Endometrial gene expression of lactating Holstein cows: Impact of pre-estrus progesterone and intensity of estrous expression
Bibliographic record
Abstract
This study aimed to evaluate if different concentrations of progesterone (P4) before estrus and different intensities of estrous expression affected endometrial gene expression in lactating Holstein cows. Animals were randomly assigned into 2 experimental groups: control P4 and low P4. Cows underwent a presynchronization protocol involving a GnRH injection and P4 implant, followed by a PGF 2α injection and implant removal after 7 d, and a second GnRH injection 48 h later. The P4 treatment began 3 d after the second GnRH injection, with low P4 cows receiving 3 PGF 2α injections (12 h apart), and control P4 cows receiving no PGF 2α injections. Five days after the start of treatment, all cows underwent a hormonal protocol identical to the presynchronization, except an estradiol cypionate injection replaced the second GnRH, given 24 h after P4 implant removal. Low P4 cows received additional PGF 2α injections at 24, 36, and 48 h after the start of this second protocol. Physical activity was monitored by an activity monitor, and the duration and intensity of estrus were measured. A total of 33 cows (control P4: n=16; low P4: n=17) were submitted to uterine biopsy 7 and 14 d after the identified estrous event. Total RNA was extracted from each sample and the NanoString nCounter system was used to determine the abundance of specific mRNA molecules for 91 genes. In addition to the P4 treatment, cows were classified as high or low estrous expression based on the median estrous intensity and duration. Gene expression data were normalized and analyzed using a mixed linear regression model with cow as random intercept. Significance for differential expression was set at false discovery rate <0.1 and absolute fold change ≥1.5. The P4 treatment was not associated with changes in endometrial gene expression 7 d after estrus. However, at d 14, a total of 17 target gene transcripts were differentially expressed between the treatment groups. In low P4 cows, upregulated genes were related to the immune system ( CXCL8 , CCL22 , IL1B , IL1A , PTX3 ) and extracellular matrix remodeling ( MMP3 , MMP9 , MMP1 ), compared with control P4. Estrous expression alone did not affect gene expression. However, its interaction with the P4 treatment influenced several target genes, with most changes observed 14 d postestrus. Low P4 concentrations during the follicular growth in cows that had low intensity of estrus were linked to decreased endometrial expression of growth factors ( IGF1 , IGF2 ) and increased expression of genes related to the immune system ( CCL22 , CCL2 , CCL4 , MUC1 , NFKB2 , PTX3 ) and PGF 2α synthesis ( SLCO2A1 , PTGES ) 14 d after estrus compared control P4. Pathway analysis linked β-estradiol as a potential upstream regulator of the genes affected by the interaction between P4 and estrus. When estradiol concentrations near the onset of estrus were measured, we found that estradiol modulated endometrial expression of IGF1 and MUC1 genes, but this effect was observed only under the low P4 treatment. In conclusion, our study revealed substantial differences in endometrial gene expression between cows treated with different P4 concentrations during the follicular growth and expressing different intensities of estrus.
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".