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Sökning: WFRF:(Jiang Ge ning)

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1.
  • Liu, Jin-ming, et al. (författare)
  • Mid-term effects of lung volume reduction surgery on pulmonary function in patients with chronic obstructive pulmonary disease
  • 2007
  • Ingår i: Chinese Medical Journal. - Chinese Medical Association. - 0366-6999. ; 120:8, s. 658-662
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Now lung volume reduction surgery (LVRS) has become one of the most effective methods for the management of some cases of severe chronic obstructive pulmonary disease (COPD). We evaluated the mid-term effects of LVRS on pulmonary function in patients with severe COPD. Methods Ten male patients with severe COPD aged 38-70 years underwent LVRS and their pulmonary function was assessed before, 3 months and 3 years after surgery. The spirometric and gas exchange parameters included residual volume, total lung capacity, inspiratory capacity, forced vital capacity, forced expiratory volume in one second, diffusion capacity for CO, and arterial blood gas. A 6-minute walk distance (6MWD) test was performed. Results As to preoperative assessment, most spirometric parameters and 6MWD were significantly improved after 3 months and slightly 3 years after LVRS. Gas exchange parameters were significantly improved 3 months after surgery, but returned to the preoperative levels after 3 years. Conclusions LVRS may significantly improve pulmonary function in patients with severe COPD indicating for LVRS. Mid-term pulmonary function 3 years after surgery can be decreased to the level at 3 months after surgery. Three years after LVRS, lung volume and pulmonary ventilation function can be significantly improved, but the improvement in gas exchange function was not significant.
2.
  • Shi, Leming, et al. (författare)
  • The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
  • 2010
  • Ingår i: Nature Biotechnology. - 1087-0156. ; 28:8, s. 827-838
  • Tidskriftsartikel (refereegranskat)abstract
    • Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.
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