Association Between Individual Air Pollution (PM10, PM2.5) Exposure and Adverse Pregnancy Outcomes in Korea: A Multicenter Prospective Cohort, Air Pollution on Pregnancy Outcome (APPO) Study.

BACKGROUND: Prenatal exposure to ambient air pollution is linked to a higher risk of unfavorable pregnancy outcomes. However, the association between pregnancy complications and exposure to indoor air pollution remains unclear. The Air Pollution on Pregnancy Outcomes research is a hospital-based prospective cohort research created to look into the effects of aerodynamically exposed particulate matter (PM)10 and PM2.5 on pregnancy outcomes. METHODS: This prospective multicenter observational cohort study was conducted from January 2021 to June 2023. A total of 662 women with singleton pregnancies enrolled in this study. An AirguardK® air sensor was installed inside the homes of the participants to measure the individual PM10 and PM2.5 levels in the living environment. The time-activity patterns and PM10 and PM2.5, determined as concentrations from the time-weighted average model, were applied to determine the anticipated exposure levels to air pollution of each pregnant woman. The relationship between air pollution exposure and pregnancy outcomes was assessed using logistic and linear regression analyses. RESULTS: Exposure to elevated levels of PM10 throughout the first, second, and third trimesters as well as throughout pregnancy was strongly correlated with the risk of pregnancy problems according to multiple logistic regression models adjusted for variables. Except for in the third trimester of pregnancy, women exposed to high levels of PM2.5 had a high risk of pregnancy complications. During the second trimester and entire pregnancy, the risk of preterm birth (PTB) increased by 24% and 27%, respectively, for each 10 µg/m3 increase in PM10. Exposure to high PM10 levels during the second trimester increased the risk of gestational diabetes mellitus (GDM) by 30%. The risk of GDM increased by 15% for each 5 µg/m3 increase in PM2.5 during the second trimester and overall pregnancy, respectively. Exposure to high PM10 and PM2.5 during the first trimester of pregnancy increased the risk of delivering small for gestational age (SGA) infants by 96% and 26%, respectively. CONCLUSION: Exposure to high concentrations of PM10 and PM2.5 is strongly correlated with the risk of adverse pregnancy outcomes. Exposure to high levels of PM10 and PM2.5 during the second trimester and entire pregnancy, respectively, significantly increased the risk of PTB and GDM. Exposure to high levels of PM10 and PM2.5 during the first trimester of pregnancy considerably increased the risk of having SGA infants. Our findings highlight the need to measure individual particulate levels during pregnancy and the importance of managing air quality in residential environment.

Correction: Park et al. Effect of Particulate Matter 2.5 on Fetal Growth in Male and Preterm Infants through Oxidative Stress. Antioxidants 2023, 12, 1916.

In the original publication [...].

Urinary metabolite biomarkers of pregnancy complications associated with maternal exposure to particulate matter.

Particulate matter 2.5 (PM2.5) is associated with reproductive health and adverse pregnancy outcomes. However, studies evaluating biological markers of PM2.5 are lacking, and identifying biomarkers for estimating prenatal exposure to prevent pregnancy complications is essential. Therefore, we aimed to explore urine metabolites that are easy to measure as biomarkers of exposure. In this matched case-control study based on the PM2.5 exposure, 30 high PM2.5 group (>15 µg/m3) and 30 low PM2.5 group (<15 µg/m3) were selected from air pollution on pregnancy outcome (APPO) cohort study. We used a time-weighted average model to estimate individual PM exposure, which used indoor PM2.5 and outdoor PM2.5 concentrations by atmospheric measurement network based on residential addresses. Clinical characteristics and urine samples were collected from participants during the second trimester of pregnancy. Urine metabolites were quantitatively measured using gas chromatography-mass spectrometry following multistep chemical derivatization. Statistical analyses were conducted using SPSS version 21 and MetaboAnalyst 5.0. Small for gestational age and gestational diabetes (GDM) were significantly increased in the high PM2.5 group, respectively (P = 0.042, and 0.022). Fifteen metabolites showed significant differences between the two groups (P < 0.05). Subsequent pathway enrichment revealed that four pathways, including pentose and glucuronate interconversion with three pentose sugars (ribose, arabinose, and xylose; P < 0.05). The concentration of ribose increased preterm births (PTB) and GDM (P = 0.044 and 0.049, respectively), and the arabinose concentration showed a tendency to increase in PTB (P = 0.044). Therefore, we identified urinary pentose metabolites as biomarkers of PM2.5 and confirmed the possibility of their relationship with pregnancy complications.

