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Record W3196644657 · doi:10.1113/jp281292

Impact of maternal late gestation undernutrition on surfactant maturation, pulmonary blood flow and oxygen delivery measured by magnetic resonance imaging in the sheep fetus

2021· article· en· W3196644657 on OpenAlexaff
Jiaqi Ren, Jack R. T. Darby, Mitchell C. Lock, Stacey L. Holman, Brahmdeep S. Saini, Emma L. Bradshaw, Sandra Orgeig, Sunthara Rajan Perumal, Michael D. Wiese, Christopher K. Macgowan, Mike Seed, Janna L. Morrison

Bibliographic record

VenueThe Journal of Physiology · 2021
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsFetusMagnetic resonance imagingPulmonary surfactantGestationOxygen deliveryBlood flowMedicineOxygenPhysiologyNuclear magnetic resonancePregnancyInternal medicineChemistryBiologyRadiologyPhysicsBiochemistry

Abstract

fetched live from OpenAlex

Abstract Restriction of fetal substrate supply has an adverse effect on surfactant maturation in the lung and thus affects the transition from in utero placental oxygenation to pulmonary ventilation ex utero. The effects on surfactant maturation are mediated by alteration in mechanisms regulating surfactant protein and phospholipid synthesis. This study aimed to determine the effects of late gestation maternal undernutrition (LGUN) and LGUN plus fetal glucose infusion (LGUN+G) compared to Control on surfactant maturation and lung development, and the relationship with pulmonary blood flow and oxygen delivery ( ) measured by magnetic resonance imaging (MRI) with molecules that regulate lung development. LGUN from 115 to 140 days’ gestation significantly decreased fetal body weight, which was normalized by glucose infusion. LGUN and LGUN+G resulted in decreased fetal plasma glucose concentration, with no change in fetal arterial compared to control. There was no effect of LGUN and LGUN+G on the mRNA expression of surfactant proteins (SFTP) and genes regulating surfactant maturation in the fetal lung. However, blood flow in the main pulmonary artery was significantly increased in LGUN, despite no change in blood flow in the left or right pulmonary artery and to the fetal lung. There was a negative relationship between left pulmonary artery flow and to the left lung with SFTP‐B and GLUT1 mRNA expression, while their relationship with VEGFR2 was positive. These results suggest that increased pulmonary blood flow measured by MRI may have an adverse effect on surfactant maturation during fetal lung development. image Key points Maternal undernutrition during gestation alters fetal lung development by impacting surfactant maturation. However, the direction of change remains controversial. We examined the effects of maternal late gestation maternal undernutrition (LGUN) on maternal and fetal outcomes, signalling pathways involved in fetal lung development, pulmonary haemodynamics and oxygen delivery in sheep using a combination of molecular and magnetic resonance imaging (MRI) techniques. LGUN decreased fetal plasma glucose concentration without affecting arterial . Surfactant maturation was not affected; however, main pulmonary artery blood flow was significantly increased in the LGUN fetuses. This is the first study to explore the relationship between in utero MRI measures of pulmonary haemodynamics and lung development. Across all treatment groups, left pulmonary artery blood flow and oxygen delivery were negatively correlated with surfactant protein B mRNA and protein expression in late gestation.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.264
Teacher spread0.249 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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