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      Macrophages exert homeostatic actions in pregnancy to protect against preterm birth and fetal inflammatory injury

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          Abstract

          Macrophages are commonly thought to contribute to the pathophysiology of preterm labor by amplifying inflammation — but a protective role has not previously been considered to our knowledge. We hypothesized that given their antiinflammatory capability in early pregnancy, macrophages exert essential roles in maintenance of late gestation and that insufficient macrophages may predispose individuals to spontaneous preterm labor and adverse neonatal outcomes. Here, we showed that women with spontaneous preterm birth had reduced CD209 +CD206 + expression in alternatively activated CD45 +CD14 +ICAM3 macrophages and increased TNF expression in proinflammatory CD45 +CD14 +CD80 +HLA-DR + macrophages in the uterine decidua at the materno-fetal interface. In Cd11b DTR/DTR mice, depletion of maternal CD11b + myeloid cells caused preterm birth, neonatal death, and postnatal growth impairment, accompanied by uterine cytokine and leukocyte changes indicative of a proinflammatory response, while adoptive transfer of WT macrophages prevented preterm birth and partially rescued neonatal loss. In a model of intra-amniotic inflammation–induced preterm birth, macrophages polarized in vitro to an M2 phenotype showed superior capacity over nonpolarized macrophages to reduce uterine and fetal inflammation, prevent preterm birth, and improve neonatal survival. We conclude that macrophages exert a critical homeostatic regulatory role in late gestation and are implicated as a determinant of susceptibility to spontaneous preterm birth and fetal inflammatory injury.

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          STRING v10: protein–protein interaction networks, integrated over the tree of life

          The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein–protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein–protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.
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            Epidemiology and causes of preterm birth

            Summary This paper is the first in a three-part series on preterm birth, which is the leading cause of perinatal morbidity and mortality in developed countries. Infants are born preterm at less than 37 weeks' gestational age after: (1) spontaneous labour with intact membranes, (2) preterm premature rupture of the membranes (PPROM), and (3) labour induction or caesarean delivery for maternal or fetal indications. The frequency of preterm births is about 12–13% in the USA and 5–9% in many other developed countries; however, the rate of preterm birth has increased in many locations, predominantly because of increasing indicated preterm births and preterm delivery of artificially conceived multiple pregnancies. Common reasons for indicated preterm births include pre-eclampsia or eclampsia, and intrauterine growth restriction. Births that follow spontaneous preterm labour and PPROM—together called spontaneous preterm births—are regarded as a syndrome resulting from multiple causes, including infection or inflammation, vascular disease, and uterine overdistension. Risk factors for spontaneous preterm births include a previous preterm birth, black race, periodontal disease, and low maternal body-mass index. A short cervical length and a raised cervical-vaginal fetal fibronectin concentration are the strongest predictors of spontaneous preterm birth.
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              Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis

              Summary Background Preterm birth is the leading cause of death in children younger than 5 years worldwide. Although preterm survival rates have increased in high-income countries, preterm newborns still die because of a lack of adequate newborn care in many low-income and middle-income countries. We estimated global, regional, and national rates of preterm birth in 2014, with trends over time for some selected countries. Methods We systematically searched for data on preterm birth for 194 WHO Member States from 1990 to 2014 in databases of national civil registration and vital statistics (CRVS). We also searched for population-representative surveys and research studies for countries with no or limited CRVS data. For 38 countries with high-quality data for preterm births in 2014, data are reported directly. For countries with at least three data points between 1990 and 2014, we used a linear mixed regression model to estimate preterm birth rates. We also calculated regional and global estimates of preterm birth for 2014. Findings We identified 1241 data points across 107 countries. The estimated global preterm birth rate for 2014 was 10·6% (uncertainty interval 9·0–12·0), equating to an estimated 14·84 million (12·65 million–16·73 million) live preterm births in 2014. 12· 0 million (81·1%) of these preterm births occurred in Asia and sub-Saharan Africa. Regional preterm birth rates for 2014 ranged from 13·4% (6·3–30·9) in North Africa to 8·7% (6·3–13·3) in Europe. India, China, Nigeria, Bangladesh, and Indonesia accounted for 57·9 million (41×4%) of 139·9 million livebirths and 6·6 million (44×6%) of preterm births globally in 2014. Of the 38 countries with high-quality data, preterm birth rates have increased since 2000 in 26 countries and decreased in 12 countries. Globally, we estimated that the preterm birth rate was 9×8% (8×3–10×9) in 2000, and 10×6% (9×0–12×0) in 2014. Interpretation Preterm birth remains a crucial issue in child mortality and improving quality of maternal and newborn care. To better understand the epidemiology of preterm birth, the quality and volume of data needs to be improved, including standardisation of definitions, measurement, and reporting. Funding WHO and the March of Dimes.
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                Author and article information

                Contributors
                Journal
                JCI Insight
                JCI Insight
                JCI Insight
                JCI Insight
                American Society for Clinical Investigation
                2379-3708
                8 October 2021
                8 October 2021
                8 October 2021
                : 6
                : 19
                : e146089
                Affiliations
                [1 ]Robinson Research Institute and Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia.
                [2 ]Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, US Department of Health and Human Services; Bethesda, Maryland, and Detroit, Michigan, USA.
                [3 ]Department of Obstetrics and Gynecology and
                [4 ]Department of Biochemistry, Microbiology and Immunology, Wayne State University School of Medicine, Detroit, Michigan, USA.
                [5 ]University of South Australia Cancer Research Institute, Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia.
                [6 ]Department of Obstetrics and Gynecology, University of Michigan Medical School, Ann Arbor, Michigan, USA.
                [7 ]Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA.
                [8 ]Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan, USA.
                [9 ]Detroit Medical Center, Detroit, Michigan, USA.
                Author notes
                Address correspondence to: Sarah A. Robertson, Robinson Research Institute, Adelaide School of Medicine, University of Adelaide, Adelaide Health and Medical Sciences Building, North Terrace, Adelaide SA 5005, Australia. Phone: 61.8.8313.4094; Email: sarah.robertson@ 123456adelaide.edu.au . Or to: Nardhy Gomez-Lopez, Department of Obstetrics and Gynecology, Wayne State University, School of Medicine, Perinatology Research Branch, NICHD/NIH/DHHS, 275 E. Hancock St., Detroit, Michigan 48201, USA. Phone: 313.577.8904; Email: nardhy.gomez-lopez@ 123456wayne.edu .
                Author information
                http://orcid.org/0000-0002-3406-5262
                http://orcid.org/0000-0002-0923-0553
                http://orcid.org/0000-0001-8417-5542
                http://orcid.org/0000-0002-9967-0084
                Article
                146089
                10.1172/jci.insight.146089
                8525593
                34622802
                7d4a9b0c-1417-4dea-9279-9c438336c7e6
                © 2021 Gomez-Lopez et al.

                This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 November 2020
                : 20 August 2021
                Funding
                Funded by: National Health and Medical Research Council of Australia
                Award ID: project grant APP1140916 (to SAR)
                Award ID: fellowship APP1012386 (to KD)
                Funded by: National Institutes of Health
                Award ID: HHSN275201300006C
                This study was supported by funds from the National Health and Medical Research Council of Australia (NHMRC) project grant APP1140916 (to SAR) and fellowship APP1012386 (to KD).
                This study was supported by funds from the Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services (NICHD/NIH/DHHS) under Contract No. HHSN275201300006C.
                Categories
                Research Article

                reproductive biology,cytokines,macrophages,obstetrics/gynecology

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