
AbstractPreterm birth is the leading cause of neonatal morbidity and mortality. Although the underlying causes of pregnancy-associated complication are numerous, it is well established that infection and inflammation represent a highly significant risk factor in preterm birth. However, despite the clinical and public health significance, infectious agents, molecular trigger(s), and immune pathways underlying the pathogenesis of preterm birth remain underdefined and represent a major gap in knowledge. Here, we provide an overview of recent clinical and animal model data focused on the interplay between infection-driven inflammation and induction of preterm birth. Furthermore, here, we highlight the critical gaps in knowledge that warrant future investigations into the interplay between immune responses and induction of preterm birth.
Inflammation, Neutrophils, Macrophages, Toll-Like Receptors, Dendritic Cells, Infections, Immunity, Innate, Killer Cells, Natural, Disease Models, Animal, Pregnancy, Animals, Cytokines, Humans, Premature Birth, Female, Receptors, Immunologic
Inflammation, Neutrophils, Macrophages, Toll-Like Receptors, Dendritic Cells, Infections, Immunity, Innate, Killer Cells, Natural, Disease Models, Animal, Pregnancy, Animals, Cytokines, Humans, Premature Birth, Female, Receptors, Immunologic
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 220 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
