Early prenatal screening with an ultrasound (US) can significantly lower newborn mortality caused by congenital heart diseases (CHDs). However, the need for expertise in fetal cardiologists and the high volume of screening cases limit the practically achievable detection rates. Hence, automated prenatal screening to support clinicians is desirable. This paper presents and analyses potential deep learning (DL) techniques to diagnose CHDs in fetal USs. Four convolutional neural network architectures were compared to select the best classifier with satisfactory results. Hence, dense convolutional network (DenseNet) 201 architecture was selected for the classification of seven CHDs, such as ventricular septal defect, atrial septal defect, atrioventricular septal defect, Ebstein’s anomaly, tetralogy of Fallot, transposition of great arteries, hypoplastic left heart syndrome, and a normal control. The sensitivity, specificity, and accuracy of the DenseNet201 model were 100%, 100%, and 100%, respectively, for the intra-patient scenario and 99%, 97%, and 98%, respectively, for the inter-patient scenario. We used the intra-patient DL prediction model to validate our proposed model against the prediction results of three expert fetal cardiologists. The proposed model produces a satisfactory result, which means that our model can support expert fetal cardiologists to interpret the decision to improve CHD diagnostics. This work represents a step toward the goal of assisting front-line sonographers with CHD diagnoses at the population level.

Placental soluble fms-like tyrosine kinase-1 (sFlt-1) which is an antagonist of vascular endothelial growth factor and placental growth factor (PIGF), is considered as one of etiology factors cause endothelial damage in preeclampsia due to increase of sFlt-1 level that change vascular endothelial integrity. This study aims to analyze the difference of sFlt-1 and PlGF concentration in severe preeclampsia and normal pregnancy, and the correlation between both in occurrence of severe preeclampsia. This is case control study involving 18 subjects with severe preeclampsia and 19 subjects with normal pregnancy as controls who met inclusion and exclusion criteria. Concentration of sFlt-1 and PlGF are measured with ELISA. Statistical analysis is performed with Chi square test, Fisher’s exact test, T test, Mann–Whitney test, and Spearman’s rank correlation test. This study results in no significant difference in characteristics of gestational age, and parity in both study groups. Median concentration of sFlt-1 in severe preeclampsia is higher (20,524.75 pg/mL) compared with normal pregnancy (6820.4 pg/mL). Concentration of PlGF is lower in severe preeclampsia (47 pg/mL) compared with normal pregnancy (337 pg/mL). sFlt-1 concentration is higher in severe preeclampsia compared to normal pregnancy. PlGF concentration is lower in severe preeclampsia compared to normal pregnancy. Ratio of sFlt-1 and PlGF concentration is significantly correlated in both severe preeclampsia and normal pregnancy. There is a significant negative correlation between the concentration of sFLt-1 and PlGF in normal pregnancy.

Background: Low birth weight (LBW) is a risk factor associated with endometriosis. Our study aimed to analyze the risk of endometriosis in women with a LBW history and the relationships of progesterone receptor B (PR-B) gene promoter methylation, DNA methyltransferase-1 (DNMT1) expression, PR-B expression, and vascular endothelial growth factors (VEGF) with endometriosis. Methods: This study was conducted in two stages, a retrospective case-control design and a cross-sectional design, with 52 cases of endometriosis and 30 controls, which were further subdivided into LBW and non-LBW groups, at Hasan Sadikin General Hospital and its hospital networks from October 2017 to August 2021. Menstrual blood was taken from subjects and analyzed using pyrosequencing techniques to assess DNA methylation, while q-RT PCR was used to assess gene expression. Results: There were significant differences in PR-B methylation, DNMT1 expression, PR-B expression, and VEGF expression (p < 0.001) between the case and control groups. There was a significant negative correlation between PR-B methylation and PR-B expression (r = −0.558; p = 0.047). Based on a multiple logistic analysis, the most dominant factor affecting endometriosis incidence is PR-B (OR 10.40, 95% CI 3.24–33.4, R² = 45.8). We found that patients with a low birth weight history had a 1.41-times-higher risk of developing endometriosis (95% CI 0.57–3.49, p = 0.113), although the relationship was not statistically significant. Conclusion: Endometriosis is associated with PR-B gene promoter hypermethylation, decreased PR-B expression, and increased DNMT1 and VEGF expression. The methylation of PR-B is the most dominant factor affecting endometriosis incidence.

Background and Objectives: Preeclampsia has been linked to an inflammatory response that may be brought on by endothelial cell dysfunction. This paper investigates the pathomechanism of syncytiotrophoblast basement membrane (STBM) damage and Placental Protein 13 (PP13) release, which may have a role in systemic endothelial dysfunction in preeclampsia. Materials and Methods: This comparative cross-sectional study involves 54 preeclampsia patients (27 early-onset preeclampsia and 27 late-onset preeclampsia) and 27 pregnant women with normal blood pressure. An enzyme-linked immunosorbent assay was performed to evaluate maternal blood levels of PP13. Following birth, a portion of the placenta was collected for transmission electron microscope (TEM) and immunohistochemical (IHC) analysis. The data were analyzed using STATA version 15. Results: PP13 expression in the placental syncytiotrophoblast was significantly lower in the early-onset preeclampsia, compared to late-onset preeclampsia and normotensive pregnancy, group (p < 0.001). In contrast, serum PP13 levels were found to be the highest in the early-onset preeclampsia group, although no significant difference were found in mean maternal serum levels of PP13 between the three groups. The decreased PP13 expression in placental syncytiotrophoblast can be attributed to the greater extent of damage in the STBM in early-onset preeclampsia that leads to the release of a larger amount of PP13 into maternal circulation. The hypothesis aligns with the TEM analysis results. Preeclamptic pregnancies showed placental syncytiotrophoblast aponeurosis, whereas normotensive pregnancies did not. Placental lesions and STBM shedding were found to be more pronounced in early-onset preeclampsia compared to late-onset preeclampsia. Conclusions: PP13 and STBM damage may play a role in systemic endothelial dysfunction in preeclampsia.

Preeclampsia is a major cause of morbidity and mortality, both maternal and perinatal. The etiology and pathophysiology of preeclampsia remain unknown. Research shows the implantation of the placenta in preeclampsia occurs due to incomplete angiogenic imbalance as one of the preeclampsia pathogenesis. PlGF is angiogenic protein which is synthesized in placenta by mRNA PlGF. When damage occurs, mRNA will be released from cell and form cell-free mRNA. This study aims to analyze the differences between the PlGF mRNA expression in severe preeclampsia and normal pregnancy as well as to measure the relationship between cell-free mRNA and levels of PlGF with the incidence of severe preeclampsia. The method used in this study is an observational analytic study with cross-sectional design. Blood samples were obtained from patients with preeclampsia and normal pregnancies as the controlling factors in accordance with inclusion and exclusion criterias. Examination of the PlGF level was measured by ELISA method and mRNA PIGF expression was measured by RT-PCR. Physical and laboratory examinations of patients were recorded and collected as data. Calculations were done by statistical analysis. Mean of the cell-free mRNA PlGF expression level in severe preeclampsia is 2.2983 ng/mL within the scale of 1.96–2.83 ng/mL and deviation standard of 0.1897. Using Pearson Analysis Test, the result shows that there is a positive correlation between cell-free mRNA expression and PlGF protein level in severe preeclampsia, with r = 0.640 dan p < 0.004. There is no difference between expression of cell-free mRNA PlGF in severe preeclampsia serum and normal pregnancy. There is a significant correlation between expression of cell-free mRNA and PlGF protein level in severe preeclampsia.