Impact of a long photoperiod during lactation on immune status of piglets1
Bibliographic record
Abstract
The effects of a long photoperiod treatment around parturition and throughout lactation on immune status of piglets were studied. Sows were assigned to 2 light regimens: i) standard short photoperiod (SP, n = 17), 8 h of daily light from d 112 of gestation until d 23 of lactation; and ii) long photoperiod (LP, n = 17), 23 h of daily light from d 112 of gestation to d 4 of lactation and 16 h thereafter. In front of the crates, under the side heat lamps and behind the sow, light intensities were 59 ± 5, 109 ± 6, and 44 ± 6 lx, respectively. On d 15 of lactation and at weaning (d 23), 2 piglets of similar BW per litter were selected and immunized intramuscularly with ovalbumin (OVA). Blood samples (5 mL serum and 10 mL whole blood) were taken at d 15 and d 23 of lactation, and at d 30, 37, and 44 of age after weaning to evaluate the antibody response to OVA and measure phagocytosis, lymphocyte proliferative response, and different circulating blood lymphocyte populations of piglets. Results showed that phagocytosis was increased in piglets submitted to LP (P < 0.05). A treatment × time interaction (P < 0.001) indicated that SP piglets developed a better IgG response to OVA than LP piglets. The percentage of B lymphocytes was also increased (P = 0.02) in SP piglets compared with piglets exposed to LP during lactation; the lymphocyte response to OVA tended to be enhanced (P = 0.07) over time in SP piglets. Different subpopulations of CD8+ lymphocytes were markedly increased in SP piglets at 23 d of age compared with piglets exposed to LP (treatment × time: P < 0.05). These results suggest that exposure of piglets to LP during lactation seems to reduce the capacity of piglets to develop a strong immune response to novel antigens. This may have important consequences on the ability of piglets to resist an infection after weaning.
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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".