Evidence map›Paper›PMID 37032711›Full record

ReviewDiscover nano2023

Impact of nanotechnology on conventional and artificial intelligence-based biosensing strategies for the detection of viruses.

Murugan Ramalingam, Abinaya Jaisankar, Lijia Cheng, Sasirekha Krishnan, Liang Lan, Anwarul Hassan, Hilal Turkoglu Sasmazel, Hirokazu Kaji, Hans-Peter Deigner, Jose Luis Pedraz and 3 more

Abstract readReview
In one paragraph

Review in Discover nano, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Advanced Nanostructured Coatings Based on Doped TiOMolecules (Basel, Switzerland) · 2023
    Review
  11. Article
  12. 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

13 authors.

Murugan RamalingamSchool of Basic Medical Sciences, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu, 610106 China.
Abinaya Jaisankar *Centre for Biomaterials, Cellular and Molecular Theranostics, School of Mechanical Engineering, Vellore Institute of Technology, Vellore, 632014 India.
Lijia Cheng *School of Basic Medical Sciences, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu, 610106 China.
Sasirekha KrishnanCentre for Biomaterials, Cellular and Molecular Theranostics, School of Mechanical Engineering, Vellore Institute of Technology, Vellore, 632014 India.
Liang LanSchool of Basic Medical Sciences, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu, 610106 China.
Anwarul HassanDepartment of Mechanical and Industrial Engineering, Biomedical Research Center, Qatar University, 2713, Doha, Qatar.
Hilal Turkoglu SasmazelDepartment of Metallurgical and Materials Engineering, Faculty of Engineering, Atilim University, 06836 Ankara, Turkey.
Hirokazu KajiDepartment of Biomechanics, Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, Tokyo, 101-0062 Japan.
Hans-Peter DeignerInstitute of Precision Medicine, Medical and Life Sciences Faculty, Furtwangen University, 78054 Villingen-Schwenningen, Germany.
Jose Luis PedrazNanoBioCel Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country, 01006 Vitoria-Gasteiz, Spain.
Hae-Won KimInstitute of Tissue Regeneration Engineering, Dankook University, Cheonan, 31116 Republic of Korea.
Zheng ShiSchool of Basic Medical Sciences, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu, 610106 China.
Giovanna MarrazzaDepartment of Chemistry "Ugo Schiff", University of Florence, 50019 Sesto Fiorentino, Florence, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent years have witnessed the emergence of several viruses and other pathogens. Some of these infectious diseases have spread globally, resulting in pandemics. Although biosensors of various types have been utilized for virus detection, their limited sensitivity remains an issue. Therefore, the development of better diagnostic tools that facilitate the more efficient detection of viruses and other pathogens has become important. Nanotechnology has been recognized as a powerful tool for the detection of viruses, and it is expected to change the landscape of virus detection and analysis. Recently, nanomaterials have gained enormous attention for their value in improving biosensor performance owing to their high surface-to-volume ratio and quantum size effects. This article reviews the impact of nanotechnology on the design, development, and performance of sensors for the detection of viruses. Special attention has been paid to nanoscale materials, various types of nanobiosensors, the internet of medical things, and artificial intelligence-based viral diagnostic techniques.

Indexed as

Artificial intelligenceNanobiosensorsNanomaterialsNanotechnologyViral diagnostics

Identifiers

PMID37032711
PMCPMC10066940

What Socratic 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 Socratic graph.