| Title |
Association between the traditional Chinese medicine pathological factors of opioid addiction and DRD2/ANKK1 TaqIA polymorphisms
|
|---|---|
| Published in |
BMC Complementary Medicine and Therapies, July 2015
|
| DOI | 10.1186/s12906-015-0727-z |
| Pubmed ID | |
| Authors |
Meimei Cai, Zhiyang Su, Hong Zou, Qin Zhang, Jianying Shen, Lingyuan Zhang, Teng Wang, Zhaoyang Yang, Candong Li |
| Abstract |
As we known, Traditional Chinese Medicine (TCM) helps to prevent the relapse of drug addiction. However, the scientific basis of TCM remains unclear because of limitations of current reductionist approaches. We aimed to explore the possible mechanism of how ANKK1 TaqIA (A1/A2) [rs1800497(T/C)] affects the relapse of opioid addiction on the perspective of Chinese traditional medicine. The ANKK1 TaqIA (A1/A2) [rs1800497(T/C)] of the dopamine D2 receptor (DRD2) polymorphisms were genotyped in a case-control sample consisting of 347 opioid addicts and 155 healthy controls with RT-PCR and the TCM pathological factors were collected by means of Syndrome Elements Differentiation in the case-control sample. DRD2/ANKK1 TaqIA Polymorphisms has no relation with opioid addiction relapse; but for those who were diagnosed with phlegm syndrome, DRD2/ANKK1 TaqIA Polymorphisms affect the replapse of apioid addiction (P < 0.05). DRD2/ANKK1 TaqIA is associated with opioid addict and it is obvious in opioid addicts who suffer from the phlegm syndrome. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 25% |
| Other | 2 | 10% |
| Librarian | 2 | 10% |
| Professor > Associate Professor | 2 | 10% |
| Student > Master | 2 | 10% |
| Other | 3 | 15% |
| Unknown | 4 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 20% |
| Medicine and Dentistry | 4 | 20% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 10% |
| Psychology | 2 | 10% |
| Social Sciences | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 6 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 July 2015.
All research outputs
#15,339,713
of 22,816,807 outputs
Outputs from BMC Complementary Medicine and Therapies
#2,043
of 3,630 outputs
Outputs of similar age
#153,721
of 262,956 outputs
Outputs of similar age from BMC Complementary Medicine and Therapies
#49
of 94 outputs
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