Evidence map›Paper›PMID 33015361›Full record

ReviewAPL photonics2020

Engineering photonics solutions for COVID-19.

Maria Soler, Alexis Scholtz, Rene Zeto, Andrea M Armani

Abstract readReview
In one paragraph

Review in APL photonics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Evaluation of the effectiveness of UV-C dose for photoinactivation of SARS-CoV-2 in contaminated N95 respirator, surgical and cotton fabric masks.Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology · 2022
    Article
  5. Review
  6. Review
  7. Review
  8. On-Chip Optical Detection of Viruses: A Review.Advanced photonics research · 2021
    Article
  9. 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

4 authors.

Maria SolerNanobiosensors and Bioanalytical Applications Group (NanoB2A), Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC, BIST and CIBER-BBN, Barcelona, Spain.
Alexis ScholtzDepartment of Biomedical Engineering, University of Southern California, Los Angeles, California 90089, USA.
Rene ZetoMork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the impact of COVID-19 on society became apparent, the engineering and scientific community recognized the need for innovative solutions. Two potential roadmaps emerged: developing short-term solutions to address the immediate needs of the healthcare communities and developing mid/long-term solutions to eliminate the over-arching threat. However, in a truly global effort, researchers from all backgrounds came together in tackling this challenge. Short-term efforts have focused on re-purposing existing technologies and leveraging additive manufacturing techniques to address shortages in personal protective equipment and disinfection. More basic research efforts with mid-term and long-term impact have emphasized developing novel diagnostics and accelerating vaccines. As a foundational technology, photonics has contributed directly and indirectly to all efforts. This perspective will provide an overview of the critical role that the photonics field has played in efforts to combat the immediate COVID-19 pandemic as well as how the photonics community could anticipate contributing to future pandemics of this nature.

Identifiers

PMID33015361
PMCPMC7523711

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.