Background: The benefits of physical activity during pregnancy include lower maternal weight gain, a lower likelihood of gestational diabetes, low back pain, preeclampsia, preterm delivery, caesarian delivery, and macrosomia. This study aimed to examine the factors associated with insufficient leisure-time physical activity (LTPA) during the first trimester. Methods: A cross-sectional study was conducted at the Clinic for Obstetrics and Gynecology of Clinical Center of Serbia, Belgrade, between January and June of 2018. The final analyses included 162/175 pregnant women. The questionnaire was used to obtain social characteristics, pregnancy, and lifestyle characteristics (Pregnancy Risk Assessment Monitoring System—PRAMS), pre-pregnancy LTPA (International Physical Activity Questionnaire—IPAQ), and LTPA during the first trimester (Pregnancy Physical Activity Questionnaire—PPAQ). Women were classified into two groups of sufficient and insufficient LTPA during the first trimester based on the recommendations of the World Health Organization. Multivariate logistic regression analysis was applied. Results: A total of 27.2% of the women had insufficient LTPA during pregnancy. Insufficient LTPA during pregnancy was associated with <12 years of education (OR: 2.3, 95% CI: 1.05–5.04), self-rated financial status as poor (OR: 0.34, 95% CI: 0.14–0.79), and hours spent walking before pregnancy (OR: 0.87, 95% CI: 0.77–0.99). Conclusions: Our results can help direct health care professionals advice for women who are planning pregnancy towards walking as it seems to be sustained during pregnancy.

Background: The aim of the present study was to investigate the relationship between mid-trimester ultrasound fetal liver length (FLL) and gestational diabetes mellitus (GDM) in a high-risk population. Methods: A prospective study was performed in 331 women with singleton pregnancies who were at high risk of GDM and were undergoing a midtrimester ultrasound examination. The ultrasound scan at 23 weeks gestation was followed by a 100-g oral glucose tolerance test (OGTT) at 24 weeks gestation. Correlations between FLL and OGTT results at different time points were tested. Receiver operating characteristic (ROC) analysis of FLL as a potential prognostic factor for GDM was also performed. Results: In GDM patients, there was a significant positive correlation (P < 0.01) between FLL and OGTT glycemia immediately before and 60, 120, and 180 min after glucose intake. Mean FLL in GDM was significantly higher than in healthy subjects (41.04 vs 31.09 mm, respectively; P < 0.001). When tested as a potential prognostic factor for GDM, fetal liver measurements showed excellent diagnostic performance. The ROC analysis established a cut-off value of FLL of 39 mm for the prediction GDM, with sensitivity of 71.76%, specificity 97.56%, positive predictive value 91.0%, and negative predictive value 90.9%. The usefulness of FLL measurements was supported by a high area under the ROC curve (90.5%). Conclusion: In conclusion, there is a strong correlation between FLL and OGTT results, with FLL possibly serving as a valid marker for the prediction of GDM in high-risk populations.

No abstract

Previous adverse pregnancy outcomes (APO) in women with hereditary thrombophilia have emerged as new indications for prophylactic use of low-molecular-weight heparin (LMWH) during pregnancy. Recent meta-analysis conducted to establish if LMWH may prevent recurrent placenta-mediated pregnancy complications point to important therapeutic effect but these findings are absolutely not universal. Furthermore, previous studies regarding LMWH prophylaxis for APO in women with inherited thrombophilia were performed in high risk patients with previous adverse health outcomes in medical, family and/or obstetric history. Therefore, the aim of this study was to investigate the effects of LMWH prophylaxis on pregnancy outcomes in women with inherited thrombophilias regardless of the presence of previous adverse health outcomes in medical, family, and obstetric history. Prospective analytical cohort study included all referred women with inherited thrombophilia between 11 and 15 weeks of gestation and followed-up to delivery. Patients were allocated in group with LWMH prophylaxis (study group) and control group without LWMH prophylaxis. The groups were compared for laboratory parameters and Doppler flows of umbilical artery at 28 th to 30th, 32nd to 34th and 36th to 38th gestational weeks (gw), and for obstetric and perinatal outcomes. The study group included 221 women and control group included 137 women. Mean resistance index of the umbilical artery Ri in 28 to 30, 32 to 34, and 36 to 38 gw were significantly higher in the control group compared to study group (0.71 ± 0.02 vs 0.69 ± 0.02; 0.67 ± 0.03 vs 0.64 ± 0.02; and 0.67 ± 0.05 vs 0.54 ± 0.08, respectively). Intrauterine fetal death (IUFD) and miscarriages were statistically significantly more frequent in control group compared to the patients in study ( P < .001). The frequencies of fetal growth restriction (FGR) and APO were significantly higher in the control group compared to the study group ( P = .008 and P < .001, respectively). In a multivariate regression model with APO as a dependent variable, only Ri was detected as a significant protective factor for APO, after adjusting for age and LMWH prophylaxis ( P < .001). We have demonstrated better perinatal outcomes in women with LMWH prophylaxis for APO compared to untreated women.

