Evidence map›Paper›PMID 40538746›Full record

ArticleRSC advances2025

LC-MS Orbitrap-based metabolomics using a novel hybrid zwitterionic hydrophilic interaction liquid chromatography and rigorous metabolite identification reveals doxorubicin-induced metabolic perturbations in breast cancer cells.

Salah Abdelrazig, Áine McCabe, Alia Yasin, Rajneil Chaudhary, Michael A Ochsenkühn, David Scicchitano, Shady A Amin

Abstract read
In one paragraph

Article in RSC advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

7 authors.

Salah AbdelrazigMarine Microbiomics Lab, Biology Program, New York University Abu Dhabi (NYUAD) P.O. Box 129188 Abu Dhabi United Arab Emirates salah.Abdelrazig@nyu.edu samin@nyu.edu.ORCID https://orcid.org/0000-0001-6231-1267
Áine McCabeDivision of Science, New York University Abu Dhabi P.O. Box 129188 Abu Dhabi United Arab Emirates.
Alia YasinDivision of Science, New York University Abu Dhabi P.O. Box 129188 Abu Dhabi United Arab Emirates.
Rajneil ChaudharyMarine Microbiomics Lab, Biology Program, New York University Abu Dhabi (NYUAD) P.O. Box 129188 Abu Dhabi United Arab Emirates salah.Abdelrazig@nyu.edu samin@nyu.edu.
Michael A OchsenkühnMarine Microbiomics Lab, Biology Program, New York University Abu Dhabi (NYUAD) P.O. Box 129188 Abu Dhabi United Arab Emirates salah.Abdelrazig@nyu.edu samin@nyu.edu.
David ScicchitanoDivision of Science, New York University Abu Dhabi P.O. Box 129188 Abu Dhabi United Arab Emirates.
Shady A AminMarine Microbiomics Lab, Biology Program, New York University Abu Dhabi (NYUAD) P.O. Box 129188 Abu Dhabi United Arab Emirates salah.Abdelrazig@nyu.edu samin@nyu.edu.ORCID https://orcid.org/0000-0003-3780-8102

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The identification of metabolites in biological samples presents a challenge in untargeted metabolomics, mainly due to limited databases and inadequate chromatography. Current LC columns suffer from high pH instability (silica-based), low efficiencies and pressure limitations (polymer-based), or inadequate retention of polar/semi-polar metabolites (reverse-phase). In this study, a comprehensive LC-MS workflow was developed to address these limitations using a novel zwitterionic HILIC (Z-HILIC), high-resolution MS, deep-scan data-dependent acquisition (DDA), and a large chemical library comprising 990 standards. The method performance was evaluated and compared with a widely-used ZIC-

Identifiers

PMID40538746
PMCPMC12177712

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.