| Title |
Bladder Cancer Diagnosis and Identification of Clinically Significant Disease by Combined Urinary Detection of Mcm5 and Nuclear Matrix Protein 22
|
|---|---|
| Published in |
PLOS ONE, July 2012
|
| DOI | 10.1371/journal.pone.0040305 |
| Pubmed ID | |
| Authors |
John D. Kelly, Tim J. Dudderidge, Alex Wollenschlaeger, Odu Okoturo, Keith Burling, Fiona Tulloch, Ian Halsall, Teresa Prevost, Andrew Toby Prevost, Joana C. Vasconcelos, Wendy Robson, Hing Y. Leung, Nikhil Vasdev, Robert S. Pickard, Gareth H. Williams, Kai Stoeber |
| Abstract |
Urinary biomarkers for bladder cancer detection are constrained by inadequate sensitivity or specificity. Here we evaluate the diagnostic accuracy of Mcm5, a novel cell cycle biomarker of aberrant growth, alone and in combination with NMP22. |
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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Tanzania, United Republic of | 1 | 3% |
| Brazil | 1 | 3% |
| Unknown | 37 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 20% |
| Lecturer > Senior Lecturer | 4 | 10% |
| Student > Postgraduate | 4 | 10% |
| Student > Master | 4 | 10% |
| Other | 3 | 8% |
| Other | 6 | 15% |
| Unknown | 11 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 35% |
| Biochemistry, Genetics and Molecular Biology | 4 | 10% |
| Agricultural and Biological Sciences | 3 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 5% |
| Nursing and Health Professions | 1 | 3% |
| Other | 5 | 13% |
| Unknown | 11 | 28% |