Development of a recombinase polymerase amplification combined with lateral flow dipstick assay for rapid and sensitive detection of bean common mosaic virus
Bibliographic record
Abstract
Abstract Bean common mosaic virus (BCMV) is one of the most widespread and damaging viruses of cultivated legumes in the world. In addition to serious yield reduction and germplasm decline, BCMV infection also makes legumes more vulnerable to other pathogens. Early diagnosis of the virus is particularly important in limiting its spread. Recombinase polymerase amplification (RPA) is a novel isothermic amplification technology. The whole reaction can be done outside the laboratory environment after the nucleic acid sample is obtained. In this study, we established a rapid and sensitive RPA combined with the lateral flow dipstick (LFD) assay for detection of BCMV, based on the conserved BCMV coat protein (CP) gene sequence. Specific primers and a probe were designed, which amplify ~ 150 bp CP fragments from BCMV-infected samples under a constant temperature of 37 °C for 20 min. The end-labeled amplification products were detected by high-affinity LFD within 5 min. Sensitivity of this RPA-LFD assay was 1000 times greater than that of the conventional polymerase chain reaction (PCR) assay. Furthermore, when the primers/probe were used against related potyviruses including soybean mosaic virus (SMV), bean yellow mosaic virus (BYMV), and turnip mosaic virus (TuMV), the three potyviruses were not detected, indicating that the assay was BCMV species-specific. The RPA-LFD assay was also successfully applied for the detection of seed-borne BCMV in beans. The RPA-LFD assay has great potential application in the rapid diagnosis of BCMV in the field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".