Earlier detection of gestational diabetes impacts on medication requirements, neonatal and maternal outcomes.

AIM: Gestational diabetes (GD) is a global health concern with significant implications for maternal and neonatal outcomes. This study investigates the association between early GD (eGD) diagnosis (<24 weeks), pharmacotherapy requirements and adverse neonatal outcomes. MATERIALS AND METHODS: A cohort of 369 pregnant women underwent a 75-g oral glucose tolerance test. Maternal variables, pharmacotherapy prescriptions and neonatal outcomes were analysed employing t-tests, χ2 tests, and logistic regression. A p < .05 was considered significant. RESULTS: Early GD increased the odds of neonatal hypoglycaemia [odds ratio (OR): 18.57, p = .013] and respiratory distress syndrome (OR: 4.75, p = .034). Nutritional therapy prescription by an accredited nutritionist was the most common treatment in women diagnosed after 24 weeks, but those with eGD required more frequently specialized nutritional consulting + metformin to achieve glycaemic control (p = .027). eGD was associated with a higher requirement of nutritional therapy prescription + metformin (OR: 2.26, 95% confidence interval: 1.25-4.09, p = .007) and with maternal hyperglycaemia during the post-partum period at 2 h of the oral glucose tolerance test (OR: 1.03, 95% confidence interval: 1.02-1.13, p = .024). CONCLUSION: Timely diagnosis and personalized treatment of GD are desirable because an earlier presentation is related to a higher risk of adverse neonatal and maternal outcomes.

Optimizing perinatal wellbeing in pregnancy with obesity: a clinical trial with a multi-component nutrition intervention for prevention of gestational diabetes and infant growth and neurodevelopment impairment.

Pregnancy complicated by obesity represents an increased risk of unfavorable perinatal outcomes such as gestational diabetes mellitus (GDM), hypertensive disorders in pregnancy, preterm birth, and impaired fetal growth, among others. Obesity is associated with deficiencies of micronutrients, and pregnant women with obesity may have higher needs. The intrauterine environment in pregnancies complicated with obesity is characterized by inflammation and oxidative stress, where maternal nutrition and metabolic status have significant influence and are critical in maternal health and in fetal programming of health in the offspring later in life. Comprehensive lifestyle interventions, including intensive nutrition care, are associated with a lower risk of adverse perinatal outcomes. Routine supplementation during pregnancy includes folic acid and iron; other nutrient supplementation is recommended for high-risk women or women in low-middle income countries. This study is an open label randomized clinical trial of parallel groups (UMIN Clinical Trials Registry: UMIN000052753, https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000060194) to evaluate the effect of an intensive nutrition therapy and nutrient supplementation intervention (folic acid, iron, vitamin D, omega 3 fatty acids, myo-inositol and micronutrients) in pregnant women with obesity on the prevention of GDM, other perinatal outcomes, maternal and newborn nutritional status, and infant growth, adiposity, and neurodevelopment compared to usual care. Given the absence of established nutritional guidelines for managing obesity during pregnancy, there is a pressing need to develop and implement new nutritional programs to enhance perinatal outcomes.

Isolation of Primary Human Decidual Cells from the Fetal Membranes of Term Placentae.

The maternal decidua is a transient and dynamic tissue that functions as an immunoprivileged matrix related to nutritional and endocrine processes. The function of decidual cells is key to the success of embryo implantation and the maintenance of pregnancy with a positive maternal-fetal outcome. Therefore, establishing a method to optimize the isolation of primary decidual cells is essential. Our protocol described here provides a good yield of decidual cells in an optimized time.

Antepartum Fetal Surveillance and Optimal Timing of Delivery in Diabetic Women: A Narrative Review.