Maternal PM2.5 exposure is associated with preterm birth and gestational diabetes mellitus, and mitochondrial OXPHOS dysfunction in cord blood.

Maternal exposure to fine particulate matter (PM2.5) is associated with adverse pregnancy and neonatal health outcomes. To explore the mechanism, we performed mRNA sequencing of neonatal cord blood. From an ongoing prospective cohort, Air Pollution on Pregnancy Outcome (APPO) study, 454 pregnant women from six centers between January 2021 and June 2022 were recruited. Individual PM2.5 exposure was calculated using a time-weighted average model. In the APPO study, age-matched cord blood samples from the High PM2.5 (˃15 ug/m3; n = 10) and Low PM2.5 (≤ 15 ug/m3; n = 30) groups were randomly selected for mRNA sequencing. After selecting genes with differential expression in the two groups (p-value < 0.05 and log2 fold change > 1.5), pathway enrichment analysis was performed, and the mitochondrial pathway was analyzed using MitoCarta3.0. The risk of preterm birth (PTB) increased with every 5 µg/m3 increase of PM2.5 in the second trimester (odds ratio 1.391, p = 0.019) after adjusting for confounding variables. The risk of gestational diabetes mellitus (GDM) increased in the second (odds ratio 1.238, p = 0.041) and third trimester (odds ratio 1.290, p = 0.029), and entire pregnancy (odds ratio 1.295, p = 0.029). The mRNA-sequencing of cord blood showed that genes related to mitochondrial activity (FAM210B, KRT1, FOXO4, TRIM58, and FBXO7) and PTB-related genes (ADIPOR1, YBX1, OPTN, NFkB1, HBG2) were upregulated in the High PM2.5 group. In addition, exposure to high PM2.5 affected mitochondrial oxidative phosphorylation (OXPHOS) and proteins in the electron transport chain, a subunit of OXPHOS. These results suggest that exposure to high PM2.5 during pregnancy may increase the risk of PTB and GDM, and dysregulate PTB-related genes. Alterations in mitochondrial OXPHOS by high PM2.5 exposure may occur not only in preterm infants but also in normal newborns. Further studies with larger sample sizes are required.

Effect of Particulate Matter 2.5 on Fetal Growth in Male and Preterm Infants through Oxidative Stress.

Particulate matter 2.5 (PM2.5) levels are associated with adverse pregnancy outcomes. In this retrospective cohort study, we examined whether the concentration of indoor PM2.5 affected pregnancy outcomes. Additionally, we evaluated biomarkers of pregnancy-related complications caused by fine dust. We collected clinical information and data based on residential addresses from the Air Korea database to assess PM2.5 exposure levels. As a multicenter prospective cohort study, we measured the indoor PM2.5 concentration and inflammatory and oxidative stress markers. The PM2.5 concentration of the low-birth-weight (LBW) delivery group was 27.21 µg/m3, which was significantly higher than that of the normal-birth-weight (NBW) group (26.23 µg/m3) (p = 0.02). When the newborns were divided by sex, the PM2.5 concentration of the LBW group was 27.89 µg/m3 in male infants, which was significantly higher than that of the NBW group (26.26 µg/m3) (p = 0.01). In the prospective study, 8-hydroxy-2-deoxyguanosine significantly increased in the high-concentration group (113.55 ng/mL, compared with 92.20 ng/mL in the low-concentration group); in the high-concentration group, the rates of preterm birth (PTB) and small size for gestational age significantly increased (p < 0.01, p = 0.01). This study showed an association between PM2.5, oxidative stress, and fetal growth, with the PTB group being more vulnerable.

