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Mendeley readers
Attention Score in Context
| Title |
Gene polymorphisms associated with non-alcoholic fatty liver disease and coronary artery disease: a concise review
|
|---|---|
| Published in |
Lipids in Health and Disease, March 2016
|
| DOI | 10.1186/s12944-016-0221-8 |
| Pubmed ID | |
| Authors |
Xiao-Lin Li, Jian-Qing Sui, Lin-Lin Lu, Nan-Nan Zhang, Xin Xu, Quan-Yong Dong, Yong-Ning Xin, Shi-Ying Xuan |
| Abstract |
Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease which represents a wide spectrum of hepatic damage. Several studies have reported that NAFLD is a strong independent risk factor for coronary artery disease (CAD). And patients with NAFLD are at higher risk and suggested undergoperiodic cardiovascular risk assessment. Cardiovascular disease (CVD) is responsible for the main cause of death in patients with NAFLD, and is mostly influenced by genetic factors. Both NAFLD and CAD are heterogeneous disease. Common pathways involved in the pathogenesis of NAFLD and CAD includes insulin resistance (IR), atherogenic dyslipidemia, subclinical inflammation, oxidative stress, etc. Genomic characteristics of these two diseases have been widely studied, further research about the association of these two diseases draws attention. The gene polymorphisms of adiponectin-encoding gene (ADIPOQ), leptin receptor (LEPR), apolipoprotein C3 (APOC3), peroxisome proliferator-activated receptors (PPAR), sterol regulatory elementbinding proteins (SREBP), transmembrane 6 superfamily member 2 (TM6SF2), microsomal triglyceride transfer protein (MTTP), tumor necrosis factors-alpha (TNF-α) and manganese superoxide dismutase (MnSOD) have been reported to be related to NAFLD and CAD. In this review, we aimed to provide an overview of recent insights into the genetic basis of NAFLD and CAD. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 1% |
| Unknown | 68 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 13 | 19% |
| Researcher | 11 | 16% |
| Student > Bachelor | 10 | 14% |
| Student > Doctoral Student | 5 | 7% |
| Other | 4 | 6% |
| Other | 13 | 19% |
| Unknown | 13 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 33% |
| Biochemistry, Genetics and Molecular Biology | 11 | 16% |
| Agricultural and Biological Sciences | 9 | 13% |
| Nursing and Health Professions | 3 | 4% |
| Immunology and Microbiology | 3 | 4% |
| Other | 4 | 6% |
| Unknown | 16 | 23% |
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 11 March 2016.
All research outputs
#18,447,592
of 22,856,968 outputs
Outputs from Lipids in Health and Disease
#983
of 1,448 outputs
Outputs of similar age
#218,346
of 300,113 outputs
Outputs of similar age from Lipids in Health and Disease
#21
of 35 outputs
Altmetric has tracked 22,856,968 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,448 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 300,113 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.