Effects of oxygen levels and a Lactobacillus plantarum strain on mortality and immune response of chickens at high altitude
Bibliographic record
Abstract
Chickens reared in high altitude regions suffer from a high mortality, possibly due to poor immune responses induced by hypoxia. This experiment was conducted to evaluate whether increasing the oxygen level or administration of a probiotic could improve mortality and immune response of chickens at high altitude (2,986 m above the sea level). One-d-old chickens were randomly allocated to 1 of 6 treatments in a 2 × 3 factorial arrangement. The first factor was the oxygen level (low and high), while the second factor was the diet (basal diet, basal diet containing aureomycin, and basal diet plus L. plantarum). Increasing the oxygen level significantly reduced the mortality and improved immune responses. The levels of IgA, IgG, IL-10 and anti-BSA antibodies were significantly higher, while IL-1β, LITAF were significantly lower in chickens reared in the high-oxygen room. In the low-oxygen room, L. plantarum significantly decreased the mortality of chickens compared with the other 2 groups. Moreover, L. plantarum significantly increased the levels of IgA, anti-BSA antibodies, IL-10 and decreased IL-1β, LITAF compared with the control group. These results demonstrated that increasing oxygen level or administration of L. plantarum can improve health status of chickens in high altitude regions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".