Detection of FeChPV in a cat shelter outbreak of upper respiratory tract disease in China
Bibliographic record
Abstract
Feline parvovirus often causes a fatal infectious disease and has a serious impact on domestic cats and wild felines. Feline chaphamaparvovirus (FeChPV) is a novel type of feline parvovirus that has been successively identified in Canada, Italy, and Turkey. The prevalence and pathogenicity of FeChPV in other regions is still unknown. In this study, we recorded the detection of FeChPV in a cat shelter in China. A high prevalence (81.08%, 30/37) of FeChPV was detected in cats with symptoms of upper respiratory tract disease (URTD) in this cat shelter. Multiple pathogen testing indicated high coinfection rates of 80% (24/30) with other common viruses in FeChPV-positive cats. Analyses of the necropsy and histopathological findings revealed severe lymphadenitis, encephalitis, and viral DNA in several tissues (including brain) of the deceased cat. Finally, we obtained nearly full-length genomes of four strains with 98.4%~98.6% homology with previously reported genomes. Notably, VP1 proteins showed seven unique amino acid mutations, while NS1 proteins carried eight mutations. In the evolutionary tree based on VP1 and NS1, the sequences clustered in a large branch with Italian and Canadian FeChPV strains. Given the possible association of FeChPV with URTD, further studies are necessary to evaluate the pathogenicity and epidemiological characteristics of this novel feline pathogen.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".