Evidence map›Paper›PMID 29866265›Full record

ArticleAnalytica chimica acta2018

SPME-GC×GC-TOF MS fingerprint of virally-infected cell culture: Sample preparation optimization and data processing evaluation.

Giorgia Purcaro, Pierre-Hugues Stefanuto, Flavio A Franchina, Marco Beccaria, Wendy F Wieland-Alter, Peter F Wright, Jane E Hill

Abstract readEvaluation StudyValidation Study
In one paragraph

Article in Analytica chimica acta, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

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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

7 authors.

Giorgia PurcaroThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, United States. Electronic address: Giorgia.purcaro@dartmouth.edu.
Pierre-Hugues StefanutoThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, United States.
Flavio A FranchinaThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, United States.
Marco BeccariaThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, United States.
Wendy F Wieland-AlterGeisel School of Medicine, Dartmouth College, Hanover, NH, 03755, United States.
Peter F WrightGeisel School of Medicine, Dartmouth College, Hanover, NH, 03755, United States; Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, United States.
Jane E HillThayer School of Engineering, Dartmouth College, Hanover, NH, 03755, United States; Geisel School of Medicine, Dartmouth College, Hanover, NH, 03755, United States.

Funding

Toward Rapid, Non-Invasive, Highly Sensitive, Multiplex Detection of Respiratory PathogensR21AI121076 · NIAID · DARTMOUTH COLLEGE · PI HILL, JANE, LUNDBLAD, LENNART KARL ALF · 2016 to 2017
$449k
NIAID NIH HHS R21 AI121076
6 · The paper itself

Abstract

Untargeted metabolomics study of volatile organic compounds produced by different cell cultures is a field that has gained increasing attention over the years. Solid-phase microextraction has been the sampling technique of choice for most of the applications mainly due to its simplicity to implement. However, a careful optimization of the analytical conditions is necessary to obtain the best performances, which are highly matrix-dependent. In this work, five different solid-phase microextraction fibers were compared for the analysis of the volatiles produced by cell culture infected with the human respiratory syncytial virus. A central composite design was applied to determine the best time-temperature combination to maximize the extraction efficiency and the salting-out effect was evaluated as well. The linearity of the optimized method, along with limits of detection and quantification and repeatability was assessed. Finally, the effect of i) different normalization techniques (i.e. z-score and probabilistic quotient normalization), ii) data transformation (i.e. in logarithmic scale), and iii) different feature selection algorithms (i.e. Fisher ratio and random forest) on the capability of discriminating between infected and not-infected cell culture was evaluated.

Indexed as

Solid Phase MicroextractionAnalysis of VarianceBiomarkersGas Chromatography-Mass SpectrometryHep G2 CellsHumansLimit of DetectionMetabolomicsRespiratory Syncytial VirusesRespiratory Syncytial Virus InfectionsTemperatureTime FactorsVolatile Organic CompoundsBiomarkersVolatile Organic CompoundsChemometricsComprehensive two-dimensional gas chromatography (GC×GC)Data processingSolid-phase microextraction (SPME)VirusVolatile organic compounds (VOCs)

Identifiers

PMID29866265
PMCPMC5992496

What OpenQuestion holds

Textmetadata
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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.