Antepartum fetal surveillance (AFS) is essential for pregnant women with diabetes to mitigate the risk of stillbirth. However, there is still no universal consensus on the optimal testing method, testing frequency, and delivery timing. This review aims to comprehensively analyze the evidence concerning AFS and the most advantageous timing for delivery in both gestational and pregestational diabetes mellitus cases. This review's methodology involved an extensive literature search encompassing international diabetes guidelines and scientific databases, including PubMed, MEDLINE, Google Scholar, and Scopus. The review process meticulously identified and utilized pertinent articles for analysis. Within the scope of this review, a thorough examination revealed five prominent international guidelines predominantly addressing gestational diabetes. These guidelines discuss the utility and timing of fetal well-being assessments and recommendations for optimal pregnancy resolution timing. However, the scarcity of clinical trials directly focused on this subject led to a reliance on observational studies as the basis for most recommendations. Glucose control, maternal comorbidities, and the medical management received are crucial in making decisions regarding AFS and determining the appropriate delivery timing.

AI-Enhanced Analysis Reveals Impact of Maternal Diabetes on Subcutaneous Fat Mass in Fetuses without Growth Alterations.

Pregnant women with diabetes often present impaired fetal growth, which is less common if maternal diabetes is well-controlled. However, developing strategies to estimate fetal body composition beyond fetal growth that could better predict metabolic complications later in life is essential. This study aimed to evaluate subcutaneous fat tissue (femur and humerus) in fetuses with normal growth among pregnant women with well-controlled diabetes using a reproducible 3D-ultrasound tool and offline TUI (Tomographic Ultrasound Imaging) analysis. Additionally, three artificial intelligence classifier models were trained and validated to assess the clinical utility of the fetal subcutaneous fat measurement. A significantly larger subcutaneous fat area was found in three-femur and two-humerus selected segments of fetuses from women with diabetes compared to the healthy pregnant control group. The full classifier model that includes subcutaneous fat measure, gestational age, fetal weight, fetal abdominal circumference, maternal body mass index, and fetal weight percentile as variables, showed the best performance, with a detection rate of 70%, considering a false positive rate of 10%, and a positive predictive value of 82%. These findings provide valuable insights into the impact of maternal diabetes on fetal subcutaneous fat tissue as a variable independent of fetal growth.

A Novel Predictive Machine Learning Model Integrating Cytokines in Cervical-Vaginal Mucus Increases the Prediction Rate for Preterm Birth.

Preterm birth (PB) is a leading cause of perinatal morbidity and mortality. PB prediction is performed by measuring cervical length, with a detection rate of around 70%. Although it is known that a cytokine-mediated inflammatory process is involved in the pathophysiology of PB, none screening method implemented in clinical practice includes cytokine levels as a predictor variable. Here, we quantified cytokines in cervical-vaginal mucus of pregnant women (18-23.6 weeks of gestation) with high or low risk for PB determined by cervical length, also collecting relevant obstetric information. IL-2, IL-6, IFN-γ, IL-4, and IL-10 were significantly higher in the high-risk group, while IL-1ra was lower. Two different models for PB prediction were created using the Random Forest machine-learning algorithm: a full model with 12 clinical variables and cytokine values and the adjusted model, including the most relevant variables-maternal age, IL-2, and cervical length- (detection rate 66 vs. 87%, false positive rate 12 vs. 3.33%, false negative rate 28 vs. 6.66%, and area under the curve 0.722 vs. 0.875, respectively). The adjusted model that incorporate cytokines showed a detection rate eight points higher than the gold standard calculator, which may allow us to identify the risk PB risk more accurately and implement strategies for preventive interventions.

Regulation of MMP-2 by IL-8 in Vascular Endothelial Cells: Probable Mechanism for Endothelial Dysfunction in Women with Preeclampsia.

