Evidence map›Paper›PMID 37466681›Full record

ReviewAnalytical and bioanalytical chemistry2023

Chemical tagging mass spectrometry: an approach for single-cell omics.

Haiyan Lu, Hua Zhang, Lingjun Li

Open access · greenAbstract readReview
In one paragraph

Review in Analytical and bioanalytical chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.8field-weighted citation impact, top 17% of its field
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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Recent advances and future developments in ultrasensitive omics.Analytical and bioanalytical chemistry · 2023
    Article
  8. 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 at 1 institution in 1 country.

Haiyan Lu *School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
Hua Zhang *School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
Lingjun LiSchool of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA. lingjun.li@wisc.edu.ORCID http://orcid.org/0000-0003-0056-3869
University of Wisconsin–Madison · US

Funding

WU P&FP30DK020579 · NIDDK · WASHINGTON UNIVERSITY · PI Clay F. Semenkovich · 2013 to 2026
$27.1M
Radionuclide Production and Radiochemistry Core Description CoreP01CA250972 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI KIM, KYUNGMANN · 2020 to 2024
$12.5M
Mass Spectrometric Studies of Neuropeptides in FeedingR01DK071801 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI LINGJUN LI · 2006 to 2026
$6.7M
Creating a region- specific biomolecular atlas of the brain of Alzheimer’s diseaseR01AG078794 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI LINGJUN LI, Luigi Puglielli · 2022 to 2026
$3.7M
Di-Leu-enabled multiplexed quantitation for biomarker discovery and validation in Alzheimer's diseaseRF1AG052324 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2018 to 2018
$2.4M
DiLeu-enabled multiplexed quantitation for biomarker discovery and validation in Alzheimer’s diseaseR01AG052324 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI LINGJUN LI · 2023 to 2026
$2.3M
Acquisition of a High-Field Dual Source FTICR-MS for Pharmaceutical ResearchS10RR029531 · NCRR · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2011 to 2011
$2.1M
Acquisition of a Dual-Source, High-Performance, Ion Mobility, Quadrupole Time-of-Flight Mass Spectrometry System for Biomedical Research at UW-MadisonS10OD028473 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2021 to 2021
$1.3M
Acquisition of a High Resolution High Speed MALDI Mass Spectrometer for Biomedical Research at UW-MadisonS10OD025084 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI LI, LINGJUN · 2018 to 2018
$598k
NCI NIH HHS P01 CA250972NCI NIH HHS P01CA250972NCRR NIH HHS S10 RR029531NIA NIH HHS R01 AG052324NIA NIH HHS R01 AG078794NIA NIH HHS RF1 AG052324NIA NIH HHS RF1AG052324NIDDK NIH HHS P30 DK020579NIDDK NIH HHS R01 DK071801NIH HHS S10 OD025084NIH HHS S10 OD028473
6 · The paper itself

Abstract

Single-cell (SC) analysis offers new insights into the study of fundamental biological phenomena and cellular heterogeneity. The superior sensitivity, high throughput, and rich chemical information provided by mass spectrometry (MS) allow MS to emerge as a leading technology for molecular profiling of SC omics, including the SC metabolome, lipidome, and proteome. However, issues such as ionization suppression, low concentration, and huge span of dynamic concentrations of SC components lead to poor MS response for certain types of molecules. It is noted that chemical tagging/derivatization has been adopted in SCMS analysis, and this strategy has been proven an effective solution to circumvent these issues in SCMS analysis. Herein, we review the basic principle and general strategies of chemical tagging/derivatization in SCMS analysis, along with recent applications of chemical derivatization to single-cell metabolomics and multiplexed proteomics, as well as SCMS imaging. Furthermore, the challenges and opportunities for the improvement of chemical derivatization strategies in SCMS analysis are discussed.

Indexed as

MetabolomeMetabolomicsLipidomicsMass SpectrometryProteomicsChemical derivatizationLipidomicsMass spectrometry imagingMetabolomicsProteomicsSingle-cell analysis

Identifiers

PMID37466681
PMCPMC10729908
OpenAlexW4384664949

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.