Cigarette Smoke Condensate Exposure Induces Receptor for Advanced Glycation End-Products (RAGE)-Dependent Sterile Inflammation in Amniotic Epithelial Cells

Recommendations from the COST action CA17116 (SPRINT) for the standardization of perinatal derivative preparation and in vitro testing

Many preclinical studies have shown that birth-associated tissues, cells and their secreted factors, otherwise known as perinatal derivatives (PnD), possess various biological properties that make them suitable therapeutic candidates for the treatment of numerous pathological conditions. Nevertheless, in the field of PnD research, there is a lack of critical evaluation of the PnD standardization process: from preparation to in vitro testing, an issue that may ultimately delay clinical translation. In this paper, we present the PnD e-questionnaire developed to assess the current state of the art of methods used in the published literature for the procurement, isolation, culturing preservation and characterization of PnD in vitro. Furthermore, we also propose a consensus for the scientific community on the minimal criteria that should be reported to facilitate standardization, reproducibility and transparency of data in PnD research. Lastly, based on the data from the PnD e-questionnaire, we recommend to provide adequate information on the characterization of the PnD. The PnD e-questionnaire is now freely available to the scientific community in order to guide researchers on the minimal criteria that should be clearly reported in their manuscripts. This review is a collaborative effort from the COST SPRINT action (CA17116), which aims to guide future research to facilitate the translation of basic research findings on PnD into clinical practice.

Node embedding-based graph autoencoder outlier detection for adverse pregnancy outcomes

Adverse pregnancy outcomes, such as low birth weight (LBW) and preterm birth (PTB), can have serious consequences for both the mother and infant. Early prediction of such outcomes is important for their prevention. Previous studies using traditional machine learning (ML) models for predicting PTB and LBW have encountered two important limitations: extreme class imbalance in medical datasets and the inability to account for complex relational structures between entities. To address these limitations, we propose a node embedding-based graph outlier detection algorithm to predict adverse pregnancy outcomes. We developed a knowledge graph using a well-curated representative dataset of the Emirati population and two node embedding algorithms. The graph autoencoder (GAE) was trained by applying a combination of original risk factors and node embedding features. Samples that were difficult to reconstruct at the output of GAE were identified as outliers considered representing PTB and LBW samples. Our experiments using LBW, PTB, and very PTB datasets demonstrated that incorporating node embedding considerably improved performance, achieving a 12% higher AUC-ROC compared to traditional GAE. Our study demonstrates the effectiveness of node embedding and graph outlier detection in improving the prediction performance of adverse pregnancy outcomes in well-curated population datasets.

RAGE and HMGB1 expressions in fetal membranes of premature rupture of membranes patients

BACKGROUND Premature rupture of membranes (PROM) often occurs in pregnancy. The fetal membrane weakening is caused by inflammation involving receptor activation for advanced glycation end-products (RAGE) and high mobility group box protein 1 (HMGB1). The associations between RAGE and HMGB1 with PROM are rarely studied. Hence, this study aimed to determine those associations in fetal membranes with PROM occurrence. METHODS This case-control study was conducted at Dr. Ramelan Central Naval Hospital, Surabaya, Indonesia, from August to November 2019. The subjects, determined using a non-probability sampling method (a saturated sample), were divided into PROM and normal pregnancy with intact fetal membranes (control) groups. Fetal membrane specimens were collected during vaginal and cesarean section deliveries. The expressions of RAGE and HMGB1 were determined using the immunohistochemical method and further analyzed using the Mann–Whitney U test. RESULTS The expression of RAGE in fetal membranes with PROM was significantly higher than the control (52.74% versus 14.9% expression/mm2, p<0.001), as well as the expression of HMGB1 (45.9% versus 8.5% expression/mm2, p<0.001). CONCLUSIONS The higher expressions of RAGE and HMGB1 in fetal membranes were associated with PROM.

RAGE against the Machine: Can Increasing Our Understanding of RAGE Help Us to Battle SARS-CoV-2 Infection in Pregnancy?

The receptor of advanced glycation end products (RAGE) is a receptor that is thought to be a key driver of inflammation in pregnancy, SARS-CoV-2, and also in the comorbidities that are known to aggravate these afflictions. In addition to this, vulnerable populations are particularly susceptible to the negative health outcomes when these afflictions are experienced in concert. RAGE binds a number of ligands produced by tissue damage and cellular stress, and its activation triggers the proinflammatory transcription factor Nuclear Factor Kappa B (NF-κB), with the subsequent generation of key proinflammatory cytokines. While this is important for fetal membrane weakening, RAGE is also activated at the end of pregnancy in the uterus, placenta, and cervix. The comorbidities of hypertension, cardiovascular disease, diabetes, and obesity are known to lead to poor pregnancy outcomes, and particularly in populations such as Native Hawaiians and Pacific Islanders. They have also been linked to RAGE activation when individuals are infected with SARS-CoV-2. Therefore, we propose that increasing our understanding of this receptor system will help us to understand how these various afflictions converge, how forms of RAGE could be used as a biomarker, and if its manipulation could be used to develop future therapeutic targets to help those at risk.

Tobacco use during pregnancy

The use of tobacco during pregnancy is the leading preventable cause of pregnancy complications and adverse birth outcomes. In high-income countries, around one in 10 pregnant women smokes tobacco, while smokeless tobacco is the primary form of tobacco used in many low- and middle-income countries. Although the risk of tobacco-related harms can be reduced substantially if mothers cease smoking in the first trimester of pregnancy, the proportion of women who successfully quit smoking during pregnancy remains modest. Psychosocial interventions are first-line treatment, with some high-quality evidence showing that counselling is effective in promoting smoking cessation among pregnant women. There is insufficient evidence regarding the efficacy and safety of smoking cessation pharmacotherapies when used during pregnancy, although in some countries nicotine replacement therapy is recommended for pregnant women who have been unable to quit without pharmacological assistance. E-cigarettes are increasingly being used as a smoking cessation aid in the general population of smokers, but more research is needed to determine if e-cigarettes are a safe and effective treatment option for pregnant women.