Evidence map›Paper›PMID 34786750›Full record

ReviewMass spectrometry reviews2023

Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis.

Qin Fu, Christopher I Murray, Oleg A Karpov, Jennifer E Van Eyk

Open access · greenAbstract readReview
In one paragraph

Review in Mass spectrometry reviews, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

26 citing papers in PubMed, 60 citations in OpenAlex.

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  18. Proteomics of the heart.Physiological reviews · 2024
    Review
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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

4 authors at 2 institutions in 1 country.

Qin FuSmidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Christopher I MurraySmidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Oleg A KarpovSmidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Jennifer E Van EykSmidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Cedars-Sinai Medical Center · USCedars-Sinai Smidt Heart Institute · US

Funding

Genomic and Proteomic Architecture of AtherosclerosisR01HL111362 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI HERRINGTON, DAVID MCLEOD · 2012 to 2021
$17.2M
NHLBI NIH HHS R01 HL111362
6 · The paper itself

Abstract

Sample preparation for mass spectrometry-based proteomics has many tedious and time-consuming steps that can introduce analytical errors. In particular, the steps around the proteolytic digestion of protein samples are prone to inconsistency. One route for reliable sample processing is the development and optimization of a workflow utilizing an automated liquid handling workstation. Diligent assessment of the sample type, protocol design, reagents, and incubation conditions can significantly improve the speed and consistency of preparation. When combining robust liquid chromatography-mass spectrometry with either discovery or targeted methods, automated sample preparation facilitates increased throughput and reproducible quantitation of biomarker candidates. These improvements in analysis are also essential to process the large patient cohorts necessary to validate a candidate biomarker for potential clinical use. This article reviews the steps in the workflow, optimization strategies, and known applications in clinical, pharmaceutical, and research fields that demonstrate the broad utility for improved automation of sample preparation in the proteomic field.

Indexed as

ProteinsProteomicsBiomarkersHumansMass SpectrometrySpecimen HandlingBiomarkersProteinsautomationhigh throughputoptimizationproteomicsquantitative mass spectrometryrobotsample preparation

Identifiers

PMID34786750
PMCPMC10339360
OpenAlexW3213542070

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.