Association of Serum Folate and Vitamin B 12 Concentrations with Obesity in Chinese Children and Adolescents.

Objective: This study aimed to evaluate the associations of serum folate and/or vitamin B 12 concentrations with obesity among Chinese children and adolescents. Methods: A cross-sectional study was conducted including 3,079 Chinese children and adolescents, aged 6 to 17 years, from Jiangsu, China. Anthropometric indices, such as, children's body mass index (BMI), BMI z-scores, waist circumference, and waist-to-height ratio were utilized. Multivariable linear regression and generalized additive models were used to investigate the associations of serum folate and vitamin B 12 levels with anthropometric indices and odds of obesity. Results: We observed that serum vitamin B 12 concentrations were inversely associated with all anthropometric indices and the odds of general obesity [odds ratio ( OR) = 0.68; 95% confidence interval ( CI) = 0.59, 0.78] and abdominal obesity ( OR = 0.68; 95% CI = 0.60, 0.77). When compared to participants with both serum vitamin levels in the two middle quartiles, those with both serum folate and vitamin B 12 levels in the highest quartile were less prone to general ( OR = 0.31, 95% CI = 0.19, 0.50) or abdominal obesity ( OR = 0.46, 95% CI = 0.31, 0.67). Conversely, participants with vitamin B 12 levels in the lowest quartile alongside folate levels in the highest quartile had higher odds of abdominal obesity ( OR = 2.06, 95% CI = 1.09, 3.91). Conclusion: Higher serum vitamin B 12 concentrations, but not serum folate concentrations, were associated with lower odds of childhood obesity. Children and adolescents with high levels of vitamin B 12 and folate were less likely to be obese.

MMGan: a multimodal MR brain tumor image segmentation method.

Computer-aided diagnosis has emerged as a rapidly evolving field, garnering increased attention in recent years. At the forefront of this field is the segmentation of lesions in medical images, which is a critical preliminary stage in subsequent treatment procedures. Among the most challenging tasks in medical image analysis is the accurate and automated segmentation of brain tumors in various modalities of brain tumor MRI. In this article, we present a novel end-to-end network architecture called MMGan, which combines the advantages of residual learning and generative adversarial neural networks inspired by classical generative adversarial networks. The segmenter in the MMGan network, which has a U-Net architecture, is constructed using a deep residual network instead of the conventional convolutional neural network. The dataset used for this study is the BRATS dataset from the Brain Tumor Segmentation Challenge at the Medical Image Computing and Computer Assisted Intervention Society. Our proposed method has been extensively tested, and the results indicate that this MMGan framework is more efficient and stable for segmentation tasks. On BRATS 2019, the segmentation algorithm improved accuracy and sensitivity in whole tumor, tumor core, and enhanced tumor segmentation. Particularly noteworthy is the higher dice score of 0.86 achieved by our proposed method in tumor core segmentation, surpassing those of stateof-the-art models. This study improves the accuracy and sensitivity of the tumor segmentation task, which we believe is significant for medical image analysis. And it should be further improved by replacing different loss functions such as cross-entropy loss function and other methods.

Child marriage among Somali refugees in Ethiopia: a cross sectional survey of adolescent girls and adult women.

BACKGROUND: Despite child marriage receiving increased attention over the past two decades, research on child marriage in humanitarian settings remains scarce. This study sought to quantify child marriage among Somali adolescent girls residing in Kobe refugee camp in Ethiopia and to identify its correlates and consequences. METHODS: A cross-sectional survey was conducted using multi-stage cluster-based sampling with probability proportional to size. We randomly sampled households that have at least one female aged 15-49 and at least one adolescent female aged 10-19. In addition to calculating the proportion of girls married under age 18, we used survival methods - namely Kaplan Meier graphs and Cox proportional hazard models - to identify risk factors associated with child marriage in this context. We also used descriptive statistics to describe marital age preferences among female adults and presented measures of important sexual and reproductive health indicators among married adolescent girls. RESULTS: A total of 603 adult women were surveyed and a household roster was created with information on 3319 household members, of whom 522 were adolescent girls aged 15-19. Of those, 14% were currently married (95% Confidence Interval [CI] 0.11-0.18), and 11% were ever married under age 18 (95% CI 8-15%). Several variables were found to be significantly associated with hazard of child marriage including schooling, sex and employment status of head of household, as well as number of girls under age 18 in the childhood home.. Adult women tended to incorrectly identify minimum legal age at marriage and preferred low marital age for boys and girls - particularly in households of child brides. Among married adolescent girls, contraceptive use was very low (11%; 95% CI 4.94-22.40), and early childbearing was common (60%; 95% CI 45.56-72.89). CONCLUSIONS: This research contributes to the evidence base on child marriage in humanitarian settings. Insights generated from this study have the potential to inform programs and interventions aiming to prevent and mitigate the impacts of this harmful practice.