Evidence map›Paper›PMID 35735523›Full record

ArticleBiosensors2022

From a Chemotherapeutic Drug to a High-Performance Nanocatalyst: A Fast Colorimetric Test for Cisplatin Detection at ppb Level.

Valentina Mastronardi, Mauro Moglianetti, Edoardo Ragusa, Rodolfo Zunino, Pier Paolo Pompa

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2022. 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
0.9field-weighted citation impact, top 29% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

5 authors at 2 institutions in 1 country.

Valentina MastronardiNanobiointeractions & Nanodiagnostics, Istituto Italiano di Tecnologia (IIT), Via Morego, 16163 Genova, Italy.ORCID 0000-0003-0185-1934
Mauro MoglianettiNanobiointeractions & Nanodiagnostics, Istituto Italiano di Tecnologia (IIT), Via Morego, 16163 Genova, Italy.ORCID 0000-0003-0747-7963
Edoardo RagusaDepartment of Electrical, Electronic, Telecommunications Engineering and Naval Architecture, University of Genova, Via Opera Pia, 11a, 16145 Genova, Italy.ORCID 0000-0002-5527-6325
Rodolfo ZuninoDepartment of Electrical, Electronic, Telecommunications Engineering and Naval Architecture, University of Genova, Via Opera Pia, 11a, 16145 Genova, Italy.
Pier Paolo PompaNanobiointeractions & Nanodiagnostics, Istituto Italiano di Tecnologia (IIT), Via Morego, 16163 Genova, Italy.ORCID 0000-0001-7549-0612
Italian Institute of Technology · ITUniversity of Genoa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A rapid point-of-care method for the colorimetric detection of cisplatin was developed, exploiting the efficient conversion of the chemotherapeutic drug into a high-performance nanocatalyst with peroxidase enzyme mimics. This assay provides high specificity and ppb-detection sensitivity with the naked eye or a smartphone-based readout, outperforming many standard laboratory-based techniques. The nanocatalyst-enabled colorimetric assay can be integrated with machine-learning methods, providing accurate quantitative measurements. Such a combined approach opens interesting perspectives for the on-site monitoring of both chemotherapeutic patients to achieve optimal treatments and healthcare workers to prevent their unsafe exposure.

Indexed as

CisplatinColorimetryHumansLimit of DetectionSmartphoneCisplatincisplatincolorimetric testmachine learningnanocatalystpoint-of-care

Identifiers

PMID35735523
PMCPMC9221495
OpenAlexW4281610480

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.