预测：2016年FDA即将批准新药概述

2015 年全年美国 FDA 共批准 45 个新分子实体和新生物制品,本文列出了 2016 年可能获 FDA 批准的新药目录,并对具体批准日 期进行了预测。     

褐飞虱（Nilaparvata lugens (Stal)）前期迁入与ENSO指标的遥相关及其中长期预测

分析了全国6个不同褐飞虱发生区内16个监测点的褐飞虱（Nilaparvata lugens（St（a）l））前期迁入量与从前两年1月至当年6月各月ENSO 指标（包括4个Nino区海温和南方涛动指数（SOI）的月平均距平值）遥相关的时空分布.结果表明,与褐飞虱前期迁入量显著遥相关的ENSO指标主要为N3区、N4区和N3.4区的海温,三者共占显著相关指标总数的71.8%.在时间分布上,显著遥相关的ENSO指标主要分布在前两年和前一年（约占84%）,当年仅占16.7%.从相关性质来看,褐飞虱前期迁入量与各Nino区海温在前两年至前一年春季之前呈负相关,而与前一年冬季至当年春季呈正相关;与前一年夏秋季ENSO指标的相关性质则无明显规律.褐飞虱前期迁入量与各Nino区海温和与SOI遥相关的相关性质相反.以前期显著相关的ENSO指标为预测因子,用逐步回归法建立褐飞虱前期迁入量的中长期预测方程.筛选出历史回检率和预测准确性较高的方程,经集成后共获得12个预报模型,可提前3～27个月作出预测,预测的准确率为88.9%.     

Progress toward forecasting product quality and quantity of mammalian cell culture processes by performance‐based modeling

The production of biopharmaceuticals requires highly sophisticated, complex cell based processes. Once a process has been developed, acceptable ranges for various control parameters are typically defined based on process characterization studies often comprising several dozens of small scale bioreactor cultivations. A lot of data is generated during these studies and usually only the information needed to define acceptable ranges is processed in more detail. Making use of the wealth of information contained in such data sets, we present here a methodology that uses performance data (such as metabolite profiles) to forecast the product quality and quantity of mammalian cell culture processes based on a toolbox of advanced statistical methods. With this performance based modeling (PBM) the final product concentration and 12 quality attributes (QAs) for two different biopharmaceutical products were predicted in daily intervals throughout the main stage process. The best forecast was achieved for product concentration in a very early phase of the process. Furthermore, some glycan isoforms were predicted with good accuracy several days before the bioreactor was harvested. Overall, PBM clearly demonstrated its capability of early process endpoint prediction by only using commonly available data, even though it was not possible to predict all QAs with the desired accuracy. Knowing the product quality prior to the harvest allows the manufacturer to take counter measures in case the forecasted quality or quantity deviates from what is expected. This would be a big step towards real‐time release, an important element of the FDA's PAT initiative. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1119–1127, 2015     

A mathematical model for mugwort (Artemisia vulgaris L.) pollen forecasts

Pollen forecasts are a fundamental prerequisite to obtain prophylactic measures for allergic individuals. Mugwort belongs to the most relevant allergenic pollen types after grasses and birch. An approach to modeling of mugwort pollen concentrations has not been attempted previously in Germany. A process-oriented mathematical model for the relative local daily average mugwort airborne pollen concentration was developed on the basis of pollen and weather data measured during a 6-year period. The model depends on the daily minimum and maximum temperature, amount of precipitation and atmospheric pressure, which have to and can be supplied by measurement and prediction. The comparison of modeling results and pollen counting for an additional year confirms the fitness of the model. A computer program was written, which rests upon the model and supplies daily predictions of mugwort pollen flight during the period of the weather forecast. The latter should allow a pollen forecasting period of about 5 days, with an accuracy of about 32–63% explained variance, which in view of the low mugwort pollen counts (nine grains/m³ maximum in the validation year) represents a high relative measurement error. The mathematical model may serve to improve and rationalize of present pollen forecasts.     

影响二化螟种群变化的主导因素分析及其趋势的简易预测

通过对广德县1978～1994年二化螟系统调查资料的分析,表明7～10月为引起种群数量年变化的关键时期;7、8月的平均温度为引起种群年变化的主导因子。并选用7月均温,建立了年变化趋势的简易预测方法,16年回检,正确率达87．5％,2年预检,准确率为100％。     

A predictive study on the beginning of the pollen season for Gramineae andolea europaea L.

Summary On the basis of the results of seven years (1982–1988) of pollen and meteorological monitoring in the atmosphere of Perugia and Ascoli Piceno (central Italy) beginning of pollen season forecasts for Gramineae and Olea europaea L. are reported. The beginning of the pollen season for grass varied between May 2 nd and May 27th while for Olea it varied between May 26 th and June 23rd. By a statistical analysis of these data several significant correlations were found between the onset of the principal period of pollination and the air temperature in the preceding months and the number of ?heat units? required to flower. Utilizing multiple regressions a predictive method of the beginning of pollen season for both the taxa is reported.     

