Evidence map›Paper›PMID 36560241›Full record

ArticleSensors (Basel, Switzerland)2022

Fluorescent Imprinted Nanoparticles for Sensing of Chlorogenic Acid in Coffee Extracts.

Anggy Lusanna Gutiérrez-Ortiz, Veronica Vida, Matjaž Peterka, Jasmina Tušar, Federico Berti, Luciano Navarini, Cristina Forzato

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. 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
0.4field-weighted citation impact, top 46% of its field
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, 5 citations in OpenAlex.

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

7 authors at 2 institutions in 2 countries.

Anggy Lusanna Gutiérrez-OrtizDipartimento di Scienze Chimiche e Farmaceutiche, Università degli Studi di Trieste, Via Giorgieri 1, 34127 Trieste, Italy.
Veronica VidaDipartimento di Scienze Chimiche e Farmaceutiche, Università degli Studi di Trieste, Via Giorgieri 1, 34127 Trieste, Italy.
Matjaž PeterkaCOBIK, Mirce 21, 5270 Ajdovščina, Slovenia.
Jasmina TušarCOBIK, Mirce 21, 5270 Ajdovščina, Slovenia.
Federico BertiDipartimento di Scienze Chimiche e Farmaceutiche, Università degli Studi di Trieste, Via Giorgieri 1, 34127 Trieste, Italy.ORCID 0000-0001-5608-3798
Luciano NavariniIllycaffè S.p.A., Via Flavia 110, 34147 Trieste, Italy.ORCID 0000-0002-9539-7500
Cristina ForzatoDipartimento di Scienze Chimiche e Farmaceutiche, Università degli Studi di Trieste, Via Giorgieri 1, 34127 Trieste, Italy.ORCID 0000-0003-4213-9089
University of Trieste · ITCentre of Excellence for Biosensors, Instrumentation and Process Control · SI

Funding

European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie 642014
6 · The paper itself

Abstract

Green coffee beans are particularly rich in chlorogenic acids (CGAs), and their identification and quantification are usually performed by HPLC, coupled with mass spectrometry (LC-MS). Although there are a few examples of molecularly imprinted polymers (MIPs) for chlorogenic acid (5-CQA) recognition present in the literature, none of them are based on optical fluorescence, which is very interesting given its great sensitivity. In the present manuscript, fluorescent polymeric imprinted nanoparticles were synthetized following the non-covalent approach using hydrogenated 5-

Indexed as

Chlorogenic AcidNanoparticlesCaffeineChromatography, High Pressure LiquidPolymersCaffeineChlorogenic AcidPolymerschlorogenic acidsfluorescencemolecularly imprinted polymerspolyphenolssensor

Identifiers

PMID36560241
PMCPMC9785805
OpenAlexW4312211797

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.