Inhibition of interleukin-1 signaling protects against Group B streptococcus-induced preterm birth and fetal loss in mice
Bibliographic record
Abstract
Group B streptococcus is a common microbial agent associated with spontaneous preterm birth and fetal inflammatory response syndrome. In this study, we evaluated the utility of rytvela, a novel peptide antagonist of the interleukin-1 receptor, to suppress inflammatory activation, prolong gestation and improve neonatal outcomes induced in mice by Group B streptococcus. Pregnant mice were administered rytvela or PBS on gestation day 16.5, immediately prior and following surgical administration of heat-killed Group B streptococcus (hkGBS) or PBS into the uterine cavity. Treatment with rytvela prevented preterm delivery and alleviated fetal demise in utero and in the perinatal phase elicited by hkGBS. Compared to pups exposed to hkGBS alone, pups of dams co-administered rytvela exhibited substantially improved survival and growth through to weaning. Analysis by qPCR showed expression of inflammatory cytokine genes Il1b, Il6, Tnf, and Ifng in uterine tissues, and Il1b, Il6, and Tnf in fetal membranes, were stimulated by hkGBS and this increase was suppressed by co-administration of rytvela. Premature induction of uterine activation gene Ptgs2 in the myometrium was also attenuated by rytvela treatment. These data show that activation of IL1-mediated signaling in response to Group B streptococcus triggers an inflammatory cascade that causes preterm parturition and fetal inflammatory injury, and that rytvela can suppress inflammatory mediators to substantially improve pregnancy and fetal outcomes. Our findings add to accumulating evidence supporting clinical investigation of rytvela for fetal protection and delaying preterm birth.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".