Impact of zinc and arginine on antioxidant status of weanling piglets raised under commercial conditions
Bibliographic record
Abstract
The effects of dietary zinc and L-arginine supplements on the weight gain, feed efficiency, antioxidant capacity and oxidative status of weanling piglets raised under commercial conditions were examined. A total of 288 piglets aged 21 d were fed for 15 d a diet supplemented or not with 2,500 mg/kg of zinc (provided as zinc oxide) and 1% L-arginine·HCl. The 4 treatments were distributed in a randomized complete block design with 6 initial body weight categories (12 animals per pen). Access to feed and water was ad libitum. Data were analyzed as a 2 × 2 factorial experiment using the SAS MIXED procedure, with zinc and arginine as the main independent variables. Blood collection day (d 8 and 15, samples were collected from the same 2 piglets in each pen before the morning feeding) was included as a third factor. The zinc supplement increased the average daily gain (ADG) from d 0 to 7, d 8 to 15 and d 0 to 15 (0.289 vs. 0.217 kg/d), average daily feed intake (ADFI) from d 8 to 15 and d 0 to 15 (0.338 vs. 0.279 kg/d) and the gain to feed (G:F) ratio from d 0 to 7 and d 0 to 15 (0.86 vs. 0.77) (P < 0.001). Both supplements significantly decreased the malondialdehyde concentration (zinc: 4.37 vs. 3.91 μmol/L, P = 0.005; arginine: 4.38 vs. 3.89 μmol/L, P = 0.002). Total antioxidant capacity and reduced glutathione (GSH) increased from d 8 to 15 (0.953 vs. 1.391 μmol/L, 2.22 vs. 3.37 μmol/L, P < 0.05) regardless of dietary treatment. Total and oxidized GSH concentrations on d 8 were higher in response to the combined supplements (zinc × arginine interaction, P < 0.05). Piglets fed either Zn-supplemented diet had a lower haptoglobin serum concentration (509 vs. 1,417 mg/L; P < 0.001). In conclusion, the zinc supplement improved piglet growth performance (ADG and ADFI) and oxidative status (based on malondialdehyde concentration). The arginine supplement had a limited effect on growth performance and oxidative status under these conditions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".