Novel Toll-like receptor-4 antagonist (+)-naloxone protects mice from inflammation-induced preterm birth
Bibliographic record
Abstract
Toll-like receptor 4 (TLR4) activation by bacterial infection, or by sterile inflammatory insult is a primary trigger of spontaneous preterm birth. Here we utilize mouse models to investigate the efficacy of a novel small molecule TLR4 antagonist, (+)-naloxone, the non-opioid isomer of the opioid receptor antagonist (-)-naloxone, in infection-associated preterm birth. Treatment with (+)-naloxone prevented preterm delivery and alleviated fetal demise in utero elicited by i.p. LPS administration in late gestation. A similar effect with protection from preterm birth and perinatal death, and partial correction of reduced birth weight and postnatal mortality, was conferred by (+)-naloxone administration after intrauterine administration of heat-killed E. coli. Local induction by E. coli of inflammatory cytokine genes Il1b, Il6, Tnf and Il10 in fetal membranes was suppressed by (+)-naloxone, and cytokine expression in the placenta, and uterine myometrium and decidua, was also attenuated. These data demonstrate that inhibition of TLR4 signaling with the novel TLR4 antagonist (+)-naloxone can suppress the inflammatory cascade of preterm parturition, to prevent preterm birth and perinatal death. Further studies are warranted to investigate the utility of small molecule inhibition of TLR-driven inflammation as a component of strategies for fetal protection and delaying preterm birth in the clinical setting.
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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 | 0.001 | 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) | 0.001 | 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 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".