Personal exposure of PM2.5 and metabolic syndrome markers of pregnant women in South Korea: APPO study.

We examined the association between exposure to PM2.5, focused on individual exposure level, and metabolic dysfunction during pregnancy. APPO study (Air Pollution on Pregnancy Outcome) was a prospective, multicenter, observational cohort study conducted from January 2021 to March 2023. Individual PM2.5 concentrations were calculated using a time-weighted average model. Metabolic dysfunction during pregnancy was assessed based on a modified definition of metabolic syndrome and its components, accounting for pregnancy-specific criteria. Exposure to PM2.5 during pregnancy was associated with worsened metabolic parameters especially glucose metabolism. In comparison to participants exposed to the low PM2.5 group, those exposed to high PM2.5 levels exhibited increased odds of gestational diabetes mellitus (GDM) after adjusting for confounding variables in different adjusted models. Specifically, in model 1, the adjusted odds ratio (aOR) was 3.117 with a 95% confidence interval (CI) of 1.234-7.870; in model 2, the aOR was 3.855 with a 95% CI of 1.255-11.844; in model 3, the aOR was 3.404 with a 95% CI of 1.206-9.607; and in model 4, the aOR was 2.741 with a 95% CI of 0.712-10.547. Exposure to higher levels of PM2.5 during pregnancy was associated with a tendency to worsen metabolic dysfunction markers specifically in glucose homeostasis. Further research is needed to investigate the mechanisms underlying the effects of ambient PM2.5 on metabolic dysfunction during pregnancy.

Decidual lymphatic endothelial cell-derived granulocyte-macrophage colony-stimulating factor induces M1 macrophage polarization via the NF-κB pathway in severe pre-eclampsia.

PROBLEM: Direct interactions between macrophages and lymphatic vessels have been shown previously. In pre-eclampsia (PE), macrophages are dominantly polarized into a proinflammatory M1 phenotype and lymphangiogenesis is defective in the decidua. Here, we investigated whether decidual lymphatic endothelial cells (dLECs) affect macrophage polarization in PE. METHOD OF STUDY: THP-1 macrophages were cocultured with dLECs or cultured in the conditioned medium (CM) of dLECs. Macrophage polarization was measured using flow cytometry. Granulocyte-macrophage colony-stimulating factor (GM-CSF) expression in dLECs was measured using qRT-PCR and ELISA. The activation of nuclear translocation of nuclear factor-κ (NF-κB), an upstream signaling molecule of GM-CSF, was assessed by immunocytochemical localization of p65. Through GM-CSF knockdown and NF-κB inhibition in dLEC, we evaluated whether the GM-CSF/NF-κB pathway of PE dLEC affects decidual macrophage polarization. RESULTS: The ratio of inflammatory M1 macrophages with HLA-DR+ /CD80+ markers significantly increased following coculturing with PE dLECs or culturing in PE dLEC CM, indicating that the PE dLEC-derived soluble factor acts in a paracrine manner. GM-CSF expression was significantly upregulated in PE dLECs. Recombinant human GM-CSF induced macrophage polarization toward an M1-like phenotype, whereas its knockdown in PE dLECs suppressed it, suggesting PE dLECs induce M1 macrophage polarization by secreting GM-CSF. The NF-κB p65 significantly increased in PE dLECs compared to the control, and pretreatment with an NF-κB inhibitor significantly suppressed GM-CSF production from PE dLECs. CONCLUSIONS: In PE, dLECs expressing high levels of GM-CSF via the NF-κB-dependent pathway play a role in inducing decidual M1 macrophage polarization.

Differential Expression of NME4 in Trophoblast Stem-Like Cells and Peripheral Blood Mononuclear Cells of Normal Pregnancy and Preeclampsia.

