The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Investigation of Human Blood Plasma Sample Preparation for Performing Metabolomics Using Ultrahigh Performance Liquid Chromatography/Mass Spectrometry
Abstract
The following study investigates the preparation of human blood plasma for metabolomic profiling analysis by ultrahigh performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC/TOFMS) in a novel two-step design study. Four different organic solvents (acetonitrile, acetone, methanol, and ethanol) were used to assess human blood plasma preparation via protein precipitation. The optimal conditions for sample preparation were investigated, with consideration to the number of extracted markers, data quality/reproducibility, and column lifetime prolongation. Isotopically labeled internal standards were used to monitor data quality/reproducibility. Gel electrophoresis was also used to measure the protein content in the supernatant of the "first design step" allowing assessment of the amount of protein that would be injected/accumulate onto the column after many injections that would be apparent in a global metabolic profiling study. The second design step followed on from the results obtained in step one, with four of the best conditions selected and further investigated, looking at the effects of vortex time and temperature on precipitation/extraction. Two choices of solvent compositions were found to be "optimal" for preparation of plasma for global metabolic profiling analysis; these were "methanol/ethanol" (1:1, v/v) and "methanol/acetonitrile/acetone" (1:1:1, v/v/v) added to plasma (4:1 ratio, 400 microL total volume).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Metabolomics Standards Initiative (MSI)
Fiehn, O., Robertson, D., Griffin, J., van der Werf, M., Nikolau, B., Morrison, N., Sumner, L. W., Goodacre, R., Hardy, N. W., Taylor, C., et al. (2007) · Metabolomics · doi:10.1007/s11306-007-0070-6 · Cited by 518
Cited by
The Human Serum Metabolome (HUSERMET) Consortium, Dunn, W. B., Broadhurst, D., Begley, P., Zelena, E., Francis-McIntyre, S., Anderson, N., Brown, M., Knowles, J. D., Halsall, A., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.335 · Cited by 3,294
Integrated omics: tools, advances and future approaches
Misra, B. B., Langefeld, C., Olivier, M., & Cox, L. A. (2019) · Journal of Molecular Endocrinology · doi:10.1530/jme-18-0055 · Cited by 686
Masson, P., Alves, A. C., Ebbels, T. M. D., Nicholson, J. K., & Want, E. J. (2010) · Analytical Chemistry · doi:10.1021/ac101722e · Cited by 173
Xie, Y., Zou, X., Han, J., Zhang, Z., Feng, Z., Ouyang, Q., Hua, S., Liu, Z., Li, C., Cai, Y., et al. (2022) · Experimental Neurology · doi:10.1016/j.expneurol.2022.114081 · Cited by 80
Barri, T., Holmer-Jensen, J., Hermansen, K., & Dragsted, L. O. (2012) · Analytica Chimica Acta · doi:10.1016/j.aca.2011.12.065 · Cited by 57
Metadata
- Authors
- Bruce, S. J., Tavazzi, I., Parisod, V., Rezzi, S., Kochhar, S., & Guy, P. A.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2009-03-26
- Volume
- 81
- Issue
- 9
- Pages
- 3285-3296
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2062058561
- Cited by
- 321
- References
- 1
- FWCI
- 8.28
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Investigation of Human Blood Plasma Sample Preparation for Performing Metabolomics Using Ultrahigh Performance Liquid Chromatography/Mass Spectrometry. https://app.cochat.ai/papers/10.1021/ac8024569
- The paper
- Bruce, S. J., Tavazzi, I., Parisod, V., Rezzi, S., Kochhar, S., & Guy, P. A. (2009). Investigation of Human Blood Plasma Sample Preparation for Performing Metabolomics Using Ultrahigh Performance Liquid Chromatography/Mass Spectrometry. Analytical Chemistry. https://doi.org/10.1021/ac8024569
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.