Interleukins’ expression profile changes in granulosa cells of preovulatory follicles during the postpartum period in dairy cows
Bibliographic record
Abstract
The postpartum period in dairy cows is associated with a state of temporary negative energy balance and could induce functional changes into ovarian granulosa cells (GC) resulting in significant impact on the ovarian function and fertility. Yet, the regulation of interleukin receptors (ILRs) in GC as well as ILs expression profile during the postpartum period have not been fully investigated. We hypothesized that the postpartum period is associated with changes in ILs expression profile that could affect follicular development and ovulation rate. First, we aimed to investigate the expression and regulation of different IL and IL receptors in GC at different stages of follicular development and then analyse the changes in target ILs expression profile induced during the postpartum period. In the first objective, normal cycling cows were selected and GC were collected from small follicles (SF), dominant follicles at day 5 of the estrous cycle (DF), and ovulatory follicles, 24 h following hCG injection (OF). In the second objective, dairy cows between 50 and 70 days postpartum were randomly selected, and β-hydroxybutyrate (BHB) concentrations were measured in blood samples in order to assign cows to the BHB+ group (>1.4 mmol/L) or BHB− group (<1.2 mmol/L). GC were collected from preovulatory follicles by transvaginal aspiration. Total RNA was extracted from GC of all groups for analysis of target ILs and ILRs expression. Steady-state mRNA levels of IL4R was strongest in the DF, while IL15R expression was greatest in the OF, and IL21R showed increased steady-state mRNA levels in the corpus luteum as compared to the different groups of follicles. Overall, expression of IL1A, IL1B, IL8, IL15, IL23 and TNFα was stronger in OF as compared to DF, while IL4 and IL10 expression was stronger in SF than in DF. Similarly, expression of IL1A, IL1B, IL8, IL15, IL23, and TNFα were significantly stronger in GC of BHB+ cows than in the control, while IL4 expression was significantly reduced in BHB+ as compared to control cows. We have established an IL expression profile, which suggest a correlation with BHB levels during the postpartum period. Additionally, we have demonstrated a differential regulation of target ILRs in GC at different stages of follicular development. Overall, these data provide a better understanding of the changes that could affect follicular development and ovulation during the postpartum period and lay the ground for further investigations.
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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 | 0.000 | 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".