Endothelial dysfunction (ED) in preeclampsia (PE) results from the convergence of oxidative stress, inflammation, and alterations in extracellular matrix components, affecting vascular tone and permeability. The molecular network leading to ED includes IL-8 and MMP-2. In vitro, IL-8 regulates the concentration and activity of MMP-2 in the trophoblast; this interaction has not been studied in endothelial cells during PE. We isolated human umbilical vein endothelial cells (HUVECs) from women with healthy pregnancies (NP, n = 15) and PE (n = 15). We quantified the intracellular concentration of nitric oxide and reactive oxygen species with colorimetric assays, IL-8 with ELISA, and MMP-2 with zymography and using an ELISA-type system. An IL-8 inhibition assay was used to study the influence of this cytokine on MMP-2 concentration and activity. HUVECs from women with PE showed significantly higher oxidative stress than NP. IL-8 and MMP-2 were found to be significantly elevated in PE HUVECs compared to NP. Inhibition of IL-8 in HUVECs from women with PE significantly decreased the concentration of MMP-2. We demonstrate that IL-8 is involved in the mechanisms of MMP-2 expression in HUVECs from women with PE. Our findings provide new insights into the molecular mechanisms regulating the ED distinctive of PE.

Impact of Protease Inhibitor-Based Highly Active Antiretroviral Therapy on Fetal Subcutaneous Fat Tissue in HIV-Pregnant Women in a Middle-Income Country.

BACKGROUND: HIV infection continues to be a global public health challenge, affecting approximately 1.7 million reproductive-aged women. Protease inhibitor-based highly active antiretroviral therapy (PI-HAART) has significantly reduced the risk of vertical transmission of HIV from mother to child. Nevertheless, concerns linger regarding the long-term effects, particularly on body composition, notably subcutaneous fat tissue (SFT). Although HIV-associated lipodystrophy syndrome (LS) has been well documented in adults and older children, its impact on fetuses exposed to PI-HAART remains underexplored. This study aims to evaluate SFT in the fetuses of HIV-pregnant women exposed to PI-HAART, assessing the potential clinical implications. METHODS: We conducted a comparative study between HIV-pregnant women receiving PI-HAART and an HIV-negative control group. Fetometry measurements were obtained via 3D ultrasound. SFT in the fetal arm and thigh segments was assessed. Data were analyzed using lineal multivariate regression and receiver-operating characteristics (ROC)-curve analysis. RESULTS: Fetuses exposed to PI-HAART exhibited a significant reduction in subcutaneous fat, particularly in the proximal third-middle union of the femur (coefficient: -2.588, p = 0.042). This reduction was correlated with lower newborn serum glucose levels (65.7 vs. 56.1, p = 0.007; coefficient: -1.277, p = 0.045). CONCLUSIONS: Our study sheds light on the connection between PI-HAART, fetal subcutaneous fat, and neonatal health. These findings might reveal the long-lasting effects of PI-HAART on newborns and children's well-being. Our results emphasize the need for a more balanced approach to managing pregnant women with HIV in developing countries and open new venues for research on the impact of intrauterine PI-HAART exposure on energy metabolism and fetal programming.

Association between 25-OH Vitamin D Deficiency and COVID-19 Severity in Pregnant Women.

Evidence from studies in the general population suggests an association between vitamin D insufficiency/deficiency and COVID-19 susceptibility and disease severity. The present study was performed on 165 third-trimester pregnant women at the time of delivery. Seventy-nine women tested negative for SARS-CoV-2. From 86 women testing positive, 32 were asymptomatic, 44 presented a mild form of the disease, and 10 experienced severe symptoms. Serum 25-OH vitamin D levels were measured on blood samples collected on admission. Low vitamin D levels were detected in symptomatic but not asymptomatic COVID-19 patients compared to healthy women (p = 0.0227). In addition, 20 (45.4%) pregnant women in the mild COVID-19 group and 6 (60%) in the severe group were vitamin D deficient (p = 0.030). On the other hand, lasso regression analysis showed that 25-OH vitamin D deficiency is an independent predictor of severe COVID-19 with an odds ratio (OR) of 5.81 (95% CI: 1.108-30.541; p = 0.037). These results show the relationship between vitamin D deficiency in pregnant women and the severity of COVID-19 infection and support the recommendation to supplement with vitamin D to avoid worse COVID-19 outcomes during pregnancy.

miR-21 differentially regulates IL-1ß and IL-10 expression in human decidual cells infected with streptococcus B.

