Evidence map›Paper›PMID 36773114›Full record

ArticleMikrochimica acta2023

Red emissive N-doped carbon dots encapsulated within molecularly imprinted polymers for optosensing of pyrraline in fatty foods.

Chenchen Xie, Jingbo He, Chen Meng, Xiaolin Chen, Huilin Liu, Baoguo Sun

Abstract read
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In one paragraph

Article in Mikrochimica acta, 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. Neuropilin-1: A Multifaceted Target for Cancer Therapy.Current oncology (Toronto, Ont.) · 2025
    Review
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.

Chenchen XieSchool of Food and Health, Beijing Technology & Business University (BTBU), Beijing, 100048, China.
Jingbo HeSchool of Food and Health, Beijing Technology & Business University (BTBU), Beijing, 100048, China.
Chen MengSchool of Food and Health, Beijing Technology & Business University (BTBU), Beijing, 100048, China.
Xiaolin ChenSchool of Food and Health, Beijing Technology & Business University (BTBU), Beijing, 100048, China.
Huilin LiuSchool of Food and Health, Beijing Technology & Business University (BTBU), Beijing, 100048, China. liuhuilin@btbu.edu.cn.ORCID http://orcid.org/0000-0002-5698-0453
Baoguo SunSchool of Food and Health, Beijing Technology & Business University (BTBU), Beijing, 100048, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel and facile method was proposed for preparation of red emissive N-doped carbon dots encapsulated within molecularly imprinted polymers (RNCDs@MIPs) using a one-pot room-temperature reverse microemulsion polymerization. RNCDs used citric acid and urea as carbon and nitrogen sources by one-step solvothermal synthesis with the optimum emission of 620 nm. Unique optical properties of RNCDs coupled with high selective MIPs make the RNCDs@MIPs conjugate capable to adsorb specific targets of pyrraline (PRL), such a binding event was then transduced to quench fluorescence response signal of the RNCDs. RNCDs@MIPs for PRL showed linearity from 0.1 to 40 μg/L, with a detection limit of 65 ng/L. The RNCDs@MIPs exhibited a good reproducibility of 4.67% obtained from four times of rebinding for PRL. The optosensing probe was successfully applied to the detection of PRL in fatty foods with the spiked recovery of 85.93-106.96%.

Indexed as

Molecular ImprintingQuantum DotsCarbonMolecularly Imprinted PolymersNorleucinePolymersPyrrolesReproducibility of Results2-formyl-5-(hydroxymethyl)pyrrole-1-norleucineCarbonMolecularly Imprinted PolymersNorleucinePolymersPyrrolesCarbon dotsMolecularly imprinted polymersOptosensingPyrraline determination

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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.