Intra-uterine growth retardation affects birthweight and postnatal development in pigs, impairing muscle accretion, duodenal mucosa morphology and carcass traits
Bibliographic record
Abstract
The present study investigated the occurrence of intra-uterine growth retardation (IUGR) in newborn (n=40) and 150-day-old (n=240) pigs of different birthweight ranges (high, HW: 1.8-2.2kg; low, LW: 0.8-1.2kg) from higher-parity commercial sows and its impact on their subsequent development and carcass traits in a Brazilian commercial production system. HW newborn pigs had heavier organs than LW pigs (P<0.01), and all brain:organ weight ratios were higher (P<0.01) in LW compared with HW offspring, providing strong evidence of IUGR in the LW piglets. HW pigs had higher bodyweights and average daily gain (ADG) in all phases of production (P<0.05), but ADG in the finisher phase was similar in both groups. Additionally, LW newborn and 150-day-old pigs showed a lower percentage of muscle fibres and a higher percentage of connective tissue in the semitendinosus muscle, greater fibre number per mm(2) and a lower height of the duodenal mucosa (P<0.05). On the other hand, HW pigs had higher hot carcass weight, meat content in the carcass and yield of ham, shoulder and belly (P<0.01). Hence, lower-birthweight piglets may suffer from IUGR, which impairs their growth performance, muscle accretion, duodenal mucosa morphology and carcass traits.
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 | 0.000 |
| 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".