| Title |
Relationship of genetic causes and inhibin B in non obstructive azoospermia spermatogenic failure
|
|---|---|
| Published in |
BMC Medical Genomics, September 2017
|
| DOI | 10.1186/s12881-017-0456-x |
| Pubmed ID | |
| Authors |
Qing-jun Chu, Rui Hua, Chen Luo, Qing-jie Chen, Biao Wu, Song Quan, Yong-tong Zhu |
| Abstract |
Chromosomal disorders in non obstructive azoospermia (NOA) may have an important influence on spermatogenesis, which may be reflected by the serum inhibin B levels. Till now, few studies have concerned the relationship of genetic causes and inhibin B in NOA. In this retrospective study, 322 men with NOA in Center for Reproductive Medicine, Nanfang Hospital, Southern Medical University were collected. The level of follicle stimulating hormone (FSH), inhibin B, Y chromosome microdeletion test (YCMD) and karyotype were measured. Abnormal karyotypes were present in 38.5% of NOA, and YCMD were present in 18.0%, there was a high correlation between karyotypes and YCMD (χ(2) = 11.892, P < 0.001). The level of inhibin B in chromosomal abnormality from lowest to highest was 46,XX (or 45,X), 47, XXY, mosaics, polymorphisms, inversion and translocation. And the level of inhibin B within Non-AZF a&b region deletion was higher than AZF a&b microdeletion. According to the level of inhibin B, spermatogenesis in chromosomal abnormality from lowest to highest was 46,XX (or 45,X), 47, XXY, mosaics, polymorphisms, inversion and translocation. And spermatogenesis within Non-AZF a&b region deletion was better than AZF a&b microdeletion. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 22% |
| Student > Bachelor | 3 | 17% |
| Student > Ph. D. Student | 2 | 11% |
| Other | 1 | 6% |
| Researcher | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 7 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 28% |
| Medicine and Dentistry | 4 | 22% |
| Agricultural and Biological Sciences | 2 | 11% |
| Unknown | 7 | 39% |
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 13 September 2017.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from BMC Medical Genomics
#1,566
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Outputs of similar age
#236,011
of 323,170 outputs
Outputs of similar age from BMC Medical Genomics
#21
of 43 outputs
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