Human Fibroblasts Are Permissive for Porcine Cytomegalovirus In Vitro
Bibliographic record
Abstract
BACKGROUND: Xenotransplantation with pig organs is being considered to alleviate donor organ shortages; however, the risk of introducing porcine viruses into humans is heightened in this setting. The goal of this study was to determine the infectious potential of porcine cytomegalovirus (PCMV), a xenozoonotic virus of interest, in human fibroblasts in vitro. METHODS: Confluent human cells were incubated with live PCMV, heat-killed PCMV, or medium alone. Infection was investigated by testing for viral-induced cytopathic effect, assaying viral transcription by nested RT-PCR and subsequent sequencing, and detecting viral protein expression by Western blotting. Plaque neutralization experiments were also performed. RESULTS: Cells incubated with PCMV demonstrated significant cytopathic effect by 7 days postinfection, and reverse-transcriptase polymerase chain reaction sequencing identified PCMV DNA polymerase in these infected cells. In Western blots, monoclonal antibodies (mAbs) to human CMV glycoprotein B and pig serum presumed to contain anti-PCMV antibodies detected characteristic proteins in experimentally infected human cells and positive controls but not in negative controls. Furthermore, one of these mAbs and the pig serum neutralized PCMV infection in vitro. CONCLUSIONS: These results are a first demonstration that PCMV can infect human fibroblasts in vitro.
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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) | 0.003 | 0.001 |
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".