Joint effect of maternal pre-pregnancy body mass index and folic acid supplements on gestational diabetes mellitus risk: a prospective cohort study.

BACKGROUND: The joint effect of folic acid (FA) supplements and maternal pre-pregnancy body mass index (BMI) on gestational diabetes mellitus (GDM) has not been fully addressed. This study aimed to examine the joint effect of FA supplements and pre-pregnancy BMI on GDM. METHODS: Pregnant women at 4 to 14 weeks of gestation (n = 3186) were recruited during their first prenatal visit in Qingdao from May 1, 2019, to June 27, 2021. The main outcome was GDM at 24-28 weeks' gestation. Screening was based on 75 g 2-hour oral glucose tolerance (OGTT), a fasting glucose ≥ 5.1 mmol/L, or a 1-hour result ≥ 10.0 mmol/L, or a 2-hour result ≥ 8.5 mmol/L. The interactive effect of FA supplements and pre-pregnancy BMI on GDM was examined using logistic regression analysis and ratio of odds ratios (ROR) was used to compare subgroup differences. RESULTS: Overall, 2,095 pregnant women were included in the analysis, and GDM incidence was 17.76%. Compared with women with pre-pregnancy BMI lower than 25.0 kg/m2 and FA-Sufficient supplements ≥ 400 µg/day (FA-S) population, the adjusted odds ratios (aORs) of FA-S and FA-Deficiency supplements < 400 µg/d (FA-D) were 3.57 (95% confidence interval [CI]: 2.02-6.34) and 10.82 (95% CI: 1.69-69.45) for the obese women (BMI ≥ 30.0 kg/m2), and the aORs of FA-S and FA-D were 2.17 (95% CI: 1.60-2.95) and 3.27 (95% CI: 1.55-6.92) for overweight women (25.0 kg/m2 ≤ BMI < 30.0 kg/m2). However, the risk of GDM did not differ significantly between the FA-D and the FA-S group in pre-pregnancy obese women (ROR = 2.70, 95%CI: 0.47-2.30), or overweight women (ROR = 0.66, 95%CI: 0.30-1.49). After further stratification of FA supplementation time, F-D and FA-S in obese women showed an interaction when FA supplement intake time < 3 months. However, there was no significant difference between subgroups (ROR = 1.63, 95% CI: 0.37-7.04). CONCLUSION: Maternal pre-pregnancy BMI was associated with the incidence of GDM, the dose of FA supplementation from pre-pregnancy to early pregnancy was not found to be related to the incidence of GDM. The dosage of FA supplement was not associated with GDM irrespective of maternal pre-pregnancy BMI.

The possible role of visceral fat in early pregnancy as a predictor of gestational diabetes mellitus by regulating adipose-derived exosomes miRNA-148 family: protocol for a nested case-control study in a cohort study.

BACKGROUND: Gestational diabetes mellitus (GDM) has become alarming public health concern. It is associated with adverse pregnancy outcomes and increased risk of postpartum type 2 diabetes. Pre-pregnant body mass index (BMI), waist circumference and other anthropometric parameters have been proposed to predict GDM. However, visceral fat thickness can better reflect the distribution of body fat, and may more accurately predict the risk of GDM. Visceral fat thickness may lead to insulin resistance by regulating the adipose-derived exosomes miRNA-148 family, which affect the development of GDM. Evidence from prospective cohort studies on visceral fat thickness as a predictor of GDM and the possible mechanisms is still insufficient. METHODS: In this prospective cohort study, we will recruit 3000 women at first antenatal visit between 4 and 12 weeks of gestation. Baseline socio-demographic factors and visceral fat thickness will be assessed by questionnaire form and the ultrasonic measurement, respectively. At 20 weeks of gestation, 10 ml blood samples will be drawn and we will extract adipose-derived exosomes miRNA on the basis of nested case-control study. GDM will be screened at 24-28 weeks' gestation and the expression of miRNA-148 family between pregnant women with GDM and without GDM will be analyzed. Intermediary analysis will be used to investigate whether visceral fat thickness can predict GDM by regulating adipose-derived exosomes miRNA-148 family. DISCUSSION: We hypothesized that visceral fat thickness may predict GDM by regulating the miRNA-148 family of adipose-derived exosomes. The findings of the study will assist in further clarifying the pathophysiological mechanism of GDM, it will also provide technical support for effective screening of high-risk pregnant women with GDM.

