Orphan Nuclear Receptor NR4A1 Is a Negative Regulator of DHT-Induced Rat Preantral Follicular Growth
Bibliographic record
Abstract
Nuclear receptor subfamily 4 group A member1 (NR4A1), an orphan nuclear receptor, is involved in the transcriptional regulation of thecal cell androgen biosynthesis and paracrine factor insulin-like 3 (INSL3) expression. Androgens are known to play an important regulatory role in ovarian follicle growth. Using a chronically androgenized rat model, a preantral follicle culture model and virus-mediated gene delivery, we examined the role and regulation of NR4A1 in the androgenic control of preantral follicular growth. In the present study, Ki67 staining was increased in preantral follicles on ovarian sections from 5α-dihydrotestosterone (DHT)-treated rats. Preantral follicles from DHT-treated rats cultured for 4 d exhibited increased growth and up-regulation of mRNA abundance of G(1)/S-specific cyclin-D2 (Ccnd2) and FSH receptor (Fshr). Similarly, DHT (1 μm) increased preantral follicular growth and Ccnd2 and Fshr mRNA abundance in vitro. The NR4A1 expression was high in theca cells and was down-regulated by DHT in vivo and in vitro. Forced expression of NR4A1 augmented preantral follicular growth, androstenedione production, and Insl3 expression in vitro. Inhibiting the action of androgen (with androgen receptor antagonist flutamide) or INSL3 (with INSL3 receptor antagonist INSL3 B-chain) reduced NR4A1-induced preantral follicular growth. Furthermore, NR4A1 overexpression enhanced DHT-induced preantral follicular growth, a response attenuated by inhibiting INSL3. In conclusion, DHT promotes preantral follicular growth and attenuates thecal NR4A1 expression in vivo and in vitro. Our findings are consistent with the notion that NR4A1 serves as an important point of negative feedback to minimize the excessive preantral follicle growth in hyperandrogenism.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".