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BACKGROUND: Perioperative stroke is a severe complication following surgery. To identify patients at risk for perioperative stroke, several prediction models based on the preoperative factors were suggested. Prediction models often focus on preoperative patient characteristics to assess stroke risk. However, most existing models primarily base their predictions on the patient's baseline characteristics before surgery. We aimed to develop a machine-learning model incorporating both pre- and intraoperative variables to predict perioperative stroke. METHODS AND RESULTS: This study included patients who underwent noncardiac surgery at 2 hospitals with the data of 15 752 patients from Seoul National University Hospital used for development and temporal internal validation, and the data of 449 patients from Boramae Medical Center used for external validation. Perioperative stroke was defined as a newly developed ischemic lesion on diffusion-weighted imaging within 30 days of surgery. We developed a prediction model composed of pre- and intraoperative factors (integrated model) and compared it with a model consisting of preoperative features alone (preoperative model). Perioperative stroke developed in 109 (0.69%) patients in the Seoul National University Hospital group and 11 patients (2.45%) in the Boramae Medical Center group. The integrated model demonstrated superior predictive performance with area under the curve values of 0.824 (95% CI, 0.762-0.880) versus 0.584 (95% CI, 0.499-0.667; P<0.001) in the internal validation; and 0.716 (95% CI, 0.560-0.859) versus 0.505 (95% CI, 0.343-0.654; P=0.018) in the external validation, compared to the preoperative model. CONCLUSIONS: We suggest that incorporating intraoperative factors into perioperative stroke prediction models can improve their accuracy.
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Introduction: Although the safety and effectiveness of COVID-19 vaccination during pregnancy have been proven, there is still little data explaining neonatal outcomes of maternal pre-pregnancy vaccination. Methods: Here, we investigated the impact of vaccination and SARS-CoV-2 infection on maternal-neonate immune response in a cohort study involving 141 pregnant individuals, and defined the importance of maternal COVID-19 vaccination timing for its effectiveness. Results and discussion: Our data indicate that vertically transferred maternal hybrid immunity provides significantly better antiviral protection for a neonate than either maternal post-infection or post-vaccination immunity alone. Higher neutralization potency among mothers immunized before pregnancy and their newborns highlights the promising role of pre-pregnancy vaccination in neonatal protection. A comparison of neutralizing antibody titers calculated for each dyad suggests that infection and pre-/during-pregnancy vaccination all support transplacental transfer, providing the offspring with strong passive immunity against SARS-CoV-2. Analysis of neutralizing antibody levels in maternal sera collected during pregnancy and later during delivery shows that immunization may exert a positive effect on maternal protection.
Subject(s)
Antibodies, Neutralizing , Antibodies, Viral , COVID-19 Vaccines , COVID-19 , Immunity, Maternally-Acquired , Pregnancy Complications, Infectious , SARS-CoV-2 , Vaccination , Humans , Female , Pregnancy , COVID-19/prevention & control , COVID-19/immunology , COVID-19 Vaccines/immunology , COVID-19 Vaccines/administration & dosage , Infant, Newborn , SARS-CoV-2/immunology , Antibodies, Neutralizing/blood , Antibodies, Neutralizing/immunology , Antibodies, Viral/blood , Antibodies, Viral/immunology , Vaccination/methods , Adult , Cohort Studies , Pregnancy Complications, Infectious/prevention & control , Pregnancy Complications, Infectious/immunologyABSTRACT
This study investigates the applicability of six transition metal dichalcogenides to efficient therapeutic drug monitoring of ten antiepileptic drugs using laser desorption/ionization-mass spectrometry. We found that molybdenum ditelluride and tungsten ditelluride are suitable for the sensitive quantification of therapeutic drugs. The contribution of tellurium to the enhanced efficiency of laser desorption ionization was validated through theoretical calculations utilizing an integrated model that incorporates transition-metal dichalcogenides and antiepileptic drugs. The results of our theoretical calculations suggest that the relatively low surface electron density for the tellurium-containing transition metal dichalcogenides induces stronger Coulombic interactions, which results in enhanced laser desorption and ionization efficiency. To demonstrate applicability, up to 120 patient samples were analyzed to determine drug concentrations, and the results were compared with those of immunoassay and liquid chromatography-tandem mass spectrometry. Agreements among these methods were statistically evaluated using the Passing-Bablok regression and Bland-Altman analysis. Furthermore, our method has been shown to be applicable to the simultaneous detection and multiplexed quantification of antiepileptic drugs.
