International Symposium on Ruminant Physiology: Maternal nutrient supply—Impacts on physiological and whole-animal outcomes in offspring
Bibliographic record
Abstract
Demands for animal products are projected to increase in the future, and animal production is key to agricultural sustainability and food security; consequently, enhancing ruminant livestock production efficiencies in sustainable ways is a major goal for the livestock industry. Developmental programming is the concept that various stressors, including compromised maternal nutrition during critical developmental windows will result in both short- and long-term changes in the offspring. Ruminant models of developmental programming indicate that compromised maternal nutrition, including global under- and overnutrition, macronutrients, and specific micronutrients, including amino acids (Met and Arg), vitamins (folate, B 12 , and choline), and minerals (sulfur, cobalt, and selenium) can alter offspring outcomes. Data also suggest that maternal histotrophic composition, placental function, and likely fetal nutrient supply are altered by compromised maternal nutrition. Likewise, in offspring, visceral organ mass and function, metabolism, growth, and reproduction are affected. Findings from multi-omics approaches demonstrate that compromised maternal nutrition alters transcript abundance, metabolomic profiles, and multiple metabolic pathways. The underlying mechanisms of developmental programming are driven by epigenetic events, which depend on one-carbon metabolism and micronutrient supply. Current findings indicate that developmental programming in ruminants is real, that maternal nutrition can be a major driver of developmental programming, and that genomic and metabolomic changes in offspring are modulated by altered maternal nutrition during critical windows of development. Research needs in the area of developmental programming in ruminants include enhanced understanding of the underlying mechanisms, practical relevance to production systems, effects on short- and long-term animal health including longevity, interrelationships between maternal and paternal influences, intergenerational effects, and interrelationships with the host microbiome. Additionally, strategic supplementation and precision nutrition approaches should be developed to foster the positive and mitigate the negative aspects of developmental programming to improve the efficiency and sustainability of ruminant livestock production systems.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".