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OBJECTIVE: To assess prenatal ultrasonographic findings and postnatal outcomes in fetuses with intracranial hemorrhage (ICH). METHODS: This retrospective study included fetuses prenatally diagnosed with ICH between December 2012 and August 2023. Maternal characteristics, prenatal ultrasonographic findings, and postnatal outcomes were reviewed. RESULTS: Twenty-seven fetuses with ICH were reviewed. Intracranial hemorrhage was classified as grade 3 and 4 in 24 fetuses. Twenty-two fetuses had ICH, four had ICH with subdural hemorrhage, and one had ICH with subarachnoid hemorrhage. Ventriculomegaly was the most common ultrasonographic finding, and was observed in 22 of the 27 (81.5%) fetuses. Seven fetuses were lost to follow-up, and four intrauterine fetal deaths occurred. The remaining 16 fetuses were delivered at a median gestational age of 35+2 weeks. The infants were followed-up for 40.1 months (range, 4-88). Nine of the 16 infants underwent ventriculoperitoneal placement. One infant underwent brain surgery for severe epilepsy. Motor impairment, including cerebral palsy, was observed in 13 infants (81.2%). Neurologic impairment occurred in six infants (37.5%), developmental delay in nine (56.2%), and epilepsy in 11 (68.7%). CONCLUSION: Fetal ICH is a rare complication diagnosed during pregnancy, which results in subsequent fetal neurological sequelae or death. This study demonstrated that the common ultrasonographic findings in fetal ICH were progressive ventriculomegaly and increased periventricular echogenicity. Fetuses diagnosed with prenatal ICH, especially those affected by higher-grade ICH, may be at an increased risk of long-term neurodevelopmental problems.
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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.
Subject(s)
Air Pollutants , Air Pollution , Diabetes, Gestational , Pregnancy Complications , Premature Birth , Pregnancy , Infant, Newborn , Female , Humans , Pregnancy Outcome , Particulate Matter/adverse effects , Particulate Matter/analysis , Air Pollutants/adverse effects , Air Pollutants/analysis , Prospective Studies , Premature Birth/epidemiology , Premature Birth/etiology , Air Pollution/adverse effects , Air Pollution/analysis , Republic of Korea/epidemiology , ChinaABSTRACT
In the original publication [...].
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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.
Subject(s)
Air Pollutants , Air Pollution , Diabetes, Gestational , Premature Birth , Infant, Newborn , Female , Pregnancy , Humans , Particulate Matter/analysis , Maternal Exposure/adverse effects , Air Pollutants/analysis , Cohort Studies , Case-Control Studies , Arabinose/analysis , Ribose/analysis , Air Pollution/adverse effectsABSTRACT
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 (Ë15 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.
Subject(s)
Air Pollutants , Air Pollution , Diabetes, Gestational , Premature Birth , Pregnancy , Infant, Newborn , Female , Humans , Maternal Exposure , Air Pollutants/analysis , Fetal Blood/chemistry , Prospective Studies , Oxidative Phosphorylation , Infant, Premature , Particulate Matter/analysis , Air Pollution/analysis , RNA, MessengerABSTRACT
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.
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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.
Subject(s)
Air Pollutants , Air Pollution , Metabolic Syndrome , Pregnancy , Humans , Female , Air Pollutants/analysis , Pregnant Women , Particulate Matter/analysis , Prospective Studies , Metabolic Syndrome/epidemiology , Air Pollution/analysis , Pregnancy Outcome , Republic of Korea/epidemiologyABSTRACT
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.
Subject(s)
NF-kappa B , Pre-Eclampsia , Pregnancy , Female , Humans , NF-kappa B/metabolism , Granulocyte-Macrophage Colony-Stimulating Factor/metabolism , Pre-Eclampsia/metabolism , Endothelial Cells/metabolism , Macrophages/metabolism , Macrophage Colony-Stimulating FactorABSTRACT
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.
Subject(s)
Pre-Eclampsia , Trophoblasts , Infant, Newborn , Pregnancy , Humans , Female , Trophoblasts/metabolism , Placenta/metabolism , Tumor Suppressor Protein p53/metabolism , Reactive Oxygen Species/metabolism , Leukocytes, Mononuclear/metabolism , Nucleoside Diphosphate Kinase D/metabolismABSTRACT
Zinc-ion batteries (ZIBs) have drawn much attention for next-generation energy storage for smart and wearable electronics due to their high theoretical gravimetric/volumetric energy capacities, safety from explosive hazards, and cost-effectiveness. However, current state-of-the-art ZIBs lack the energy capacity necessary to facilitate smart functionalities for intelligent electronics. In this work, a "π-bridge spacer"-embedded electron donor-acceptor polymer cathode combined with a Zn2+ -ion-conducting electrolyte is proposed for a smart and flexible ZIB to provide high electrochromic-electrochemical performances. The π-bridge spacer endows the polymeric skeleton with improved physical ion accessibility and sensitive charge transfer through the cycles, providing extremely stable cyclability with high specific capacity (110 mAh g-1 ) at very fast rates (8 A g-1 ) and large coloration efficiency (79.8 cm2 C-1 ) under severe mechanical deformation over a long period. These results are markedly outstanding compared to the topological analogue without the π-bridge spacer (80 mAh g-1 at current density of 8 A g-1 , 63.0 cm2 C-1 ). The design to incorporate a π-bridge spacer realizes notable electrochromism behaviors and high electrochemical performance, which sheds light on the rational development of multifunctional flexible-ZIBs with color visualization properties for widespread usage in powering smart electronics.