Subject(s)
Anticonvulsants , Drug Monitoring , Drug Monitoring/methods , Humans , Anticonvulsants/chemistry , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods , Chalcogens/chemistryABSTRACT
BACKGROUND: Intraoperative hypotension can lead to postoperative organ dysfunction. Previous studies primarily used invasive arterial pressure as the key biosignal for the detection of hypotension. However, these studies had limitations in incorporating different biosignal modalities and utilizing the periodic nature of biosignals. To address these limitations, we utilized frequency-domain information, which provides key insights that time-domain analysis cannot provide, as revealed by recent advances in deep learning. With the frequency-domain information, we propose a deep-learning approach that integrates multiple biosignal modalities. METHODS: We used the discrete Fourier transform technique, to extract frequency information from biosignal data, which we then combined with the original time-domain data as input for our deep learning model. To improve the interpretability of our results, we incorporated recent interpretable modules for deep-learning models into our analysis. RESULTS: We constructed 75,994 segments from the data of 3,226 patients to predict hypotension during surgery. Our proposed frequency-domain deep-learning model outperformed conventional approaches that rely solely on time-domain information. Notably, our model achieved a greater increase in AUROC performance than the time-domain deep learning models when trained on non-invasive biosignal data only (AUROC 0.898 [95% CI: 0.885-0.91] vs. 0.853 [95% CI: 0.839-0.867]). Further analysis revealed that the 1.5-3.0 Hz frequency band played an important role in predicting hypotension events. CONCLUSION: Utilizing the frequency domain not only demonstrated high performance on invasive data but also showed significant performance improvement when applied to non-invasive data alone. Our proposed framework offers clinicians a novel perspective for predicting intraoperative hypotension.
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This study aimed to assess the current status of gestational diabetes mellitus (GDM) diagnosis and management, and the demand for a digital healthcare system, in order to develop an optimal digital-based management model for GDM. An anonymous online survey was conducted targeting pregnant/postpartum women (Group W), internal medicine physicians (Group P), and obstetricians (group O) from September 6, 2022 to December 31, 2022. The survey assessed the women's knowledge of GDM and gathered information about healthcare professionals' (HCPs) current GDM management practices. All groups were asked about their acceptance of and demands for a digital healthcare system for GDM. Statistical comparisons between groups were conducted using the chi-square test or Fisher's exact test where appropriate. A total of 168 participants were in Group W, 185 in Group P, and 256 in Group O. Participants from all groups recognized the need for a digital healthcare system for GDM (Group W: 95.8%, Group P: 85.9%, Group O: 60%). However, HCPs showed less willingness to integrate these systems into their clinics than pregnant/postpartum women. Essential features identified were recording blood glucose levels and insulin, along with automatic data linkage from self-monitoring devices. Group W showed a higher preference for lab test access, search functionality, and fetal weight assessment than groups P and O (all P < .0001), while Groups P and O had a greater preference for recording insulin and maternal body weight compared to Group W (P = .0141 and .0023, respectively). Both pregnant/postpartum women and HCPs acknowledged the benefits of utilizing a digital healthcare system for managing GDM. However, there were differences in perspectives among these groups.
Subject(s)
Diabetes, Gestational , Humans , Diabetes, Gestational/therapy , Female , Pregnancy , Cross-Sectional Studies , Adult , Surveys and Questionnaires , Health Personnel , TelemedicineABSTRACT
Recently, various fundamental properties of GaPS4 such as anisotropy and strain-induced properties have been reported, but the impacts of the stacking sequence in layered materials remain ambiguous. This ambiguity is evident in the inconsistent Raman scattering data reported for GaPS4, suggesting a significant influence of stacking order on its physical properties. To demonstrate the discrepancies, this study investigates the vibrational characteristics of 2D GaPS4 under different stacking sequences using both experimental observations and theoretical models (AA and AB sequences) through density functional theory calculations. The results of our theoretical calculations revealed that the identical stacking sequence structure significantly influences the vibrational configurations of GaPS4, which results in divergent configurations of Raman scattering spectra including unidentified Raman peaks. Our study addresses not only the clarification of the ambiguity of experimental observations but also qualitative criteria to evaluate the degree of each stacking sequence.
