Low weight piglets show differences in intestinal microbiota, intestinal transcriptome and immune cell profile compared to high weight piglets during the first two weeks of lactation
Bibliographic record
Abstract
Abstract Piglets born with lower weight and showing low performances during the first weeks of lactation are associated with higher risks of gastroenteric diseases after weaning. Therefore, we investigated the developmental differences between these pigs compared to the high weight piglets. Eight litters adjusted to 12 piglets were used. In each litter, piglets showing the lowest weight gain (LWG) or the highest weight gain (HWG)in the first week of life were selected. For each piglets enrolled, ileal gene expression, immune cell populations and microbiota profiles were studied. Results obtained from microarray and Q-PCR analysis showed that, at 16 days of age, the expression of genes involved in oxidative stress and immune response was altered in LWG piglets’ ileum. Analysis of the LH-PCR data of the microbiota using non-metric multidimensional scaling (NMS) and blocked multiresponse permutation procedure (MRBP) revealed that the microbiota of the HWG and LWG piglets tended to differ in ileal mucosa (p = .097) and differed incolonic lumen (p = .024). From day 8 to 16, LWG piglets failed to show an increase of CD21+ B cells in their blood (P weight × day = 0.01), but showed an increase of CD4+CD8α-Th cells (P = 0.002), unlike the HWG piglets. Percentages of CD14+ monocytes and other MHC-II+ cells were respectively higher and lower on day 8 compared to day 16 (P < 0.01). Moreover, LPS activated PBMC from LWG piglets produced less IL-6 (P < 0.05). These results suggest that piglets low performances during lactation affect the development of their immune system and is associated with differences in intestinal gene expression profile and microbiota.
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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) | 0.001 | 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".