Non-invasive prediction of preeclampsia using the maternal plasma cell-free DNA profile and clinical risk factors

BackgroundPreeclampsia (PE) is a pregnancy complication defined by new onset hypertension and proteinuria or other maternal organ damage after 20 weeks of gestation. Although non-invasive prenatal testing (NIPT) has been widely used to detect fetal chromosomal abnormalities during pregnancy, its performance in combination with maternal risk factors to screen for PE has not been extensively validated. Our aim was to develop and validate classifiers that predict early- or late-onset PE using the maternal plasma cell-free DNA (cfDNA) profile and clinical risk factors.MethodsWe retrospectively collected and analyzed NIPT data of 2,727 pregnant women aged 24–45 years from four hospitals in China, which had previously been used to screen for fetal aneuploidy at 12 + 0 ~ 22 + 6 weeks of gestation. According to the diagnostic criteria for PE and the time of diagnosis (34 weeks of gestation), a total of 143 early-, 580 late-onset PE samples and 2,004 healthy controls were included. The wilcoxon rank sum test was used to identify the cfDNA profile for PE prediction. The Fisher’s exact test and Mann–Whitney U-test were used to compare categorical and continuous variables of clinical risk factors between PE samples and healthy controls, respectively. Machine learning methods were performed to develop and validate PE classifiers based on the cfDNA profile and clinical risk factors.ResultsBy using NIPT data to analyze cfDNA coverages in promoter regions, we found the cfDNA profile, which was differential cfDNA coverages in gene promoter regions between PE and healthy controls, could be used to predict early- and late-onset PE. Maternal age, body mass index, parity, past medical histories and method of conception were significantly differential between PE and healthy pregnant women. With a false positive rate of 10%, the classifiers based on the combination of the cfDNA profile and clinical risk factors predicted early- and late-onset PE in four datasets with an average accuracy of 89 and 80% and an average sensitivity of 63 and 48%, respectively.ConclusionIncorporating cfDNA profiles in classifiers might reduce performance variations in PE models based only on clinical risk factors, potentially expanding the application of NIPT in PE screening in the future

Impact of Replacing Soft Drinks with Dairy Products on Micronutrient Intakes of Chinese Preschool Children: A Simulation Study

At present, energy surplus and micronutrient deficiency coexist in preschool children in China. The low intake of dairy products accompanied by an increased consumption of soft drinks in this age group reveals some of the reasons for this phenomenon. The purpose of this study was to evaluate the improvement of key micronutrients in preschool children by quantifying the dietary nutritional gap before and after simulating the use of dairy products instead of equal amounts of soft drinks. In the cross-sectional dietary intake survey of infants and young children in China (2018–2019), 676 preschool children aged 3–6 years were randomly selected. Four days of dietary data were collected through an online diary for simulation. The individual intake of soft drinks was substituted at a corresponding volume by soymilk, cow’s milk, or formulated milk powder for preschool children (FMP-PSC). In these three models, the simulated nutrient intake and nutrient inadequacy or surplus were compared with the actual baseline data of the survey. The results of this study indicated that all three models made the nutrient intakes of this group more in line with the recommendations. For the whole population, the replacement of soymilk improved the intake of zinc (from 4.80 to 4.85 mg/d), potassium (from 824.26 to 836.82 mg/d), vitamin A (from 211.57 to 213.92 μg retinol activity equivalent/d), and vitamin B9 (from 115.94 to 122.79 μg dietary folate equivalent/d); the simulation of cow’s milk improved the intake of calcium (from 311.82 to 330.85 mg/d), zinc (from 4.80 to 4.87 mg/d), potassium (from 824.26 to 833.62 mg/d), vitamin A (from 211.57 to 215.12 μg retinol activity equivalent/d), vitamin B2 (from 0.53 to 0.54 mg/d), and vitamin B12 (from 1.63 to 1.67 μg/d); and the substitution of FMP-PSC improved the intake of calcium (from 311.82 to 332.32 mg/d), iron (from 9.91 to 9.36 mg/d), zinc (from 4.80 to 4.96 mg/d), potassium (from 824.26 to 828.71 mg/d), vitamin A (from 211.57 to 217.93 μg retinol activity equivalent/d), vitamin B2 (from 0.53 to 0.54 mg/d), vitamin B9 (from 115.94 to 118.80 μg RA dietary folate equivalent/d), and vitamin B12 (from 1.63 to 1.70 μg/d). Therefore, correct nutritional information should be provided to parents and preschool children. In addition to changing the consumption behavior of soft drinks, it is also necessary to have a diversified and balanced diet. When necessary, the use of food ingredients or nutritional fortifiers can be encouraged

