Comparison of Methods for Extraction of Infectious Influenza Virus from Raw Milk Cheeses
Bibliographic record
Abstract
In recent years, the highly pathogenic avian influenza (HPAI) H5N1 viruses have spread widely among birds and multiple mammal species. The HPAI spillover to dairy cattle, and its excretion in milk in high-titers has created a new interface for human exposure and has raised food safety concerns. Multiple lines of evidence show that pasteurization is effective in inactivation of influenza viruses. In Canada, dairy products must be pasteurized with the exception of cheese. Since influenza viruses were not considered as foodborne, there is no data available regarding their survival in cheeses and no standard method exists for their extraction from food commodities, including dairy products. Herein, we examined the efficacy of multiple methods for the extraction of infectious H1N1 virus (as a representative for type A influenza viruses) from cream cheese made from unpasteurized milk. We used murine norovirus (MNV) as a surrogate for human norovirus and also as a process control virus and examined the efficacy of the employed methods by plaque assay. The limit of detection for the two best-performing methods was determined using a variety of soft and firm raw-milk cheeses. The described methods assist health authorities for the surveillance of foodborne viruses in dairy products.
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 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".