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The properties of transition metal dichalcogenides (TMDCs) are critically dependent on the dielectric constant of substrates, which significantly limits their application. To address this issue, we used a perfluorinated polyether (PFPE) self-assembled monolayer (SAM) with low surface energy to increase the van der Waals (vdW) gap between TMDCs and the substrate, thereby reducing the interaction between them. This resulted in a reduction in the subthreshold swing value, an increase in the photoluminescence intensity of excitons, and a decrease in the doping effect by the substrate. This work will provide a new way to control the TMDC/dielectric interface and contribute to expanding the applicability of TMDCs.
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Background & Aims: Adverse pregnancy outcomes (APOs) can worsen cardiometabolic risk factors in women, raising their likelihood of developing cardiometabolic diseases at a young age after their initial pregnancy. Nevertheless, there are limited data on the risk of newly developing metabolic dysfunction-associated steatotic liver disease (MASLD) in women who have had APOs. This study aimed to evaluate the risk of new-onset MASLD after experiencing APOs. Methods: Singleton pregnant women who underwent national health screenings 1 year before pregnancy and 1 year after delivery were included in this study. APOs were defined as the presence of at least one of the followings: hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), preterm birth, low birth weight, and placental abruption. The primary outcome was new-onset MASLD based on the presence of APOs. Results: Among 80,037 study participants, 9,320 (11.6%) experienced APOs during pregnancy. Women who experienced APOs had an increased risk of developing new-onset MASLD after delivery even after adjustments for various covariates (adjusted odds ratio [OR] 1.58, 95% CI 1.45-1.72). In particular, women who experienced either HDP or GDM showed a significantly increased risk of developing new-onset MASLD (adjusted OR 2.20, 95% CI 1.81-2.67, for HDP and adjusted OR 1.83, 95% CI 1.65-2.03, for GDM). Moreover, there was a tendency toward an increased risk of new-onset MASLD according to the number of APOs (p <0.001 for trend of odds). Conclusions: APOs were associated with the risk of new-onset MASLD after delivery. Specifically, only HDP or GDM were identified as risk factors for new-onset MASLD. Impact and implications: This nationwide cohort study confirms that postpartum women with a history of adverse pregnancy outcomes (APOs) are at an increased risk of developing metabolic dysfunction-associated steatotic liver disease (MASLD). These findings may bring us one step closer to understanding the exact mechanisms underlying such an important association between prior APOs and cardiovascular disease (CVD) risk among postpartum women. This bidirectional association between APOs and MASLD highlights the importance of considering pregnancy history in assessing CVD risk in women. It suggests a need for closer monitoring and lifestyle interventions for women with a history of APOs to reduce the risk of MASLD and subsequent CVD complications.
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Recent studies reported the long-term cardiovascular risk of preeclampsia. However, only a few studies have investigated the association between preeclampsia and long-term cardiovascular disease in Asian populations, although there could be racial/ethnic differences in the risk of cardiovascular diseases. Therefore, we aimed to evaluate the long-term effects of preeclampsia on cardiovascular disease in an Asian population. This study included 68,658 parous women in the Health Examinees Study (HEXA) cohort of South Korea and compared the risk of long-term cardiovascular disease, including ischemic heart disease and stroke, according to the history of preeclampsia. We also performed a meta-analysis combining current study data with data from existing literature in the Asian population. Among the study population, 3413 (5.23%) women had a history of preeclampsia, and 767 (1.12%) and 404 (0.59%) women developed ischemic heart disease and stroke for 22 years. Women with a history of preeclampsia were at a higher risk for both ischemic heart disease (adjusted hazard ratio 1.66 [1.19-2.04]) and stroke (adjusted hazard ratio 1.48 [1.02-2.16]) than those without. In the meta-analysis, the pooled hazard ratio of ischemic heart disease and stroke were also increased in women with a history of preeclampsia (ischemic heart disease 1.65 [1.51-1.82]; stroke 1.78 [1.52-2.10]).
