Evidence map›Paper›PMID 37268814›Full record

ArticleScientific reports2023

Ultra-high performance liquid chromatography high-resolution mass spectrometry for metabolomic analysis of dental calculus from Duke Alessandro Farnese and Maria D'Aviz.

Nicolo' Riboni, Federica Bianchi, Monica Mattarozzi, Marianna Peracchia, Marco Meleti, Maria Careri

Abstract read
In one paragraph

Article in Scientific reports, 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

6 authors.

Nicolo' RiboniDepartment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area Delle Scienze 17/A, 43124, Parma, Italy. nicolo.riboni@unipr.it.
Federica BianchiDepartment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area Delle Scienze 17/A, 43124, Parma, Italy. federica.bianchi@unipr.it.ORCID 0000-0001-7880-5624
Monica MattarozziDepartment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area Delle Scienze 17/A, 43124, Parma, Italy.
Marianna PeracchiaDepartment of Medicine and Surgery, Centro Universitario di Odontoiatria, University of Parma, Via Gramsci 14, 43126, Parma, Italy.
Marco MeletiDepartment of Medicine and Surgery, Centro Universitario di Odontoiatria, University of Parma, Via Gramsci 14, 43126, Parma, Italy.
Maria CareriDepartment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area Delle Scienze 17/A, 43124, Parma, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dental calculus is a valuable resource for the reconstruction of dietary habits and oral microbiome of past populations. In 2020 the remains of Duke Alessandro Farnese and his wife Maria D'Aviz were exhumed to get novel insights into the causes of death. This study aimed to investigate the dental calculus metabolome of the noble couple by untargeted metabolomics. The pulverized samples were decalcified in a water-formic acid mixture, extracted using methanol/acetonitrile and analyzed by ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) using a reversed-phase separation followed by electrospray ionization and full scan in positive and negative ion mode. Waters Synapt-G2-Si High-Definition hybrid quadrupole time-of-flight mass spectrometer was used. Significant features were then identified using MS

Indexed as

Dental CalculusMetabolomicsChromatography, High Pressure LiquidHumansMass SpectrometryMetabolome

Identifiers

PMID37268814
PMCPMC10238497

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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.