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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.
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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.
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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.
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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.
Subject(s)
Premature Birth , Ureaplasma Infections , Case-Control Studies , Female , Humans , Infant, Newborn , Lactobacillus/genetics , Pregnancy , Premature Birth/microbiology , Prevotella/genetics , RNA, Ribosomal, 16S/genetics , Term Birth , Ureaplasma/genetics , Vagina/microbiologyABSTRACT
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.
Subject(s)
Cerebrovascular Disorders , Moyamoya Disease , Cerebrovascular Disorders/epidemiology , Cesarean Section , Female , Humans , Male , Moyamoya Disease/complications , Moyamoya Disease/epidemiology , Pregnancy , Pregnant Women , Republic of Korea/epidemiology , Risk FactorsABSTRACT
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.
Subject(s)
Premature Birth , Serpins , Amniotic Fluid/metabolism , Female , Humans , Hydrogen Peroxide/metabolism , Infant, Newborn , Pregnancy , Pregnancy Trimester, Second , Premature Birth/etiology , Serpins/metabolism , Term Birth , Transcription Factors/metabolismABSTRACT
Content store (CS) is one of the main components of information-centric networking (ICN), which enables content objects to be cached and retrieved from any intermediate node in the network. However, in existing ICN designs, CS information is not exploited to coordinate content caching and content retrieval. CS of nodes in the network operates independently while Interest packets forwarding mainly uses forwarding information base (FIB). This paper highlights the importance of CS information for efficient content caching and content retrieval to improve the performance of information-centric networking, especially in resource-constrained environments like the Internet of Things. We propose an efficient caching policy to coordinate the CS of a node with its neighbor nodes in a distributed manner so that more and more popular content objects are cached in the neighborhood of the node. To exploit and coordinate CS information among nodes, we urge to enable CS information in the data plane of the network and design an efficient way for CS information transmission. Each node contributes to the objective of its neighborhood by maximizing its number of unique popular content objects being cached in its CS and not cached in the CS of its neighbors. We implement the proposed policy on top of state-of-the-art popularity-based caching schemes. Through analysis and experiments, we show that the proposed caching policy achieves a significant improvement in terms of cache hit ratio, stretch ratio, content retrieval latency, and energy efficiency significantly compared to state-of-the-art schemes.
Subject(s)
Policy , Physical PhenomenaABSTRACT
Existing information-centric networking (ICN) designs for Internet of Things (IoT) mostly make caching decisions based on probability or content popularity. From the energy-efficient perspective, those strategies may not always be energy efficient in resource-constrained IoT because without considering the energy reward of caching decisions, inappropriate routers and content objects may be selected for caching, which may lead to negative energy rewards. In this paper, we analyze the energy consumption of content caching and content retrieval in resource-constrained IoT and calculate caching energy reward as a key metric to measure the energy efficiency of a caching decision. We then propose an efficient cache placement and cache replacement mechanism based on the caching energy reward to improve the energy efficiency of caching decisions. Through analysis and experimental results, we show that the proposed mechanism achieves a significant improvement in terms of energy efficiency, stretch ratio, and cache hit ratio compared to state-of-the-art caching schemes.
Subject(s)
Internet of Things , Physical Phenomena , RewardABSTRACT
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.
ABSTRACT
One of the main advantages of information-centric networking (ICN) is that a requested piece of content can be retrieved from a content store (CS) at any intermediate node, instead of its original content producer. In existing ICN designs, nodes forward Interest packets mainly based on forwarding information base (FIB). FIB is constructed from name prefixes registered by content producers with a list of next hops to the name prefixes. The ICN forwarding engine uses those information to forward Interest packets towards corresponding content producers. CS information of a node is currently used only for checking the availability of cached content objects at the node and is not considered in the data plane of existing ICN forwarding mechanisms. This paper highlights the importance of CS information in an ICN forwarding mechanism and enables neighbor CS information in the data plane to improve the cache hit ratio and forwarding efficiency, especially for resource-constraint Internet of Things (IoT). We propose an efficient CS-based forwarding scheme for IoT. The proposed forwarding scheme exploits CS information of neighbors to find efficient routes to forward Interest packets toward nearby nodes with corresponding cached content. For that, we carefully design an efficient way for CS information sharing using counting bloom filter. We implement the proposed scheme and compare with state-of-the-art ICN forwarding schemes in IoT. Experimental results indicate that the proposed forwarding scheme achieves a significant improvement in terms of cache hit ratio, energy efficiency, content retrieval latency, and response rate.