Evidence map›Paper›PMID 41090524›Full record

ArticleAnalytical chemistry2025

High Dynamic Range Peptide Mass Spectrometry Using Segmented Precursor Ion Accumulation.

Maria C Panepinto, Francesca Minicozzi, Paolo Cifani

Abstract read
In one paragraph

Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Maria C PanepintoCold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, United States.ORCID 0000-0001-7040-8181
Francesca MinicozziCold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, United States.ORCID 0009-0007-7910-3342
Paolo CifaniCold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, United States.ORCID 0000-0002-4403-1277

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Limited sensitivity and depth of proteome sampling in experiments using data-dependent acquisition (DDA) mass spectrometry are usually attributed to an insufficient rate of fragmentation spectra acquisition relative to the number of coeluting potential targets. Here, we demonstrated that limited sensitivity and dynamic range of MS1 scans reduce detection of low-intensity ions and thus their selection for fragmentation. As abundant ions occupy a large fraction of the ion accumulation capacity, we sought to improve MS1 detection of rare analytes by an easily implementable strategy based on gas-phase segmentation of the MS1 scan range, followed by coaccumulation and detection of all ions. The quadrupolar isolation windows used to segment the MS1 scan range are designed to transmit, on average, an equal number of charges, consistent with the parameter used by many recent mass spectrometers to regulate ion trap filling. This strategy, which we named high dynamic range MS1 (HDR-MS1), reduces the contribution of abundant ions to reaching the maximum ion capacity. As a result, HDR MS1 showed improved dynamic range and sensitivity compared to conventional full-range scans, resulting in a higher number of peptides and protein identifications under identical MS2 parameters, less redundant precursor ion sampling, and a higher rate of quantified precursor ions. HDR MS1 scans are compatible with any DDA precursor selection filter and MS2 parameter, and the generated files can be analyzed using any software for peptide-spectral matching and quantification.

Indexed as

Mass SpectrometryPeptidesIonsTandem Mass SpectrometryIonsPeptides

Identifiers

PMID41090524
PMCPMC12574650

What OpenQuestion holds

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Registered trials

None linked

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.