Extracellular vesicles as prospective biological indicators for midgestational placental complications in the mouse
Bibliographic record
Abstract
Background: Placental dysfunction is often associated with reproductive complications such as preeclampsia, intrauterine growth restriction (IUGR), and preterm birth. Currently, the early diagnosis and intervention of these pathologies remain challenging due to the invasive nature of placental tissue sampling. Liquid biopsies of extracellular vesicles (EVs) released from the placenta have emerged as a prospective minimally invasive diagnostic strategy that could provide insight into the maternal-fetal interface because of the active role EVs play in mediating placental development and function. However, the lack of information on EVs directly from placenta at disease onset has questioned the representativeness of placental EVs as pathological indicators. To address these concerns, this study assessed the accuracy with which tissue-derived D10.5 placental EVs could identify phenotypes exhibited by a reproductively challenged Nodal conditional knockout mouse model at mid-gestation. Method: Implantation sites from female mice with a uterine-specific knockdown of the Nodal gene were examined from D8.5 to D14.5 utilizing histological analysis, Western blotting, and RT-qPCR to characterize their mid-gestational phenotypes. Placental EVs were then isolated from D10.5 placenta using enzymatic digestion, differential centrifugation, filtration, and size-exclusion chromatography. The final EV fractions were concentrated and validated with size analysis, canonical protein markers, and morphology assessment. Differential expression analysis across the EV samples was performed using proteomics and miRNA-Seq. Functional enrichment analysis of dysregulated EV factors was then completed using several gene ontology databases along with a literature review to determine whether placental EVs could indicate the reproductive abnormalities presented by the mutant mice. Results: Uterine-specific deletion of Nodal resulted in IUGR and fetal loss in mutant dams. Decidualization and placentation defects were observed, including thinner decidual and placental tissues, impaired angiogenesis, and an altered junctional zone within the maternal-fetal interface. Bioinformatics analysis of EV cargo identified 31 differentially expressed proteins and 10 miRNAs specifically linked to placental development, oxidative stress, angiogenesis, and immunomodulation. Notably, 15 of these proteins and six of these miRNAs have been previously associated with pregnancy complications, further supporting the prospects of placental EVs as biomarkers for various placental diseases. Conclusion: These findings suggest that placental EVs can reflect compromised placental function and could serve as pathological indicators for the early detection of pregnancy complications. Their potential diagnostic utility could improve maternal and neonatal health outcomes by enabling earlier intervention and monitoring of high-risk pregnancies.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".