Role of GDNF, GFRα1 and GFAP in a Bifidobacterium-Intervention Induced Mouse Model of Intestinal Neuronal Dysplasia

ObjectiveTo investigate the effects of glial cell-derived neurotrophic factor (GDNF), GDNF family receptor alpha 1 (GFRα1), and glial fibrillary acidic protein (GFAP) on colonic motility in a mouse model of intestinal neuronal dysplasia by intervention with Bifidobacterium and to explore the influence of Bifidobacterium on enteric glial cells (EGCs).MethodsWestern blotting and qRT-PCR were employed to detect the expression of GFRα1 and GFAP in colonic tissues of mice with or without Tlx2 mutations, and ELISA was used to detect the expression of GDNF in serum. IHC was used to detect the appearance of the ganglion cells. Subsequently, Tlx2 homozygous mutant (Tlx2−/−) mice were treated with Bifidobacterium. Colonic motility was measured before and after intervention by measuring the glass bead expelling time. The variations in abdominal circumference and GDNF, GFRα1, and GFAP expression were measured. In addition, 16SrRNA gene sequencing was performed to detect the abundance of the intestinal microbiota.ResultsThe mRNA and protein expression of GFRα1 and GFAP was decreased in the colonic tissues of Tlx2−/− mice and GDNF expression was decreased in serum compared with Tlx2+/− and WT mice. After confirming the colonization of Bifidobacterium by 16S rRNA gene sequencing, the expelling time and abdominal distension were ameliorated, and the expression of GFAP, GDNF, and GFRα1 was increased.ConclusionsThe expression of GDNF, GFRα1, and GFAP is associated with colonic motility. The altered expression of EGC-related factors suggested that Bifidobacterium may be involved in the EGC activation process. The amelioration of IND symptoms after intervention with Bifidobacterium prompted the elicitation of adjuvant therapy.

Establishment of a New Equation for Ultrasonographic Estimated Foetal Weight in Chongqing: a Prospective Study

Background: Variations in foetal growth between populations should not be ignored, and a single universal standard is not appropriate for everyone. Therefore, it is necessary to develop a new ultrasound estimation equation that adapts better to regional population characteristics. The purpose of this study was to create a new equation for ultrasound estimation of foetal weight according to the local population in Chongqing and compare it with representative equations. Methods: This prospective study included data on pregnant women who gave birth to a child at full term in our hospital from December 2016 to November 2019. Foetal ultrasound parameters included biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur diaphysis length (FDL). The foetal weight compensation model was established by using the second-order linear regression model, and then, the foetal weight equation was established by utilizing the multiple reverse elimination regression technique. Last, the absolute error and relative error were used to compare the accuracy of the equations established in this study with representative equations. Results: Through the foetal weight compensation equation, the new equation suitable for Chongqing foetuses was successfully established with the variables of BPD, HC, AC, and FDL. The following foetal weight prediction equation was established in this study: Log 10 (EFW)=3.002741+0.00005944*(BPD^2)+0.00000222*(HC^2)-0.000002078*(AC^2)+0.00004262*(FDL^2)-0.008753*BPD-0.000884*HC+0.003206*AC-0.002894*FDL (BPD: mm; HC: mm; AC: mm; FDL: mm). In the sets established by the 1925 data, the mean absolute error and standard deviation of the estimation error of the new equation were 178.9 g and 140.3 g respectively. In the validation sets established with 300 data points, the mean absolute error and standard deviation of the new equation were 173.08 g and 128.59 g respectively. Compared with representative equations, the mean absolute error and the standard deviation of the new equation were the lowest. The equation established in this study better predicted foetal weight(P<.001). Conclusions: According to the local population characteristics of Chongqing, this study created a foetal weight estimation equation that is more accurate and suitable. This equation is clinically valuable for the monitoring and management of foetal weight.

A nomogram for Antenatal Estimation of Cephalopelvic Disproportion in Primiparous Women based on MRI Measurements

Objective: To develop and validate a predictive model assessing the risk of cesarean delivery in primiparous women based on the findings of magnetic resonance imaging (MRI) studies. Design: Observational study Setting: University teaching hospital. Population: 168 primiparous women with clinical findings suggestive of cephalopelvic disproportion. Methods: All women underwent MRI measurements prior to the onset of labor. A nomogram model to predict the risk of cesarean delivery was proposed based on the MRI data. The discrimination of the model was calculated by the area under the receiver operating characteristic curve (AUC) and calibration was assessed by calibration plots. The decision curve analysis was applied to evaluate the net clinical benefit. Main Outcome Measures: Cesarean delivery. Results: A total of 88 (58.7%) women achieved vaginal delivery, and 62 (41.3%) required cesarean section caused by obstructed labor. In multivariable modeling, the maternal body mass index before delivery, induction of labor, bilateral femoral head distance, obstetric conjugate, fetal head circumference and fetal abdominal circumference were significantly associated with the likelihood of cesarean delivery. The discrimination calculated as the AUC was 0.845 (95% CI: 0.783-0.908; P < 0.001). The sensitivity and specificity of the nomogram model were 0.918 and 0.629, respectively. The model demonstrated satisfactory calibration. Moreover, the decision curve analysis proved the superior net benefit of the model compared with each factor included. Conclusion: Our study provides a nomogram model that can accurately identify primiparous women at risk of cesarean delivery caused by cephalopelvic disproportion based on the MRI measurements.

