Impact of the Addition of a Centrifugal Pump in a Preterm Miniature Pig Model of the Artificial Placenta
Bibliographic record
Abstract
The recent demonstration of normal development of preterm sheep in an artificial extrauterine environment has renewed interest in artificial placenta (AP) systems as a potential treatment strategy for extremely preterm human infants. However, the feasibility of translating this technology to the human preterm infant remains unknown. Here we report the support of 13 preterm fetal pigs delivered at 102 ± 4 days (d) gestation, weighing 616 ± 139 g with a circuit consisting of an oxygenator and a centrifugal pump, comparing these results with our previously reported pumpless circuit (n = 12; 98 ± 4 days; 743 ± 350 g). The umbilical vessels were cannulated, and fetuses were supported for 46.4 ± 46.8 h using the pumped AP versus 11 ± 13 h on the pumpless AP circuit. Upon initiation of AP support on the pumped system, we observed supraphysiologic circuit flows, tachycardia, and hypertension, while animals maintained on a pumpless AP circuit exhibited subphysiologic flows. On the pumped AP circuit, there was a progressive decline in umbilical vein (UV) flow and oxygen delivery. We conclude that the addition of a centrifugal pump to the AP circuit improves survival of preterm pigs by augmenting UV flow through the reduction of right ventricular afterload. However, we continued to observe the development of heart failure within a matter of days.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".