Evidence map›Paper›PMID 37504143›Full record

ArticleBiosensors2023

Time-Resolved Fluorescence Spectroscopy of Molecularly Imprinted Nanoprobes as an Ultralow Detection Nanosensing Tool for Protein Contaminants.

Alessandra Maria Bossi, Alice Marinangeli, Alberto Quaranta, Lucio Pancheri, Devid Maniglio

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 35% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Alessandra Maria BossiDepartment of Biotechnology, University of Verona, Strada Le Grazie 15, 37134 Verona, Italy.ORCID 0000-0002-2542-8412
Alice MarinangeliDepartment of Biotechnology, University of Verona, Strada Le Grazie 15, 37134 Verona, Italy.ORCID 0009-0003-5605-4980
Alberto QuarantaDepartment of Industrial Engineering, University of Trento, Via Sommarive 9, Povo, 38123 Trento, Italy.ORCID 0000-0003-1320-091X
Lucio PancheriDepartment of Industrial Engineering, University of Trento, Via Sommarive 9, Povo, 38123 Trento, Italy.ORCID 0000-0002-3954-7308
Devid ManiglioDepartment of Industrial Engineering, University of Trento, Via Sommarive 9, Povo, 38123 Trento, Italy.ORCID 0000-0002-1653-861X
University of Trento · ITUniversity of Verona · IT

Funding

Ministero dell'Università e della Ricerca (MUR) DM 351 doctoral programTrento University-Bando Covid 19 OPTOVIR
6 · The paper itself

Abstract

Currently, optical sensors based on molecularly imprinted polymers (MIPs) have been attracting significant interest. MIP sensing relies on the combination of the MIP's selective capability, which is conveyed to the polymeric material by a template-assisted synthesis, with optical techniques that offer exquisite sensitivity. In this work, we devised an MIP nanoparticle optical sensor for the ultralow detection of serum albumin through time-resolved fluorescence spectroscopy. The Fluo-nanoMIPs (∅~120 nm) were synthetized using fluorescein-O-methacrylate (0.1×, 1×, 10× mol:mol versus template) as an organic fluorescent reporter. The ability of 0.1× and 1×Fluo-nanoMIPs to bind albumin (15 fM-150 nM) was confirmed by fluorescence intensity analyses and isothermal titration calorimetry. The apparent dissociation constant (K

Indexed as

Molecular ImprintingNanoparticlesAlbuminsLimit of DetectionSpectrometry, FluorescenceAlbuminslifetime decaymolecularly imprinted polymersnanosensoroptical sensortime resolved fluorescence spectroscopywine

Identifiers

PMID37504143
PMCPMC10377162
OpenAlexW4384770205

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.