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Record W7035908687

Advancing Fetal-Maternal Health: Microphysiological Models for Placental Development

2024· dissertation· en· W7035908687 on OpenAlexfundno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2024
Typedissertation
Languageen
FieldEnvironmental Science
TopicSoil Geostatistics and Mapping
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchMcMaster University
KeywordsPlacentaTrophoblastFetusPlacentationSpiral arteryUmbilical veinPregnancyStem cell
DOInot available

Abstract

fetched live from OpenAlex

The placenta is a highly vascularized, temporary organ developed in pregnancy that is composed of both maternal and fetal cells. It plays a pivotal role in gestational health by facilitating embryo implantation and fostering nutrient exchange between mother and fetus. Placental malformation and the diffusion of harmful exogenous substances through the placental barrier can cause pregnancy complications and, in more severe cases, death of the mother or the fetus. Further, the placenta undergoes profound morphological and functional changes throughout pregnancy. Establishing models to mimic these phenomena at different stages of pregnancy informs prescription drug safety and expedites the development of placental disease treatments. Mouse models are often used to simulate human fetal development despite major interspecies differences. These limitations drive researchers to developing in vitro models consisting of human-derived cells. This thesis presents three 3D vascularized placental models utilizing human placental stem cells (PSCs) and human umbilical vein endothelial cells (HUVECs) which can model multiple placental phenomena across early- and late-stage pregnancy. The first model features a 3D fibrin hydrogel network with self-assembled vasculature and a monolayer of syncytialized human trophoblastic stem cells (STs) serving as a platform for barrier studies at the maternal-fetal interface. By tuning trophoblast differentiation and vascularization of this model to mimic the early- and late-stage placenta, it was revealed that placental barrier permeability was dependent on placental maturity and that the vascular barrier is also a critical determinant of what molecules can be passed from the mother to the fetus. The design and manufacturing of this model were then streamlined to meet the demands of large-scale drug studies in the second placental barrier model. Placental invasion into the maternal decidua is carefully orchestrated by multiple cell types to prevent over- and under-invasion, both of which can be dangerous to the mother and fetus. Understanding the biochemical and environmental cues that permit this healthy invasion can allow for improved diagnostics and treatments of placental diseases, such as preeclampsia and placenta accreta. Thus, the third model presented herein is a placental invasion model with chorionic villus-like structures seeded with invasive extravillous cytotrophoblasts (EVTs) and a perfusable vascular channel. Collectively, these models facilitate the exploration of placental morphogenesis and function throughout various stages of pregnancy. They offer a valuable tool for probing placental dysfunctions and assessing drug safety, ultimately contributing to advancements in fetal-maternal health.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.013
GPT teacher head0.218
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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