Performance of First-Trimester Fetal Echocardiography in Diagnosing Fetal Heart Defects: Meta-analysis and Systematic Review.

OBJECTIVES: Early fetal echocardiography is becoming increasing common during the nuchal translucency scan period. The aim of this meta-analysis was to assess the accuracy of first-trimester fetal echocardiography in diagnosing congenital heart defects (CHDs). METHODS: The databases of PubMed, Embase, the Cochrane Library, and the Cumulative Index to Nursing and Allied Health Literature were systematically searched for the candidate articles, and the references of included studies were also examined. We recorded the characteristics of the included studies and assessed the quality of each study by the Quality Assessment of Diagnostic Accuracy Studies tool. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated with Meta-Disc version 1.4 software (Ramón y Cajal Hospital, Madrid, Spain). We also evaluated the publication bias by using Stata version 12.0 software (StataCorp, College Station, TX). RESULTS: This meta-analysis included 18 studies with 26,201 fetal hearts. The overall pooled sensitivity, specificity, PLR, and NLR were 0.750, 0.999, 392.95, and 0.277, respectively. The DOR and AUC were 1736.0 and 0.9331. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC for major CHDs were 0.838, 1.000, 725.69, 0.203, 5084.8, and 0.9617. CONCLUSIONS: First-trimester fetal echocardiography had high value in diagnosing CHDs, especially major CHDs.

Fracture loads and failure modes of customized and non-customized zirconia abutments.

OBJECTIVE: This study aimed to evaluate the fracture load and pattern of customized and non-customized zirconia abutments with Morse-taper connection. METHODS: 18 implants were divided into 3 groups according to the abutments used: Zr - with non-customized zirconia abutments; Zrc - with customized zirconia abutments; and Ti - with titanium abutments. To test their load capacity, a universal test machine with a 500-kgf load cell and a 0.5-mm/min speed were used. After, one implant-abutment assembly from each group was analyzed by Scanning Electron Microscopy (SEM). For fractographic analysis, the specimens were transversely sectioned above the threads of the abutment screw in order to examine their fracture surfaces using SEM. RESULTS: A significant difference was noted between the groups (Zr=573.7±11.66N, Zrc=768.0±8.72N and Ti=659.1±7.70N). Also, the zirconia abutments fractured while the titanium abutments deformed plastically. Zrc presented fracture loads significantly higher than Zr (p=0.009). All the zirconia abutments fractured below the implant platform, starting from the area of contact between the abutment and implant and propagating to the internal surface of the abutment. All the zirconia abutments presented complete cleavage in the mechanical test. Fractography detected differences in the position and pattern of fracture between the two groups with zirconia abutments, probably because of the different diameters in the transmucosal region. SIGNIFICANCE: Customization of zirconia abutments did not affect their fracture loads, which were comparable to that of titanium and much higher than the maximum physiological limit for the anterior region of the maxilla.

Custom Morse taper zirconia abutments: Influence on marginal fit and torque loss before and after thermomechanical cycling.

