Effects of Red Rooibos on Mandibular Bone Structure in Sprague-Dawley Rats at 4 Months Post-Lactation
Bibliographic record
Abstract
Physiological changes during pregnancy and lactation result in challenges to the maternal rodent skeleton. Red rooibos (RR) supplementation to rats was previously shown to support the recovery of tibia bone structure through to 4 months post-lactation. Given the associations between oral and systemic health, this research used multiple ROIs within the mandible to determine: if there are differences in trabecular bone structure at 4 months post-lactation compared to the non-pregnant control; the effects of a RR intervention administered from pre-pregnancy through 4 months post-lactation on trabecular bone structure compared to no RR intervention; and if measured outcomes are similar among groups regardless of the ROI studied. 6-week-old female Sprague-Dawley rats (n=42) were randomized to PREG TEA (pregnancy and lactation; supplemental level of RR in water ~2600 mg/kg body weight/day), PREG WAT (pregnancy and lactation; water), or GROWTH CON (non-pregnant control; water), bred at 8-weeks of age and maintained until 4 months post-lactation when mandibles were excised. Micro-computed tomography was used to measure bone structure at four ROIs: fixed shape or manually drawn ROI in molar 1 (M1) or molar 2 (M2) site. At M1, analyses using a fixed ROI demonstrated that PREG TEA had a higher bone volume fraction (p<0.05) and lower trabecular separation (p<0.05) compared to PREG WAT. This may be explained by the structural outcomes characterizing trabecular struts, in which degree of anisotropy was lower (p<0.05) in PREG WAT compared to GROWTH CON. Irrespective of whether the ROI was drawn manually or fixed, the PREG TEA group demonstrated a partial recovery as trabecular number, separation, and thickness were not significantly different from GROWTH CON (p>0.05), whereas PREG WAT had significantly lower (p<0.05) bone volume fraction and trabecular number than GROWTH CON. At M2, few significant outcomes were observed regardless of ROI. This may be due to the lower amount of bone present at this site. Pregnancy and lactation resulted in deficits to mandible bone, but RR supplementation supported partial recovery, which aligns with previous findings for tibia. Findings can inform future research about which mandible site to select to measure a response to a dietary intervention.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".