Subject(s)
Cardiovascular Diseases , Myocardial Ischemia , Pre-Eclampsia , Stroke , Female , Humans , Pregnancy , Cardiovascular Diseases/epidemiology , Cohort Studies , Myocardial Ischemia/epidemiology , Pre-Eclampsia/epidemiology , Risk Factors , Stroke/epidemiologyABSTRACT
BACKGROUND: Ultrasonographic soft markers are normal variants, rather than fetal abnormalities, and guidelines recommend a detailed survey of fetal anatomy to determine the necessity of antenatal karyotyping. Anecdotal reports have described cases with ultrasonographic soft markers in which chromosomal microarray analysis (CMA) revealed pathogenic copy number variants (CNVs) despite normal results on conventional karyotyping, but CMA for ultrasonographic soft markers remains a matter of debate. In this systematic review, we evaluated the clinical significance of CMA for pregnancies with isolated ultrasonographic soft markers and a normal fetal karyotype. METHODS: An electronic search was conducted by an experienced librarian through the MEDLINE, Embase, and Cochrane CENTRAL databases. We reviewed 3,338 articles (3,325 identified by database searching and 13 by a hand search) about isolated ultrasonographic soft markers, and seven ultrasonographic markers (choroid plexus cysts, echogenic bowel, echogenic intracardiac focus, hypoplastic nasal bone, short femur [SF], single umbilical artery, and urinary tract dilatation) were included for this study. RESULTS: Seven eligible articles were included in the final review. Pathogenic or likely pathogenic CNVs were found in fetuses with isolated ultrasonographic soft markers and a normal karyotype. The overall prevalence of pathogenic or likely pathogenic CNVs was 2.0% (41 of 2,048). The diagnostic yield of CMA was highest in fetuses with isolated SF (9 of 225, 3.9%). CONCLUSION: CMA could aid in risk assessment and pregnancy counseling in pregnancies where the fetus has isolated ultrasonographic soft markers along with a normal karyotype.
Subject(s)
Fetus , Microarray Analysis , Ultrasonography, Prenatal , Female , Humans , Pregnancy , Fetus/diagnostic imaging , KaryotypingABSTRACT
Fetal growth restriction (FGR) is one of the leading causes of perinatal morbidity and mortality. Many studies have reported an association between FGR and fetal Doppler indices focusing on umbilical artery (UA), middle cerebral artery (MCA), and ductus venosus (DV). The uteroplacental-fetal circulation which affects the fetal growth consists of not only UA, MCA, and DV, but also umbilical vein (UV), placenta and uterus itself. Nevertheless, there is a paucity of large-scale cohort studies that have assessed the association between UV, uterine wall, and placental thickness with perinatal outcomes in FGR, in conjunction with all components of the uteroplacental-fetal circulation. Therefore, this multicenter study will evaluate the association among UV absolute flow, placental thickness, and uterine wall thickness and adverse perinatal outcome in FGR fetuses. This multicenter retrospective cohort study will include singleton pregnant women who undergo at least one routine fetal ultrasound scan during routine antepartum care. Pregnant women with fetuses having structural or chromosomal abnormalities will be excluded. The U-AID indices (UtA, UA, MCA, and UV flow, placental and uterine wall thickness, and estimated fetal body weight) will be measured during each trimester of pregnancy. The study population will be divided into two groups: (1) FGR group (pregnant women with FGR fetuses) and (2) control group (those with normal growth fetus). We will assess the association between U-AID indices and adverse perinatal outcomes in the FGR group and the difference in U-AID indices between the two groups.
Subject(s)
Fetus , Placenta , Female , Humans , Pregnancy , Biometry , Cohort Studies , Fetal Development , Fetal Growth Retardation/diagnostic imaging , Fetal Growth Retardation/epidemiology , Fetus/diagnostic imaging , Fetus/blood supply , Gestational Age , Multicenter Studies as Topic , Placenta/diagnostic imaging , Retrospective Studies , Ultrasonography, Doppler , Ultrasonography, Prenatal/methods , Umbilical Arteries/diagnostic imagingABSTRACT
OBJECTIVE: Adenomyosis impacts pregnancy outcomes, although there is a lack of consensus regarding the actual effects. It is likely, however, that the severity of adenomyosis or ultrasound findings or timing of diagnosis can have different effects on adverse pregnancy outcomes (APOs). METHODS: In this study, we aimed to investigate the impact of the timing of adenomyosis diagnosis on pregnancy outcomes. Singleton pregnant women who delivered between 2017 and 2022 were analyzed based on the timing of adenomyosis diagnosis, using a national database. The final cohort was classified into three groups: 1) group 1, without adenomyosis; 2) group 2, those diagnosed with adenomyosis before pregnancy; and 3) group 3, those diagnosed with adenomyosis during pregnancy. RESULTS: A total of 1,226,475 cases were ultimately included in this study. Women with a diagnosis of adenomyosis had a significantly higher risk of APOs including hypertensive disorder during pregnancy (HDP), gestational diabetes mellitus (GDM), postpartum hemorrhage, placental abruption, preterm birth, and delivery of a small-for-gestational-age infant even after adjusting for covariates. In particular, concerning HDP, the risk was highest in group 3 (group 2: adjusted odds ratio [aOR], 1.15 vs. group 3: aOR, 1.36). However, the highest GDM risk was in group 2 (GDM; group 2: aOR, 1.24 vs. group 3: aOR, 1.04). CONCLUSION: The increased risk of APO differed depending on the timing of adenomyosis diagnosis. Therefore, efforts for more careful monitoring and prevention of APOs may be necessary when such women become pregnant.
