Detection of IgG antibody against the porcine norovirus GII.11 in human, domestic and wild animals
Bibliographic record
Abstract
Zoonotic diseases pose a critical threat to global public health, with noroviruses (NoVs) increasingly recognized for their potential to cross species barriers. Traditionally, NoVs were considered host-specific; however, recent evidence suggests the possibility of interspecies transmission. This study investigates the zoonotic potential of porcine NoV (PorNoV) genotype GII.11, which shares high genetic similarity with human NoVs (HuNoVs), by detecting GII.11-specific IgG antibodies in humans and various animals using a Luciferase Immunosorbent Assay (LISA). Seroprevalence was observed in humans (15.2%), pigs (49.3%), dogs (30.6%), wild rats (9.5%), and bats (65.1%), marking the first detection of GII.11 PorNoV antibodies in humans and non-swine species. Bats exhibited the highest seropositivity and antibody levels [vs. humans (P = 0.0011) and pigs (P = 0.0164)], suggesting their potential role as reservoirs. These findings provide serological evidence for anthropozoonotic transmission, challenging the paradigm of strict host specificity in NoVs. Enhanced surveillance of PorNoV in animal reservoirs and high-risk human populations is needed to mitigate zoonotic spillover risks. Further research should aim to elucidate mechanisms of transmission and the clinical significance of cross-species NoVs exposure.
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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 | 0.001 | 0.001 |
| 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".