Intrauterine infections caused by bacteria like group B streptococcus (GBS) and the subsequent activation of the maternal inflammatory response have been long suspected to be the underlying cause of preterm labor. The inflammatory network triggered by maternal decidua has been widely described and includes the secretion of pro- and anti-inflammatory cytokines as IL-1ß and IL-10; however, the mechanisms that regulate their secretion have not been completely elucidated. MicroRNAs (miRNAs) are critical modulators of the inflammatory response by regulating cytokine expression in several cell types. Here, we explored the role of miR-21 in the expression of IL-1ß and IL-10 in human decidual stromal cells (DSCs) exposed in vitro to GBS. We observed that IL1B and IL10 expression at the mRNA level was increased in DSCs after GBS infection. IL-10 but not IL-1ß secretion was detected in the culture supernatants. We found a higher miR-21 expression (22-fold) in infected DSCs as compared with non-infected cells. miR-21 functional analysis revealed that DSCs transfected with an antagomiR vs. miR-21 significantly increased the secretion of IL-1ß but decreased that of IL-10 in DSCs cells infected with GBS. Our results suggest that miR-21 participates in balancing the inflammatory response in infected decidua through at least IL-1ß and IL-10 regulation. This is the first study attributing a functional role of miR-21 in the regulation of key molecules involved in the inflammatory response in infected DSCs, providing new insights into the epigenetic control of human decidual inflammation.

Molecular Insights into the Thrombotic and Microvascular Injury in Placental Endothelium of Women with Mild or Severe COVID-19.

Clinical manifestations of coronavirus disease 2019 (COVID-19) in pregnant women are diverse, and little is known of the impact of the disease on placental physiology. Severe acute respiratory syndrome coronavirus (SARS-CoV-2) has been detected in the human placenta, and its binding receptor ACE2 is present in a variety of placental cells, including endothelium. Here, we analyze the impact of COVID-19 in placental endothelium, studying by immunofluorescence the expression of von Willebrand factor (vWf), claudin-5, and vascular endothelial (VE) cadherin in the decidua and chorionic villi of placentas from women with mild and severe COVID-19 in comparison to healthy controls. Our results indicate that: (1) vWf expression increases in the endothelium of decidua and chorionic villi of placentas derived from women with COVID-19, being higher in severe cases; (2) Claudin-5 and VE-cadherin expression decrease in the decidua and chorionic villus of placentas from women with severe COVID-19 but not in those with mild disease. Placental histological analysis reveals thrombosis, infarcts, and vascular wall remodeling, confirming the deleterious effect of COVID-19 on placental vessels. Together, these results suggest that placentas from women with COVID-19 have a condition of leaky endothelium and thrombosis, which is sensitive to disease severity.

Vitamin D Deficiency in Mexican Pregnant Women: Is Supplementation with ≤400 IU/day Enough?

Controversy remains surrounding vitamin D routine supplementation in healthy pregnancy, and the doses are unclear. The aim of this study was to describe maternal vitamin D status throughout pregnancy in a group of Mexican women and evaluate the effect of frequently prescribed doses of vitamin D3 on longitudinal 25-OH-D concentrations, adjusting for obesity, season, and other factors. We conducted a cohort study (Instituto Nacional de Perinatología-INPer) (2017-2020)) of healthy pregnant women without complications. Pregestational overweight/obesity (body mass index ≥ 25), vitamin D3 supplementation (prescribed by physician; 0-250, 250-400, and >400 IU/day), and serum 25-OH-D concentrations (ELISA) were evaluated in each trimester of pregnancy. Vitamin D deficiency or insufficiency was computed (<20 and <30 ng/mL, respectively). We studied 141 adult women; 58.5% had pregestational obesity or overweight. In the first trimester, 45.8% of the women were supplemented with vitamin D3; 51.4% had vitamin D insufficiency and 37.3%, deficiency. In the third trimester, 75.4% of the women were supplemented, and 20% of them still had deficiency. The final general mixed linear model showed that 25-OH-D significantly increased throughout pregnancy (p < 0.001); the highest increase was observed in the third trimester in women with doses >400 IU/day of vitamin D3 (+4 ng/mL, 95% CI: 1.72-8.11 ng/mL). In winter/autumn, 25-OH-D concentrations were also lower (p ≤ 0.05). In this group of pregnant Mexican women, the prevalence of vitamin D deficiency and insufficiency was high. A higher increase in 25-OH-D concentrations during pregnancy was observed when the women were supplemented with >400 IU/day. Common supplementation doses of 250-400 IU/day were insufficient for achieving an adequate maternal vitamin D status.