Diabetes in pregnancy is associated with adverse pregnancy outcomes including preterm birth. Although the mechanisms leading to these pregnancy complications are still poorly understood, aberrant angiogenesis and endothelial dysfunction play a key role. FKBPL and SIRT-1 are critical regulators of angiogenesis, however, their roles in pregnancies affected by diabetes have not been examined before in detail. Hence, this study aimed to investigate the role of FKBPL and SIRT-1 in pre-gestational (type 1 diabetes mellitus, T1D) and gestational diabetes mellitus (GDM). Placental protein expression of important angiogenesis proteins, FKBPL, SIRT-1, PlGF and VEGF-R1, was determined from pregnant women with GDM or T1D, and in the first trimester trophoblast cells exposed to high glucose (25 mM) and varying oxygen concentrations [21%, 6.5%, 2.5% (ACH-3Ps)]. Endothelial cell function was assessed in high glucose conditions (30 mM) and following FKBPL overexpression. Placental FKBPL protein expression was downregulated in T1D (FKBPL; p&lt;0.05) whereas PlGF/VEGF-R1 were upregulated (p&lt;0.05); correlations adjusted for gestational age were also significant. In the presence of GDM, only SIRT-1 was significantly downregulated (p&lt;0.05) even when adjusted for gestational age (r=-0.92, p=0.001). Both FKBPL and SIRT-1 protein expression was reduced in ACH-3P cells in high glucose conditions associated with 6.5%/2.5% oxygen concentrations compared to experimental normoxia (21%; p&lt;0.05). FKBPL overexpression in endothelial cells (HUVECs) exacerbated reduction in tubule formation compared to empty vector control, in high glucose conditions (junctions; p&lt;0.01, branches; p&lt;0.05). In conclusion, FKBPL and/or SIRT-1 downregulation in response to diabetic pregnancies may have a key role in the development of vascular dysfunction and associated complications affected by impaired placental angiogenesis.

Gray-level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computational method for the assessment of textural patterns, applicable in almost any area of microscopy. The aim of our research was to perform the GLCM analysis of cell nuclei in Saccharomyces cerevisiae yeast cells after the induction of sublethal cell damage with ethyl alcohol, and to evaluate the performance of various machine learning (ML) models regarding their ability to separate damaged from intact cells. For each cell nucleus, five GLCM parameters were calculated: angular second moment, inverse difference moment, GLCM contrast, GLCM correlation, and textural variance. Based on the obtained GLCM data, we applied three ML approaches: neural network, random trees, and binomial logistic regression. Statistically significant differences in GLCM features were observed between treated and untreated cells. The multilayer perceptron neural network had the highest classification accuracy. The model also showed a relatively high level of sensitivity and specificity, as well as an excellent discriminatory power in the separation of treated from untreated cells. To the best of our knowledge, this is the first study to demonstrate that it is possible to create a relatively sensitive GLCM-based ML model for the detection of alcohol-induced damage in Saccharomyces cerevisiae cell nuclei.

No abstract

No abstract