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Introduction: Lung image segmentation plays an important role in computer-aid pulmonary disease diagnosis and treatment. Methods: This paper explores the lung CT image segmentation method by generative adversarial networks. We employ a variety of generative adversarial networks and used their capability of image translation to perform image segmentation. The generative adversarial network is employed to translate the original lung image into the segmented image. Results: The generative adversarial networks-based segmentation method is tested on real lung image data set. Experimental results show that the proposed method outperforms the state-of-the-art method. Discussion: The generative adversarial networks-based method is effective for lung image segmentation. [ABSTRACT FROM AUTHOR]

Deuterium labelling techniques have shown widespread applications in organic synthesis, analytic chemistry, life science and material science. The design of practical deuteration reactions which is environmentally friendly is highly desired for pharmaceutical development and industrial processes while remaining underexplored. We herein report a convenient, transition metal-free strategy for reductive deuteration of ketone derivatives to α-deuterated alcohols by employing a conjugated aryl amine-based organophotocatalyst, a dipropyl disulfide cocatalyst and an inorganic reductant. Upon irradiation with visible light and under an air atmosphere, a variety of diaryl ketones, heteroaryl ketones, cyclic ketones, α-ketoesters, benzil derivatives, aliphatic ketones and drug-like molecules were converted into corresponding α-deuterated aryl alcohols in good to excellent yields and with high deuterium incorporation (up to 99% D-incorporation). Only low toxic side-products, such as sodium salts and carbon dioxide, were generated. Consequently, the synthetic utility of this method is highlighted by the preparation of several D-labeled drug-like molecules, including orphenadrine, carbinoxamine and modafinil. [ABSTRACT FROM AUTHOR]

Background: High dimensional mediation analysis is frequently conducted to explore the role of epigenetic modifiers between exposure and health outcome. However, the issue of high dimensional mediation analysis with unmeasured confounders for survival analysis in observational study has not been well solved. Methods: In this study, we proposed an instrumental variable based approach for high dimensional mediation analysis with unmeasured confounders in survival analysis for epigenetic study. We used the Sobel's test, the Joint test, and the Bootstrap method to test themediation effect. A comprehensive simulation study was conducted to decide the best test strategy. An empirical study based on DNA methylation data of lung cancer patients was conducted to illustrate the performance of the proposed method. Results: Simulation study suggested that the proposed method performed well in the identifying mediating factors. The estimation of the mediation effect by the proposed approach is also reliable with less bias compared with the classical approach. In the empirical study, we identified two DNA methylation signatures including cg21926276 and cg26387355 with a mediation effect of 0.226 (95%CI: 0.108-0.344) and 0.158 (95%CI: 0.065-0.251) between smoking and lung cancer using the proposed approach. Conclusion: The proposed method obtained good performance in simulation and empirical studies, it could be an effective statistical tool for high dimensional mediation analysis. [ABSTRACT FROM AUTHOR]

Background Healthy life expectancy (HLE) projections are required for optimising social and health service management in the future. Existing studies on the topic were usually conducted by selecting a single model for analysis. We thus aimed to use an ensembled model to project the future HLE for 202 countries/region. Methods We obtained data on age-sex-specific HLE and the sociodemographic index (SDI) level of 202 countries from 1990 to 2019 from the Global Burden of Disease (GBD) database and used a probabilistic Bayesian model comprised of 21 forecasting models to predict their HLE in 2030. Results In general, HLE is projected to increase in all 202 countries, with the least probability of 82.4% for women and 81.0% for men. Most of the countries with the lowest projected HLE would be located in Africa. Women in Singapore have the highest projected HLE in 2030, with a 94.5% probability of higher than 75.2 years, which is the highest HLE in 2019 across countries. Maldives, Kuwait, and China are projected to have a probability of 49.3%, 41.2% and 31.6% to be the new entries of the top ten countries with the highest HLE for females compared with 2019. Men in Singapore are projected to have the highest HLE at birth in 2030, with a 93.4% probability of higher than 75.2 years. Peru and Maldives have a probability of 48.7% and 35.3% being new top ten countries in male's HLE. The female advantage in HLE will shrink by 2030 in 117 countries, especially in most of the high SDI and European countries. Conclusions HLE will likely continue to increase in most countries and regions worldwide in the future. More attention needs to be paid to combatting obesity, chronic diseases, and specific infectious diseases, especially in African and some Pacific Island countries. Although gender gaps may not be fully bridged, HLE could partially mitigate and even eliminate them through economic development and improvements in health care. [ABSTRACT FROM AUTHOR]

Background: Motivation is the impetus for patients to seek orthodontic treatment, affecting adherence, treatment outcomes, and satisfaction. The aim of this study was to assess the motivation of adult female patients seeking orthodontic treatment, and classify the patients according to their motivations. Methods: This study used Q-methodology as the main tool. Q-samples were collected and categorized (35 items). Forty-two adult female patients were interviewed before treatment as the P-sample, and their responses were categorized into the Q-methodology grid. Participants were asked to rank-order a set of 35 statements (Q-sample) from "agree most" to "disagree most" (Q-sorting). The finished Q-grids were analyzed using PQ method 2.35. Results: Four main factors were identified based on how adult female patients ranked statements: factor 1, patients who focus on their self-perception of their appearance; factor 2, patients who are concerned about the esthetics and function of their teeth; factor 3, patients who are easily influenced by others; factor 4, patients who want to improve their confidence and avoid negative thoughts caused by their teeth. The remaining patients who had other views did not match any of the above four groups. Conclusion: The motivations of adult female patients seeking orthodontic treatment are complex. This study found that most adult female patients fell into one of four typical factor groups. Our findings may improve the adherence of adult female patients by developing a more ideal treatment program. [ABSTRACT FROM AUTHOR]