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Aims: To explore the inter-predictive role and causal relationship between family functioning, self-perceived burden and loneliness in people with type 2 diabetes. Methods: In this study, patients with type 2 diabetes admitted to two tertiary care hospitals in China were selected for an 8-month follow-up, and the patients' scores on the Family Functioning, Self-perceived Burden, and Loneliness scales were measured repeatedly at three time periods: during hospitalisation (T1), 1 month after discharge (T2), and 3 months after discharge (T3). Results: The results showed that family function at the T1 time point had a negative predictive effect on self-perceived burden at the T2 time point, β = − 0.43, P = 0.005. Loneliness at the T1 time point had a positive predictive effect on self-perceived burden at the T2 time point, β = 0.08, P = 0.021. Unlike the pathway at time point T1, family functioning at time point T2 negatively predicted loneliness at time point T3, β = − 0.32, P = 0.013. Loneliness at time point T2 positively predicted family functioning at time point T3, β = 0.025, P = 0.013. Loneliness at time point T2 negatively predicted self-perceived burden at time point T3 (P = 0.011). Conclusions: The results of the cross-lagged analysis show that there is a mutually predictive and moderating relationship between family functioning and loneliness in patients with type 2 diabetes. Loneliness can predict the level of self-perceived burden at the next time point. [ABSTRACT FROM AUTHOR]

• The first large-scale multicenter retrospective study conducted in Northern China. • Both outcomes of fresh and frozen-thawed embryo transfer cycles in IVF were explored. • Exposure to O 3 , CO, and NO 2 are negatively associated with fresh transfer outcomes. • SO 2 exposure is inversely correlated with pregnancy outcomes in FET cycles. • Air pollution is associated with higher risk of ectopic pregnancy and lower oocyte yield. Exposure to ambient air pollution has been reported to be inversely correlated with human reproductive health. However, the results of previous studies exploring the association between air pollution and in vitro fertilization (IVF) outcomes are conflicting, and further research is needed to clarify this association. This study aimed to investigate the associations between exposure to air pollutants and IVF outcomes. We conducted a multicenter retrospective cohort study involving 20,835 patients from four cities in Northern China, contributing to 11,787 fresh embryo transfer cycles, 9050 freeze-all cycles, and 17,676 frozen-thawed embryo transfer (FET) cycles during 2014–2018. We calculated the daily average concentrations of six criteria air pollutants (PM 2.5 , PM 10 , O 3 , NO 2 , CO, and SO 2) during different exposure windows in IVF treatment timeline using data from the air monitoring station nearest to the residential site as approximate individual exposure. Generalized estimation equation models were used to assess the association between air pollution exposure and IVF outcomes. Exposure to O 3 , NO 2 , and CO during most exposure windows in fresh embryo transfer cycles were correlated with lower possibilities of biochemical pregnancy, clinical pregnancy, and live birth. An inverse association of exposure to O 3 and SO 2 with pregnancy outcomes was observed in FET cycles. In addition, we found a significant association of exposure to air pollutants with a higher risk of ectopic pregnancy and lower oocyte yield. Our study provided large-scale human evidence of the association between air pollution and adverse human reproductive outcomes in the population opting for IVF. Thus, exposure to air pollutants in the population opting for IVF should be limited to improve treatment outcomes. [ABSTRACT FROM AUTHOR]

To assess the associations between air pollution and the pregnancy rate of IVF, we performed a retrospective cohort study on 1455 women who underwent the first fresh IVF cycle at a fertility center from January 2014 to April 2018 and lived in Shenyang during treatment. Binary logistic regression models were used to evaluate the effect of an interquartile range increase in each pollutant on the intrauterine pregnancy rate. Both average chronic and daily acute exposure to air pollution were considered. Increased O 3 (adjusted OR = 0.87, 95% CI: 0.81, 0.98) during the period from gonadotropins starting to oocyte retrieval was associated with decreased probability of intrauterine pregnancy, especially the day before oocyte retrieval (adjusted OR = 0.86, 95% CI: 0.78, 0.95). Our results suggest that exposure to O 3 before oocyte retrieval has an adverse effect on intrauterine pregnancy. Future studies should be performed in order to confirm our findings., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Clinical named entity recognition (CNER) is a fundamental and crucial task for clinical and translation research. In recent years, deep learning methods have achieved significant success in CNER tasks. However, these methods depend greatly on recurrent neural networks (RNNs), which maintain a vector of hidden activations that are propagated through time, thus causing too much time to train models. In this paper, we propose a residual dilated convolutional neural network with the conditional random field (RD-CNN-CRF) for the Chinese CNER, which makes the model asynchronous in computation and thus speeding up the training period dramatically. To be more specific, Chinese characters and dictionary features are first projected into dense vector representations, then they are fed into the residual dilated convolutional neural network to capture contextual features. Finally, a conditional random field is employed to capture dependencies between neighboring tags and obtain the optimal tag sequence for the entire sequence. Computational results on the CCKS-2017 Task 2 benchmark dataset show that our proposed RD-CNN-CRF method competes favorably with state-of-the-art RNN-based methods both in terms of computational performance and training time.