Evidence map›Paper›PMID 38798769›Full record

ArticleFrontiers in nutrition2024

Development of a highly sensitive method based on QuEChERS and GC-MS/MS for the determination of polycyclic aromatic hydrocarbons in infant foods.

Mariateresa Ingegno, Rosalia Zianni, Ines Della Rovere, Andrea Chiappinelli, Valeria Nardelli, Francesco Casamassima, Anna Calitri, Maurizio Quinto, Donatella Nardiello, Marco Iammarino

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. EAVLD 2024 - 7Italian journal of food safety · 2024
    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

10 authors.

Mariateresa IngegnoStruttura Complessa di Chimica, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Foggia, Italy.
Rosalia ZianniStruttura Complessa di Chimica, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Foggia, Italy.
Ines Della RovereStruttura Complessa di Chimica, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Foggia, Italy.
Andrea ChiappinelliStruttura Complessa di Chimica, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Foggia, Italy.
Valeria NardelliStruttura Complessa di Chimica, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Foggia, Italy.
Francesco CasamassimaStruttura Complessa di Chimica, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Foggia, Italy.
Anna CalitriStruttura Complessa di Chimica, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Foggia, Italy.
Maurizio QuintoDepartment of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, Foggia, Italy.
Donatella NardielloDepartment of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, Foggia, Italy.
Marco IammarinoStruttura Complessa di Chimica, Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Foggia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polycyclic aromatic hydrocarbons (PAHs) are environmental contaminants that can be found in various food products, including those intended for infants. Due to their potential health risks, it is crucial to develop sensitive analytical methods for the accurate determination of PAHs in infant foods. This study describes the development and validation of a highly sensitive method for the quantification of European PAH markers, namely benzo[a]pyrene, benzo[a]anthracene, chrysene, and benzo[b]fluoranthene, using gas chromatography-tandem mass spectrometry (GC-MS/MS), in baby food samples. The first step was the optimization of the sample preparation procedure, performed using different methods based on the QuEChERS approach, also testing different extraction solvents. Several factors such as extraction efficiency, selectivity, and recovery were evaluated to choose the most effective procedure for sample preparation. Furthermore, the GC-MS/MS method was optimized, evaluating parameters such as linearity, sensitivity, accuracy, and robustness using spiked infant food samples. The method demonstrated excellent linearities with a correlation coefficient higher than 0.999 over a wide concentration range, and limits of detection and limits of quantification in the range 0.019-0.036 μg/kg and 0.06-0.11 μg/kg, respectively. Extraction recoveries were between 73.1 and 110.7%, with relative standard deviations always lower than 8%. These findings are compliant with the indications of the European Commission (Reg. 836/2011). To assess the applicability of the method to official control activities, a survey was conducted on commercially available infant food products. Four markers were determined in commercial samples belonging to different food categories for infants and young children. The outcome of this monitoring showed that PAH contamination, in all samples, was below the quantification limits. In conclusion, the developed GC-MS/MS method provides a highly sensitive and reliable approach for the determination of PAHs in baby foods. The optimized sample preparation, instrumental parameters, and validation results ensure accurate quantification of 4 PAHs even at trace levels. This method could contribute to the assessment of PAH exposure in infants and it could support regulatory efforts to ensure the safety and quality of infant food products with regular monitoring.

Indexed as

food safetyGC–MS/MSinfant foodspolycyclic aromatic hydrocarbons (PAHs)QuEChERSvalidation

Identifiers

PMID38798769
PMCPMC11116592

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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.