrative analysis of compound response and gene expression datasets generates an opportunity to capture the possible mechanism of compounds by using signature genes on diverse types of cancer cell lines. Here, we integrated datasets of compound response and gene expression profiles on NCI60 cell lines and constructed a network, revealing the relationship for 801 compounds and 341 gene probes. As examples, obtusol, which shows an exclusive sensitivity on a small number of colon cell lines, is related to a set of gene probes that have unique overexpression in colon cell lines. We also found that the SLC7A11 gene, a direct target of miR-26b, might be a key element in understanding the action of many diverse classes of anticancer compounds. We demonstrated that this network might be useful for studying the mechanisms of varied compound response on diverse cancer cell lines.