ArticleCurrent opinion in solid state & materials science2022
Overcoming the limitations of COVID-19 diagnostics with nanostructures, nucleic acid engineering, and additive manufacturing.
Article in Current opinion in solid state & materials science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 17 citations in OpenAlex.
- Selective capture and digital counting of intact HIV pseudovirus using designer DNA nets, tethered motion, and photonic resonator interferometric scattering microscopy.APL bioengineering · 2026Article
- Evaporation-Enhanced Redox Cycling for Rapid Detection of Attomolar SARS-CoV-2 Virions Using Nanolithography-Free Electrochemical Devices.Advanced materials technologies · 2025Article
- Sustainable materials and COVID-19 detection biosensor: A brief review.Sensors international · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
The COVID-19 pandemic revealed fundamental limitations in the current model for infectious disease diagnosis and serology, based upon complex assay workflows, laboratory-based instrumentation, and expensive materials for managing samples and reagents. The lengthy time delays required to obtain test results, the high cost of gold-standard PCR tests, and poor sensitivity of rapid point-of-care tests contributed directly to society's inability to efficiently identify COVID-19-positive individuals for quarantine, which in turn continues to impact return to normal activities throughout the economy. Over the past year, enormous resources have been invested to develop more effective rapid tests and laboratory tests with greater throughput, yet the vast majority of engineering and chemistry approaches are merely incremental improvements to existing methods for nucleic acid amplification, lateral flow test strips, and enzymatic amplification assays for protein-based biomarkers. Meanwhile, widespread commercial availability of new test kits continues to be hampered by the cost and time required to develop single-use disposable microfluidic plastic cartridges manufactured by injection molding. Through development of novel technologies for sensitive, selective, rapid, and robust viral detection and more efficient approaches for scalable manufacturing of microfluidic devices, we can be much better prepared for future management of infectious pathogen outbreaks. Here, we describe how photonic metamaterials, graphene nanomaterials, designer DNA nanostructures, and polymers amenable to scalable additive manufacturing are being applied towards overcoming the fundamental limitations of currently dominant COVID-19 diagnostic approaches. In this paper, we review how several distinct classes of nanomaterials and nanochemistry enable simple assay workflows, high sensitivity, inexpensive instrumentation, point-of-care sample-to-answer virus diagnosis, and rapidly scaled manufacturing.
Indexed as
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What OpenQuestion holds
Registered trials
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.