Identification of Downregulated Messenger RNAs in Bovine Granulosa Cells of Dominant Follicles Following Stimulation with Human Chorionic Gonadotropin1
Bibliographic record
Abstract
Molecular determinants and mechanisms involved in ovarian follicular growth, ovulation, and luteinization are not well understood. The objective of this study was to identify genes expressed in bovine granulosa cells (GC) of dominant follicles (DF) and downregulated after hCG-induced ovulation, using the suppression subtractive hybridization (SSH). GC were collected from DF at Day 5 of the estrous cycle and from ovulatory follicles (OF) obtained 23 h following injection of hCG. A subtracted cDNA library (DF-OF) was generated and screened using unsubtracted (DF, OF) and subtracted (DF-OF, OF-DF) cDNAs as complex (32)P-probes. A total of 32 nonredundant cDNAs were identified: 23 cDNAs matched with sequences of known biological function and 9 cDNAs with complete or partial sequences of undefined biological function. Detection of genes known to be downregulated during the periovulatory period in the bovine species, such as CPD, CYP11A1, CYP19A1, FSHR, LRP8/ ApoER2, and SERPINE2, validated the physiological model and analytical techniques used. For a subset of genes, such as ARFGAP3, CYP11A1, CYP19A1, FSHR, FST, GJA1, IDH3, INHBA, LHCGR, LHCGR lacking exon 10, PRC1, PRG1, RPA2, SCD, and TRIB2, gene expression profiles were compared by virtual Northern blot or reverse transcriptase-polymerase chain reaction from follicles obtained at different developmental stages. Results confirmed a downregulation of the respective mRNAs in GC of OF compared with that of DF. We conclude that we have identified novel genes that are downregulated by hCG in bovine GC of DF during the periovulatory period, which may contribute to follicular growth, ovulation, and/or luteinization.
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 | 0.001 | 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) | 0.000 | 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".