BACKGROUND: Preeclampsia (PE) is known to arise from insufficient trophoblast invasion as uterine spiral arteries lack remodeling. A significant reduction in placental perfusion induces an ischemic placental microenvironment due to reduced oxygen delivery to the placenta and fetus, leading to oxidative stress. Mitochondria are involved in the regulation of cellular metabolism and the production of reactive oxygen species (ROS). NME/NM23 nuceloside diphosphate kinase 4 (NME4) gene is known to have the ability to supply nucleotide triphosphate and deoxynucleotide triphosphate for replication and transcription of mitochondria. Our study aimed to investigate changes in NME4 expression in PE using trophoblast stem-like cells (TSLCs) from induced pluripotent stem cells (iPSCs) as a model of early pregnancy and peripheral blood mononuclear cells (PBMNCs) as a model of late preterm pregnancy. METHODS: Transcriptome analysis using TSLCs was performed to identify the candidate gene associated with the possible pathophysiology of PE. Then, the expression of NME4 associated with mitochondrial function, p53 associated with cell death, and thioredoxin (TRX) linked to ROS were investigated through qRT-PCR, western blotting and deoxynucleotidyl transferase (TdT)-mediated deoxyuridine triphosphate (dUTP) nick end labelling (TUNEL) assay. RESULTS: In patients with PE, NME4 was significantly downregulated in TSLCs but upregulated in PBMNCs. p53 was shown to be upregulated in TSLCs and PBMNCs of PE. In addition, western blot analysis confirmed that TRX expression had the tendency to increase in TSLCs of PE. Similarly, TUNEL analysis confirmed that the dead cells were higher in PE than in normal pregnancy. CONCLUSION: Our study showed that the expression of the NME4 differed between models of early and late preterm pregnancy of PE, and suggests that this expression pattern may be a potential biomarker for early diagnosis of PE.

Migrated Pancreaticojejunal Stent Forming a Stent-Stone Complex in the Jejunum with Resultant Small Bowel Obstruction: A Case Report.

Transanastomotic pancreatic duct stent placement during reconstruction following pancreaticoduodenectomy is widely performed to prevent postoperative pancreatic fistulas and duct stenosis. However, stent-related complications, such as stent occlusion and migration, may occur. Here, we report a rare case of a migrated pancreatic duct plastic stent. After pylorus-preserving pancreaticoduodenectomy, the stent migrated to the jejunum and served as a nidus of the stent-stone complex, which developed jejunal obstruction. The stent-stone complex was removed by explorative laparotomy.

The introduction to air pollution on pregnancy outcome (APPO) study: a multicenter cohort study.

OBJECTIVE: The air pollution on pregnancy outcome (APPO) study is a prospective hospital-based cohort study designed to investigate the maternal and fetal effects of a particulate matter with an aerodynamic below 10 µm (PM10) and PM2.5 (below 2.5 µm) exposure. This study aims to analyze a relationship between particulate matter and adverse pregnancy outcomes and to find related biomarkers and develop management guidelines. METHODS: About 1,200 pregnant women are recruited for 3 years (from January 2021 to December 2023) from seven university hospitals to investigate the effects of particulate matter on pregnancy complications and adverse pregnancy outcomes. We collect biological samples by 5 mL of maternal venous blood and 15 mL of urine in each trimester of pregnancy, and 5 mL of umbilical cord blood and 2×2×2 cm of placental tissue are collected after delivery. In addition, by applying PM10 and PM2.5 concentration values and time-activity patterns from the time weighted average model, the individual predicted exposure of air pollution for the pregnant women are obtained. RESULTS: The average exposure of PM10 and PM2.5 of the participants in the entire period of pregnancy, was exceeded the World Health Organization air quality guidelines (an annual level, PM10 >15 µg/m3, PM2.5 >5 µg/m3). Moreover, it was revealed that the PM concentration was increasing toward the 3rd trimester of pregnancy. CONCLUSION: The APPO study will be able to identify the degree of exposure to air pollution in pregnant women and use it as basic data for estimating individual exposure to particulate matter. And the results of the APPO study will facilitate in the development of health management for pregnant women against air pollution.

