2 Acute phase response to lipopolysaccharide challenge in beef steers supplemented with prebiotic blends
Bibliographic record
Abstract
Abstract A study was conducted to determine the effects of two prebiotic blends on the acute phase response (APR) following lipopolysaccharide (LPS) challenge in steers. Crossbred steers (n = 36; 273±4 kg) were fed for 21d on three different treatments: 1) Control, fed a standard receiving ration; 2) Control ration supplemented with a Prebiotic/Probiotic blend (28.4 g/hd/d; PMI); and 3) Control ration supplemented with a DFM/Prebiotic blend (19.0 g/hd/d; PMI). On d20, calves were fitted with indwelling rectal temperature (RT) monitors and jugular catheters and moved into individual stanchions in a covered barn. On d21, blood samples were collected, and sickness behavior scores recorded at 0.5-h intervals from -2 to 8h and again at 24h relative to an i.v. challenge with 0.25 µg/kg BW LPS. Serum was isolated and stored until analyzed for pro-inflammatory cytokines, cortisol and glucose concentrations. Complete blood counts were measured every 2h from -2 to 8h and again at 24h. Pre-challenge RT measured for 18h prior to the challenge tended (P = 0.10) to be affected by treatment such that calves fed the Prebiotic/Probiotic blend had greater RT than Control and tended to be greater than calves fed the DFM/Prebiotic blend (38.9, 39.2, and 39.0±0.1oC, respectively). Post-challenge RT increased 0.8–1.0oC on average but did not differ between treatments (P = 0.53). Sickness behavior scores were not different between treatments (P = 0.14). There were no differences in white blood cell or differential counts between treatments (P ≥ 0.25). Serum concentrations of TNF-α, IL-6, and IFN-γ increased in response to the challenge (P < 0.01) but were not different between treatments (P ≥ 0.26). Serum cortisol and glucose concentrations were reduced in both supplemented groups compared to Control steers (P ≤ 0.006). Therefore, the data suggest that the effects of the prebiotic blends during an immune challenge were limited to alterations in metabolic biomarkers and energy utilization.
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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) | 0.001 | 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".