The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Imaging of peptides in the rat brain using MALDI-FTICR mass spectrometry
Open accessAbstract
Analytical methods are pursued to measure the identity and location of biomolecules down to the subcellular (microm) level. Available mass spectrometric imaging methods either compromise localization accuracy or identification accuracy in their analysis of surface biomolecules. In this study, imaging FTICR-MS is applied for the spatially resolved mass analysis of rat brain tissue with the aim to optimize protein identification by the high mass accuracy and online MS/MS capabilities of the technique. Mass accuracies up to 6 ppm were obtained in the direct MALDI-analysis of the tissue together with a spatial resolution of 200 microm. The spatial distributions of biomolecules differing in mass by less than 0.1 Da could be resolved, and are shown to differ significantly. Online MS/MS analysis of selected ions was demonstrated. A comparison of the FTICR-MS imaging results with stigmatic TOF imaging on the same sample is presented. To reduce the extended measuring times involved, it is recommended to restrict the FTICR-MS analyses to areas of interest as can be preselected by other, faster imaging methods.
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
Mass spectrometry-based proteomics
Aebersold, R., & Mann, M. (2003) · Nature · doi:10.1038/nature01511 · Cited by 6,955
Cited by
McDonnell, L. A., & Heeren, R. M. A. (2007) · Mass Spectrometry Reviews · doi:10.1002/mas.20124 · Cited by 1,082
Self-citationA concise review of mass spectrometry imaging
Amstalden van Hove, E. R., Smith, D. F., & Heeren, R. M. A. (2010) · Journal of Chromatography A · doi:10.1016/j.chroma.2010.01.033 · Cited by 416
Self-citationMALDI Imaging of Lipid Biochemistry in Tissues by Mass Spectrometry
Zemski Berry, K. A., Hankin, J. A., Barkley, R. M., Spraggins, J. M., Caprioli, R. M., & Murphy, R. C. (2011) · Chemical Reviews · doi:10.1021/cr200280p · Cited by 386
Körber, A., Anthony, I. G. M., & Heeren, R. M. A. (2025) · Analytical Chemistry · doi:10.1021/acs.analchem.4c05249 · Cited by 88
Self-citation
Metadata
- Authors
- Taban, I. M., Altelaar, A. F. M., van der Burgt, Y. E. M., McDonnell, L. A., Heeren, R. M. A., Fuchser, J., & Baykut, G.
- Venue
- Journal of the American Society for Mass Spectrometry
- Publisher
- American Chemical Society (ACS)
- Published
- 2007-01-01
- Volume
- 18
- Issue
- 1
- Pages
- 145-151
- ISSN
- 1044-0305 (ISSN-L)
- OpenAlex
- W2021945130
- Cited by
- 164
- References
- 1
- FWCI
- 4.73
- Type
- journal article
- Language
- en
- Open access
- green
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
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.