Sources and contamination routes of seafood with human pathogenic <i>Vibrio</i> spp.: A <i>Farm‐to‐Fork</i> approach
Bibliographic record
Abstract
Vibrio spp., known human foodborne pathogens, thrive in freshwater, estuaries, and marine settings, causing vibriosis upon ingestion. The rising global vibriosis cases due to climate change necessitate a deeper understanding of Vibrio epidemiology and human transmission. This review delves into Vibrio contamination in seafood, scrutinizing its sources and pathways. We comprehensively assess the contamination of human-pathogenic Vibrio in the seafood chain, covering raw materials to processed products. A "Farm-to-Fork" approach, aligned with the One Health concept, is essential for grasping the complex nature of Vibrio contamination. Vibrio's widespread presence in natural and farmed aquatic environments establishes them as potential entry points into the seafood chain. Environmental factors, including climate, human activities, and wildlife, influence contamination sources and routes, underscoring the need to understand the origin and transmission of pathogens in raw seafood. Once within the seafood chain, the formation of protective biofilms on various surfaces in production and processing poses significant food safety risks, necessitating proper cleaning and disinfection to prevent microbial residue. In addition, inadequate seafood handling, from inappropriate processing procedures to cross-contamination via pests or seafood handlers, significantly contributes to Vibrio food contamination, thus warranting attention to reduce risks. Information presented here support the imperative for proactive measures, robust research, and interdisciplinary collaboration in order to effectively mitigate the risks posed by human pathogenic Vibrio contamination, safeguarding public health and global food security. This review serves as a crucial resource for researchers, industrials, and policymakers, equipping them with the knowledge to develop biosecurity measures associated with Vibrio-contaminated seafood.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".