Bibliographic record
Abstract
Prolactin and prolactin receptor signaling and function are complex in nature and intricate in function. Basic, pre-clinical and translational research has opened up our eyes to the understanding that prolactin and prolactin receptor signaling function differently within different cellular contexts and microenvironmental conditions. Its multiple roles in normal physiology are subverted in cancer initiation and progression, and gradually we are teasing out the intricacies of function and therapeutic value. Recently, we observed that prolactin has a role in accelerating the time to bone metastasis in breast cancer patients and identified the mechanism by which prolactin stimulated breast cancer cell-mediated lytic osteoclast formation. The possibility that the prolactin receptor is a marker for metastasis, and specifically bone metastasis, is one that may have to be put into the context of the different variants of prolactin, different prolactin receptor isoforms and intricate signaling pathways that are regulated by the microenvironment. The more complete the picture, the better one can test biomarker identity and design clinical trials to test therapeutic intervention. This review will cover the recent advances and highlight the complexity of prolactin receptor biology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".