| Title |
The application of NMR-based metabonomics in neurological disorders
|
|---|---|
| Published in |
Neurotherapeutics, September 2012
|
| DOI | 10.1016/j.nurx.2006.05.004 |
| Pubmed ID | |
| Authors |
Elaine Holmes, Tsz M. Tsang, Sarah J. Tabrizi |
| Abstract |
Advances in postgenomic technologies have radically changed the information output from complex biological systems, generating vast amounts of high complexity data that can be interpreted by means of chemometric and bioinformatic methods to achieve disease diagnosis and prognosis. High-resolution nuclear magnetic resonance (NMR) spectroscopy of biofluids such as plasma, cerebrospinal fluid (CSF), and urine can generate robust, interpretable metabolic fingerprints that contain latent information relating to physiological or pathological status. This technology has been successfully applied to both preclinical and clinical studies of neurodegenerative diseases such as Huntington's disease, muscular dystrophy, and cerebellar ataxia. An extension of this technology, (1)H magic-angle-spinning (HRMAS) NMR spectroscopy, can be used to generate metabolic information on small intact tissue samples, providing a metabolic link between metabolic profiling of biofluids and histology. In this review we provide a summary of high-resolution NMR studies in neurodegenerative disease and explore the potential of metabonomics in evaluating disease progression with respect to therapeutic intervention. |
Mendeley readers
The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 2% |
| Netherlands | 1 | 1% |
| Romania | 1 | 1% |
| Slovakia | 1 | 1% |
| Unknown | 81 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 24% |
| Student > Ph. D. Student | 15 | 17% |
| Professor | 8 | 9% |
| Professor > Associate Professor | 7 | 8% |
| Student > Master | 6 | 7% |
| Other | 14 | 16% |
| Unknown | 15 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 22% |
| Medicine and Dentistry | 14 | 16% |
| Chemistry | 13 | 15% |
| Neuroscience | 7 | 8% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Other | 10 | 12% |
| Unknown | 19 | 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 23 June 2015.
All research outputs
#7,356,343
of 25,374,647 outputs
Outputs from Neurotherapeutics
#698
of 1,307 outputs
Outputs of similar age
#53,352
of 187,001 outputs
Outputs of similar age from Neurotherapeutics
#16
of 36 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,307 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one is in the 45th percentile – i.e., 45% 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 187,001 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 69% of its contemporaries.
We're also able to compare this research output to 36 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 55% of its contemporaries.