ReviewMolecular diagnosis & therapy2023
Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies.
Review in Molecular diagnosis & therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Neuromorphic chips for biomedical engineering.Mechanobiology in medicine · 2025Review
- The potential relationship between EasyNAT system Tt values and Cobas z480 Ct values in the detection of SARS-Cov-2.Practical laboratory medicine · 2024Article
- Emerging Landscape of Mesenchymal Stem Cell Senescence Mechanisms and Implications on Therapeutic Strategies.ACS pharmacology & translational science · 2024Review
- Emerging Landscape of Preclinical Models for Studying COVID-19 Neurologic Diseases.ACS pharmacology & translational science · 2023Review
- Emerging Landscape of Nanobodies and Their Neutralizing Applications against SARS-CoV-2 Virus.ACS pharmacology & translational science · 2023Review
- Evaluation of Potential Peptide-Based Inhibitors against SARS-CoV-2 and Variants of Concern.BioMed research international · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In 2019, a new coronavirus was identified that has caused significant morbidity and mortality worldwide. Like all RNA viruses, severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) evolves over time through random mutation resulting in genetic variations in the population. Although the currently approved coronavirus disease 2019 vaccines can be given to those over 5 years of age and older in most countries, strikingly, the number of people diagnosed positive for SARS-Cov-2 is still increasing. Therefore, to prevent and control this epidemic, early diagnosis of infected individuals is of great importance. The current detection of SARS-Cov-2 coronavirus variants are mainly based on reverse transcription-polymerase chain reaction. Although the sensitivity of reverse transcription-polymerase chain reaction is high, it has some disadvantages, for example, multiple temperature changes, long detection time, complicated operation, expensive instruments, and the need for professional personnel, which brings considerable inconvenience to the early diagnosis of this virus. This review comprehensively summarizes the development and application of various current detection technologies for novel coronaviruses, including isothermal amplification, CRISPR-Cas detection, serological detection, biosensor, ensemble, and microfluidic technology, along with next-generation sequencing. Those findings offer us a great potential to replace or combine with reverse transcription-polymerase chain reaction detection to achieve the purpose of allowing predictive diagnostics and targeted prevention of SARS-Cov-2 in the future.
Indexed as
Identifiers
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.