Comparative gene expression analysis of stemness between periodontal ligament and umbilical cord tissues in humans.

Background/purpose: Due to their regenerative potential, periodontal ligament (PDL) and umbilical cord (UBC) tissues are an attractive potential mesenchymal stem cells (MSCs) source. This study compared the expression patterns of genes related to stemness between fresh PDL and UBC tissues. Materials and methods: PDL tissues were collected from 38 permanent premolars extracted for orthodontic purposes, and UBC tissues were obtained from three newborns. Each sample was immediately frozen to prevent RNA degradation. cDNA microarray analysis, quantitative real-time polymerase chain reaction (PCR), and immunohistochemical staining were performed. Gene expression patterns associated with dental stemness (DS) and induced pluripotent stemness (iPS) were compared between PDL and UBC tissues. Results: In the cDNA microarray analyses, the expressions of most iPS genes were greater in the PDL than in the UBC. Meanwhile, the expressions of most DS genes were greater in the UBC than in the PDL. Quantitative real-time PCR analyses showed that the expression levels of matrix metallopeptidase 13 (MMP13), ADAM metallopeptidase domain 22 (ADAM22), vascular cell adhesion protein 1 (VCAM1), and kruppel-like factor 4 (KLF4) genes were greater in the PDL than in the UBC, while the expressions of melanoma cell adhesion molecule (MCAM) and activated leukocyte cell adhesion molecule (ALCAM) were greater in the UBC than in the PDL. Conclusion: These results suggest that UBC and PDL tissues showed slightly different expression patterns of genes related to stemness, which warrants further investigation to use these tissues for future regeneration and implantation therapies.

Predicting preterm birth through vaginal microbiota, cervical length, and WBC using a machine learning model.

An association between the vaginal microbiome and preterm birth has been reported. However, in practice, it is difficult to predict premature birth using the microbiome because the vaginal microbial community varies highly among samples depending on the individual, and the prediction rate is very low. The purpose of this study was to select markers that improve predictive power through machine learning among various vaginal microbiota and develop a prediction algorithm with better predictive power that combines clinical information. As a multicenter case-control study with 150 Korean pregnant women with 54 preterm delivery group and 96 full-term delivery group, cervicovaginal fluid was collected from pregnant women during mid-pregnancy. Their demographic profiles (age, BMI, education level, and PTB history), white blood cell count, and cervical length were recorded, and the microbiome profiles of the cervicovaginal fluid were analyzed. The subjects were randomly divided into a training (n = 101) and a test set (n = 49) in a two-to-one ratio. When training ML models using selected markers, five-fold cross-validation was performed on the training set. A univariate analysis was performed to select markers using seven statistical tests, including the Wilcoxon rank-sum test. Using the selected markers, including Lactobacillus spp., Gardnerella vaginalis, Ureaplasma parvum, Atopobium vaginae, Prevotella timonensis, and Peptoniphilus grossensis, machine learning models (logistic regression, random forest, extreme gradient boosting, support vector machine, and GUIDE) were used to build prediction models. The test area under the curve of the logistic regression model was 0.72 when it was trained with the 17 selected markers. When analyzed by combining white blood cell count and cervical length with the seven vaginal microbiome markers, the random forest model showed the highest test area under the curve of 0.84. The GUIDE, the single tree model, provided a more reasonable biological interpretation, using the 10 selected markers (A. vaginae, G. vaginalis, Lactobacillus crispatus, Lactobacillus fornicalis, Lactobacillus gasseri, Lactobacillus iners, Lactobacillus jensenii, Peptoniphilus grossensis, P. timonensis, and U. parvum), and the covariates produced a tree with a test area under the curve of 0.77. It was confirmed that the association with preterm birth increased when P. timonensis and U. parvum increased (AUC = 0.77), which could also be explained by the fact that as the number of Peptoniphilus lacrimalis increased, the association with preterm birth was high (AUC = 0.77). Our study demonstrates that several candidate bacteria could be used as potential predictors for preterm birth, and that the predictive rate can be increased through a machine learning model employing a combination of cervical length and white blood cell count information.

