ReviewProteomics2021
Proteomics in the COVID-19 Battlefield: First Semester Check-Up.
Review in Proteomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Taxonomical and functional changes in COVID-19 faecal microbiome could be related to SARS-CoV-2 faecal load.Environmental microbiology · 2022Article
- Looking at COVID-19 from a Systems Biology Perspective.Biomolecules · 2022Review
- N-glycosylation profiles of the SARS-CoV-2 spike D614G mutant and its ancestral protein characterized by advanced mass spectrometry.Scientific reports · 2021Article
- Heterogeneity of SARS-CoV-2 virus produced in cell culture revealed by shotgun proteomics and supported by genome sequencing.Analytical and bioanalytical chemistry · 2021Article
- Discovery Proteomics for COVID-19: Where We Are Now.Journal of proteome research · 2021Review
- Can molecular mimicry explain the cytokine storm of SARS-CoV-2?: An in silico approach.Journal of medical virology · 2021Article
- SOD1 is a Possible Predictor of COVID-19 Progression as Revealed by Plasma Proteomics.ACS omega · 2021Article
- Applied Proteomics in 'One Health'.Proteomes · 2021Review
- Can proteomics-based approaches further help COVID-19 prevention and therapy?Expert review of proteomics · 2021Article
- Application of spectral library prediction for parallel reaction monitoring of viral peptides.Proteomics · 2021Article
- Proteomics in the COVID-19 Battlefield: First Semester Check-Up.Proteomics · 2021Review
- Proteomics-based mass spectrometry profiling of SARS-CoV-2 infection from human nasopharyngeal samples.Mass spectrometry reviewsReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Proteomics offers a wide collection of methodologies to study biological systems at the finest granularity. Faced with COVID-19, the most worrying pandemic in a century, proteomics researchers have made significant progress in understanding how the causative virus hijacks the host's cellular machinery and multiplies exponentially, how the disease can be diagnosed, and how it develops, as well as its severity predicted. Numerous cellular targets of potential interest for the development of new antiviral drugs have been documented. Here, the most striking results obtained in the proteomics field over this first semester of the pandemic are presented. The molecular machinery of SARS-CoV-2 is much more complex than initially believed, as many post-translational modifications can occur, leading to a myriad of proteoforms and a broad heterogeneity of viral particles. The interplay of protein-protein interactions, protein abundances, and post-translational modifications has yet to be fully documented to provide a full picture of this intriguing but lethal biological threat. Proteomics has the potential to provide rapid detection of the SARS-CoV-2 virus by mass spectrometry proteotyping, and to further increase the knowledge of severe respiratory syndrome COVID-19 and its long-term health consequences.
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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.