Evidence map›Paper›PMID 41175218›Full record

ArticleAnalytical and bioanalytical chemistry2025

A bio-SPME-LC-MS/MS method for the quantitative determination of cannabinoids in plasma samples: analytical strategy for optimization of matrix modification.

Camila Marchioni, Emanuela Gionfriddo

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Analytical and bioanalytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Camila MarchioniDepartment of Pathology, Federal University of Santa Catarina, Rua Engenheiro Agronômico Andrei Cristian Ferreira, S/N - Trindade, Florianópolis, SC, 88040-900, Brazil. camila.marchioni@ufsc.br.ORCID http://orcid.org/0000-0003-2482-914X
Emanuela GionfriddoDepartment of Chemistry, University at Buffalo, The State University of New York, Buffalo, NY, USA.ORCID http://orcid.org/0000-0002-1836-1950

Funding

Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina 1668/2024
6 · The paper itself

Abstract

Cannabis sp. has been widely used for both medicinal and recreational purposes globally. Analyzing cannabinoids and their metabolites in human plasma samples is crucial for managing acute intoxications and for therapeutic monitoring in patients. This study describes the optimization and validation of an innovative, sensitive, simple, and environmentally friendly biocompatible solid-phase microextraction (bio-SPME) method using a hydrophilic-lipophilic balance (HLB)/polyacrylonitrile (PAN)-thin film for the quantification of cannabinoids (cannabidiol, tetrahydrocannabinol, and cannabinol) and their main metabolites (11-hydroxy-Δ9-tetrahydrocannabinol and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol acid) in human plasma samples. Extraction efficiency was compared between two geometry SPME devices (e.g., thin film and fiber geometry), showing that the use of the thin film microextraction (TFME) device improved extraction performance. Matrix modification was optimized using a central composite design to determine the optimal combination of sample dilution, organic modifier addition, and salt usage. The most effective matrix modification was achieved with 380 µL of phosphate-buffered saline solution containing 0.015 mol L

Indexed as

CannabinoidsSolid Phase MicroextractionTandem Mass SpectrometryChromatography, LiquidHumansLimit of DetectionLiquid Chromatography-Mass SpectrometryReproducibility of ResultsCannabinoidsCannabinoidsDI-SPMEMatrix modificationPlasma samplesThin film microextraction

Identifiers

PMID41175218

What OpenQuestion holds

Textmetadata
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.