Nutritional Programming of Bone Structure in Male Offspring by Maternal Consumption of Citrus Flavanones
Bibliographic record
Abstract
Maternal exposure to hesperidin (HSP) and naringin (NAR) during pregnancy and lactation transiently compromised bone mineral density (BMD) and bone structure at the proximal tibia in female CD-1 offspring. We examined whether maternal consumption of HSP + NAR during pregnancy and lactation compromises BMD, bone structure, and bone strength in male CD-1 offspring. Male CD-1 offspring, from mothers fed a control diet (CON, n = 10) or a 0.5% HSP + 0.25% NAR diet (HSP + NAR, n = 8) for 5 weeks before mating and throughout pregnancy and lactation, were weaned and fed CON until 6 months of age. In vivo micro-computed tomography (µCT) measured tibia BMD and structure at 2, 4, and 6 months of age. Ex vivo µCT measured femur and lumbar vertebrae (LV) structure at age 6 months. Ex vivo BMD (femur, LV) and biomechanical strength (femur and tibia midpoint, femur neck) were assessed at age 6 months by dual energy x-ray absorptiometry and strength testing, respectively. At all ages, HSP + NAR offspring had greater (p < 0.05) proximal tibia cortical structure compared to CON offspring. At age 4 months, proximal tibia trabecular structure was greater (p < 0.05) than CON offspring. At age 6 months, femur neck and LV trabecular structure were greater (p < 0.05) than CON offspring. Our results demonstrate that unlike our previous study of female offspring, maternal consumption of HSP + NAR resulted in greater bone structure at the proximal tibia in male CD-1 offspring that persisted to 6 months of age. Thus, maternal programming of offspring BMD and bone structure from consumption of HSP + NAR occurred as a sex-specific response.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".