The sFlt-1/PlGF ratio as a triage tool to identify superimposed preeclampsia in women with chronic hypertension in emergency rooms.

OBJECTIVES: Assess the usefulness of the sFlt-1/PlGF ratio for the differential diagnosis of uncontrolled chronic hypertension vs. superimposed preeclampsia. STUDY DESIGN: We performed a cross-sectional study from 2015 to 2017 and 42 women with initial diagnosis of superimposed preeclampsia were enrolled in the emergency room. After a 12 week follow up patients were grouped as superimposed preeclampsia (Group A) and uncontrolled chronic hypertension (Group B) according to the American College of Obstetricians and Gynecologist criteria. A group of 33 healthy women paired by gestational age were included as controls (Group C). Maternal serum levels of sFlt-1 and PlGF were measured at enrollment, and the ratios of the groups were compared. MAIN OUTCOME MEASURES: Superimposed preeclampsia vs. uncontrolled chronic hypertension. RESULTS: After follow-up, group distribution was 30 women in Group A, 12 women in Group B, and 25 women in Group C. The sFlt-1/PlGF ratio was higher in women with superimposed preeclampsia than in women with uncontrolled chronic hypertension (215.5 vs. 9.65, p < 0.001). The control group displayed lower ratio values (3.66, p < 0.001). The sFlt-1 concentration was higher in Group A than in Group B (7564 vs. 1281 pg/mL, p < 0.001) and the PlGF level was lower in Group A (34.39 vs. 169 pg/mL, p < 0.001). CONCLUSIONS: The sFlt-1/PlGF ratio exhibits good performance for the differential diagnosis of superimposed preeclampsia vs. uncontrolled chronic hypertension.

Placental Microarray Profiling Reveals Common mRNA and lncRNA Expression Patterns in Preeclampsia and Intrauterine Growth Restriction.

Preeclampsia (PE) and Intrauterine Growth Restriction (IUGR) are major contributors to perinatal morbidity and mortality. These pregnancy disorders are associated with placental dysfunction and share similar pathophysiological features. The aim of this study was to compare the placental gene expression profiles including mRNA and lncRNAs from pregnant women from four study groups: PE, IUGR, PE-IUGR, and normal pregnancy (NP). Gene expression microarray analysis was performed on placental tissue obtained at delivery and results were validated using RTq-PCR. Differential gene expression analysis revealed that the largest transcript variation was observed in the IUGR samples compared to NP (n = 461; 314 mRNAs: 252 up-regulated and 62 down-regulated; 133 lncRNAs: 36 up-regulated and 98 down-regulated). We also detected a group of differentially expressed transcripts shared between the PE and IUGR samples compared to NP (n = 39), including 9 lncRNAs with a high correlation degree (p < 0.05). Functional enrichment of these shared transcripts showed that cytokine signaling pathways, protein modification, and regulation of JAK-STAT cascade are over-represented in both placental ischemic diseases. These findings contribute to the molecular characterization of placental ischemia showing common epigenetic regulation implicated in the pathophysiology of PE and IUGR.

Key Clinical Factors Predicting Adipokine and Oxidative Stress Marker Concentrations among Normal, Overweight and Obese Pregnant Women Using Artificial Neural Networks.