Addressing instance ambiguity in web harvesting

Web Harvesting enables the enrichment of incomplete data sets by retrieving required information from the Web. However, the ambiguity of instances may greatly decrease the quality of the harvested data, given that any instance in the local data set may become ambiguous when attempting to identify it on the Web. Although plenty of disambiguation methods have been proposed to deal with the ambiguity problems in various settings, none of them are able to handle the instance ambiguity problem in Web Harvesting. In this paper, we propose to do instance disambiguation in Web Harvesting with a novel disambiguation method inspired by the idea of collaborative identity recognition. In particular, we expect to find some common properties in forms of latent shared attribute values among instances in the list, such that these shared attribute values can differentiate instances within the list against those ambiguous ones on the Web. Our extensive experimental evaluation illustrates the utility of collaborative disambiguation for a popular Web Harvesting application, and shows that it substantially improves the accuracy of the harvested data

Effects of the Long-Term Climate Change and Selective Discharge Schemes on the Thermal Stratification of a Large Deep Reservoir, Xin’anjiang Reservoir, China

The effects of global warming and precipitation changes on water temperature and thermocline parameters, such as thermocline depth, thickness, and strength, were assessed. A catchment model, coupled with a reservoir thermal model with meteorological input calculated by a downscaled general circulation model (GCM) projection under three representative concentration pathways (RCPs), was applied to the Xin’anjiang Reservoir, located in southeast China. The results indicate that water temperature in each layer increased (decreased) with the rise (decline) in air temperature, especially the surface water temperature. There was a significant negative (positive) correlation between thermocline depth (strength) and air temperature during the period of stratification weakness. The most sensitive phenomenon of water temperature-to-precipitation changes occurred in the middle layer (depth = 30 m). Additionally, the thermocline depth and thickness increased with decreases in hydraulic residence time, which were caused by precipitation increases. According to the simulation experiments driven by RCP outputs, mean water temperature in each water layer in the future (2096–2100) has a strong response to increases in air temperature, which is projected to increase by 0.11–0.62 °C for RCP2.6, 0.76–1.19 °C for RCP4.5, and 1.50–2.35 °C for RCP8.5, compared to the baseline (2012–2016). However, mean water temperature in each water layer from 2096 to 2100 underwent a slight decrease caused by precipitation changes, with a 0.03–0.25 °C decrease for RCP2.6, 0.07–0.40 °C for RCP4.5, and 0.04–0.29 °C for RCP8.5, compared to 2012–2016. The mean thermocline depth in the future (2096–2100) will be significantly decreased, while the mean thermocline thickness will be slightly increased. Over a multiyear timescale, the impacts of air temperature changes are stronger than those induced by precipitation variations. However, the effects of hydraulic residence time changes caused by precipitation changes (especially rainstorm) should be considered in the management of deep reservoirs

Effects of the Long-Term Climate Change and Selective Discharge Schemes on the Thermal Stratification of a Large Deep Reservoir, Xin’anjiang Reservoir, China