Ureaplasma and Prevotella colonization with Lactobacillus abundance during pregnancy facilitates term birth.

Ureaplasma and Prevotella infections are well-known bacteria associated with preterm birth. However, with the development of metagenome sequencing techniques, it has been found that not all Ureaplasma and Prevotella colonizations cause preterm birth. The purpose of this study was to determine the association between Ureaplasma and Prevotella colonization with the induction of preterm birth even in the presence of Lactobacillus. In this matched case-control study, a total of 203 pregnant Korean women were selected and their cervicovaginal fluid samples were collected during mid-pregnancy. The microbiome profiles of the cervicovaginal fluid were analyzed using 16S rRNA gene amplification. Sequencing data were processed using QIIME1.9.1. Statistical analyses were performed using R software, and microbiome analysis was performed using the MicrobiomeAnalyst and Calypso software. A positive correlation between Ureaplasma and other genera was highly related to preterm birth, but interestingly, there was a negative correlation with Lactobacillus and term birth, with the same pattern observed with Prevotella. Ureaplasma and Prevotella colonization with Lactobacillus abundance during pregnancy facilitates term birth, although Ureaplasma and Prevotella are associated with preterm birth. Balanced colonization between Lactobacillus and Ureaplasma and Prevotella is important to prevent preterm birth.

Energy-efficient recovery of fermented butyric acid using octyl acetate extraction.

BACKGROUND: A butyric acid recovery process using octyl acetate is proposed, and the design details of the extraction and subsequent distillation processes were investigated. Ternary equilibrium data for the extractor design were derived from molecular simulations and experimental measurements. RESULTS: A new procedure for estimating the thermodynamic parameters was introduced to determine the effect of the parameters on extractor design by comparison with previously reported parameters. Using the proposed recovery process with the newly estimated thermodynamic model, 99.8% butyric acid was recovered from the fermentation broth at a recovery rate of 99%. The energy demand for the proposed process was found to be lower than the average demand for several reported butyric acid recovery processes. CONCLUSIONS: The investment cost is projected to be lower than that of other butyric acid processes due to the high efficiency of extraction solvent. The recovery cost of butyric acid was comparable to its selling price.

The risk for future cerebrovascular disease in pregnant women with Moyamoya disease: a nationwide population-based study in South Korea.

BACKGROUND: Physiologic changes during pregnancy affect the development of postpartum cerebrovascular disease (CVD) in women with Moyamoya disease. Due to the rare prevalence of Moyamoya disease and its large regional variations, large-scale based studies on the risk of CVD after delivery have not been conducted. This study aimed to evaluate whether women with Moyamoya disease have an increased risk of CVD after delivery. METHODS: Research data was collected from the National Health Insurance Claims Database of the Health Insurance Review and Assessment Service. Patients who delivered in Korea from 2007 to 2014 were enrolled in this study. We classified women as having CVD if they were diagnosed with any of the following conditions between delivery and December 31, 2016; cerebral infarction (I63.X in the International Classification of Diseases-10th Revision [ICD-10]) and/or intracranial hemorrhage (I61.X, I62.X in ICD-10) and/or subarachnoid hemorrhage (I60.X in ICD-10). Women with Moyamoya disease were identified as having I67.5 in ICD-10. We matched the study cohort by the ratio of 1:10 to analyze the risk CVD occurrence. The matching technique applied in this study was based on the variables of age and parity. To evaluate the adjusted hazard ratio (HR) for CVD in women with Moyamoya disease, we used multivariate Cox proportional hazard regression. RESULTS: Among a total of 3,611,216 Korean women who underwent delivered, we identified 412 women with Moyamoya disease diagnosis and 1420 age- and parity-matched women without Moyamoya disease (control). Compared to the control group, women with Moyamoya disease had a significantly higher rate of Cesarean section, overt DM, and essential hypertension (all p < 0.0001). Among women with Moyamoya disease, 55 (13.35%) women developed CVD within the follow-up postpartum period. The presence of Moyamoya disease was associated with an increased risk of CVD after delivery (adjusted HR 37.42; 95% confidence interval (CI) 17.50-80.02 within 2.3 years) after adjusting for pregnancy-induced hypertension, gestational diabetes mellitus, pregestational diabetes, chronic hypertension. CONCLUSION: This population based study showed that the occurrence rate of CVD after delivery was higher in women with Moyamoya disease than in those without. Therefore, careful and long-term postpartum surveillance is required for women with Moyamoya disease.

