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Mendeley readers
Attention Score in Context
| Title |
Proteomic profiling of lymphocytes in autoimmunity, inflammation and cancer
|
|---|---|
| Published in |
Journal of Translational Medicine, January 2014
|
| DOI | 10.1186/1479-5876-12-6 |
| Pubmed ID | |
| Authors |
Jiebai Zhou, Zhitu Zhu, Chunxue Bai, Hongzhi Sun, Xiangdong Wang |
| Abstract |
Lymphocytes play important roles in the balance between body defense and noxious agents involved in a number of diseases, e.g. autoimmune diseases, allergic inflammation and cancer. The proteomic analyses have been applied to identify and validate disease-associated and disease-specific biomarkers for therapeutic strategies of diseases. The proteomic profiles of lymphocytes may provide more information to understand their functions and roles in the development of diseases, although proteomic approaches in lymphocytes are still limited. The present review overviewed the proteomics-based studies on lymphocytes to headlight the proteomic profiles of lymphocytes in diseases, such as autoimmune diseases, allergic inflammation and cancer, with a special focus on lung diseases. We will explore the potential significance of diagnostic biomarkers and therapeutic targets from the current status in proteomic studies of lymphocytes and discuss the value of the currently available proteomic methodologies in the lymphocytes research. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 4% |
| Unknown | 24 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 32% |
| Student > Ph. D. Student | 6 | 24% |
| Student > Bachelor | 5 | 20% |
| Researcher | 4 | 16% |
| Unknown | 2 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 24% |
| Medicine and Dentistry | 3 | 12% |
| Nursing and Health Professions | 3 | 12% |
| Chemistry | 3 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 8% |
| Other | 5 | 20% |
| Unknown | 3 | 12% |
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 08 January 2014.
All research outputs
#20,215,721
of 22,738,543 outputs
Outputs from Journal of Translational Medicine
#3,304
of 3,975 outputs
Outputs of similar age
#264,136
of 304,598 outputs
Outputs of similar age from Journal of Translational Medicine
#78
of 115 outputs
Altmetric has tracked 22,738,543 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,975 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.