Evidence map›Paper›PMID 36802528›Full record

ArticleAnalytical chemistry2023

Scalable Analysis of Untargeted LC-HRMS Data by Means of SQL Database Archiving.

Marie Mardal, Petur W Dalsgaard, Brian S Rasmussen, Kristian Linnet, Christian B Mollerup

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Article in Analytical chemistry, 2023. 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
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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Marie MardalDepartment of Forensic Medicine, University of Copenhagen, Frederik V's vej 11, Ø Copenhagen, Denmark.ORCID 0000-0002-3203-7305
Petur W DalsgaardDepartment of Forensic Medicine, University of Copenhagen, Frederik V's vej 11, Ø Copenhagen, Denmark.
Brian S RasmussenDepartment of Forensic Medicine, University of Copenhagen, Frederik V's vej 11, Ø Copenhagen, Denmark.
Kristian LinnetDepartment of Forensic Medicine, University of Copenhagen, Frederik V's vej 11, Ø Copenhagen, Denmark.
Christian B MollerupDepartment of Forensic Medicine, University of Copenhagen, Frederik V's vej 11, Ø Copenhagen, Denmark.ORCID 0000-0001-8187-6474

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is widely used to detect chemicals with a broad range of physiochemical properties in complex biological samples. However, the current data analysis strategies are not sufficiently scalable because of data complexity and amplitude. In this article, we report a novel data analysis strategy for HRMS data founded on structured query language database archiving. A database called ScreenDB was populated with parsed untargeted LC-HRMS data after peak deconvolution from forensic drug screening data. The data were acquired using the same analytical method over 8 years. ScreenDB currently holds data from around 40,000 data files, including forensic cases and quality control samples that can be readily sliced and diced across data layers. Long-term monitoring of system performance, retrospective data analysis for new targets, and identification of alternative analytical targets for poorly ionized analytes are examples of ScreenDB applications. These examples demonstrate that ScreenDB makes a significant improvement to forensic services and that the concept has potential for broad applications for all large-scale biomonitoring projects that rely on untargeted LC-HRMS data.

Indexed as

Forensic MedicineChromatography, LiquidMass SpectrometryRetrospective Studies

Identifiers

PMID36802528
PMCPMC10018448

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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.