| Title |
Molecular differential diagnosis of follicular thyroid carcinoma and adenoma based on gene expression profiling by using formalin-fixed paraffin-embedded tissues
|
|---|---|
| Published in |
BMC Medical Genomics, October 2013
|
| DOI | 10.1186/1755-8794-6-38 |
| Pubmed ID | |
| Authors |
Aleksandra Pfeifer, Bartosz Wojtas, Malgorzata Oczko-Wojciechowska, Aleksandra Kukulska, Agnieszka Czarniecka, Markus Eszlinger, Thomas Musholt, Tomasz Stokowy, Michal Swierniak, Ewa Stobiecka, Dagmara Rusinek, Tomasz Tyszkiewicz, Monika Kowal, Michal Jarzab, Steffen Hauptmann, Dariusz Lange, Ralf Paschke, Barbara Jarzab |
| Abstract |
Differential diagnosis between malignant follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. Molecular markers may potentially support a differential diagnosis between FTC and FTA in postoperative specimens. The purpose of this study was to derive molecular support for differential post-operative diagnosis, in the form of a simple multigene mRNA-based classifier that would differentiate between FTC and FTA tissue samples. |
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 % |
|---|---|---|
| Brazil | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 45 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 29% |
| Student > Ph. D. Student | 5 | 11% |
| Professor | 4 | 9% |
| Other | 4 | 9% |
| Student > Bachelor | 3 | 7% |
| Other | 8 | 18% |
| Unknown | 8 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 19 | 42% |
| Biochemistry, Genetics and Molecular Biology | 8 | 18% |
| Agricultural and Biological Sciences | 4 | 9% |
| Veterinary Science and Veterinary Medicine | 1 | 2% |
| Nursing and Health Professions | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 10 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 10 May 2021.
All research outputs
#6,931,229
of 22,727,570 outputs
Outputs from BMC Medical Genomics
#322
of 1,218 outputs
Outputs of similar age
#63,396
of 209,119 outputs
Outputs of similar age from BMC Medical Genomics
#6
of 23 outputs
Altmetric has tracked 22,727,570 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,218 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 72% of its peers.
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 209,119 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.