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Expression quantitative trait loci (eQTL) analysis measures the contribution of genetic variation in gene expression on complex traits. Although this methodology has been used to examine gene regulation in numerous human tissues, eQTL research in solid tissues is relatively lacking. We conducted eQTL analysis on placentas collected from an East Asian population in an effort to identify gene regulatory mechanisms in this tissue. Placentas (n = 102) were collected at the time of cesarean delivery. mRNA was extracted, sequenced with NGS, and compared with matched maternal and fetal DNA arrays performed using maternal and neonatal cord blood. Linear regression modeling was performed using tensorQTL. Fine-mapping along with epigenomic annotation was used to select putative functional variants. We identified 2,703 coding genes that contained at least one eQTL with statistical significance (false discovery rate <0.05). After fine-mapping, we found 108 previously unreported eQTL variants with posterior inclusion probability >0.1. Of these, 19% were located in genomic regions with evidence from public placental epigenome suggesting that they may be functionally relevant. For example, variant rs28379289 located in the placenta-specific regulatory region changes the binding affinity of transcription factor leading to higher expression of LGALS3, which is known to affect placental function. This study expands the knowledge base of regulatory elements within the human placenta and identifies 108 previously unreported placenta eQTL signals, which are listed in our publicly available GMI eQTL database. Further studies are needed to identify and characterize genetic regulatory mechanisms that affect placental function in normal pregnancy and placenta-related diseases.
Subject(s)
East Asian People , Quantitative Trait Loci , Female , Humans , Infant, Newborn , Pregnancy , Genome-Wide Association Study , Placenta , Polymorphism, Single Nucleotide/genetics , Quantitative Trait Loci/geneticsABSTRACT
OBJECTIVE: To evaluate the risk of metabolic syndrome (MS) after recurrent pregnancy loss (RPL) using UK Biobank data. A history of pregnancy loss is associated with the development of cardiovascular diseases in the future. However, the association between RPL and subsequent MS is poorly understood. Therefore, we aimed to check the risk of MS after RPL. DESIGN: The study population was divided into 2 groups according to reproductive history: women with a history of RPL and women without a history of RPL. Recurrent pregnancy loss was defined as 2 or more spontaneous miscarriages, and MS was defined as at least 3 of the following: abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol levels, high-blood pressure, and hyperglycemia. SETTING: UK Biobank resource. PATIENTS: The UK Biobank is a prospective cohort study that enrolled individuals aged between 40 and 69 years whose medical and reproductive histories were retrieved at enrollment. In this cohort, only women with a history of at least one pregnancy were selected. INTERVENTIONS: Recurrent pregnancy loss. MAIN OUTCOME MEASURES: The primary outcome was the prevalence of MS. The secondary outcomes were 5 diagnostic components of MS. RESULTS: We analyzed 228,674 women, including 15,702 with a history of RPL and 212,972 without a history of RPL. Women with a history of RPL have a higher prevalence of MS between the ages of 40 and 60 years (33.0% vs. 31.5%). After adjusting for covariates (age, race, number of live births, early menopause, smoking, alcohol consumption, and physical activity), the increased risk of MS after RPL remained significant (adjusted odds ratio, 1.10; 95% confidence interval, 1.06-1.15). Furthermore, in the analysis of the 5 diagnostic components of MS, a history of RPL significantly increased the risk of abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol levels, and hyperglycemia. CONCLUSION: Middle-aged women with a history of RPL have an increased risk of MS.
