Effectiveness of Standard UV Depuration at Inactivating <i>Cryptosporidium parvum</i> Recovered from Spiked Pacific Oysters ( <i>Crassostrea gigas</i> )
Bibliographic record
Abstract
When filter-feeding shellfish are consumed raw, because of their ability to concentrate and store waterborne pathogens, they are being increasingly associated with human gastroenteritis and have become recognized as important pathogen vectors. In the shellfish industry, UV depuration procedures are mandatory to reduce pathogen levels prior to human consumption. However, these guidelines are based around more susceptible fecal coliforms and Salmonella spp. and do not consider Cryptosporidium spp., which have significant resistance to environmental stresses. Thus, there is an urgent need to evaluate the efficiency of standard UV depuration against the survival of Cryptosporidium recovered from shellfish. Our study found that in industrial-scale shellfish depuration treatment tanks, standard UV treatment resulted in a 13-fold inactivation of recovered, viable C. parvum oocysts from spiked (1 x 10(6) oocysts liter (-1)) Pacific oysters. Depuration at half power also significantly reduced (P < 0.05; ninefold) the number of viable oocysts recovered from oysters. While UV treatment resulted in significant reductions of recovered viable oocysts, low numbers of viable oocysts were still recovered from oysters after depuration, making their consumption when raw a public health risk. Our study highlights the need for increased periodic monitoring programs for shellfish harvesting sites, improved depuration procedures, and revised microbial quality control parameters, including Cryptosporidium assessment, to minimize the risk of cryptosporidiosis.
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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 | 0.000 | 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".