Loss of Panx1 Impairs Mammary Gland Development at Lactation: Implications for Breast Tumorigenesis
Bibliographic record
Abstract
Pannexin1 (Panx1) subunits oligomerize to form large-pore channels between the intracellular and extracellular milieu that have been shown to regulate proliferation, differentiation and cell death mechanisms. These key cellular responses are ultimately necessary for normal tissue development and function but the role of Panx1 in development, differentiation and function in many tissues remains unexplored, including that of the breast. Panx1 was identified to be expressed in the mammary gland through western blot and immunofluorescent analysis and is dynamically upregulated during pregnancy and lactation. In order to evaluate the role of Panx1 in the context of mammary gland development and function, Panx1-/- mice were evaluated in comparison to wild-type mice in the mammary glands of virgin, lactating and involuting mice. Our results revealed that Panx1 ablation did not affect virgin or involuting mammary glands following histological and whole mount analysis. Panx1 was necessary for timely alveolar development during early lactation based on a decreased number of alveolar lumen following histological analysis and reduced proliferation following Ki67 immunofluorescent labelling. Importantly, the loss of Panx1 in lactating mammary glands did not overtly affect epithelial or secretory differentiation of the mammary gland suggesting that Panx1 is not critical in normal mammary gland function. In addition, PANX1 mRNA expression was correlated with negative clinical outcomes in patients with breast cancer using in silico arrays. Together, our results suggest that Panx1 is necessary for timely alveolar development following the transition from pregnancy to lactation, which may have implications extending to patients with breast cancer.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".