Identification of a novel gene signature in second-trimester amniotic fluid for the prediction of preterm birth.

Preterm birth affects approximately 5% to 7% of live births worldwide and is the leading cause of neonatal morbidity and mortality. Amniotic fluid supernatant (AFS) contains abundant cell-free nucleic acids (cfNAs) that can provide genetic information associated with pregnancy complications. In the current study, cfNAs of AFS in the early second-trimester before the onset of symptoms of preterm birth were analyzed, and we compared gene expression levels between spontaneous preterm birth (n = 5) and term birth (n = 5) groups using sequencing analysis. Differential expression analyses detected 24 genes with increased and 6 genes with decreased expression in the preterm birth group compared to term birth. Upregulated expressions of RDH14, ZNF572, VOPP1, SERPINA12, and TCF15 were validated in an extended AFS sample by quantitative PCR (preterm birth group, n = 21; term birth group, n = 40). Five candidate genes displayed a significant increase in mRNA expression in immortalized trophoblast HTR-8/SVneo cell with H2O2 treatment. Moreover, the expression of five candidate genes was increased to more than twofold by pretreatment with lipopolysaccharide in HTR-8/SVneo cells. Changes in gene expression between preterm birth and term birth is strongly correlated with oxidative stress and infection during pregnancy. Specific expression patterns of genes could be used as potential markers for the early identification of women at risk of having a spontaneous preterm birth.

Reproductive, Obstetric and Neonatal Outcomes in Women with Congenital Uterine Anomalies: A Systematic Review and Meta-Analysis.

Congenital uterine anomalies (CUA) may influence reproductive performance, resulting in adverse pregnancy associated complications. This study aimed to assess the association of CUA subtypes with reproductive, obstetric, and perinatal outcomes. We performed a systematic search of the MEDLINE, EMBASE, and Cochrane libraries for studies comparing pregnancy outcomes between women with CUA and those with a normal uterus. The random effects model was used to estimate the odds ratios (ORs) with a 95% confidence interval (CI). Women with CUA had a lower rate of live births (OR 0.47; 95% CI 0.33-0.69), and a higher rate of first trimester miscarriage (OR, 1.79; 95% CI 1.34-2.4), second trimester miscarriage (OR 2.92; 95% CI 1.35-6.32), preterm birth (OR 2.98; 95% CI 2.43-3.65), malpresentation (OR 9.1; 95% CI 5.88-14.08), cesarean section (OR 2.87; 95% CI 1.56-5.26), and placental abruption (OR 3.12; 95% CI 1.58-6.18). Women with canalization defects appear to have the poorest reproductive performance during early pregnancy. However, unification defects were associated with obstetric and neonatal outcomes throughout the course of pregnancy. It may be beneficial for clinicians to advise on potential complications that may be increased depending on the type and severity of CUA.

QoS-Based Service-Time Scheduling in the IoT-Edge Cloud.