茶黑刺粉虱蛹和卵的发育分级及与其防治适期的相关性

20 0 0年 4～ 6月 ,每 5日在皖南黑刺粉虱Aleurocanthusspiniferus(Quaintance)常发茶园中以平行跳跃法选 5 0个样方。每样方为 1m茶行 ,查其上、中、下层各 2片成叶上各虫态粉虱的数量 ;采回 2 0 0头蛹于立体显微镜下解剖。越冬代蛹期 32～ 38d。据蛹体形态和颜色的显著变化而分为 4级 :体液乳白色( 1 2～ 1 4d)、体液淡黄色 ( 6～ 8d)、体液橙红色 ( 1 1～ 1 2d)和体液淡紫色阶段 ( 3～ 4d)。引入该粉虱于盆载茶苗上 ,观察其生物学习性。第 1代卵期 2 2～ 2 8d ,据卵颜色的显著变化分为 4级 :乳白色 ( 2～ 4d)、淡黄色 ( 2～ 3d)、橙红色 ( 1 5～ 1 7d)和紫黑色阶段 ( 3～ 4d)。第 1代幼虫期 2 5～ 2 8d ,其中 1龄 9～ 1 2d ,2龄 9d ,3龄 7d ,蛹期 7～ 8d。越冬代成虫盛期和第 1代 1龄盛期为防治适期 ,可较好地用蛹或卵的分龄分级法预测。越冬代蛹全部羽化之时 ,又恰是 1龄幼虫盛期 ,易于掌握     

Global evaluation of a semiempirical model for yield anomalies and application to within‐season yield forecasting

Quantifying the influence of weather on yield variability is decisive for agricultural management under current and future climate anomalies. We extended an existing semiempirical modeling scheme that allows for such quantification. Yield anomalies, measured as interannual differences, were modeled for maize, soybeans, and wheat in the United States and 32 other main producer countries. We used two yield data sets, one derived from reported yields and the other from a global yield data set deduced from remote sensing. We assessed the capacity of the model to forecast yields within the growing season. In the United States, our model can explain at least two‐thirds (63%–81%) of observed yield anomalies. Its out‐of‐sample performance (34%–55%) suggests a robust yield projection capacity when applied to unknown weather. Out‐of‐sample performance is lower when using remote sensing‐derived yield data. The share of weather‐driven yield fluctuation varies spatially, and estimated coefficients agree with expectations. Globally, the explained variance in yield anomalies based on the remote sensing data set is similar to the United States (71%–84%). But the out‐of‐sample performance is lower (15%–42%). The performance discrepancy is likely due to shortcomings of the remote sensing yield data as it diminishes when using reported yield anomalies instead. Our model allows for robust forecasting of yields up to 2 months before harvest for several main producer countries. An additional experiment suggests moderate yield losses under mean warming, assuming no major changes in temperature extremes. We conclude that our model can detect weather influences on yield anomalies and project yields with unknown weather. It requires only monthly input data and has a low computational demand. Its within‐season yield forecasting capacity provides a basis for practical applications like local adaptation planning. Our study underlines high‐quality yield monitoring and statistics as critical prerequisites to guide adaptation under climate change.     

应用前期ENSO指标做棉铃虫大发生预测

分析了山东郓城26a(1974～1999)和德州22a(1978～1999)棉铃虫3代百株累计卵量、江苏丰县20a(1980～1999)棉铃虫2代百株累计卵量与从前两年1月份开始到当年7月份的ENSO指标(包括厄尔尼诺5个海温区N12、N3、N4、NC、NW的月平均海温距平)和南方涛动指数(SOI)的遥相关关系。遥相关分析结果表明德州、郓城三代卵量和丰县二代卵量与ENSO各指标遥相关关系的时间变化规律很相似,与各时段的N4均呈正相关,与NW和SOI大多数月份呈负相关。从中筛选出相关显著(p<0.05)的区域和时段作为预测因子,根据判别分析法用不同因子或因子组合分别建立了郓城、德州棉铃虫三代卵、丰县棉铃虫二代卵量的大发生预测模型,并对各模型进行回测检验及5～6a的预测检验,根据其预测效果筛选出最佳的灾变预测模型。结果表明,N4区的因子或因子组合建立的模型对德州、郓城棉铃虫三代卵量和丰县棉铃虫二代卵量的预测效果最好,可提前15～25个月做出大发生预测。     

Transport of airborne pollen into the city of Thessaloniki: the effects of wind direction, speed and persistence

We examined the effect of the wind vector analyzed into its three components (direction, speed and persistence), on the circulation of pollen from different plant taxa prominent in the Thessaloniki area for a 4-year period (1996–1999). These plant taxa were Ambrosia spp., Artemisia spp., Chenopodiaceae, Corylus spp., Cupressaceae, Olea europaea, Pinaceae, Platanus spp., Poaceae, Populus spp., Quercus spp., and Urticaceae. Airborne pollen of Cupressaceae, Urticaceae, Quercus spp. and O. europaea make up approximately 70% of the total average annual pollen counts. The set of data that we worked with represented days without precipitation and time intervals during which winds blew from the same direction for at least 4 consecutive hours. We did this in order to study the effect of the different wind components independently of precipitation, and to avoid secondary effects produced by pollen resuspension phenomena. Factorial regression analysis among the summed bi-hourly pollen counts for each taxon and the values of wind speed and persistence per wind direction gave significant results in 22 cases (combinations of plant taxa and wind directions). The pollen concentrations of all taxa correlated significantly with at least one of the three wind components. In seven out of the 22 taxon-wind direction combinations, the pollen counts correlated positively with wind persistence, whereas this was the case for only two of the taxon-wind speed combinations. In seven cases, pollen counts correlated with the interaction effect of wind speed and persistence. This shows the importance of wind persistence in pollen transport, particularly when weak winds prevail for a considerable part of the year, as is the case for Thessaloniki. Medium/long-distance pollen transport was evidenced for Olea (NW, SW directions), Corylus (NW, SW), Poaceae (SW) and Populus (NW).