Rapid detection of human rotavirus using colorimetric nucleic acid sequence-based amplification (NASBA)âenzyme-linked immunosorbent assay in sewage treatment effluent
Bibliographic record
Abstract
A colorimetric nucleic acid sequence-based amplification-enzyme-linked immunosorbent assay (NASBA-ELISA) was developed for rapid detection and identification of human rotavirus. Oligonucleotide primers targeting gene 9 encoding a serotype-specific antigen VP7 were selected and used for the amplification of viral RNA by the isothermal NASBA process, resulting in the accumulation of biotinylated RNA amplicons. Amplicons were hybridized with a specific amino-linked oligonucleotide probe covalently immobilized on microtiter plates. The DNA-RNA hybrids were colorimetrically detected by the addition of streptavidin-peroxidase conjugate and tetramethylbenzidine substrate. Using the NASBA-ELISA system, as little as 0.2 PFU (4 x 10(1) PFU ml(-1)) and 15 PFU (3 x 10(3) PFU ml(-1)) of rotavirus were detected within 6 h in spiked MQ water and sewage treatment effluent respectively. No interference was encountered in the amplification and detection of rotavirus in the presence of non-target RNA or DNA. Moreover, the presence of non-target bacteria and virus does not generate any non-specific signal, confirming the specificity of the developed NASBA-ELISA system and its effectiveness in specifically detecting rotavirus. The NASBA-ELISA system offers several advantages in terms of sensitivity, rapidity and simplicity. This technique should be readily adaptable for detection of other RNA viruses in both foods and clinical samples.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".