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PurposeVarious treatments have been investigated for Graves’ ophthalmopathy (GO). We aimed to provide an overall profile of the efficacy and tolerability of various interventions for active and moderate to severe GO.MethodsPubMed, Embase and the Cochrane Central Register of Controlled Trials were searched on 6 July 2018. Randomised controlled trials (RCT) investigating GO treatments were included. Two researchers independently extracted data according to a predefined form. A random effects network meta-analysis was performed using a frequentist approach. The primary outcome was efficacy, and the secondary outcome was tolerability (side effect discontinuation).ResultsThirty-three studies with 1846 patients with GO were included. Orbital radiotherapy (ORT) plus intravenous glucocorticoids (IVGC) (OR 27.11; 95% CI 4.57 to 160.92), mycophenolate mofetil (MMF) (24.40, 95% CI 5.28 to 112.67), oral glucocorticoids (OGC) plus ciclosporin (20.22, 95% CI 1.60 to 255.20), IVGC plus MMF (12.08, 95% CI 2.96 to 49.35), teprotumumab (8.92, 95% CI 2.51 to 31.77), ORT plus OGC (4.88, 95% CI 1.25 to 19.06), rituximab (RTX) (4.85, 95% CI 1.18 to 19.86), somatostatin analogues (4.23, 95% CI 1.60 to 11.16), OGC plus azathioprine (AzA) (5.77, 95% CI 1.17 to 28.47) and IVGC (4.96, 95% CI 1.96 to 12.55) showed significantly better improvement than no treatment. ORT plus IVGC ranked first, followed by MMF. High heterogeneity and significant local inconsistency were observed in the RTX studies. The results of the sensitivity analyses were similar to those of the main analysis.ConclusionA robust recommendation regarding the best treatment cannot be made, because most evidence was rated as low or very low quality according to the Grading of Recommendations, Assessment, Development and Evaluations framework. Large RCTs and individual participant data meta-analyses are necessary to confirm these results and explore potential moderators.PROPERO trial registration numberCRD42018103029.
Background Influenza epidemics pose a threat to human health. It has been reported that meteorological factors (MFs) are associated with influenza. This study aimed to explore the similarities and differences between the influences of more comprehensive MFs on influenza in cities with different economic, geographical and climatic characteristics in Fujian Province. Then, the information was used to predict the daily number of cases of influenza in various cities based on MFs to provide bases for early warning systems and outbreak prevention. Method Distributed lag nonlinear models (DLNMs) were used to analyse the influence of MFs on influenza in different regions of Fujian Province from 2010 to 2021. Long short-term memory (LSTM) was used to train and model daily cases of influenza in 2010–2018, 2010–2019, and 2010–2020 based on meteorological daily values. Daily cases of influenza in 2019, 2020 and 2021 were predicted. The root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (SMAPE) were used to quantify the accuracy of model predictions. Results The cumulative effect of low and high values of air pressure (PRS), air temperature (TEM), air temperature difference (TEMD) and sunshine duration (SSD) on the risk of influenza was obvious. Low (< 979 hPa), medium (983 to 987 hPa) and high (> 112 hPa) PRS were associated with a higher risk of influenza in women, children aged 0 to 12 years, and rural populations. Low (< 9 °C) and high (> 23 °C) TEM were risk factors for influenza in four cities. Wind speed (WIN) had a more significant effect on the risk of influenza in the ≥ 60-year-old group. Low (< 40%) and high (> 80%) relative humidity (RHU) in Fuzhou and Xiamen had a significant effect on influenza. When PRS was between 1005–1015 hPa, RHU > 60%, PRE was low, TEM was between 10–20 °C, and WIN was low, the interaction between different MFs and influenza was most obvious. The RMSE, MAE, MAPE, and SMAPE evaluation indices of the predictions in 2019, 2020 and 2021 were low, and the prediction accuracy was high. Conclusion All eight MFs studied had an impact on influenza in four cities, but there were similarities and differences. The LSTM model, combined with these eight MFs, was highly accurate in predicting the daily cases of influenza. These MFs and prediction models could be incorporated into the influenza early warning and prediction system of each city and used as a reference to formulate prevention strategies for relevant departments.
