Effects of supplementary selenium source on antioxidant status, inflammatory signaling, and gene expression of immune cells during endotoxin challenge in lactating Holstein cows
Bibliographic record
Abstract
The objective of this experiment was to determine how source of supplementary selenium (Se) affects antioxidant status, inflammatory signaling, and gene expression of immune cells during an intramammary endotoxin challenge. Twenty mid-lactation multiparous Holstein cows (591 ± 46 kg BW) were blocked by days in milk (157 ± 17) and randomly assigned to 1 of 2 treatments: (1) 0.30 mg/kg on a dry matter basis (100% of NASEM requirements) of supplementary organic (ORG; selenized yeast) Se premix; or (2) 0.30 mg/kg of supplementary inorganic (INO; sodium selenite) Se premix. Both treatments were top dressed and mixed into a basal ration that was fed once daily. Dry matter intake and milk production were recorded daily. Following a 12-wk dietary adaptation period, cows received an intramammary infusion of 50 µg of LPS (Escherichia coli strain O111:B4) in one front udder quarter. Blood and milk were sampled throughout the 24 h following the infusion, and peripheral blood mononuclear cells (PBMC) were isolated from blood for gene expression analyses. Compared with the INO treatment, the ORG treatment had higher Se concentrations in serum and in milk during the LPS challenge. No treatment differences were detected for plasma glutathione peroxidase activity or ferric-reducing ability of plasma. The ORG cows had higher plasma concentrations of C-C motif ligand 3, whereas INO cows had higher concentrations of interleukin 36 receptor antagonist and C-X-C motif chemokine ligand 10 within the 24 h following LPS infusion. Cows on the INO treatment had higher gene expression of IL8 in PBMC. These results indicated that source of Se may have influenced inflammatory signaling through cytokine production.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".