Ablation of calcitonin/calcitonin gene-related peptide-α impairs fetal magnesium but not calcium homeostasis
Bibliographic record
Abstract
We used the calcitonin/calcitonin gene-related peptide (CGRP)-alpha gene knockout model (Ct/Cgrp null) to determine whether calcitonin and CGRPalpha are required for normal fetal mineral homeostasis and placental calcium transfer. Heterozygous (Ct/Cgrp(+/-)) and Ct/Cgrp null females were mated to Ct/Cgrp(+/-) males. One or two days before term, blood was collected from mothers and fetuses and analyzed for ionized Ca, Mg, P, parathyroid hormone (PTH), and calcitonin. Amniotic fluid was collected for Ca, Mg, and P. To quantify skeletal mineral content, fetuses were reduced to ash, dissolved in nitric acid, and analyzed by atomic absorption spectroscopy for total Ca and Mg. Placental transfer of (45)Ca at 5 min was assessed. Ct/Cgrp null mothers had significantly fewer viable fetuses in utero compared with Ct/Cgrp(+/-) and wild-type mothers. Fetal serum Ca, P, and PTH did not differ by genotype, but serum Mg was significantly reduced in null fetuses. Placental transfer of (45)Ca at 5 min was normal. The calcium content of the fetal skeleton was normal; however, total Mg content was reduced in Ct/Cgrp null skeletons obtained from Ct/Cgrp null mothers. In summary, maternal absence of calcitonin and CGRPalpha reduced the number of viable fetuses. Fetal absence of calcitonin and CGRPalpha selectively reduced serum and skeletal magnesium content but did not alter ionized calcium, placental calcium transfer, and skeletal calcium content. These findings indicate that calcitonin and CGRPalpha are not needed for normal fetal calcium metabolism but may regulate aspects of fetal Mg metabolism.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".