Insights Into Extracellular Vesicle/Exosome and miRNA Mediated Bi-Directional Communication During Porcine Pregnancy
Bibliographic record
Abstract
Spontaneous fetal loss is one of the most important challenges that commercial pig industry is still facing in North America. Research over the decade provided significant insights into some of the associated mechanisms including uterine capacity, placental efficiency, deficits in vasculature, and immune-inflammatory alterations at the maternal-fetal interface. Pigs have unique epitheliochorial placentation where maternal and fetal layers lay in opposition without any invasion. This has provided researchers opportunities to accurately tease out some of the mechanisms associated with maternal-fetal interface adaptations to the constantly evolving needs of a developing conceptus. Another unique feature of porcine pregnancy is the conceptus derived recruitment of immune cells during the window of conceptus attachment. These immune cells in turn participate in pregnancy associated vascular changes and contribute toward tolerance to the semi-allogeneic fetus. However, the precise mechanism of how maternal-fetal cells communicate during the critical times in gestation is not fully understood. Recently, it has been established that bi-directional communication between fetal trophoblasts and maternal cells/tissues is mediated by extracellular vesicles (EVs) including exosomes. These EVs are detected in a variety of tissues and body fluids and their role has been described in modulating several physiological and pathological processes including vascularization, immune-modulation, and homeostasis. Recent literature also suggests that these EVs (exosomes) carry cargo (nucleic acids, protein, and lipids) as unique signatures associated with some of the pregnancy associated pathologies. In this review, we provide overview of important mechanisms in porcine pregnancy success and failure and summarize current knowledge about the unique cargo containing biomolecules in EVs. We also discuss how EVs (including exosomes) transfer their contents into other cells and regulate important biological pathways critical for pregnancy success.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".