Basic Researches On The Etiology And Mechanism Of Neural Tube Defects

Objective: This study reported the effects of retinoic acid upon the spatiotemporal expressions of Vangl1 and Vangl2 in mouse fetuses.Material and method: Single dose of 120 mg/kg body weight of all trans-retinoic acid suspended in olive oil was administered intragastrically to each pregnant BALB/C mice on embryonic day (E) 9.5 (group 1, G1) or E10.5 (group 2, G2); mice treated with pure olive oil on E9.5 or E10.5 served as control groups. The expressions of Vangl1 and Vangl2 in fetuses were investigated by reverse transcriptase PCR (RT-PCR) and their spatial and temporal expressions were detected by whole-mount in situ hybridization (WISH) on E10.5, E11.5, E13.5, E15.5, E17.5 and E19.5 respectively.Results: The study indicated that the incidence of NTDs in live birth and craniofacial NTDs rate were significantly higher in G1 (100% and 25.6%) than that in G2 (78.2% and 5.7%), both P < 0.05. Vangl1 and Vangl2 were strongly expressed throughout neurulation in embryos of control groups. G1 embryos exhibited a dramatic downregulation of Vangl1 and Vangl2 expressions from cranial region to posterior neuropore compared with the control group of G1 (all P < 0.05). In contrast, the both transcripts in G2 embryos were significantly downregulated and weakly expressed in whole embryos from E11.5 to E13.5 and in the spinal region of neural tube from E15.5 to E19.5, but moderately downregulated in the cranial region of neural tube from E15.5 Conclusion: Vangl1 and Vangl2 transcripts downregulation might be implicated in the occurrence of mouse NTDs induced by retinoic acid. Background: Neural tube defects (NTDs) are complex disease caused by multiple genes and environmental factors. Folic acid is a known environmental factor for NTDs. Folate metabolism pathway genes have been examined for association with NTDs, but most of these genes were studied individually, often with different populations providing conflicting results.Objective: Folate pathway genes SNPs in Chinese families with NTDs were investigated to discover the genetic and environmental factors that contribute to the cause of NTDs.Materials and Methods: We genotyped 28 SNPs in 12 genes in a total of 117 NTDs individuals from 115 family and 216 parental controls mainly Han Chinese from central China. Family-based association analysis was performed by case-parent control study and transmission/ disequilibrium test (TDT) to evaluate the association between SNPs and environmental risk factors: no peri-pregnant folate supplementation, gestational diabetes mellitus (GDM) and peri-pregnant taking medicine. These genes are: folate receptor 1 (FOLR1), folate receptor 2 (FOLR2), solute carrier family 19 member 1 (SLC19A1), transcobalamin II (TCN2), methylenetetrahydrofolate dehydrogenase 1 (MTHFD1), serine hydroxymethyltransferase 1 (SHMT1), 5,10-methylenetetrahydrofolate reductase (MTHFR), 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), 5-methyltetrahydrofolate-homocysteine methyltransferase reductase (MTRR), betaine-homocysteine methyltransferase (BHMT), cystathionine-beta-synthase (CBS) and endothelial nitric oxide synthase 3 (NOS3).Results: MTHFR rs1801133 was significantly associated with NTDs, and environmental risk factors, no peri-pregnant folate supplementation and GDM, had potentiation on its contribution to NTDs. BHMT rs3733890 and no peri-pregnant folate supplementation conjointly led to NTDs, while genotype can not solely cause NTDs. Other SNPs in folate pathway genes had no significant association with NTDs.Conclusion: MTHFR rs1801133 is an independent genetic risk factor of NTDs, but BHMT rs3733890 is not a major risk factor. Background: Region of interest (ROI) segmentation and boundaries identification are still extremely challenging task for automatic bone age assessment (ABAA).Objective: New algorithms, particle swarm optimization (PSO) and artificial neural network (ANN) are proposed to improve the validity, accuracy and practicality of ABAA.Materials and Methods: The concept of object-based ROI was proposed. Thirteen RUS (including radius,ulna and short finger bones) ROIs and seven carpal ROIs were appointed respectively according to Tanner-Whitehouse (TW3) method. Five features including size, morphologic features and fusion stage of each ROI were extracted and input into ANN classifiers. ANNs were built upon feed-forward multilayer networks and trained with back-propagation algorithm rules to process RUS and Carpal features respectively. About 1,046 digital left hand-wrist radiographs were randomly utilized half for training ANNs and the rest for ABAA after manual reading by revised Greulich-Pyle method.Results: The 95% confidence intervals of the difference between ABAA and manual readings were -0.010 to 0.084 years for RUS bone age and -0.055 to 0.015 years for Carpal bone age. Both RUS and Carpal ABAA systems had no significant difference compared with manual method (t = 1.563 and -1.123, both P > 0.05), and both two systems had fairly high concordance rates (97.9% and 96.5% respectively) and similar coefficient variations (3.4 and 3.7 respectively).Conclusion: PSO method made image segmentation and feature extraction more valid and accurate, and the ANN models were sophisticated in processing image information. ABAA system based on intelligent algorithms had been successfully applied to all cases from 0 to 18 years of bone age.