Subject(s)
Abortion, Habitual , Hyperglycemia , Hypertriglyceridemia , Metabolic Syndrome , Pregnancy , Middle Aged , Humans , Female , Adult , Aged , Cohort Studies , Metabolic Syndrome/diagnosis , Metabolic Syndrome/epidemiology , Prospective Studies , Biological Specimen Banks , Obesity, Abdominal/complications , Abortion, Habitual/diagnosis , Abortion, Habitual/epidemiology , Abortion, Habitual/etiology , Hyperglycemia/complications , Hypertriglyceridemia/complications , Lipoproteins, HDL , United Kingdom/epidemiologyABSTRACT
BACKGROUND: Peripartum cardiomyopathy, one of the most fatal conditions during delivery, results in heart failure secondary to left ventricular systolic dysfunction. Left ventricular dysfunction can result in abnormalities in electrocardiography. However, the usefulness of electrocardiography in the identification of peripartum cardiomyopathy in pregnant women remains unclear. OBJECTIVE: This study aimed to evaluate the effectiveness of a 12-lead electrocardiography-based artificial intelligence/machine learning-based software as a medical device for screening peripartum cardiomyopathy. STUDY DESIGN: This retrospective cohort study included pregnant women who underwent transthoracic echocardiography between a month before and 5 months after delivery and underwent 12-lead electrocardiography within 30 days of echocardiography between December 2011 and May 2022 at Seoul National University Hospital. The performance of 12-lead electrocardiography-based artificial intelligence/machine learning analysis (AiTiALVSD software; version 1.00.00, which was developed to screen for left ventricular systolic dysfunction in the general population) was evaluated for the identification of peripartum cardiomyopathy. In addition, the performance of another artificial intelligence/machine learning algorithm using only 1-lead electrocardiography to detect left ventricular systolic dysfunction was evaluated in identifying peripartum cardiomyopathy. The results were obtained under a 95% confidence interval and considered significant when P<.05. RESULTS: Among the 14,557 women who delivered during the study period, 204 (1.4%) underwent transthoracic echocardiography a month before and 5 months after delivery. Among them, 12 (5.8%) were diagnosed with peripartum cardiomyopathy. The results showed that AiTiALVSD for 12-lead electrocardiography was highly effective in detecting peripartum cardiomyopathy, with an area under the receiver operating characteristic of 0.979 (95% confidence interval, 0.953-1.000), an area under the precision-recall curve of 0.715 (95% confidence interval, 0.499-0.951), a sensitivity of 0.917 (95% confidence interval, 0.760-1.000), a specificity of 0.927 (95% confidence interval, 0.890-0.964), a positive predictive value of 0.440 (95% confidence interval, 0.245-0.635), and a negative predictive value of 0.994 (95% confidence interval, 0.983-1.000). In addition, a 1-lead (lead I) artificial intelligence/machine learning algorithm showed excellent performance; the area under the receiver operating characteristic, area under the precision-recall curve, sensitivity, specificity, positive predictive value, and negative predictive value were 0.944 (95% confidence interval, 0.895-0.993), 0.520 (95% confidence interval, 0.319-0.801), 0.833 (95% confidence interval, 0.622-1.000), 0.880 (95% confidence interval, 0.834-0.926), 0.303 (95% confidence interval, 0.146-0.460), and 0.988 (95% confidence interval, 0.972-1.000), respectively. CONCLUSION: The 12-lead electrocardiography-based artificial intelligence/machine learning-based software as a medical device (AiTiALVSD) and 1-lead algorithm are noninvasive and effective ways of identifying cardiomyopathies occurring during the peripartum period, and they could potentially be used as highly sensitive screening tools for peripartum cardiomyopathy.
