Evidence map›Paper›PMID 41452648›Full record

ArticleJournal of the American Society for Mass Spectrometry2026

UHRMS Formula Assignment: Diophantine-Based Recalibration Yields Lorentzian Mass Error Distribution as the Limiting Factor.

Neda Safaridehkohneh, Albrecht Ott

Abstract read
In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Neda SafaridehkohnehDepartment of Physics, Center for Biophysics, Saarland University, Saarbrücken 66123, Germany.ORCID 0009-0009-5542-3426
Albrecht OttDepartment of Physics, Center for Biophysics, Saarland University, Saarbrücken 66123, Germany.ORCID 0000-0003-0481-2658

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrahigh-resolution mass spectrometry (UHRMS) is a well-established analytical method for characterizing complex molecular mixtures. It is usually performed with Fourier transform techniques, based either on ion cyclotron resonance (FTICR-MS) or mass-dependent oscillations in an ion trap (FT-Orbitrap-MS). In spite of the high technical level of these instruments, often spectral interpretation remains difficult, in particular in a nontargeted approach of complex samples. Here, we introduce a Diophantine method for molecular formula assignment. Taking the ubiquitous Gaussian distribution as an example, we first show how knowledge about random mass error can be used to assign molecular formulas in a statistically consistent way. By considering all possible attributions within a large mass error range, we show how the systematic error stemming from suboptimal calibration can be distinguished from the random mass error in peak position. Correcting for systematic mass error leaves us with a quantifiable, Lorentzian random mass error as expected for Fourier transform-based instruments with long transients. This indicates that our method is self-consistent, assigning molecular formulas close to the theoretical limit of achievable accuracy.

Identifiers

PMID41452648
PMCPMC12784403

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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.