ArticlePLoS neglected tropical diseases2023
Antigen discovery by bioinformatics analysis and peptide microarray for the diagnosis of cystic echinococcosis.
Article in PLoS neglected tropical diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Recent advances in clinical and laboratory diagnosis of hydatid cyst: from imaging to recombinant and nanobiosensor-based approaches.Infection · 2026Review
- Immunogenic mapping of potential epitopes from Tc-CTL-1 for the diagnosis of murine toxocariasis.Memorias do Instituto Oswaldo Cruz · 2025Article
- Evaluation of the Local and Peripheral Immune Responses in Patients with Cystic Echinococcosis.Pathogens (Basel, Switzerland) · 2024Article
- Limited value of current and newFrontiers in parasitology · 2023Article
Corrections and comments
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Authors and funding
10 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCystic echinococcosis (CE), caused by Echinococcus granulosus sensu lato, is a neglected zoonosis. Its diagnosis relies on imaging, supported by serology, while only imaging is useful for staging and follow-up. Since diagnostic tools and expertise are not widely available, new accurate and easily implementable assays for the diagnosis and follow-up of CE are highly needed. METHODOLOGY/PRINCIPAL
findingsWe aimed to identify new E. granulosus antigens through a bioinformatics selection applied to the parasite genome, followed by peptide microarray screening and validation in ELISA, using independent panels of sera from patients with hepatic CE and clinically relevant controls. From 950 proteins selected in silico, 2,379 peptides were evaluated by microarray for IgG reactivity and eight candidates selected for validation. Reactivity to one peptide was significantly higher in the CE group (p = 0.044), but had suboptimal diagnostic accuracy. CONCLUSIONS/SIGNIFICANCE: Here we performed bioinformatics analysis and peptide microarray for antigen discovery, useful for the diagnosis of CE. Eight candidates were selected and validated. Reactivity to one peptide associated to CE but had suboptimal diagnostic accuracy. Importantly, the database developed in this study may be used to identify other antigenic candidates for CE diagnosis and follow-up.
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Registered trials
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