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Mendeley readers
| Title |
Interaction of a traditional Chinese Medicine (PHY906) and CPT-11 on the inflammatory process in the tumor microenvironment
|
|---|---|
| Published in |
BMC Medical Genomics, May 2011
|
| DOI | 10.1186/1755-8794-4-38 |
| Pubmed ID | |
| Authors |
Ena Wang, Scott Bussom, Jinguo Chen, Courtney Quinn, Davide Bedognetti, Wing Lam, Fulan Guan, Zaoli Jiang, Yichao Mark, Yingdong Zhao, David F Stroncek, Jeffrey White, Francesco M Marincola, Yung-Chi Cheng |
| Abstract |
Traditional Chinese Medicine (TCM) has been used for thousands of years to treat or prevent diseases, including cancer. Good manufacturing practices (GMP) and sophisticated product analysis (PhytomicsQC) to ensure consistency are now available allowing the assessment of its utility. Polychemical Medicines, like TCM, include chemicals with distinct tissue-dependent pharmacodynamic properties that result in tissue-specific bioactivity. Determining the mode of action of these mixtures was previously unsatisfactory; however, information rich RNA microarray technologies now allow for thorough mechanistic studies of the effects complex mixtures. PHY906 is a long used four herb TCM formula employed as an adjuvant to relieve the side effects associated with chemotherapy. Animal studies documented a decrease in global toxicity and an increase in therapeutic effectiveness of chemotherapy when combined with PHY906. |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| India | 1 | 2% |
| Qatar | 1 | 2% |
| Unknown | 46 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 20% |
| Student > Master | 8 | 16% |
| Student > Ph. D. Student | 7 | 14% |
| Student > Bachelor | 3 | 6% |
| Other | 3 | 6% |
| Other | 7 | 14% |
| Unknown | 11 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 29% |
| Agricultural and Biological Sciences | 8 | 16% |
| Biochemistry, Genetics and Molecular Biology | 7 | 14% |
| Chemistry | 2 | 4% |
| Business, Management and Accounting | 1 | 2% |
| Other | 5 | 10% |
| Unknown | 12 | 24% |