Fast and Accurate U-Net Model for Fetal Ultrasound Image Segmentation

U-Net based algorithms, due to their complex computations, include limitations when they are used in clinical devices. In this paper, we addressed this problem through a novel U-Net based architecture that called fast and accurate U-Net for medical image segmentation task. The proposed fast and accurate U-Net model contains four tuned 2D-convolutional, 2D-transposed convolutional, and batch normalization layers as its main layers. There are four blocks in the encoder-decoder path. The results of our proposed architecture were evaluated using a prepared dataset for head circumference and abdominal circumference segmentation tasks, and a public dataset (HC18-Grand challenge dataset) for fetal head circumference measurement. The proposed fast network significantly improved the processing time in comparison with U-Net, dilated U-Net, R2U-Net, attention U-Net, and MFP U-Net. It took 0.47 seconds for segmenting a fetal abdominal image. In addition, over the prepared dataset using the proposed accurate model, Dice and Jaccard coefficients were 97.62% and 95.43% for fetal head segmentation, 95.07%, and 91.99% for fetal abdominal segmentation. Moreover, we have obtained the Dice and Jaccard coefficients of 97.45% and 95.00% using the public HC18-Grand challenge dataset. Based on the obtained results, we have concluded that a fine-tuned and a simple well-structured model used in clinical devices can outperform complex models.

Pregnancy in Women With Monogenic Diabetes due to Pathogenic Variants of the Glucokinase Gene: Lessons and Challenges

Heterozygous loss-of-function variants of the glucokinase (GCK) gene are responsible for a subtype of maturity-onset diabetes of the young (MODY). GCK-MODY is characterized by a mild hyperglycemia, mainly due to a higher blood glucose threshold for insulin secretion, and an up-regulated glucose counterregulation. GCK-MODY patients are asymptomatic, are not exposed to diabetes long-term complications, and do not require treatment. The diagnosis of GCK-MODY is made on the discovery of hyperglycemia by systematic screening, or by family screening. The situation is peculiar in GCK-MODY women during pregnancy for three reasons: 1. the degree of maternal hyperglycemia is sufficient to induce pregnancy adverse outcomes, as in pregestational or gestational diabetes; 2. the probability that a fetus inherits the maternal mutation is 50% and; 3. fetal insulin secretion is a major stimulus of fetal growth. Consequently, when the fetus has not inherited the maternal mutation, maternal hyperglycemia will trigger increased fetal insulin secretion and growth, with a high risk of macrosomia. By contrast, when the fetus has inherited the maternal mutation, its insulin secretion is set at the same threshold as the mother’s, and no fetal growth excess will occur. Thus, treatment of maternal hyperglycemia is necessary only in the former situation, and will lead to a risk of fetal growth restriction in the latter. It has been recommended that the management of diabetes in GCK-MODY pregnant women should be guided by assessment of fetal growth by serial ultrasounds, and institution of insulin therapy when the abdominal circumference is ≥ 75th percentile, considered as a surrogate for the fetal genotype. This strategy has not been validated in women with in GCK-MODY. Recently, the feasibility of non-invasive fetal genotyping has been demonstrated, that will improve the care of these women. Several challenges persist, including the identification of women with GCK-MODY before or early in pregnancy, and the modalities of insulin therapy. Yet, retrospective observational studies have shown that fetal genotype, not maternal treatment with insulin, is the main determinant of fetal growth and of the risk of macrosomia. Thus, further studies are needed to specify the management of GCK-MODY pregnant women during pregnancy.

Accuracy of abdominal circumference for diagnosing overweight in six-to-seven-years-old children

Objective: To estimate the accuracy of abdominal circumference measurement as a method of diagnosing overweight in six-to-seven-years-old children. Methods: A cross-sectional study involving 1026 six-to-seven-years-old schoolchildren in southern Brazil was carried out. Children’s weight and height were collected at schools. Body mass index were calculated and categorized in z-score in eutrophy, overweight and obesity. Abdominal circumference was measured in centimeters with a tape with children in standing position at midpoint between the lower ribs margin and the iliac crest. Correlation between abdominal circumference and body mass index was performed through Pearson's correlation coefficient. Sensitivity, specificity, positive and negative predictive values of abdominal circumference were estimated. The Receiver Operating Characteristic Curve was used to measure the accuracy. Results: A positive linear correlation value of 0.582 and a determination coefficient 0.39 were observed. The accuracy value of 0.859 was observed. Sensitivity, specificity, positive and negative predictive values varied according to each value in centimeters of abdominal circumference. Conclusion: Abdominal circumference measure showed to be an accurate method for detecting overweight and obesity in six-to-seven-years-old children.