Bibliographic record
Abstract
The heart is the first organ to be functionally established during development, thus initiating blood circulation very early in gestation. Besides transporting oxygen and nutrients to ensure fetal growth, fetal circulation controls many crucial developmental events taking place within the endothelial layer through mechanical cues. Biomechanical signals induce blood vessel structural changes, establish arteriovenous specification, and control the development of hematopoietic stem cells. The inaccessibility of the developing tissues limits the understanding of the role of circulation in early human development; therefore, in vitro models are pivotal tools for the study of vessel mechanobiology. This paper describes a protocol to differentiate endothelial cells from human induced pluripotent stem cells and their subsequent seeding into a fluidic device to study their response to mechanical cues. This approach allows for long-term culture of endothelial cells under mechanical stimulation followed by retrieval of the endothelial cells for phenotypical and functional characterization. The in vitro model established here will be instrumental to elucidate the intracellular molecular mechanisms that transduce the signaling mediated by mechanical cues, which ultimately orchestrate vessel development during human fetal life.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.556 | 0.345 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".