You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Combination of serum histidine and plasma tryptophan as a potential biomarker to detect clear cell renal cell carcinoma
|
|---|---|
| Published in |
Journal of Translational Medicine, April 2017
|
| DOI | 10.1186/s12967-017-1178-8 |
| Pubmed ID | |
| Authors |
Hyung-Ok Lee, Robert G. Uzzo, Debra Kister, Warren D. Kruger |
| Abstract |
In previous work, we showed that serum-free amino acid (SFAA) profiles were different between kidney cancer patients and age and sex matched controls. The goals of the current study are to: (1) confirm our initial observation on an independent sample set; (2) examine if there were similar differences in plasma-free amino acids (PFAA); and (3) determine if removal of tumors changed SFAA and PFAA profiles. SFAA and PFAA profiles were measured in 484 samples taken from 124 healthy controls and 56 clear cell renal cell carcinoma (ccRCC) patients both before and after resection of renal tumors. SFAA and PFAA profiles taken from identical blood samples were remarkably different, with the mean individual amino acid concentrations being 40% less in plasma compared to serum. Both SFAA and PFAA profiles differed significantly between ccRCC patients and controls, but the individual amino acids that differed the most, and the direction of the changes, were quite different between the two blood components. Removal of the tumor had almost no effect on either the SFAA or PFAA profiles. A logistic regression model using serum histidine and plasma tryptophan correctly classified 85.5% of control and 84.7% of case samples. Our findings show that that tumor mass is not directly linked to alterations in blood amino acid levels, and that a combination of serum histidine and plasma tryptophan may be useful as a biomarker to detect ccRCC. |
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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 17% |
| Student > Master | 3 | 13% |
| Researcher | 3 | 13% |
| Student > Bachelor | 3 | 13% |
| Student > Postgraduate | 2 | 8% |
| Other | 2 | 8% |
| Unknown | 7 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 13% |
| Medicine and Dentistry | 3 | 13% |
| Agricultural and Biological Sciences | 3 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Nursing and Health Professions | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 10 | 42% |
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 07 April 2017.
All research outputs
#15,452,475
of 22,962,258 outputs
Outputs from Journal of Translational Medicine
#2,250
of 4,013 outputs
Outputs of similar age
#194,271
of 309,589 outputs
Outputs of similar age from Journal of Translational Medicine
#41
of 68 outputs
Altmetric has tracked 22,962,258 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,013 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 31st percentile – i.e., 31% 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 309,589 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.