Urinary electrophoretic profiles from chronic fatigue syndrome and chronic fatigue syndrome/fibromyalgia patients: a pilot study for achieving their normalization

Casado, Begoña; Zanone, Chiara; Annovazzi, Laura; Iadarola, Paolo; Whalen, Gail; Baraniuk, James N.

doi:10.1016/j.jchromb.2004.09.056

Cited by 12 publications

(31 citation statements)

References 48 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The first study used an electrophoretic analysis of urine to find potential biomarkers differentiating the two illnesses. 28 Its strength lay in its ability to present and compare data from individual patients between illness groups and healthy controls. For a peak to be considered significant, it had to come from multiple patients-thus representing a true peak rather than an outlier due to data from a single patient.…”

Section: Biomarkersmentioning

confidence: 99%

Is chronic fatigue syndrome the same illness as fibromyalgia: evaluating the 'single syndrome' hypothesis

Abbi¹,

Natelson²

2012

QJM

View full text Add to dashboard Cite

Chronic fatigue syndrome (CFS) and fibromyalgia (FM) are medically unexplained syndromes that can and often do co-occur. For this reason, some have posited that the two are part of the same somatic syndrome--examples of symptom amplification. This hypothesis would suggest that few differences exist between the two syndromes. To evaluate this interpretation, we have searched the literature for articles comparing CFS to FM, reviewing only those articles which report differences between the two. This review presents data showing differences across a number of parameters--implying that the underlying pathophysiology in CFS may differ from that of FM. We hope that our review encourages other groups to look for additional differences between CFS and FM. By continuing to preserve the unique illness definitions of the two syndromes, clinicians will be able to better identify, understand and provide treatment for these individuals.

show abstract

Section: Biomarkersmentioning

confidence: 99%

Is chronic fatigue syndrome the same illness as fibromyalgia: evaluating the 'single syndrome' hypothesis

Abbi¹,

Natelson²

2012

QJM

View full text Add to dashboard Cite

show abstract

“…Variations in migration time -a function of electroosmotic flow (EOF) inside the capillary, sample loading, wall interactions and physical errors (such as injection irreproducibility or temperature variations) -may lead to poorly reproducible data and preclude their appropriate interpretation [12] This is the most challenging point, while all the others share methodology with HPLC data pre-treatment and are well established.…”

Section: Data Pre-treatment In Ce-uv Fingerprintsmentioning

confidence: 99%

Capillary electrophoresis as a metabolomics tool for non-targeted fingerprinting of biological samples

Barbas

Moraes

Villaseñor

2011

Journal of Pharmaceutical and Biomedical Analysis

View full text Add to dashboard Cite

Metabolomics, understood as a data driven strategy trying to find markers of a situation under study without a priori hypothesis, has rapidly caught the attention and evolved from the simple pattern recognition strategy, which was a great innovation at its origins, to the interest for the final identification of markers responsible for class separation, i.e., from data to knowledge. Due to differences in physico-chemical properties and concentrations of the metabolites, but also due to differences in matrix properties, cross-platform approaches are proving to increase the capability of information. Once more techniques do not compete. This is the scene where capillary electrophoresis (CE) has its niche to provide information mainly on polar or ionic compounds in biological fluids. General advantages and disadvantages of CE for sample fingerprinting will be discussed and methods will be classified depending on the detection system (UV or MS) as this strongly affects all the conditions. Recent developments will be presented in different biological fluids, although urine is without a doubt the preferred sample for CE analysis.

show abstract

“…Capillary electrophoretic peaks span a wide range in both time and frequency domains; so it is hard to successfully apply chemometric methods used in the processing of chromatographic data to distinguish between CE peaks with a low signal-to-baseline ratio and a high noise [3][4][5]. Many factors in CE analysis such as variations in the migration time being a function of EOF inside the capillary, influence of sample loading, wall interactions, physical errors (such as injection irreproducibility or temperature variations) may lead to poorly reproducible data and preclude their appropriate interpretation [6][7][8]. During an analysis of biological samples, matrix effects are also introduced, which additionally influences the analytical performance and usually decreases the reproducibility of the obtained results.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of different warping methods for the analysis of CE profiles of urinary nucleosides

et al. 2007

View full text Add to dashboard Cite

Nowadays, numerous metabolite concentrations can readily be determined in a given biological sample by high-throughput analytical methods. However, such raw analytical data comprise noninformative components due to many disturbances normally occurring in the analyses of biological material. To eliminate those unwanted original analytical data components, advanced chemometric data preprocessing methods might be of help. Here, such methods are applied to electrophoretic nucleoside profiles in urine samples of cancer patients and healthy volunteers. In this study, three warping methods: dynamic time warping (DTW), correlation optimized warping (COW), and parametric time warping (PTW) were examined on two sets of electrophoretic data by means of quality of peaks alignment, time of preprocessing, and way of customization. The application of warping methods helped to limit shifting of peaks and enabled differentiation between whole electropherograms of healthy and cancer patients objectively by a principal component analysis (PCA). The evaluation of preprocessed data and raw data by PC analysis confirms differences between the applied warping tools and proves their suitability in metabonomic data interpretation.

show abstract

Urinary electrophoretic profiles from chronic fatigue syndrome and chronic fatigue syndrome/fibromyalgia patients: a pilot study for achieving their normalization

Cited by 12 publications

References 48 publications

Is chronic fatigue syndrome the same illness as fibromyalgia: evaluating the 'single syndrome' hypothesis

Is chronic fatigue syndrome the same illness as fibromyalgia: evaluating the 'single syndrome' hypothesis

Capillary electrophoresis as a metabolomics tool for non-targeted fingerprinting of biological samples

Evaluation of different warping methods for the analysis of CE profiles of urinary nucleosides

Contact Info

Product

Resources

About