Pleiotrophin Messenger Ribonucleic Acid Levels Increase in Mouse Endometrial Stromal Cells During Decidualization
Bibliographic record
Abstract
In mice (and other species) fibroblast-like endometrial stromal cells differentiate into large decidual cells during early pregnancy. These decidual cells, which play an important function during the process of embryo implantation, eventually die or form the maternal component of the placenta. In the current study, with the use of subtractive hybridization methods and Northern blot analysis, we found that steady-state pleiotrophin transcript levels are increased in uterine horns undergoing artificially induced decidualization compared to control horns. Steady-state pleiotrophin transcript levels were significantly (P< 0.01) greater in uterine horns undergoing decidualization compared to the control horn at 48 h and 72 h, but not 24 h, after the application of the deciduogenic stimulus to appropriately sensitized uteri. This increase in pleiotrophin transcript levels was localized to the endometrial stromal cells undergoing decidualization, as determined by in situhybridization. Finally, we also determined if pleiotrophin transcript levels were greater in implantation segments compared to inter-implantation segments of the uterus during early pregnancy. Steady-state pleiotrophin transcript levels were significantly (P< 0.01) greater in implantation compared to inter-implantation segments on day 6 to 8, but not 5 (day 1 = vaginal plug), of pregnancy. In conclusion, pleiotrophin transcript levels increase in the endometrial stromal cells during decidualization suggesting that it might play a role in the process.
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 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".