ArticleThe Veterinary record
Towards a microRNA-based Johne's disease diagnostic predictive system: Preliminary results.
Article in The Veterinary record. 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.
- Advances in paratuberculosis research and control: a comprehensive expert review.BMC veterinary research · 2026Review
- Comparison of Machine Learning Tree-Based Algorithms to Predict Future Paratuberculosis ELISA Results Using Repeat Milk Tests.Animals : an open access journal from MDPI · 2024Article
- Towards a microRNA-based Johne's disease diagnostic predictive system: Preliminary results.The Veterinary recordArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundJohne's disease, caused by Mycobacterium avium subspecies paratuberculosis (MAP), is a chronic enteritis that adversely affects welfare and productivity in cattle. Screening and subsequent removal of affected animals is a common approach for disease management, but efforts are hindered by low diagnostic sensitivity. Expression levels of small non-coding RNA molecules involved in gene regulation (microRNAs), which may be altered during mycobacterial infection, may present an alternative diagnostic method.
methodsThe expression levels of 24 microRNAs affected by mycobacterial infection were measured in sera from MAP-positive (n = 66) and MAP-negative cattle (n = 65). They were then used within a machine learning approach to build an optimal classifier for MAP diagnosis.
resultsThe method provided 72% accuracy, 73% sensitivity and 71% specificity on average, with an area under the curve of 78%. LIMITATIONS: Although control samples were collected from farms nominally MAP-free, the low sensitivity of current diagnostics means some animals may have been misclassified.
conclusionMicroRNA profiling combined with advanced predictive modelling enables rapid and accurate diagnosis of Johne's disease in cattle.
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.