Evidence map›Paper›PMID 37108497›Full record

ArticleInternational journal of molecular sciences2023

A Practical Method for Amino Acid Analysis by LC-MS Using Precolumn Derivatization with Urea.

Runjin Zhao, Biling Huang, Gang Lu, Songsen Fu, Jianxi Ying, Yufen Zhao

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

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  5. Editorial of Special Issue "Current Trends in Chemistry Towards Biology".International journal of molecular sciences · 2024
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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

6 authors at 1 institution in 1 country.

Runjin ZhaoInstitute of Drug Discovery Technology, Ningbo University, Ningbo 315211, China.
Biling HuangInstitute of Drug Discovery Technology, Ningbo University, Ningbo 315211, China.
Gang LuInstitute of Drug Discovery Technology, Ningbo University, Ningbo 315211, China.
Songsen FuInstitute of Drug Discovery Technology, Ningbo University, Ningbo 315211, China.
Jianxi YingInstitute of Drug Discovery Technology, Ningbo University, Ningbo 315211, China.ORCID 0000-0002-1035-5345
Yufen ZhaoInstitute of Drug Discovery Technology, Ningbo University, Ningbo 315211, China.
Ningbo University · CN

Funding

Ningbo Top Talent Project No. 215-432094250Scientific Research Grant of Ningbo University No. 215-432000282the National Natural Science Foundation of China No. 42003062
6 · The paper itself

Abstract

Amino acid (AA) analysis is important in biochemistry, food science, and clinical medicine. However, due to intrinsic limitations, AAs usually require derivatization to improve their separation and determination. Here, we present a liquid chromatography-mass spectrometry (LC-MS) method for the derivatization of AAs using the simple agent urea. The reactions proceed quantitatively under a wide range of conditions without any pretreatment steps. Urea-derivatized products (carbamoyl amino acids) of 20 AAs exhibit better separation on reversed-phase columns and increased response in a UV detector compared to underivatized ones. We applied this approach to AA analysis in complex samples using a cell culture media as a model, and it showed potential for the determination of oligopeptides. This fast, simple, and inexpensive method should be useful for AA analysis in complex samples.

Indexed as

Amino AcidsTandem Mass SpectrometryAminesChromatography, High Pressure LiquidChromatography, LiquidAminesAmino Acidsamino acidsderivatizationLC-MSquantitative analysisurea

Identifiers

PMID37108497
PMCPMC10138926
OpenAlexW4366090611

What OpenQuestion holds

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Registered trials

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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.