Background This study adopted complete meteorological indicators, including eight items, to explore their impact on hand, foot, and mouth disease (HFMD) in Fuzhou, and predict the incidence of HFMD through the long short-term memory (LSTM) neural network algorithm of artificial intelligence. Method A distributed lag nonlinear model (DLNM) was used to analyse the influence of meteorological factors on HFMD in Fuzhou from 2010 to 2021. Then, the numbers of HFMD cases in 2019, 2020 and 2021 were predicted using the LSTM model through multifactor single-step and multistep rolling methods. The root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (SMAPE) were used to evaluate the accuracy of the model predictions. Results Overall, the effect of daily precipitation on HFMD was not significant. Low (4 hPa) and high (≥ 21 hPa) daily air pressure difference (PRSD) and low (< 7 °C) and high (> 12 °C) daily air temperature difference (TEMD) were risk factors for HFMD. The RMSE, MAE, MAPE and SMAPE of using the weekly multifactor data to predict the cases of HFMD on the following day, from 2019 to 2021, were lower than those of using the daily multifactor data to predict the cases of HFMD on the following day. In particular, the RMSE, MAE, MAPE and SMAPE of using weekly multifactor data to predict the following week's daily average cases of HFMD were much lower, and similar results were also found in urban and rural areas, which indicating that this approach was more accurate. Conclusion This study’s LSTM models combined with meteorological factors (excluding PRE) can be used to accurately predict HFMD in Fuzhou, especially the method of predicting the daily average cases of HFMD in the following week using weekly multifactor data.
Crop yield mainly depends on environment and cultivation practices that vary according to a growing environment. However, an oat (Avena sativa L.)-common vetch (Vicia sativa L.) intercrop system has not been fully developed in the agro-pastoral ecotone of Inner Mongolia, China. This study evaluated the effects of seven treatments, including five oat-common vetch intercropping patterns, sole oat, and sole vetch on yield and quality performance at different growth periods [75 days after sowing (DAS), 90 DAS, 105 DAS], on the basis of field experiments conducted in the agro-pastoral ecotone of Inner Mongolia in 2015 and 2016. The OV3:1 (oat intercropped with common vetch at seeding ratios 3:1) treatment at 105 DAS in 2016 was superior to other treatments, as it achieved the highest shoot dry matter, increasing by 24.1% and 37.1% compared to sole oat and common vetch. The crude fat (CF) contents, CF yield, and crude protein (CP) yield increased under OV3:1, and acid detergent fiber (ADF) decreased under OV3:1, compared to monoculture. The results indicate that intercropping is an efficient cropping system for the agro-pastoral ecotone of Inner Mongolia. The appropriate proportion of oat and common vetch intercropping at 3:1 and harvesting time not only increases crop yield but also improves the crop quality.
Woodhouse-Sakati syndrome (WSS, MIM 241080) is a rare neuroendocrine disease characterized by hair loss, hypogonadism, diabetes, hearing loss, and extrapyramidal syndrome, and is usually caused by mutations in the DCAF17 gene as an inherited disease. DCAF17 plays an important role in mammalian gonadal development and infertility. So far, there have been no WSS reports in China. The patient introduced in this case is from a consanguineous family. The main symptoms of the patient were alopecia and gonadal agenesis. Other symptoms such as hearing loss, intellectual disability, and hyperglycemia were remarkable, and these symptoms are often observed in WSS patients. We found a nonsense mutation in the 11th exon of the gene DCAF17 (Refseq: NM_025000) in the patient and her younger brother, which confirmed the diagnosis of WSS. The genetic results also showed that the mutation was inherited from their healthy first-cousin parents.
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