Evidence map›Paper›PMID 27476583›Full record

ArticleJournal of proteome research2016

Development of a Pipeline for Exploratory Metabolic Profiling of Infant Urine.

Frances Jackson, Nancy Georgakopoulou, Manuja Kaluarachchi, Michael Kyriakides, Nicholas Andreas, Natalia Przysiezna, Matthew J Hyde, Neena Modi, Jeremy K Nicholson, Anisha Wijeyesekera and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of proteome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

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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

11 authors at 3 institutions in 1 country.

Frances JacksonDivision of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , South Kensington Campus, London SW7 2AZ, United Kingdom.
Nancy GeorgakopoulouDivision of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , South Kensington Campus, London SW7 2AZ, United Kingdom.
Manuja KaluarachchiMetabometrix Ltd, Bioincubator, Prince Consort Road, South Kensington, London SW7 2AZ, United Kingdom.
Michael KyriakidesDivision of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , South Kensington Campus, London SW7 2AZ, United Kingdom.
Nicholas AndreasSection of Neonatal Medicine, Department of Medicine, Imperial College London , Chelsea and Westminster Hospital Campus, London SW10 9NH, United Kingdom.
Natalia PrzysieznaSection of Neonatal Medicine, Department of Medicine, Imperial College London , Chelsea and Westminster Hospital Campus, London SW10 9NH, United Kingdom.
Matthew J HydeSection of Neonatal Medicine, Department of Medicine, Imperial College London , Chelsea and Westminster Hospital Campus, London SW10 9NH, United Kingdom.
Neena ModiSection of Neonatal Medicine, Department of Medicine, Imperial College London , Chelsea and Westminster Hospital Campus, London SW10 9NH, United Kingdom.
Jeremy K NicholsonDivision of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , South Kensington Campus, London SW7 2AZ, United Kingdom.
Anisha WijeyesekeraDivision of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , South Kensington Campus, London SW7 2AZ, United Kingdom.
Elaine HolmesDivision of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , South Kensington Campus, London SW7 2AZ, United Kingdom.
Imperial College London · GBChelsea and Westminster Hospital · GBHammersmith Hospital · GB

Funding

British Heart Foundation PG/13/49/30307Medical Research Council MC_PC_12025
6 · The paper itself

Abstract

Numerous metabolic profiling pipelines have been developed to characterize the composition of human biofluids and tissues, the vast majority of these being for studies in adults. To accommodate limited sample volume and to take into account the compositional differences between adult and infant biofluids, we developed and optimized sample handling and analytical procedures for studying urine from newborns. A robust pipeline for metabolic profiling using NMR spectroscopy was established, encompassing sample collection, preparation, spectroscopic measurement, and computational analysis. Longitudinal samples were collected from five infants from birth until 14 months of age. Methods of extraction and effects of freezing and sample dilution were assessed, and urinary contaminants from breakdown of polymers in a range of diapers and cotton wool balls were identified and compared, including propylene glycol, acrylic acid, and tert-butanol. Finally, assessment of urinary profiles obtained over the first few weeks of life revealed a dramatic change in composition, with concentrations of phenols, amino acids, and betaine altering systematically over the first few months of life. Therefore, neonatal samples require more stringent standardization of experimental design, sample handling, and analysis compared to that of adult samples to accommodate the variability and limited sample volume.

Indexed as

WorkflowHumansInfantInfant, NewbornMagnetic Resonance SpectroscopyMetabolomicsSample SizeSpecimen HandlingUrineUrine Specimen Collectioninfantmetabolic profilingmetabonomicsNMR spectroscopypipeline developmenturine

Identifiers

PMID27476583
PMCPMC5716460
OpenAlexW2488505657

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.