Outcomes of a low birth weight phenotype on piglet gut microbial composition and intestinal transcriptomic profile
Bibliographic record
Abstract
Decades of selection for increased litter size has caused a proportion of sows to consistently produce low birth weight (LBW) litters resulting in economic loss for producers due to reduced piglet survivability and growth. We hypothesized that piglets from LBW litters would have altered gut microbial composition, intestinal architecture, and intestinal transcriptomic profiles compared with piglets from high birth weight (HBW) litters. Sows were designated LBW (n = 45) or HBW (n = 46) based on litter birth weights of three successive parities. LBW piglets were 22% lighter (P < 0.001) at birth; however, no longer differed (P > 0.05) in weight at weaning compared with HBW piglets. LBW piglets had reduced (P < 0.05) fecal microbial diversity with a 114% increase in fecal Enterobacteriaceae (P < 0.05), as well as reduced (P < 0.05) abundance of cecal Roseburia and Faecalibacterium, fiber-degrading butyrate producers. Several genes associated with metabolic (PER2, CES1, KLHL38, and HK2) and immune pathways (IL-1B, IRF8, and TNIP3) were differentially expressed, suggesting altered metabolic and immune function in LBW piglets. In conclusion, LBW piglets had potentially unfavorable shifts in microbial structure in comparison to HBW piglets accompanied with alterations in metabolic and immune gene expression. Results indicate some biological consequences linking LBW phenotype to changes in production efficiency later in life.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".