ArticleRapid communications in mass spectrometry : RCM2026
A Novel Peak-Shape Aware Approach for Mass Alignment in Mass Spectrometry.
Article in Rapid communications in mass spectrometry : RCM, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A Novel Peak-Shape Aware Approach for Mass Alignment in Mass Spectrometry.Rapid communications in mass spectrometry : RCM · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
rationaleIn mass spectrometry measurements, mass shifts may be inadvertently introduced due to instrumental drift and calibration inaccuracies, potentially compromising the accuracy of subsequent data analysis. This work presents a novel, label-free algorithm to improve relative mass alignment between mass spectra. The warping function is modeled as a natural cubic spline, a suitable model for gradual, nonlinear mass shifts.
methodsThe algorithm is validated on a dataset generated from human glioblastoma multiforme samples using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging (MALDI-TOF MSI) and rapid evaporative ionization mass spectrometry (REIMS), and public datasets generated from MALDI-TOF and desorption electrospray ionization (DESI) Orbitrap instruments.
resultsThe algorithm considerably reduces the mass dispersion of the dataset and improves the similarity to a reference mass spectrum for MALDI-TOF, REIMS and DESI-Orbitrap data. It is demonstrated that the proposed method reliably corrects for severe mass shifts. The algorithm is competitive in speed and mass dispersion reduction compared to MSIWarp, a common method to correct for mass misalignment.
conclusionsThis paper presents a novel algorithm to reduce relative mass misalignment for mass spectrometry, validated on an extensive dataset. Thanks to the use of profile data, the peak shapes contribute to the computation of the warping function, and the warping function is approximated in a robust manner. An open-source Python implementation of the proposed methodology will be made accessible on GitHub: https://github.com/VanhemelThomas/psalign.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.