Evidence map›Paper›PMID 36140070›Full record

ReviewBiosensors2022

Three-Dimensional Printing and Its Potential to Develop Sensors for Cancer with Improved Performance.

João B M Rocha Neto, Juliana Coatrini Soares, Guilherme A Longhitano, Andrey Coatrini-Soares, Hernandes F Carvalho, Osvaldo N Oliveira, Marisa M Beppu, Jorge V L da Silva

Open access · goldAbstract readReview
In one paragraph

Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

4 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
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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

8 authors at 4 institutions in 1 country.

João B M Rocha NetoThree-Dimensional Research Group, Renato Archer Information Technology Center-CTI, Campinas 13069-901, Brazil.ORCID 0000-0002-5131-3184
Juliana Coatrini SoaresSão Carlos Institute of Physics, University of São Paulo, São Carlos 13566-59, Brazil.
Guilherme A LonghitanoThree-Dimensional Research Group, Renato Archer Information Technology Center-CTI, Campinas 13069-901, Brazil.ORCID 0000-0001-7598-7098
Andrey Coatrini-SoaresNanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, São Carlos 13560-970, Brazil.ORCID 0000-0003-4601-3555
Hernandes F CarvalhoInstitute of Biology, Department of Structural and Functional Biology, University of Campinas, Campinas 13083-86, Brazil.ORCID 0000-0002-3080-9447
Osvaldo N OliveiraSão Carlos Institute of Physics, University of São Paulo, São Carlos 13566-59, Brazil.
Marisa M BeppuSchool of Chemical Engineering, Department of Materials and Bioprocess Engineering, University of Campinas, Campinas 13083-852, Brazil.
Jorge V L da SilvaThree-Dimensional Research Group, Renato Archer Information Technology Center-CTI, Campinas 13069-901, Brazil.
Universidade Estadual de Campinas (UNICAMP) · BRUniversidade Federal de São Carlos · BRBrazilian Agricultural Research Corporation · BRCentro de Tecnologia da Informação Renato Archer · BR

Funding

National Council for Scientific and Technological Development #114307/2020-2São Paulo Research Foundation #2020/12980-3, #2020/05612-8, #2018/22214-6 and #2018/18953-8
6 · The paper itself

Abstract

Cancer is the second leading cause of death globally and early diagnosis is the best strategy to reduce mortality risk. Biosensors to detect cancer biomarkers are based on various principles of detection, including electrochemical, optical, electrical, and mechanical measurements. Despite the advances in the identification of biomarkers and the conventional 2D manufacturing processes, detection methods for cancers still require improvements in terms of selectivity and sensitivity, especially for point-of-care diagnosis. Three-dimensional printing may offer the features to produce complex geometries in the design of high-precision, low-cost sensors. Three-dimensional printing, also known as additive manufacturing, allows for the production of sensitive, user-friendly, and semi-automated sensors, whose composition, geometry, and functionality can be controlled. This paper reviews the recent use of 3D printing in biosensors for cancer diagnosis, highlighting the main advantages and advances achieved with this technology. Additionally, the challenges in 3D printing technology for the mass production of high-performance biosensors for cancer diagnosis are addressed.

Indexed as

Biosensing TechniquesNeoplasmsBiomarkers, TumorHumansPrinting, Three-DimensionalBiomarkers, Tumoradditive manufacturingcancerearly diagnosissensorsthree-dimensional printing

Identifiers

PMID36140070
PMCPMC9496342
OpenAlexW4293414978

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.