Polymorphisms in pulmonary innate immune system genes of swine
Bibliographic record
Abstract
Modern pigs are unusually susceptible to severe infectious pneumonia. We hypothesize that single nucleotide polymorphisms (SNPs) in innate immune system genes impair resistance to infection or promote injurious inflammatory responses in swine. The objective of this study was to characterize SNPs that code for amino acid substitutions in porcine surfactant protein‐A and ‐D (SP‐A, SP‐D), complement component C3d (C3d), and Toll‐like receptor 2 (TLR‐2). For each gene, RT‐PCR products that cover the entire coding region were subjected to single‐strand conformational polymorphism (SSCP) analysis. RT‐PCR was performed on total RNA extracted from the lungs of randomly chosen diseased pigs submitted to the Animal Health Laboratory, University of Guelph, for diagnostic investigation. Pigs were screened for SNPs by comparing silver‐stained banding patterns of digested, single‐stranded RT‐PCR products separated by SSCP gel electrophoresis. Several different banding patterns were observed in digests of SP‐A, SP‐D and TLR‐2, whereas C3d digests appeared uniform. Sequence comparisons of RT‐PCR products representing different banding patterns revealed three coding SNPs in the C‐type lectin domain of SP‐A. The C‐type lectin domain of SP‐A has an important role in binding microbial surface carbohydrates and these results suggest that pigs may differ in their innate ability to recognize and defend against some respiratory pathogens. Supported by OMAF, Ontario Pork, and the Ontario Veterinary College
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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".