How to Build CHD@ZJU

CHD related Articles were retrieved from Pubmed, by entering keywords "coronary heart disease" and constrict the publish date from 2000/1/1 to now (2013/1/23). As a result, totally 115898 articles were found and their abstracts were downloaded for text mining. Since some articles didn't contain abstracts, only 88396 abstracts remained.
The text-mining process to get CHD related genes could be divided in to 5 following steps:

  • 1) Extracting all keywords from abstracts and ignoring those keywords start with numbers. 101402 keywords were extracted.

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  • 2) Input these keywords into Gene library in ArrayTrack and find possible related genes. 4674 genes were then found.

  • 3) Put these 4674 genes again into pubmed abstracts to find related aticles. Only genes which offical name or there keyword description (such as prolactin for gene PRL) could be found in the abstract would be remained. As a result, 1247 genes were remained.

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  • 4) Manually examined on the 1247 genes to validate it was acutally related to CHD. Some genes would be filtered if it represents other meanings (such as gene CAD, Entrez ID:790, carbamoyl-phosphate synthetase 2, is mostly meant coronary arterial disease in articles). 681 genes were then validated with at least one reference.

  • 5) All genes was compared with 1078 CHD genes in RGD database, and 370 genes were overlapped. These 370 genes were labels as "RGD_Supported" and the other 293 genes were labels as "REFERED". All 663 genes had supported references in CHD@ZJU which were examined by step 4.

    • How To contact Us

    Collaboration Information: Prof. Xiaohui Fan (fanxh@zju.edu.cn)

    Website using assistance : Leihong Wu (11019004@zju.edu.cn)




    "The effect of reducing the number of cigarettes smoked on risk of lung cancer, COPD, cardiovascular disease and FEV1 - A review."
  • Author:"Lee, Peter N"

  • Published Year:2013

  • Journal:Regulatory toxicology and pharmacology : RTP

  • Abstract:"Searches identified 14 studies investigating effects of reducing cigarette consumption on lung cancer, CVD, COPD or FEV1 decline. Three were case-control studies, six cohort studies, and five follow-up studies of FEV1. Six studies consistently reported lower lung cancer risk in reducers. Compared to non-reducers, meta-analysis (random-effects) showed significantly lower risk (RR 0.81, 95% CI 0.74-0.88 for any reduction, and RR 0.78, 0.66-0.92 for the greatest reduction), with no between-study heterogeneity. Four cohort studies presented CVD results, the combined RR for any reduction being a non-significant 0.93 (0.84-1.03). An effect of reduction was not consistently seen for COPD or FEV1 decline. Four cohort studies presented all-cause mortality results, the combined RR of 0.92 (0.85-1.01) being non-significant. The RR of 0.95 (0.88-1.02) for total smoking-related cancer, from three studies, was also non-significant. The evidence has various weaknesses; few studies, few cases in reducers in some studies, limited dose-response data, incomplete adjustment for baseline consumption, questionable accuracy of the lifetime smoking history data in case-control studies, and bias in cohort studies if reducers are likelier than non-reducers to quit during follow-up. Also, the variable definitions of reduction make meta-analysis problematic. Though the results suggest some benefits of smoking reduction, more evidence is needed."

  • 10.1016/j.yrtph.2013.08.016

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