Evidence map›Paper›PMID 33554045›Full record

ReviewEmergent materials2021

A short review on nanotechnology interventions against COVID-19.

Abhimanyu Tharayil, R Rajakumari, Cintil Jose Chirayil, Sabu Thomas, Nandakumar Kalarikkal

Open access · bronzeAbstract readReview
In one paragraph

Review in Emergent materials, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 14% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. SiONanomaterials (Basel, Switzerland) · 2021
    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.

Abhimanyu Tharayil *School of Energy Materials, Mahatma Gandhi University, Kottayam, Kerala 686560 India.ORCID 0000-0002-1092-0551
R Rajakumari *International and Inter-University Centre for Nanoscience and Nanotechnology, Mahatma Gandhi University, Kottayam, Kerala 686560 India.
Cintil Jose Chirayil *Newman College, Thodupuzha, Kerala 685585 India.
Sabu ThomasSchool of Energy Materials, Mahatma Gandhi University, Kottayam, Kerala 686560 India.
Nandakumar KalarikkalInternational and Inter-University Centre for Nanoscience and Nanotechnology, Mahatma Gandhi University, Kottayam, Kerala 686560 India.
Mahatma Gandhi University · INKerala University of Health Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 has affected all major aspects of the society in a global perspective. The role of nanotechnology is much sought after in fighting this pandemic. Advanced materials based on nanotechnology are the basis of several technologies starting from masks and personal protection equipment to specific diagnostic tools that could diminish the impact of COVID-19. Development of nanotechnology-based products is therefore an absolute necessity for fight against COVID-19. We examine the fundamental concepts related to virology, histopathologic findings and how nanotechnology can help in fighting the disease. In this review we discuss the state of the art and ongoing nanotechnology-based strategies like antiviral coatings, 3D printing and therapeutics to fight against this deadly disease. The importance of using nanoparticles in point of care tests and biosensors is also highlighted.

Indexed as

3D printingAntiviral coatingsCOVID-19COVID-19 testingNanotechnology

Identifiers

PMID33554045
PMCPMC7856851
OpenAlexW3126569051

What OpenQuestion holds

Textmetadata
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.