Evidence map›Paper›PMID 28565794›Full record

ArticleExperimental and therapeutic medicine2017

Novel two-step derivation method for the synchronous analysis of inherited metabolic disorders using urine.

Xiao-Qi Sheng, Yi-Chao Wang

Open access · diamondAbstract read
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Article in Experimental and therapeutic medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 98% 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

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4 · The record

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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 at 1 institution in 1 country.

Xiao-Qi ShengHunan Province Technical Institute of Clinical Preventive and Treatment for Children's Inherited Metabolic Disorders, Maternal and Child Health Hospital of Hunan Province, Changsha, Hunan 410008, P.R. China.
Yi-Chao WangHunan Province Technical Institute of Clinical Preventive and Treatment for Children's Inherited Metabolic Disorders, Maternal and Child Health Hospital of Hunan Province, Changsha, Hunan 410008, P.R. China.
Hunan Provincial Maternal and Child Health Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the present study was to conduct preliminary clinical screening and monitoring using a novel two-step derivatization process of urine in five categories of inherited metabolic disease (IMD). Urine samples (100 µl, containing 2.5 mmol/l creatinine) were taken from patients with IMDs. The collected urine was then treated using a two-step derivatization method (with oximation and silylation at room temperature), where urea and protein were removed. In the first step of the derivatization, α-ketoacids and α-aldehyde acids were prepared by oximation using novel oximation reagents. The second-step of the derivatization was that residues were silylated for analysis. Urine samples were examined using gas chromatography/mass spectrometry (GC/MS) and a retention time-locking technique. The simultaneous analysis and identification of >400 metabolites in >130 types of IMD was possible from the GC/MS results, where the IMDs included phenylketonuria, ornithine transcarbamylase deficiency, neonatal intrahepatic cholestasis caused by citrin deficiency, β-ureidopropionase deficiency and mitochondrial metabolic disorders. This method was demonstrated to have good repeatability. Considering α-ketoglutarate (α-KG) as an example, the relative standard deviations (RSDs) of the α-KG retention time and peak area were 0.8 and 3.9%, respectively, the blank spiked recovery rate was between 89.6 and 99.8%, and the RSD was ≤7.5% (n=5). The method facilitates the analysis of thermally non-stable and semi-volatile metabolites in urine, and greatly expands the range of materials that can be synchronously screened by GC/MS. Furthermore, it provides a comprehensive, effective and reliable biochemical analysis platform for the pathological research of IMDs.

Indexed as

biomarkerinherited metabolic disorderssimultaneoustwo-step derivatizationurine

Identifiers

PMID28565794
PMCPMC5443173
OpenAlexW2594326986

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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.