Comparison of embryo implantation potential between time-lapse incubators and standard incubators: a randomized controlled study.

RESEARCH QUESTION: What are the potential clinical benefits of embryo culture and assessment in a time-lapse incubator compared with a standard incubator using static assessment? DESIGN: This large multicentre, single-blinded, randomized controlled study included 1224 participants randomly assigned (1:1) to the time-lapse or standard incubator group. In all patients one or two embryos were transferred on day 3. The primary outcome was the implantation rate in the first embryo transfer cycle. Secondary outcomes included the cumulative implantation rate, live birth rate in the first embryo transfer cycle and cumulative live birth rate. RESULTS: Among 1224 participants recruited, 1182 underwent embryo transfer. The number of successfully implanted embryos in the first transfer cycle was significantly higher in the time-lapse incubator group (time-lapse group: 52.35%, standard incubator group: 47.11%, P = 0.014). The implantation rate in the first embryo transfer cycle was still significantly higher in the time-lapse group than the standard incubator group after adjusting for age, body mass index, medical centre and embryo status (relative risk 1.11, 95% confidence interval 1.02-1.20, P = 0.020). However, the cumulative implantation rate, live birth rate in the first embryo transfer cycle and cumulative live birth rate were not statistically different between the groups. CONCLUSIONS: The implantation rate in the first embryo transfer cycle was significantly improved in the time-lapse group, but the effect of the time-lapse system on the cumulative implantation rate or cumulative live birth rate was not significant. The embryo assessment method offered by time-lapse systems rather than an undisturbed environment may play an important role in improving the implantation rate in the first embryo transfer cycle. These results are only applicable to young patients.

[Analysis of the Continuous Heavy Pollution Process in the Winter of 2016 in Beijing, Tianjin, and Hebei].

From December 16 to 21, 2016, continuous heavy haze occurred in the Beijing-Tianjin-Hebei region of China. To further understand the development mechanism of haze and improve the forecasting of haze events, a variety of data, background circulation, and the meteorological elements of this severe haze process were comprehensively analyzed. The results show that the process lasted for a long time, pollution intensity was high, influence area was wide, visibility was low, and external transport was the main cause. Aerosols were mainly distributed at a height of 600 m, and there was a certain extreme anomaly. The static weather index and air quality index showed a strong correlation. The air in the Beijing-Tianjin-Hebei region is controlled by zonal circulation in front of a high-pressure ridge, which maintains the westerly airflow. Cold-air activity is weak, and downflow is dominant. The water vapor content is low, the cloud cover is limited at high altitudes, and a warm ridge extends northwards at low altitudes. Limited static wind on the ground, high relative humidity, and low mixing-layer height are not conducive to the horizontal and vertical diffusion of pollutants.

[Relationship Between Atmospheric Visibility and PM2.5 Concentrations and Distributions].

Monitoring data were used to analyze the relationships among relative humidity (RH), visibility, and PM2.5 concentrations. A strong, linear relationship expression between the extinction coefficient and PM2.5 concentrations at different relative humidities is proposed. The mean correlation coefficient at RH 40%-90% was higher than 0.75 for most of Central and Eastern China, and reached 0.9 in Beijing. Comparatively, the extinction efficiency of PM2.5 was much larger in Beijing, the Yangzi River Delta Region, and Sichuan than in other regions. However, the influence of RH on visibility varied from region to region. In Beijing, RH dominated the decrease in visibility when RH>90%, while in Guangzhou, this was the case when RH>80%. From 1980 to 1996, the annual variation in PM2.5 concentrations was not significant in Beijing and the PM2.5 concentrations were significantly higher than in the 2000s because of the dominant mode of heating. From 1997 to 2009, PM2.5 concentrations in Beijing showed a slow downward trend, and from 2010 to 2012, showed an upward trend. Since 1980, PM2.5 concentrations in the entire country have been rising. PM2.5 concentrations have always been higher in North China than in other parts of the country.

[Concentration Characteristics of PM2.5 and the Causes of Heavy Air Pollution Events in Beijing During Autumn and Winter].

To study the changing of characteristics and formation mechanisms of PM2.5 in Beijing during the last two years, particulate matter concentrations, weather conditions, and air-mass trajectories were analyzed during severe pollution episodes in fall and winter 2016-2017 using routine observations and the TrajStat model. Results showed that 13 heavy pollution events, each lasting at least two days, occurred in Beijing. Of these, approximately 61.5% occurred in winter, characterized by heavier pollution concentrations and longer durations than those occurring in autumn. A low-pressure gradient, high humidity, low surface wind speed, low boundary layer, and particular terrain (i. e., being surrounded by mountains on three sides) all contributed to the high occurrence frequency of severe pollution episodes in autumn and winter. During the pollution episodes, the average ratio of PM2.5 to PM10 reached 0.86. The air-masses during the accumulation stage were mainly transported from the northwest, west, southwest, and southeast of Beijing. The southwestern and southeastern transmission paths accounted for 21.6% of the total pollution load. In addition, the WRF-CAMx model was used to quantitatively analyze the contributions of local and external sources to the concentrations of PM2.5 in Beijing during 16-22 December 2016. Based on this analysis, PM2.5 contributions notably varied with different air-masses; in the case of southern air-masses, external sources dominated the PM2.5 concentrations in Beijing and local contributions decreased rapidly; in contrast, in the case of northwestern air-masses, the opposite pattern occurred. Overall, the contribution of local sources to PM2.5 concentrations in Beijing varied from 16.5% to 69.3% during the monitored pollution episodes.

[Characteristics of Elements and Potential Ecological Risk Assessment of Heavy Metals in PM2.5 at the Southwest Suburb of Chengdu in Spring].

PM2.5 samples were collected at the southwest suburb of Chengdu in spring (in May 2012 and 2014). The mass concentrations of PM2.5 were determined by the weight method, and 24 chemical elements in PM2.5 were analyzed by XRF. To study the pollution characteristics and sources of chemical elements, and the potential ecological risk of heavy metals in PM2.5, the Geo-accumulation Index, Enrichment Factor, and Potential Ecological Risk Index methods were applied, respectively. The results indicated that the mass concentrations of PM2.5 in spring at the southwest suburb of Chengdu were very high, compared with American EPA's Standard and National Standard level-Ⅱ. The detection of chemical element composition in PM2.5 showed that K and S were the main elements, whereas the contents of Ga, Cs, Co, Cd, and V were the lowest. The differences of elemental concentrations in PM2.5 showed relatively large differences, when compared with domestic and foreign representative cities. Se, Cd, As, Br, S, Pb, Cl and Zn were present at an extremely high level of geo-accumulation degree, which revealed that the pollution coming from human activities was serious. The analysis results of enrichment factor showed that Se, Cd, As, Br, Cl, Pb, Zn and S elements were highly enriched or hyper accumulated, Cu, Cs, Ni, Ga and Co elements were moderately enriched, and they were mainly from human activities rather than soil dust. Cr, Mn, Ca and V elements were mildly enriched, and they were from both natural sources and human activities. Na, Ti, Al, Si and Mg elements were scarcely enriched, and they were mainly from natural sources. The ecological risk assessment of heavy metals showed that the order of potential ecological risk inedx of heavy metals in PM2.5 was Cd > As > Pb > Cu > Zn > Ni > Co > Cr > Mn > V > Ti, while the ecological harm degree of Cd was extremely strong, and the whole potential ecological risk degree was very strong.