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Objective·To explore the molecular classification and prognostic prediction of gastric cancer based on nonnegative matrix factorization (NMF).Methods·Cases of gastric cancer were acquired from Gene Expression Omnibus (GEO). Expression profiling of lncRNA was performed by using a lncRNA-mining approach. NMF model was built with Consensus Cluster Plus package. The relationship among NMF subgroups and clinical relevance was assessed. Results·According to the molecular classification based on NMF, samples were divided into three subgroups. Significant difference was observed in relapse state, lymph node ratio, Lauren classification, TNM stage and age of onset among three subgroups. High-risk group was identified with shortest relapse time by survival analysis both in GSE62254 and GSE15459. Multivariate Cox proportional-hazards regression showed that NMF model based molecular classfication could be regarded as an independent risk factor for gastric cancer. Gene set variance analysis (GSVA) and gene set enrichment analysis (GSEA) showed that the high-risk subgroup was enriched in several tumor development pathways. Conclusion·Based on NMF model, the molecular classification of gastric cancer can be used for treatment decision and prognostic prediction.
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Objective·To explore the molecular classification and prognostic prediction of gastric cancer based on nonnegative matrix factorization (NMF).Methods·Cases of gastric cancer were acquired from Gene Expression Omnibus (GEO). Expression profiling of lncRNA was performed by using a lncRNA-mining approach. NMF model was built with Consensus Cluster Plus package. The relationship among NMF subgroups and clinical relevance was assessed. Results·According to the molecular classification based on NMF, samples were divided into three subgroups. Significant difference was observed in relapse state, lymph node ratio, Lauren classification, TNM stage and age of onset among three subgroups. High-risk group was identified with shortest relapse time by survival analysis both in GSE62254 and GSE15459. Multivariate Cox proportional-hazards regression showed that NMF model based molecular classfication could be regarded as an independent risk factor for gastric cancer. Gene set variance analysis (GSVA) and gene set enrichment analysis (GSEA) showed that the high-risk subgroup was enriched in several tumor development pathways. Conclusion·Based on NMF model, the molecular classification of gastric cancer can be used for treatment decision and prognostic prediction.
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Apoptotic mechanism of Pathogenic fungi has become a focus of study due to the worsening situation of clinical drug resistance in fungi. Apoptosis of Pathogenic fungi is a complicated network involving many pathways, regulators and effectors. Besides, it is closely related to the autophagy, mitochondrial apoptotic pathways, and changes of endogenous and exogenous factors. As a new target of antifungal agent, apoptotic pathways are of great clinical importance. This paper reviews the apoptotic pathways of Pathogenic fungi.
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<p><b>AIM</b>To observe the role of nitric oxide in dorsal root ganglion (DRG) neurons and its related ionic mechanisms, and explore the function of NO in pain transmission process.</p><p><b>METHODS</b>In freshly isolated rat DRG samples, using intracellular recording technique, we perfused sodium nitroprusside (NO donor) to observe the role of NO in DRG neurons.</p><p><b>RESULTS</b>In 77.45% of the bath cells, application of sodium nitroprusside (10 -100 mmol/L) induced concentration-dependent membrane hyperpolarization (79/102), and remaining neurons had no response. The membrane conductance increased from control value of (21.06 +/- 1.94) nS to (23.08 +/- 0.92) nS during sodium nitroprusside induced hyperpolarization. L-NAME (1 mmol/L), CdCl2 (0.1 mmol/L) and non-sodium BSS failed to change the amplitude of sodium nitroprusside induced hyperpolarization. When BSS containing 10 mmol/L TEA was used, sodium nitroprusside induced hyperpolarization was obviously inhibited.</p><p><b>CONCLUSION</b>Sodium nitroprusside could cause concentration-dependent hyperpolarization in DRG neurons by activating K+ channels.</p>
Assuntos
Animais , Feminino , Masculino , Ratos , Gânglios Espinais , Fisiologia , Potenciais da Membrana , Fisiologia , Neurônios , Fisiologia , Óxido Nítrico , Farmacologia , Nitroprussiato , Farmacologia , Dor , Ratos Sprague-DawleyRESUMO
Microbial metabolomics is a subject that chiefly studying all the low molecular weight metabolites in an organism or cells during their growing process. The progress of analytical technology promotes microbial metabolomics to make advancement. In this paper, the commonly used analytical technology, sample preparation and its application were discussed and the prospects of the analytical methods were also discussed.