Incubation and rearing temperature effects on Hsp70 levels and heat stress response in broilers
Bibliographic record
Abstract
Incubation temperature (IT) was changed to evaluate if 6-wk-old birds become more tolerant to heat stress. After 13 d of incubation, 470 eggs were submitted to low (36.8°C), normal (37.8°C) and high (38.8°C) temperatures. At day 7 post-hatching, 144 birds were allocated to three rearing temperatures (48 birds/treatment): control/thermoneutral (35–24°C), high (33–30°C) or low (27–18°C) according to the age of the birds. Hsp70 levels in tissues of birds (1 d and 42 d), stress response (42 d) and performance were evaluated. High IT decreased brain (P < 0.01) and liver (P < 0.01) Hsp70 levels, whereas low IT decreased brain (P < 0.01) but increased heart (P < 0.01) Hsp70 levels in 1-d old chicks. Birds incubated at a low temperature had higher (P < 0.05) feed intake (1-42 d). High rearing temperature decreased feed intake (P <0.01) and liveweight (P <0.01). Colonic temperature was lower in birds incubated at a low temperature (P < 0.05) and higher in birds reared in a high temperature (P < 0.05) before heat stress. Birds reared in low temperature had higher increase in colonic temperature after heat stress (P < 0.05). Tissue Hsp70 levels were differently affected by rearing temperature, which affected broiler performance more than IT. Lower IT seemed to increase the sensitivity of birds to heat stress at market age. Key words: Heat resistance, Hsp70, incubation temperature, rearing temperature
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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".