Development and Evaluation of a Simple Assay for Marburg Virus Detection Using a Reverse Transcription-Loop-Mediated Isothermal Amplification Method
Bibliographic record
Abstract
Marburg virus (MARV) causes a severe hemorrhagic fever in humans with a high mortality rate. The rapid and accurate identification of the virus is required to appropriately provide infection control and outbreak management. Here, we developed and evaluated a one-step reverse transcription-loop-mediated isothermal amplification (RT-LAMP) assay for the rapid and simple detection of MARV. By combining two sets of primers specific for the Musoke and Ravn genetic lineages, a multiple RT-LAMP assay detected MARV strains of both lineages, and no cross-reactivity with other hemorrhagic fever viruses (Ebola virus and Lassa virus) was observed. The assay could detect 10(2) copies of the viral RNA per tube within 40 min by real-time monitoring of the turbidities of the reaction mixtures. The assay was further evaluated using viral RNA extracted from clinical specimens collected in the 2005 Marburg hemorrhagic fever outbreak in Angola and yielded positive results for samples containing MARV at greater than 10(4) 50% tissue culture infective doses/ml, exhibiting 78% (14 of 18 samples positive) consistency with the results of a reverse transcription-PCR assay carried out in the field laboratory. The results obtained by both agarose gel electrophoresis and naked-eye judgment indicated that the RT-LAMP assay developed in this study is an effective tool for the molecular detection of MARV. Furthermore, it seems suitable for use for field diagnostics or in laboratories in areas where MARV is endemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".