Dietary Supplementation of Female Rats with Elk Velvet Antler Improves Physical and Neurological Development of Offspring
Bibliographic record
Abstract
Elk velvet antler (EVA) has a traditional use for promotion of general health. However, evidence of EVA effects at different lifestages is generally lacking. This paper investigated the effects of long-term maternal dietary EVA supplementation on physical, reflexological and neurological development of rat offspring. Female Wistar rats were fed standard chow or chow containing 10% EVA for 90 days prior to mating and throughout pregnancy and lactation. In each dietary group, 56 male and 56 female pups were assessed for physical, neuromotor, and reflexologic development postnatally. Among the examined physical developmental parameters, incisor eruption occurred one day earlier in pups nursing dams receiving EVA. Among neuromotor developmental parameters, duration of supported and unsupported standing was longer for pups nursing EVA supplemented dams. Acquisition of neurological reflex parameters (righting reflex, negative geotaxis, cliff avoidance acoustic startle) occurred earlier in pups nursing dams receiving EVA. Longterm maternal EVA supplementation prior to and during pregnancy and lactation accelerated certain physical, reflexologic, and neuromotor developmental milestones and caused no discernible adverse effects on developing offspring. The potential benefits of maternal EVA supplementation on postnatal development warrants further investigation to determine whether EVA can be endorsed for the promotion of maternal and child health.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".