Review: Current knowledge on mammary blood flow, mammary uptake of energetic precursors and their effects on sow milk yield
Bibliographic record
Abstract
Dietary availability of nutrients to the mammary gland is a major limiting factor for sow milking potential. Nutrient availability to the udder is estimated by measuring mammary arteriovenous differences, which are affected by blood flow as well as circulating concentrations of nutrients. Mammary blood flow can be measured either directly or indirectly. Even though it is influenced by numerous factors, such as time since feeding, postural behavior, vasoactive substances, ambient temperature and litter size, authors report that the amount of plasma required to produce 1 kg of milk for a litter of 12 pigs ranges from 490 to 1050 L at peak lactation. Blood glucose is the major precursor for lactose synthesis and reported extraction rates of glucose by the mammary gland vary between 20 and 31%. Other metabolic precursors, such as triglycerides, phospholipids, acetate, propionate and lactate are also used for milk synthesis. There exists a discrepancy between estimates of energetic efficiency depending on the type of study conducted (metabolism vs. mammary balance). Endocrine status of the sow may affect mammary nutrient availability. There still exists a gap in our knowledge on relative mammary uptakes of energetic compounds other than glucose and on glucose transporter systems in porcine mammary tissue. The need for such information is of particular importance due to the increased milking demands currently made on lactating sows. Key words: Blood flow, lactation, mammary gland, nutrient uptake, sows
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".