Persistence of Hepatitis A Virus RNA in Water, on Non-porous Surfaces, and on Blueberries
Bibliographic record
Abstract
Enteric viruses, such as human norovirus and hepatitis A virus (HAV), are the leading cause of transmissible foodborne illness. Fresh produce such as berries are often contaminated by infected food handlers, soiled water, or food contact surfaces. The gold-standard method for virus detection throughout the food chain is RT-qPCR, which detects portions of genomes including non-infectious viral particles and naked viral RNA. The aim of this study was to evaluate the persistence of heat-inactivated HAV in water, phosphate-buffered saline, on stainless steel and polyvinyl chloride, and on blueberries at −80°C, −20°C, 4°C, and room temperature. In water and phosphate-buffered saline, viral RNA could be detected for up to 90 days regardless of temperature when the initial load was 2.5 × 10 4 or 2.5 × 10 6 genome copies. It was detected on polyvinyl chloride and blueberries under most conditions. On stainless steel, the large initial load persisted for 90 days, while the medium-level load was detected only up to 16 days at room temperature or 60 days at 4°C. The detection of non-infectious viral RNA can confound investigations of gastroenteritis outbreaks. Pretreatments that discriminate between naked RNA, non-infectious virions and infectious virions need to be included in the RT-qPCR method in order to reduce the risk of positive results associated with non-infectious viral particles.
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 | 0.000 | 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) | 0.001 | 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".