Objective To screen tumor biomarker of breast cancer from expressed differently in breast cancer patients and health by proteomics techniques. Methods Collecting 10 serum cases of breast cancer and healthy respectively,protein spot was separated by two-dimensional electrophoresis,protein expressed differently from breast cancer and healthy was screened by PDQuest software ,and identified by mass spectrometry. Results The 2-DE maps of breast cancer and healthy were established ,22 differentially expressed proteins were analyzed by PDQuest software,took the healthy group as the reference,there were 18 spots with up-regulated serum protein, and 4 spots with down-regulated serum proteins in breast cancer group.12 protein spots were sampled and detected by mass spectrometry. Finally ,4 differentially expressed proteins were identified successfully ,the proteins were confirmed by the database,named as ankyrin-3 isoform X7,keratin,type I cytoskeletal 9,nesprin-2 isoform X11, Dynein heavy chain 10,axonemal isoform X9. Conclusion The 4 differentially expressed proteins in healthy group and breast cancer group can be potential candidate biomarkers for diagnosis of breast cancer.

OBJECTIVE To investigate and analyze the current management of drug clinical trial institutions in Jiangxi Province and the situation of undertaking drug clinical trials after the implementation of the filing system. METHODS A survey was conducted on 38 new institutions （obtained qualifications during the implementation of the filing system） and old institutions （obtained qualifications during the implementation of the recognition system） that had completed drug clinical trial institution qualification filing for more than one year in Jiangxi Province. The survey focused on the basic information of the institutions， the number of registered principal investigator （PI）， institutional hardware and information construction， personnel allocation and training， and drug registration clinical trials undertaken by the institutions. RESULTS Of 38 institutions surveyed， there were 22 general hospitals and 16 specialized hospitals； there were 24 old institutions and 14 new institutions. Whether in general hospitals or specialized hospitals， the old institutions were better than the new institutions in the number of approved beds， the number of outpatients， the number of inpatients， the number of specialties， and the number of PI； both old and new institutions had separate offices； all new institutions were set up with GCP pharmacy. The adoption of clinical trial management system in new institutions is significantly less than in old institutions. In the general hospital， both the number of full-time managers and the number of quality controllers in old institutions were significantly more than in the new institutions， while the opposite was true at the level of specialized hospitals. In terms of centralized training on GCP， new institutions were all better than the old ones. Whether in general hospitals or specialized hospitals， the number of drug registration clinical trial projects undertaken by new institutions was significantly less than that of old ones. CONCLUSIONS The new institutions are worse than the old institutions in comprehensive strength and information construction of hospitals， and the number of clinical trials undertaken by new institutions is also less than old institutions.