Subject(s)
Cardiomyopathies , Deep Learning , Ventricular Dysfunction, Left , Humans , Female , Pregnancy , Ventricular Function, Left , Stroke Volume , Retrospective Studies , Artificial Intelligence , Peripartum Period , Electrocardiography , Cardiomyopathies/diagnosis , Cardiomyopathies/etiology , Ventricular Dysfunction, Left/diagnosis , Ventricular Dysfunction, Left/epidemiologyABSTRACT
BACKGROUND: The purpose of this study was to evaluate the effect of vanishing twin (VT) on maternal serum marker concentrations and nuchal translucency (NT). METHODS: This is a secondary analysis of a multicenter prospective cohort study in 12 institutions. Serum concentrations of pregnancy-associated plasma protein-A in the first trimester and alpha-fetoprotein (AFP), total human chorionic gonadotrophin, unconjugated estriol, and inhibin A in the second trimester were measured, and NT was measured between 10 and 14 weeks of gestation. RESULTS: Among 6,793 pregnant women, 5,381 women were measured for serum markers in the first or second trimester, including 65 cases in the VT group and 5,316 cases in the normal singleton group. The cases in the VT group had a higher median multiple of the median value of AFP and inhibin A than the normal singleton group. The values of other serum markers and NT were not different between the two groups. After the permutation test with adjustment, AFP and inhibin A remained significant differences. The frequency of abnormally increased AFP was also higher in the VT group than in the normal singleton group. CONCLUSION: VT can be considered as an adjustment factor for risk assessment in the second-trimester serum screening test.
Subject(s)
Nuchal Translucency Measurement , alpha-Fetoproteins , Pregnancy , Humans , Female , Pregnancy Trimester, Second , Prospective Studies , FamilyABSTRACT
Tryptophan hydroxylase 1 (TPH1) has emerged as a target for the treatment of metabolic diseases including obesity and fatty liver disease. A series of xanthine derivatives were synthesized and evaluated for their TPH1 inhibition. Among the synthesized compounds, compound 40 showed good in vitro activity and liver microsomal stability. Docking studies revealed that compound 40 showed better binding to TPH1 via key intermolecular interactions involving the xanthine scaffold, imidazo-thiazolyl ring, and hydroxyl-containing phenacyl moiety. In addition, compound 40 effectively suppressed the adipocyte differentiation of 3 T3-L1 cells.
Subject(s)
Alkaloids , Non-alcoholic Fatty Liver Disease , Humans , Diuretics , Non-alcoholic Fatty Liver Disease/drug therapy , Obesity/drug therapy , Tryptophan Hydroxylase/antagonists & inhibitors , Xanthines/chemistry , Xanthines/pharmacologyABSTRACT
BACKGROUND: Computational drug repurposing is crucial for identifying candidate therapeutic medications to address the urgent need for developing treatments for newly emerging infectious diseases. The recent COVID-19 pandemic has taught us the importance of rapidly discovering candidate drugs and providing them to medical and pharmaceutical experts for further investigation. Network-based approaches can provide repurposable drugs quickly by leveraging comprehensive relationships among biological components. However, in a case of newly emerging disease, applying a repurposing methods with only pre-existing knowledge networks may prove inadequate due to the insufficiency of information flow caused by the novel nature of the disease. METHODS: We proposed a network-based complementary linkage method for drug repurposing to solve the lack of incoming new disease-specific information in knowledge networks. We simulate our method under the controlled repurposing scenario that we faced in the early stage of the COVID-19 pandemic. First, the disease-gene-drug multi-layered network was constructed as the backbone network by fusing comprehensive knowledge database. Then, complementary information for COVID-19, containing data on 18 comorbid diseases and 17 relevant proteins, was collected from publications or preprint servers as of May 2020. We estimated connections between the novel COVID-19 node and the backbone network to construct a complemented network. Network-based drug scoring for COVID-19 was performed by applying graph-based semi-supervised learning, and the resulting scores were used to validate prioritized drugs for population-scale electronic health records-based medication analyses. RESULTS: The backbone networks consisted of 591 diseases, 26,681 proteins, and 2,173 drug nodes based on pre-pandemic knowledge. After incorporating the 35 entities comprised of complemented information into the backbone network, drug scoring screened top 30 potential repurposable drugs for COVID-19. The prioritized drugs were subsequently analyzed in electronic health records obtained from patients in the Penn Medicine COVID-19 Registry as of October 2021 and 8 of these were found to be statistically associated with a COVID-19 phenotype. CONCLUSION: We found that 8 of the 30 drugs identified by graph-based scoring on complemented networks as potential candidates for COVID-19 repurposing were additionally supported by real-world patient data in follow-up analyses. These results show that our network-based complementary linkage method and drug scoring algorithm are promising strategies for identifying candidate repurposable drugs when new emerging disease outbreaks.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Pandemics , Algorithms , Proteins , Drug Repositioning/methodsABSTRACT
