Effect of parity on bone mineral density in female rhesus macaques from Cayo Santiago
Bibliographic record
Abstract
This cross-sectional study investigates the relationship between parity, bone mineral density, and spontaneous osteopenia/osteoporosis in a large skeletal population of female rhesus macaques (Macaca mulatta) from the free-ranging colony of Cayo Santiago, Puerto Rico. The sample consists of 119 mature female monkeys aged 4.0-22.2 years at time of death. The data consist of measurements of bone mineral content (BMC) and bone mineral density (BMD), obtained from dual-energy X-ray absorptiometry (DEXA) of the last lumbar vertebra. After controlling for age, there is a significant increase in BMD of the spine with increasing parity (P = 0.0006), up to a parity of 7 offspring. Thus, high parity initially has a positive effect on BMD in female rhesus monkeys, but this positive effect disappears with parities that are greater than 7 offspring. After controlling for parity, however, age has a negative (P = 0.015) effect on BMD, beginning several years after the attainment of peak BMD (age 9.5 years). Thus, it appears that parity initially mitigates the effects of aging, but the positive effect of parity on BMD is eventually overwhelmed by the aging process. Mean BMC and BMD values are higher in parous females compared to nulliparous females in the same age range. Similarly, females with low parity have significantly lower mean BMD values than do age-matched high-parity controls, and the frequency of osteopenia and osteoporosis is greater in low-parity females. Forty-three percent (43%) of the osteopenic/osteoporotic females in the sample are members of the low-parity group, even though it composes only 13% (16/119) of the entire sample. This study demonstrates that the free-ranging female rhesus monkeys from Cayo Santiago are a good nonhuman primate model for the study of bone mineral density, parity, osteopenia, and osteoporosis.
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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 | 0.001 |
| 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 | 0.000 |
| 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".