The use of zirconia abutments has increased because of aesthetics, but sometimes customization is necessary and its effect is unclear. This study evaluated the marginal fit and torque loss of customized and non-customized aesthetic zirconia abutments associated with Morse taper implants before and after thermomechanical cycling. Twenty-four implant/abutment/crown sets were divided into three groups (N = 8): Zr - non-customized zirconia abutments, Zrc - customized zirconia abutments, and Ti - titanium abutments. The ceramic crowns of the upper canines were made. All of the abutments were tightened with 15-N.cm torque, and the crowns were cemented on the abutments. The misfits and torque loss were measured before and after thermomechanical cycling. The marginal fit was evaluated in two planes throughout 10 different slices, 30 measurements for each face (i.e., buccal, palatal, mesial and distal) and 120 measurements for each sample. A load of 100N, a frequency of 2Hz and 1000,000 cycles with temperature variation of 5°-55°C were used for thermomechanical cycling. Thermomechanical cycling significantly decreased the marginal misfit only with the Zrc (p = 0.002), and the Ti was significantly different from the Zr and Zrc before and after thermomechanical cycling. Thermomechanical cycling did not affect the torque losses of the groups, but a significant difference between the Zr and Zrc (p = 0.0345) before cycling was noted. Customization of zirconia abutments does not significantly affect torque loss and marginal misfit after thermomechanical cycling suggesting that they can be safe for clinical utilization.

Gene expression profiling of colorectal tumors and normal mucosa by microarrays meta-analysis using prediction analysis of microarray, artificial neural network, classification, and regression trees.

BACKGROUND: Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC) research. The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0). METHODS: Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs. PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances. RESULTS: The first screening identified 55 genes. The test accuracy of each model was over 0.97 averagely. Less than eight genes achieve excellent classification accuracy. Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1. Genes of higher significances showed lower variation in rank ordering by different methods. CONCLUSION: We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%). This method can be applied to future studies. Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC.

Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees.

BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR. The collection of microarray datasets from the Gene Expression Omnibus, four breast cancer datasets were pooled for predicting five-year breast cancer relapse. After data compilation, 757 subjects, 5 clinical variables and 13,452 genetic variables were aggregated. The bootstrap method, Mann-Whitney U test and 20-fold cross-validation were performed to investigate candidate genes with 100 most-significant p-values. The predictive powers of DT, LR and ANN models were assessed using accuracy and the area under ROC curve. The associated genes were evaluated using Cox regression. RESULTS: The DT models exhibited the lowest predictive power and the poorest extrapolation when applied to the test samples. The ANN models displayed the best predictive power and showed the best extrapolation. The 21 most-associated genes, as determined by integration of each model, were analyzed using Cox regression with a 3.53-fold (95% CI: 2.24-5.58) increased risk of breast cancer five-year recurrence. CONCLUSIONS: The 21 selected genes can predict breast cancer recurrence. Among these genes, CCNB1, PLK1 and TOP2A are in the cell cycle G2/M DNA damage checkpoint pathway. Oncologists can offer the genetic information for patients when understanding the gene expression profiles on breast cancer recurrence.

Digital image correlation analysis on the influence of crown material in implant-supported prostheses on bone strain distribution.

PURPOSE: A digital image correlation (DIC) method for full-field surface strain measurement was used to analyze the effect of two veneering materials for implant supported crowns on the strain distribution within the surrounding bone. METHODS: An epoxy resin model of a bone block was made by housing acrylic resin replicas of a mandibular first premolar and second molar together with threaded implants replacing the second premolar and first molar. Porcelain-veneered (G1 and G3) and resin-veneered (G2 and G4) screw-retained splinted crowns were fabricated and loaded with (G1 and G2) and without (G3 and G4) the presence of the second molar replica. A 2-dimensional DIC measuring system was used to record surface deformation of the bone block model at a frequency of 1.0 Hz during application of a 250-N load. RESULTS: Maximum compressive strains (ɛ(XX), %) were found for the following regions: between molars, G1 (-0.21), G2 (-0.18), G3 (-0.26), and G4 (-0.25); between implants, G1 (-0.19), G2 (-0.13), G3 (-0.19), and G4 (-0.14). The magnitude of strains in the simulated bone block with the resin-veneered crowns was lower than that with porcelain-veneered crowns, irrespective of the presence or absence of the second molar. CONCLUSIONS: The softer resin veneer helped to spread the load more evenly amongst the supporting teeth and implants, thus reducing the strains in the simulant bone block. Conversely, using the harder porcelain veneer resulted in the load being concentrated within one or two teeth or implants, thus leading to higher strain values in the bone block.