Evidence map›Paper›PMID 39230750›Full record

ArticleAnalytical and bioanalytical chemistry2025

The evolution of data treatment tools in single-particle and single-cell ICP-MS analytics.

Michail Ioannis Chronakis, Björn Meermann, Marcus von der Au

Abstract read
In one paragraph

Article in Analytical and bioanalytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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.

Michail Ioannis ChronakisDivision 1.1 - Inorganic Trace Analysis, Federal Institute for Materials Research and Testing (BAM), Richard-Willstätter-Straße 11, 12489, Berlin, Germany.
Björn MeermannDivision 1.1 - Inorganic Trace Analysis, Federal Institute for Materials Research and Testing (BAM), Richard-Willstätter-Straße 11, 12489, Berlin, Germany.
Marcus von der AuDivision 1.1 - Inorganic Trace Analysis, Federal Institute for Materials Research and Testing (BAM), Richard-Willstätter-Straße 11, 12489, Berlin, Germany. Marcus.von-der-Au@bam.de.ORCID 0000-0002-7225-7396

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-particle inductively coupled plasma-mass spectrometry (sp-ICP-MS) is one of the most powerful tools in the thriving field of nanomaterial analysis. Along the same lines, single-cell ICP-MS (sc-ICP-MS) has become an invaluable tool in the study of the variances of cell populations down to a per-cell basis. Their importance and application fields have been listed numerous times, across various reports and reviews. However, not enough attention has been paid to the immense and ongoing development of the tools that are currently available to the analytical community for the acquisition, and more importantly, the treatment of single-particle and single-cell-related data. Due to the ever-increasing demands of modern research, the efficient and dependable treatment of the data has become more important than ever. In addition, the field of single-particle and single-cell analysis suffers due to a large number of approaches for the generated data-with varying levels of specificity and applicability. As a result, finding the appropriate tool or approach, or even comparing results, can be challenging. This article will attempt to bridge these gaps, by covering the evolution and current state of the tools at the disposal of sp-ICP-MS users.

Indexed as

Mass SpectrometrySingle-Cell AnalysisAnimalsHumansCell systems/single-cell analysisData treatmentMass spectrometry/ICP-MSNanoparticles/nanotechnology

Identifiers

PMID39230750
PMCPMC11695396

What OpenQuestion holds

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LicenceCC BY
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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.