Detection of Enteric Viruses on Strawberries and Raspberries Using Capture by Apolipoprotein H
Bibliographic record
Abstract
Human noroviruses (HuNoVs) and the hepatitis A virus (HAV) are the main viral causes of foodborne illness worldwide. These viruses are frequently transmitted via fresh and frozen berries, such as strawberries and raspberries. ISO 15216:1 (2017), currently the preferred method for their detection, involves several steps and is time-consuming. Apolipoprotein H (ApoH) has been shown to have a strong affinity for several microorganisms, including HuNoVs. In this article, we report an ApoH-based method of capturing the HAV and HuNoVs adherent to berries and concentrating them for assay. The limit of detection of both viruses suspended in a buffer was low. On strawberries, the HAV was detected down to 104 genome copies/25 g in 100% of cases and down to 103 genome copies/25 g on raspberries in 50% of cases. This sensitivity was not significantly different from that of the ISO method 15216:1 (2017). HuNoV GII.4 was more difficult to detect using the ApoH method. The ApoH CaptoVIR kit does, nevertheless, appear to be usable in the near future as a single-test, multiple-detection method for viruses on fresh and frozen berries.
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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 | 0.000 | 0.000 |
| 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".