In edge computing, scheduling heterogeneous workloads with diverse resource requirements is challenging. Besides limited resources, the servers may be overwhelmed with computational tasks, resulting in lengthy task queues and congestion occasioned by unusual network traffic patterns. Additionally, Internet of Things (IoT)/Edge applications have different characteristics coupled with performance requirements, which become determinants if most edge applications can both satisfy deadlines and each user's QoS requirements. This study aims to address these restrictions by proposing a mechanism that improves the cluster resource utilization and Quality of Service (QoS) in an edge cloud cluster in terms of service time. Containerization can provide a way to improve the performance of the IoT-Edge cloud by factoring in task dependencies and heterogeneous application resource demands. In this paper, we propose STaSA, a service time aware scheduler for the edge environment. The algorithm automatically assigns requests onto different processing nodes and then schedules their execution under real-time constraints, thus minimizing the number of QoS violations. The effectiveness of our scheduling model is demonstrated through implementation on KubeEdge, a container orchestration platform based on Kubernetes. Experimental results show significantly fewer violations in QoS during scheduling and improved performance compared to the state of the art.

Ultrasonographic evaluation of ovarian mass for predicting malignancy in pregnant women.

OBJECTIVE: The purpose of this study is to compare ultrasonographic ovarian mass scoring systems in pregnant women. STUDY DESIGN: This multicenter study included women with an ovarian mass during pregnancy who were evaluated using ultrasound and underwent surgery in 11 referral hospitals. The ovarian mass was evaluated and scored using three different scoring systems(International Ovarian Tumor Analysis Assessment of Different NEoplasias in the adnexa[IOTA ADNEX], Sassone, and Lerner). The final diagnosis was made histopathologically. Receiver operating characteristic(ROC) curves were generated for each scoring system. RESULTS: During the study period, 236 pregnant women underwent surgery for an ovarian mass, including 223 women(94.5%) with a benign ovarian mass and 13 women(5.5%) with a malignant ovarian mass. Among 10 ultrasound image findings, six findings were different between benign and ovarian masses(maximal diameter of mass, maximal diameter of solid mass, wall thickness of mass, inner wall structure, thickness of septations, and papillarity). In all three scoring systems, the ovarian mass scores were significantly higher in malignant masses than in benign masses, with the highest area under the ROC curve(AUROC) in the Sassone scoring system(AUROC: 0.831 for Sassone, 0.710 for Lerner vs 0.709 for IOTA ADNEX; p < 0.05, between the Sassone and Lerner/ IOTA ADNEX). A combined model was developed with the six different ultrasound findings, and the AUROC of the combined model was 0.883(p = not significant between the combined model and Sassone). CONCLUSION: In pregnant women, malignant ovarian tumors can be predicted with high accuracy using either the Sassone scoring system or the combined model.

Prediction of preterm birth based on machine learning using bacterial risk score in cervicovaginal fluid.

PROBLEM: Preterm birth (PTB) is a major cause of increased morbidity and mortality in newborns. The main cause of spontaneous PTB (sPTB) is the activation of an inflammatory response as a result of ascending genital tract infection. Despite various studies on the effects of the vaginal microbiome on PTB, a practical method for its clinical application has yet to be developed. METHOD OF STUDY: In this case-control study, 94 Korean pregnant women with PTB (n = 38) and term birth (TB; n = 56) were enrolled. Their cervicovaginal fluid (CVF) was sampled, and a total of 10 bacteria were analyzed using multiplex quantitative real-time PCR (qPCR). The PTB and TB groups were compared, and a PTB prediction model was created using bacterial risk scores using machine learning techniques (decision tree and support vector machine). The predictive performance of the model was validated using random subsampling. RESULTS: Bacterial risk scoring model showed significant differences (P < 0.001). The PTB risk was low when the Lactobacillus iners ratio was 0.812 or more. In groups with a ratio under 0.812, moderate and high risk was classified as a U. parvum ratio of 4.6 × 10-3 . The sensitivity and specificity of the PTB prediction model using bacteria risk score were 71% and 59%, respectively, and 77% and 67%, respectively, when white blood cell (WBC) data were included. CONCLUSION: Using machine learning, the bacterial risk score in CVF can be used to predict PTB.