Cycle-dependent expression of macrophage migration inhibitory factor in the human endometrium
Bibliographic record
Abstract
BACKGROUND: Macrophage migration inhibitory factor (MIF) is a multifunctional cytokine that was shown to promote angiogenesis and tissue remodelling. Our previous studies identified MIF as one of the principal bioactive molecules involved in endothelial cell proliferation released by ectopic endometrial cells. METHODS AND RESULTS: In the present study, we examined the expression of MIF in the human endometrium and found an interesting distribution and temporal pattern of expression throughout the menstrual cycle. Immunoreactive MIF was predominant in the glands and surface epithelium. Dual immunofluorescence analysis further identified endothelial cells, macrophages and T-lymphocytes as cells markedly expressing MIF in the stroma. Quantitative assessment of MIF protein showed a regulated cycle phase-dependent expression pattern. MIF expression increased in the late proliferative/early Secretory phase of the menstrual cycle was moderate during the receptive phase or what is commonly called the implantation window before increasing again at the end of the cycle. This pattern paralleled MIF mRNA expression determined by northern blot. CONCLUSION: The cycle phase-specific expression of MIF suggests a tight regulation and perhaps different roles for this factor in the reparative, reproductive and inflammatory-like processes that occur in human endometrium during every menstrual cycle.
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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 | 0.001 | 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".