Birth weight affects immune response of piglets during the peri-weaning period
Bibliographic record
Abstract
Abstract Relationships between birth weight and a range of immune markers were studied in piglets during the peri-weaning period. A total of 47 sows and their respective litters adjusted to 12 piglets were used. Piglets were weighed after birth and within each litter 2 low weight (LW) and 2 high weight (HW) animals were identified: the average weight of the 2 groups was 1.12 and 1.81 ± 0.17 kg, respectively. Within litter, one couple of LW and HW piglets was sacrificed at 16 and 23 d of age, two days after weaning at day 21, to characterise different leukocyte subsets in mesenteric lymph nodes (MLN) and blood by flow cytometry. Jejunal mucosal and MLN samples were also collected to measure the expression of genes involved in immune response by qPCR. The percentage of blood γδT cells was higher in HW piglets before and after weaning (P=0.01 and P<0.001, respectively). At 16 d, LW animals had higher amounts of CD4+CD8+ T cells and dendritic cells in the blood (P=0.01 and P=0.04, respectively) and in MLN (P=0.02 and P=0.009 respectively), and lower count of blood cytotoxic T cells (P=0.01) than HW. Moreover, jejunal expression of TNFα was reduced in LW piglets (P=0.02), while MLN expression of CCL23, BMP2 and SPP1 was increased (P=0.003, P=0.002 and P=0.02, respectively). Two days after weaning (d 23), HW piglets had higher percentages of T cells (P=0.001) and lower amount of non-T cells (P=0.03) and natural killer cells (P=0.04) in blood compared to LW animals. These data revealed that piglet birth weight affects the proportion of leukocyte subsets in different tissues and the expression of genes involved in the immunity. Globally, our results suggest that the development of the immune system after birth differed between LW and HW piglets.
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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 | 0.001 |
| 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".