Visible and rapid detection of feline chaphamaparvovirus using multienzyme isothermal rapid amplification and lateral flow dipstick assay
Bibliographic record
Abstract
Feline chaphamaparvovirus (FeChPV) is a novel parvovirus previously reported in Canadian cats and Chinese dogs with diarrhea in 2019 and 2020, respectively. Herein, we aimed to establish a simple detection method for FeChPV in field clinics. The primers and probes for the multienzyme isothermal rapid amplification and lateral flow dipstick (MIRA-LFD) assay were designed to target the conserved regions of the FeChPV genome and determine the optimal reaction temperature and time. Without relying on precision instruments, FeChPV detection using the MIRA-LFD assay was completed within 20 min at 37°C, without any cross-reaction with other reference viruses. The newly established MIRA-LFD assay had a detection limit of 32.3 copies/μL, which was 10-fold lower than that of the nested polymerase chain reaction (PCR) assay. Furthermore, the MIRA-LFD assay detected 29 FeChPV-positive samples among 417 cats with diarrhea, providing a slightly higher positivity rate than the nested PCR assay. These results indicate that the newly developed MIRA-LFD assay for FeChPV detection is an efficient, economical, reliable, and simple method that can help in the early prevention and control of FeChPV infection.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 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".