Porcine reproductive and respiratory virus 2 infection of the fetus results in multi-organ cell cycle suppression
Bibliographic record
Abstract
Porcine reproductive and respiratory syndrome virus (PRRSV) infection during late gestation negatively affects fetal development. The objective of this study was to identify the fetal organs most severely impacted following infection, and evaluate the relationship between this response and fetal phenotypes. RNA was extracted from fetal heart, liver, lung, thymus, kidney, spleen, and loin muscle, collected following late gestation viral challenge of pregnant gilts. Initially, gene expression for three cell cycle promoters (CDK1, CDK2, CDK4) and one inhibitor (CDKN1A) were evaluated in biologically extreme phenotypic subsets including gestational age-matched controls (CON), uninfected (UNIF), high-viral load viable (HV-VIA), and high-viral load meconium-stained (HV-MEC) fetuses. There were no differences between CON and UNIF groups for any gene, indicating no impact of maternal infection alone. Relative to CON, high-viral load (HV-VIA, HV-MEC) fetuses showed significant downregulation of at least one CDK gene in all tissues except liver, while CDKN1A was upregulated in all tissues except muscle, with the heart and kidney most severely impacted. Subsequent evaluation of additional genes known to be upregulated following activation of P53 or TGFb/SMAD signaling cascades indicated neither pathway was responsible for the observed increase in CDKN1A. Finally, analysis of heart and kidney from a larger unselected population of infected fetuses from the same animal study showed that serum thyroxin and viral load were highly correlated with the expression of CDKN1A in both tissues. Collectively these results demonstrate the widespread suppression in cell division across all tissues in PRRSV infected fetuses and indicate a non-canonical regulatory mechanism.
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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) | 0.001 | 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".