Toll-Like Receptor 4 Is an Essential Upstream Regulator of On-Time Parturition and Perinatal Viability in Mice
Bibliographic record
Abstract
An inflammatory response is instrumental in the physiological process of parturition but the upstream signals initiating inflammation are undefined. Because endogenous ligands for Toll-like receptor 4 (TLR4) are released in late gestation, we hypothesized that on-time labor requires TLR4 signaling, to trigger a cytokine and leukocyte response and accelerate the parturition cascade. In pregnant TLR4-deficient (Tlr4-/-) mice, average gestation length was extended by 13 hours and increased perinatal mortality was seen compared with wild-type controls. Quantification of cytokine and uterine activation gene expression showed that late gestation induction of Il1b, Il6, Il12b, and Tnf expression seen in control placenta and fetal membranes was disrupted in Tlr4-/- mice, and accompanied by a transient delay in expression of uterine activation genes, including prostaglandin F receptor, oxytocin receptor, and connexin-43. Leukocyte populations were altered before birth in TLR4-deficient females, with fewer neutrophils and macrophages in the placenta, and fewer dendritic cells and more regulatory T cells in the myometrium. Administration of TLR4 ligand lipopolysaccharide to pregnant wild-type mice induced cytokine expression and fetal loss, whereas Tlr4-/- pregnancies were protected. The small molecule TLR4 antagonist (+)-naloxone increased mean duration of gestation by 16 hours in wild-type mice. Collectively, these data demonstrate that TLR4 is a key upstream regulator of the inflammatory response acting to drive uterine activation and control the timing of labor. Because causal pathways for term and preterm labor converge with TLR4, interventions to manipulate TLR4 signaling may have therapeutic utility for women at risk of preterm labor, or in postterm pregnancy.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".