Maternal obesity has been related to adverse neonatal outcomes and fetal programming. Oxidative stress and adipokines are potential biomarkers in such pregnancies; thus, the measurement of these molecules has been considered critical. Therefore, we developed artificial neural network (ANN) models based on maternal weight status and clinical data to predict reliable maternal blood concentrations of these biomarkers at the end of pregnancy. Adipokines (adiponectin, leptin, and resistin), and DNA, lipid and protein oxidative markers (8-oxo-2'-deoxyguanosine, malondialdehyde and carbonylated proteins, respectively) were assessed in blood of normal weight, overweight and obese women in the third trimester of pregnancy. A Back-propagation algorithm was used to train ANN models with four input variables (age, pre-gestational body mass index (p-BMI), weight status and gestational age). ANN models were able to accurately predict all biomarkers with regression coefficients greater than R² = 0.945. P-BMI was the most significant variable for estimating adiponectin and carbonylated proteins concentrations (37%), while gestational age was the most relevant variable to predict resistin and malondialdehyde (34%). Age, gestational age and p-BMI had the same significance for leptin values. Finally, for 8-oxo-2'-deoxyguanosine prediction, the most significant variable was age (37%). These models become relevant to improve clinical and nutrition interventions in prenatal care.

A multimodal imaging workflow to visualize metal mixtures in the human placenta and explore colocalization with biological response markers.

Fetal exposure to essential and toxic metals can influence life-long health trajectories. The placenta regulates chemical transmission from maternal circulation to the fetus and itself exhibits a complex response to environmental stressors. The placenta can thus be a useful matrix to monitor metal exposures and stress responses in utero, but strategies to explore the biologic effects of metal mixtures in this organ are not well-developed. In this proof-of-concept study, we used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to measure the distributions of multiple metals in placental tissue from a low-birth-weight pregnancy, and we developed an approach to identify the components of metal mixtures that colocalized with biological response markers. Our novel workflow, which includes custom-developed software tools and algorithms for spatial outlier identification and background subtraction in multidimensional elemental image stacks, enables rapid image processing and seamless integration of data from elemental imaging and immunohistochemistry. Using quantitative spatial statistics, we identified distinct patterns of metal accumulation at sites of inflammation. Broadly, our multiplexed approach can be used to explore the mechanisms mediating complex metal exposures and biologic responses within placentae and other tissue types. Our LA-ICP-MS image processing workflow can be accessed through our interactive R Shiny application 'shinyImaging', which is available at or through our laboratory's website, .

Left ventricle segmentation in fetal echocardiography using a multi-texture active appearance model based on the steered Hermite transform.

OBJECTIVE: Fetal echocardiographic analysis is essential for detecting cardiac defects at early gestational ages. Fetal cardiac function can be assessed by performing some measurements regarding the dimension and shape of the heart cavities. In this work we propose an automatic segmentation method applied to the analysis of the left ventricle in fetal echocardiography. METHODS: For segmentation of the left ventricle, we designed a novel multi-texture active appearance model (AAM) based on the Hermite transform (HT). Local orientation analysis is addressed by steering the coefficients obtained with the HT. The method basically consists of an AAM-based scheme which uses the steered HT to efficiently code texture patterns of the input image. A wider and detailed description of the image features can be obtained with this method. Compared with classic AAM methods, the segmentation performance is substantially improved with the proposed scheme. Since AAM-based approaches process local information, an automatic method is also proposed to initialize the multi-texture AAM. For this purpose, a database of pre-segmented images was built. Then, techniques such as thresholding, mathematical morphology and correlation are combined to identify the position and orientation of the left ventricle. Typical issues found in fetal cardiac ultrasound images such as different orientations and shape variations of the heart cavities can be easily handled with the designed method. RESULTS: Several images of fetal echocardiography were used to evaluate the proposed segmentation method. The algorithm performance was validated using different metrics. We used a database of 143 real images of fetal hearts acquired for different phases of the cardiac cycle. We obtained an average Dice coefficient of 0.8631 and a point-to-curve distance of 2.027 pixels. The proposed algorithm was also validated by comparing it with other segmentation methods. CONCLUSIONS: We have designed an automatic algorithm for left ventricle segmentation in fetal echocardiography. The reported results demonstrate that the proposed approach can achieve an efficient segmentation of the left ventricular cavity. Typical problems found in images of fetal echocardiography are satisfactorily handled with the proposed multi-texture AAM scheme.