Bibliographic record
Abstract
The miR-200 family of microRNAs plays a significant role in inhibiting mammary tumor growth and progression, and its members are being investigated as therapeutic targets. Additionally, if future studies can prove that miR-200s prevent mammary tumor initiation, the microRNA family could also offer a preventative strategy. Before utilizing miR-200s in a therapeutic setting, understanding how they regulate normal mammary development is necessary. No studies investigating the role of miR-200s in embryonic ductal development could be found, and only two studies examined the impact of miR-200s on pubertal ductal morphogenesis. These studies showed that miR-200s are expressed at low levels in virgin mammary glands, and elevated expression of miR-200s have the potential to impair ductal morphogenesis. In contrast to virgin mammary glands, miR-200s are expressed at high levels in mammary glands during late pregnancy and lactation. miR-200s are also found in the milk of several mammalian species, including humans. However, the relevance of miR-200s in milk remains unclear. The increase in miR-200 expression in late pregnancy and lactation suggests a role for miR-200s in the development of alveoli and/or regulating milk production. Therefore, studies investigating the consequence of miR-200 overexpression or knockdown are needed to identify the function of miR-200s in alveolar development and lactation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".