Comparative Susceptibility of Madin–Darby Canine Kidney (MDCK) Derived Cell Lines for Isolation of Swine Origin Influenza A Viruses from Different Clinical Specimens
Bibliographic record
Abstract
Madin-Darby canine kidney (MDCK) cells are commonly used for the isolation of mammalian influenza A viruses. The goal of this study was to compare the sensitivity and suitability of the original MDCK cell line in comparison with MDCK-derived cell lines, MDCK.2, MDCK SIAT-1 and MDCK-London for isolation of swine-origin influenza A viruses (IAV-S) from clinical specimens. One-hundred thirty clinical specimens collected from pigs in the form of nasal swabs, lung tissue and oral fluids that were positive by PCR for the presence of IAV-S RNA were inoculated in the cell cultures listed above. MDCK-SIAT1 cells yielded the highest proportion of positive IAV-S isolations from all specimen types. For nasal swabs, 58.62% of the specimens were IAV-S positive in MDCK-SIAT1 cells, followed by MDCK-London (36.21%), and conventional MDCK and MDCK.2 cells (27.5%). For lung specimens, 59.38% were IAV-S positive in MDCK-SIAT1 cells, followed by MDCK-London (40.63%), and conventional MDCK and MDCK.2 cells (18.75-31.25%). Oral fluids yielded the lowest number of positive virus isolation results, but MDCK-SIAT1 cells were still had the highest rate (35%) of IAV-S isolation, whereas the isolation rate in other cells ranged from 5-7.5%. Samples with lower IAV-S PCR cycle threshold (Ct) values were more suitable for culturing and isolation. The isolated IAV-S represented H1N1-β, H1N2-α, H1N1pdm and H3N2 cluster IV and cluster IVB viruses. The result of the current study demonstrated the importance of using the most appropriate MDCK cells when isolating IAV-S from clinical samples.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".