OBJECTIVES: The aim of this study was to determine the risk of congenital malformations in offspring born to women with systemic lupus erythematosus (SLE). METHODS: This nationwide population-based study included Korean women who had a singleton pregnancy. The risk of congenital malformations in women with SLE was compared with those without SLE. Multivariable analyses were performed to estimate the OR of congenital malformations. In a sensitivity analysis, the risk of malformation was compared between the offspring of women with SLE and those of propensity-matched women without SLE. RESULTS: Of a total of 3 279 204 pregnant women, 0.1% had SLE and their offspring had a higher frequency of congenital malformations (17.13% vs 11.99%, p<0.0001). After adjustment for age, parity, hypertension, diabetes, and fetal sex, the SLE group was found to be associated with an increased risk of congenital malformations in the nervous system (adjusted OR (aOR, 1.90; 95% CI, 1.20 to 3.03), eye, ear, face, and neck (aOR, 1.37; 95% CI, 1.09 to 1.71), circulatory system (aOR, 1.91; 95% CI, 1.67 to 2.20), and musculoskeletal system (aOR, 1.26; 95% CI, 1.05 to 1.52). Even after propensity matching, some of the tendencies were maintained. CONCLUSIONS: This nationwide population-based study in South Korea indicates that compared with the general population, neonates born to SLE mothers have a slightly increased risk of congenital malformations affecting the nervous system, head and neck, cardiovascular system, and musculoskeletal system. When a woman with lupus becomes pregnant, careful fetal ultrasound and newborn screening can be helpful in identifying the risk of potential malformations.
Subject(s)
Lupus Erythematosus, Systemic , Pregnancy Complications , Infant, Newborn , Humans , Pregnancy , Female , Pregnancy Complications/epidemiology , Lupus Erythematosus, Systemic/complications , Lupus Erythematosus, Systemic/epidemiology , Lupus Erythematosus, Systemic/diagnosis , Republic of Korea/epidemiologyABSTRACT
BACKGROUND: In twin pregnancies complicated by selective fetal growth restriction (sFGR), if the smaller twin is in the state of impending intra-uterine death (IUD), immediate delivery will reduce the risk of IUD of the smaller twin while exposing the larger twin to iatrogenic preterm birth (PTB). Therefore, the management options would either be to maintain pregnancy for the maturation of the larger twin despite the risk of IUD of the smaller twin or immediate delivery to prevent IUD of the smaller twin. However, the optimal gestational age of management transition from maintaining pregnancy to immediate delivery has not been established. The objective of this study was to evaluate the physician's perspective on the optimal timing of immediate delivery in twin pregnancies complicated by sFGR. METHODS: An online cross-sectional survey was performed with obstetricians and gynecologists (OBGYN) in South Korea. The questionnaire asked the following: (1) whether participants would maintain or immediately deliver a twin pregnancy complicated by sFGR with signs of impending IUD of the smaller twin; (2) the optimal gestational age of management transition from maintaining pregnancy to immediate delivery in a twin pregnancy with impending IUD of the smaller twin; and (3) the limit of viability and intact survival in general preterm neonates. RESULTS: A total of 156 OBGYN answered the questionnaires. In a clinical scenario of dichorionic (DC) twin pregnancy complicated by sFGR with signs of impending IUD of the smaller twin, 57.1% of the participants answered that they would immediately deliver the twin pregnancy. However, 90.4% answered that they would immediately deliver the pregnancy in the same scenario for monochorionic (MC) twin pregnancy. The participants designated 30 weeks for DC twin and 28 weeks for MC twin pregnancies as the optimal gestational age of management transition from maintaining pregnancy to immediate delivery. The participants regarded 24 weeks as the limit of viability and 30 weeks as the limit of intact survival in general preterm neonates. The optimal gestational age of management transition for DC twin pregnancy was correlated with the limit of intact survival in general preterm neonates (p < 0.001), but not with the limit of viability. However, the optimal gestational age of management transition for MC twin pregnancy was associated with both the limit of intact survival (p = 0.012) and viability with marginal significance (p = 0.062). CONCLUSIONS: Participants preferred to immediately deliver twin pregnancies complicated by sFGR with impending IUD of the smaller twin at the limit of intact survival (30 weeks) for DC twin pregnancies and at the midway between the limit of intact survival and viability (28 weeks) for MC twin pregnancies. More research is needed to establish guidelines regarding the optimal delivery timing for twin pregnancies complicated by sFGR.