Prenatal inflammation as a link between placental expression signature of tryptophan metabolism and preterm birth
Bibliographic record
Abstract
Spontaneous preterm birth is a serious medical condition responsible for substantial perinatal morbidity and mortality. Its phenotypic characteristics, preterm labor with intact membranes (PTL) and preterm premature rupture of the membranes (PPROM), are associated with significantly increased risks of neurological and behavioral alterations in childhood and later life. Recognizing the inflammatory milieu associated with PTL and PPROM, here, we examined expression signatures of placental tryptophan metabolism, an important pathway in prenatal brain development and immunotolerance. The study was performed in a well-characterized clinical cohort of healthy term pregnancies (n = 39) and 167 preterm deliveries (PTL, n = 38 and PPROM, n = 129). Within the preterm group, we then investigated potential mechanistic links between differential placental tryptophan pathway expression, preterm birth and both intra-amniotic markers (such as amniotic fluid interleukin-6) and maternal inflammatory markers (such as maternal serum C-reactive protein and white blood cell count). We show that preterm birth is associated with significant changes in placental tryptophan metabolism. Multifactorial analysis revealed similarities in expression patterns associated with multiple phenotypes of preterm delivery. Subsequent correlation computations and mediation analyses identified links between intra-amniotic and maternal inflammatory markers and placental serotonin and kynurenine pathways of tryptophan catabolism. Collectively, the findings suggest that a hostile inflammatory environment associated with preterm delivery underlies the mechanisms affecting placental endocrine/transport functions and may contribute to disruption of developmental programming of the fetal brain.
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 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".