Effect of dietary folic acid and energy density on immune response, gut morphology, and oxidative status in blood and breast muscle of broiler chickens
Bibliographic record
Abstract
Folic acid (FA) plays essential roles in many metabolic functions and has been reported to have antioxidant effects. Therefore, dietary supplementation with high levels of FA may improve gut health and prevent potential oxidative stress caused by feeding a high energy density diet to broiler chickens. Broiler chickens were assigned into eight treatments, consisting of either a normal energy (NE) or high energy (HE) density diet, and four FA levels (2.2, 5, 10, and 15 ppm). Data were analyzed by SAS 16 GLM procedure. Birds-fed HE diets had increased (P < 0.05) plasma concentrations of calcium and albumin but reduced (P < 0.005) weights of ceca and bursa compared with those fed NE diets. Dietary supplementation with 10 ppm FA significantly increased (P < 0.05) birds’ heart weight and bile acid concentration. Folic acid and energy density interactions were significant for jejunal villus height (VH; P = 0.0226), villus width (VW; P < 0.0001), and crypt depth (CD; P = 0.0332). Among the NE group, birds fed 5–15 ppm FA had reduced (P < .0001) VW, while in the HE groups, 15 ppm FA supplementation resulted in an increased jejunal VH (P = 0.0317) compared with other treatments. In conclusion, dietary supplementation with increased levels of FA in HE diets could be beneficial for the intestinal health of broiler chickens.
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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".