Evidence map›Paper›PMID 41547349›Full record

ArticleCell reports methods2026

HT SpaceM enables high-throughput mapping of metabolic diversity at the single-cell level.

Rune Daucke, Erwin M Schoof

Abstract read
In one paragraph

Article in Cell reports methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Rune DauckeDepartment of Biotechnology and Biomedicine, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. Electronic address: runda@dtu.dk.
Erwin M SchoofDepartment of Biotechnology and Biomedicine, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. Electronic address: erws@dtu.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Expanding metabolomic profiling to the single-cell level can reveal metabolic heterogeneity and clinically relevant subpopulations, yet existing methods lack sensitivity and scale. To address this gap, in a recent issue of Cell, Delafiori and colleagues introduce HT SpaceM, a high-throughput MALDI workflow enabling sensitive, reproducible, and scalable single-cell metabolomics.

Indexed as

High-Throughput Screening AssaysMetabolomicsSingle-Cell AnalysisSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationAnimalsHumans

Identifiers

PMID41547349
PMCPMC12853170

What Socratic holds

Textmetadata
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 Socratic graph.