Review: The amazing gain-to-feed ratio of newly weaned piglets: sign of efficiency or deficiency?
Bibliographic record
Abstract
Shortly after weaning, piglets generally eat dry feed poorly; but nevertheless, a phenomenal gain to feed ratio is achieved as they gain about as much weight as they eat (150-200 g/d). The high gain to feed ratio, though, cannot be explained by their nutrient intake nor nutrient repartitioning. Analyses based on tissue composition and bio-electrical impedance data showed that newly weaned piglets lose fat, maintain protein, and gain large amounts of water because of edema. This edema, which may well contribute up to one kg of body weight, seems to be triggered by refeeding syndrome. Refeeding syndrome in adult humans occurs when subjects fast for an extended period of time (weeks) that results in downshifts in metabolic activity and concomitant shedding of phosphate (PO4), magnesium (Mg), and potassium (K) in urine. If food is abruptly reintroduced, thus, resulting in strong insulin spikes, metabolism is triggered but hampered by a lack of PO4, Mg, K, and thiamine, causing hypophosphatemia, metabolic stress, and edema. In piglets, the same process appears to happen immediately after weaning but in hours rather than weeks, possibly linked to their high metabolic rate. Refeeding syndrome can be lethal in humans but does not appear to be directly lethal in piglets. Our attempts to prevent it through altered diet composition and/or controlled feeding programs have not resulted in better performance at the end of the nursery phase. A practical ramification of weaning-induced edema is that growth and gain to feed ratio data immediately after weaning should be interpreted with caution. In addition, diets arguably should be formulated to not strongly trigger insulin release, while high lysine levels are not needed as gain is not based on protein accretion.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".