Effects Different Levels of Nanoparticles Chromium Picolinate Supplementation on Growth Performance, Mineral Retention, and Immune Responses in Broiler Chickens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study was conducted to investigate the effects of different levels nanoparticles of chromium picolinate (NanoCrPic) on the performance, immune responses, mineral retention, and tissues accumulation of chickens. A total of 180 broilers were randomly allocated into 0 (control), 500 ppb (µg kg-1) Cr and 3000 ppb Cr groups with 6 replicates (10 birds/pen) for a 35-day experiment, the Cr is nanoparticles of chromium picolinate (NanoCrPic). In addition, 36 birds were used for metabolic experimental investigation. The results of the experimentation indicated that there were no significant differences in average body weight gain between groups, but feed conversion ratio (FCR) in 3000 ppb group was better than control group during 1-21 days. The carcass yields slightly lower in 3000 ppb group than control (p<0.1). Retention ratio of Zn, Fe, Mn, Ca, and P were significantly (p<0.05) increased in the 500 ppb Cr group. The addition of NanoCrPic caused increased mineral concentrations, such as Cr, Ca and P in the subjects’ livers. Furthermore, the addition of NanoCrPic significantly increased lymphocytes and decreased both heterophils and H/L ratio (p<0.05). The ND (Newcastle disease) antibody titer was not affected in the broilers. In conclusion, supplemental NanoCrPic improved the retention of Zn, Fe Ca, notably it increased the concentration of Cr and Ca in the liver, and also increased the number of lymphocytes in broiler chickens.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it