Mammary-specific deletion of parathyroid hormone–related protein preserves bone mass during lactation
Bibliographic record
Abstract
Large amounts of calcium are transferred to offspring by milk. This demand results in negative calcium balance in lactating mothers and is associated with rapid bone loss. The mechanisms of bone loss during lactation are only partly understood. Several studies have suggested that parathyroid hormone–related protein (PTHrP) might be secreted into the circulation by the lactating mammary gland and regulate bone turnover during lactation. Because mammary development fails in the absence of PTHrP, conventional PTHrP knockout mice cannot be used to address this possibility. To examine this hypothesis, we therefore used mice carrying a β-lactoglobulin promoter-driven Cre transgene, one null PTHrP allele, and one floxed PTHrP allele. Expression of Cre specifically in mammary epithelial cells during late pregnancy and lactation resulted in efficient deletion of the PTHrP gene; mammary gland PTHrP mRNA and milk PTHrP protein were almost completely absent. Removal of PTHrP from the lactating mammary glands resulted in reductions in levels of circulating PTHrP and 1,25-dihydroxy vitamin D and urinary cAMP. In addition, bone turnover was reduced and bone loss during lactation was attenuated. We conclude that during lactation mammary epithelial cells are a source of circulating PTHrP that promotes bone loss by increasing rates of bone resorption.
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 | 0.000 | 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".