Prolactin is an important regulator of intestinal calcium transport
Bibliographic record
Abstract
Prolactin has been shown to stimulate intestinal calcium absorption, increase bone turnover, and reduce renal calcium excretion. The small intestine, which is the sole organ supplying new calcium to the body, intensely expresses mRNAs and proteins of prolactin receptors, especially in the duodenum and jejunum, indicating the intestine as a target tissue of prolactin. A number of investigations show that prolactin is able to stimulate the intestinal calcium transport both in vitro and in vivo, whereas bromocriptine, which inhibits pituitary prolactin secretion, antagonizes its actions. In female rats, acute and long-term exposure to high prolactin levels significantly enhances the (i) transcellular active, (ii) solvent drag-induced, and (iii) passive calcium transport occurring in the small intestine. These effects are seen not only in pregnant and lactating animals, but are also observed in non-pregnant and non-lactating animals. Interestingly, young animals are more responsive to prolactin than adults. Prolactin-enhanced calcium absorption gradually diminishes with age, thus suggesting it has an age-dependent mode of action. Although prolactin's effects on calcium absorption are not directly vitamin D-dependent; a certain level of circulating vitamin D may be required for the basal expression of genes related to calcium transport. The aforementioned body of evidence supports the hypothesis that prolactin acts as a regulator of calcium homeostasis by controlling the intestinal calcium absorption. Cellular and molecular signal transductions of prolactin in the enterocytes are largely unknown, however, and still require investigation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".