ReviewJournal of proteome research2020
Utility of Proteomics in Emerging and Re-Emerging Infectious Diseases Caused by RNA Viruses.
Review in Journal of proteome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed, 45 citations in OpenAlex.
- Specimen Inactivation Methods for Proteomics─Comparisons of Irradiation, Chemical, and Heat Treatments on Downstream Serum Analyses.Journal of proteome research · 2025Article
- Serum proteomic approach to identifying differentially expressed proteins in effusive feline infectious peritonitis.Scientific reports · 2025Article
- Review
- Advances in bioinformatics and multi-omics integration: transforming viral infectious disease research in veterinary medicine.Virology journal · 2025Review
- What Can Proteomics Tell us About COVID-19 Infections? Mass Spectrometry as a Tool to Find New Proteins as Biomarkers.Current protein & peptide science · 2025Review
- Emerging Microorganisms and Infectious Diseases: One Health Approach for Health Shared Vision.Genes · 2024Review
- Review on the Applications of Selected Metal-Based Complexes on Infectious Diseases.Molecules (Basel, Switzerland) · 2024Review
- Proteomics: Unraveling the Cross Talk Between Innate Immunity and Disease Pathophysiology, Diagnostics, and Treatment Options.Advances in experimental medicine and biology · 2024Review
- Mass spectrometry-based proteomics as an emerging tool in clinical laboratories.Clinical proteomics · 2023Review
- HMGB1 is involved in viral replication and the inflammatory response in coxsackievirus A16-infected 16HBE cells via proteomic analysis and identification.Virology journal · 2023Article
- Tandem mass tag (TMT) labeling-based quantitative proteomic analysis reveals the cellular protein characteristics of 16HBE cells infected with coxsackievirus A10 and the potential effect of HMGB1 on viral replication.Archives of virology · 2023Article
- Establishing Quality Control Procedures for Large-Scale Plasma Proteomics Analyses.Journal of the American Society for Mass Spectrometry · 2023Article
- Article
- Ion Mobility Mass Spectrometry (IM-MS) for Structural Biology: Insights Gained by Measuring Mass, Charge, and Collision Cross Section.Chemical reviews · 2023Review
- Host cell proteins modulated upon Toxoplasma infection identified using proteomic approaches: a molecular rationale.Parasitology research · 2022Review
- Mining the Proteome ofAnimals : an open access journal from MDPI · 2022Review
- Selenium and protozoan parasitic infections: selenocompounds and selenoproteins potential.Parasitology research · 2022Review
- Advances in understanding of the innate immune response to human norovirus infection using organoid models.The Journal of general virology · 2022Review
- Discovery Proteomics for COVID-19: Where We Are Now.Journal of proteome research · 2021Review
- Are the Organoid Models an Invaluable Contribution to ZIKA Virus Research?Pathogens (Basel, Switzerland) · 2021Review
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 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Emerging and re-emerging infectious diseases due to RNA viruses cause major negative consequences for the quality of life, public health, and overall economic development. Most of the RNA viruses causing illnesses in humans are of zoonotic origin. Zoonotic viruses can directly be transferred from animals to humans through adaptation, followed by human-to-human transmission, such as in human immunodeficiency virus (HIV), severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and, more recently, SARS coronavirus 2 (SARS-CoV-2), or they can be transferred through insects or vectors, as in the case of Crimean-Congo hemorrhagic fever virus (CCHFV), Zika virus (ZIKV), and dengue virus (DENV). At the present, there are no vaccines or antiviral compounds against most of these viruses. Because proteins possess a vast array of functions in all known biological systems, proteomics-based strategies can provide important insights into the investigation of disease pathogenesis and the identification of promising antiviral drug targets during an epidemic or pandemic. Mass spectrometry technology has provided the capacity required for the precise identification and the sensitive and high-throughput analysis of proteins on a large scale and has contributed greatly to unravelling key protein-protein interactions, discovering signaling networks, and understanding disease mechanisms. In this Review, we present an account of quantitative proteomics and its application in some prominent recent examples of emerging and re-emerging RNA virus diseases like HIV-1, CCHFV, ZIKV, and DENV, with more detail with respect to coronaviruses (MERS-CoV and SARS-CoV) as well as the recent SARS-CoV-2 pandemic.
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.