Placental Nanoparticle Uptake-On-a-Chip: The Impact of Trophoblast Syncytialization and Shear Stress
Bibliographic record
Abstract
The placenta is a dynamic and complex organ that plays an essential role in the health and development of the fetus. Placental disorders can affect the health of both the mother and the fetus. There is currently an unmet clinical need to develop nanoparticle-based therapies to target and treat placental disorders. However, little is known about the interaction of nanoparticles (NPs) with the human placenta under biomimetic conditions. Specifically, the impact of shear stress exerted on the trophoblasts (placental epithelial cells) by the maternal blood flow, the gradual fusion of the trophoblasts along the gestation period (syncytialization), and the impact of microvilli formation on the cell uptake of NPs is not known. To this end, we designed dynamic placenta-on-a-chip models using BeWo cells to recapitulate the micro-physiological environment, and we induced different degrees of syncytialization via chemical induction with forskolin. We characterized the degree of syncytialization quantitatively by measuring beta human chorionic gonadotropin (β-hCG) secretion, as well as qualitatively by immunostaining the tight junction protein, ZO-1, and counter nuclear staining. We also characterized microvilli formation under static and dynamic conditions via F-actin staining. We used these models to measure the cell uptake of chondroitin sulfate a binding protein (CSA) conjugated and control liposomes using confocal microscopy, followed by image analysis. Interestingly, exposure of the cells to a dynamic flow of media intrinsically induced syncytialization and microvilli formation compared to static controls. Under dynamic conditions, BeWo cells produced more β-hCG in conditions that increased the cell exposure time to forskolin (p < 0.005). Our cell uptake results clearly show a combined effect of the exerted shear stress and forskolin treatment on the cell uptake of liposomes as uptake increased in forskolin exposed conditions (p < 0.05). Overall, the difference in the extent of cell uptake of liposomes among the different conditions clearly displays a need for the development of dynamic models of the placenta that consider the changes in the placental cell phenotype along the gestation period, including syncytialization, microvilli formation, and the expression of different transport and uptake receptors. Knowledge generated from this work will inform future research aiming at developing drug delivery systems targeting the placenta.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".