The effects of global warming and precipitation changes on water temperature and thermocline parameters, such as thermocline depth, thickness, and strength, were assessed. A catchment model, coupled with a reservoir thermal model with meteorological input calculated by a downscaled general circulation model (GCM) projection under three representative concentration pathways (RCPs), was applied to the Xin’anjiang Reservoir, located in southeast China. The results indicate that water temperature in each layer increased (decreased) with the rise (decline) in air temperature, especially the surface water temperature. There was a significant negative (positive) correlation between thermocline depth (strength) and air temperature during the period of stratification weakness. The most sensitive phenomenon of water temperature-to-precipitation changes occurred in the middle layer (depth = 30 m). Additionally, the thermocline depth and thickness increased with decreases in hydraulic residence time, which were caused by precipitation increases. According to the simulation experiments driven by RCP outputs, mean water temperature in each water layer in the future (2096–2100) has a strong response to increases in air temperature, which is projected to increase by 0.11–0.62 °C for RCP2.6, 0.76–1.19 °C for RCP4.5, and 1.50–2.35 °C for RCP8.5, compared to the baseline (2012–2016). However, mean water temperature in each water layer from 2096 to 2100 underwent a slight decrease caused by precipitation changes, with a 0.03–0.25 °C decrease for RCP2.6, 0.07–0.40 °C for RCP4.5, and 0.04–0.29 °C for RCP8.5, compared to 2012–2016. The mean thermocline depth in the future (2096–2100) will be significantly decreased, while the mean thermocline thickness will be slightly increased. Over a multiyear timescale, the impacts of air temperature changes are stronger than those induced by precipitation variations. However, the effects of hydraulic residence time changes caused by precipitation changes (especially rainstorm) should be considered in the management of deep reservoirs

The Impacts of a Large Water Transfer Project on a Waterbird Community in the Receiving Dam: A Case Study of Miyun Reservoir, China

As natural wetlands are degrading worldwide, artificial wetlands can operate as a substitute to provide waterbirds with refuge, but they cannot replace natural wetlands. Reservoirs, one of the most common artificial wetlands in China, can be of great importance to waterbirds. Miyun reservoir in Beijing, China, has undergone a process similar to a natural lake being constructed in a reservoir. In this study, we surveyed waterbird community composition and evaluated the corresponding land cover and land use change with satellite and digital elevation model images of both before and after the water level change. The results showed that in all modelled scenarios, when the water level rises, agricultural lands suffer the greatest loss, with wetlands and forests following. The water level rise also caused a decrease in shallow water areas and a decline in the number and diversity of waterbird communities, as the components shifted from a shallow-water preferring group (waders, geese and dabbling ducks) to a deep-water preferring group (most diving ducks, gulls and terns). Miyun reservoir ceased to be an important waterbird habitat in China and is no longer an important stopover site for white-naped cranes. A similar process is likely to occur when a natural lake is constructed in a reservoir. Therefore, we suggest that policymakers consider the needs of waterbirds when constructing or managing reservoirs

Voltage-controlled nonlinear optical properties in gold nanofilms via electrothermal effect

Abstract Dynamic control of the optical properties of gold nanostructures is crucial for advancing photonics technologies spanning optical signal processing, on-chip light sources and optical computing. Despite recent advances in tunable plasmons in gold nanostructures, most studies are limited to the linear or static regime, leaving the dynamic manipulation of nonlinear optical properties unexplored. This study demonstrates the voltage-controlled Kerr nonlinear optical response of gold nanofilms via the electrothermal effect. By applying relatively low voltages (~10 V), the nonlinear absorption coefficient and refractive index are reduced by 40.4% and 33.1%, respectively, due to the increased damping coefficient of gold nanofilm. Furthermore, a voltage-controlled all-fiber gold nanofilm saturable absorber is fabricated and used in mode-locked fiber lasers, enabling reversible wavelength-tuning and operation regimes switching (e.g., mode-locking—Q-switched mode-locking). These findings advance the understanding of electrically controlled nonlinear optical responses in gold nanofilms and offer a flexible approach for controlling fiber laser operations