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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Metabolomics As a Tool for the Characterization of Drug-Resistant Epilepsy
|
|---|---|
| Published in |
Frontiers in Neurology, September 2017
|
| DOI | 10.3389/fneur.2017.00459 |
| Pubmed ID | |
| Authors |
Federica Murgia, Antonella Muroni, Monica Puligheddu, Lorenzo Polizzi, Luigi Barberini, Gianni Orofino, Paolo Solla, Simone Poddighe, Francesco Del Carratore, Julian L. Griffin, Luigi Atzori, Francesco Marrosu |
| Abstract |
Drug resistance is a critical issue in the treatment of epilepsy, contributing to clinical emergencies and increasing both serious social and economic burdens on the health system. The wide variety of potential drug combinations followed by often failed consecutive attempts to match drugs to an individual patient may mean that this treatment stage may last for years with suboptimal benefit to the patient. Given these challenges, it is valuable to explore the availability of new methodologies able to shorten the period of determining a rationale pharmacologic treatment. Metabolomics could provide such a tool to investigate possible markers of drug resistance in subjects with epilepsy. Blood samples were collected from (1) controls (C) (n = 35), (2) patients with epilepsy "responder" (R) (n = 18), and (3) patients with epilepsy "non-responder" (NR) (n = 17) to the drug therapy. The samples were analyzed using nuclear magnetic resonance spectroscopy, followed by multivariate statistical analysis. A different metabolic profile based on metabolomics analysis of the serum was observed between C and patients with epilepsy and also between R and NR patients. It was possible to identify the discriminant metabolites for the three classes under investigation. Serum from patients with epilepsy were characterized by increased levels of 3-OH-butyrate, 2-OH-valerate, 2-OH-butyrate, acetoacetate, acetone, acetate, choline, alanine, glutamate, scyllo-inositol (C < R < NR), and decreased concentration of glucose, lactate, and citrate compared to C (C > R > NR). In conclusion, metabolomics may represent an important tool for discovery of differences between subjects affected by epilepsy responding or resistant to therapies and for the study of its pathophysiology, optimizing the therapeutic resources and the quality of life of patients. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Science communicators (journalists, bloggers, editors) | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 68 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 16% |
| Student > Ph. D. Student | 9 | 13% |
| Student > Master | 5 | 7% |
| Student > Doctoral Student | 5 | 7% |
| Other | 4 | 6% |
| Other | 14 | 21% |
| Unknown | 20 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 10 | 15% |
| Medicine and Dentistry | 10 | 15% |
| Biochemistry, Genetics and Molecular Biology | 6 | 9% |
| Agricultural and Biological Sciences | 4 | 6% |
| Chemistry | 3 | 4% |
| Other | 10 | 15% |
| Unknown | 25 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 12 February 2018.
All research outputs
#13,569,135
of 23,001,641 outputs
Outputs from Frontiers in Neurology
#5,301
of 11,904 outputs
Outputs of similar age
#159,764
of 315,686 outputs
Outputs of similar age from Frontiers in Neurology
#86
of 200 outputs
Altmetric has tracked 23,001,641 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,904 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has gotten more attention than average, scoring higher than 54% 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 315,686 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 200 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.