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Advances in genotypic antimicrobialresistance testing: a comprehensive review

Science China Life Sciences 2025年第01期 130-143页

作者： Boheng Duan Xianjun Zeng Junping Peng Huan Kui College of Nanchang University Department of Imaging The Second Affiliated Hospital of Nanchang University NHC Key laboratory of systems Biology of Pathogens National Institute of Pathogen BiologyChinese Academy of Medical Sciences & Peking Union Medical College Key laboratory of Respiratory Disease Pathogenomics Chinese Academy of Medical Sciences & Peking Union Medical College Key laboratory of Pathogen Infection Prevention and Control (Ministry of Education) State Key Laboratory of Respiratory Health and MultimorbidityNational Institute of Pathogen BiologyChinese Academy of Medical Sciences & Peking Union Medical College

Antimicrobial resistance(AMR) represents a substantial threat to global public health, complicating the treatment of common infections and leading to prolonged illness and escalated healthcare expenses. To effectively combat AMR, timely and accurate detection is crucial for AMR surveillance and individual-based therapy. Phenotypic antibiotic resistance testing(AST) has long been considered the gold standard in clinical applications, serving as the foundation for clinical AMR diagnosis and optimized therapy. It has significantly contributed to ensuring patients′ health and the development of novel antimicrobials. Despite advancements in automated culture-based AST technologies,inherent limitations impede the widespread use of phenotypic AST in AMR surveillance. Genotypic AST technologies offer a promising alternative option, exhibiting advantages of rapidity, high sensitivity, and specificity. With the continuous advancement and expanding applications of genotypic AST technologies, such as microfluidics, mass spectrometry, and high-resolution melting curve analysis, new vigor has been injected into the development and clinical implementation of genotypic AST technologies. In this narrative review, we discuss the principles, applications, and advancements of emerging genotypic AST methods in clinical settings. The comprehensive review aims to highlight the significant scientific potential of emerging genotypic AST technologies in clinical AMR diagnosis, providing insights to enhance existing methods and explore novel approaches.

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Fine-tuning the spatial allocation of phytohormones for smart canopy, smart breeding, and smart agriculture

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Science China Life Sciences 2025年第1期 309-310页

作者： Tao Zhou Lin Li National Key laboratory of Crop Genetic Improvement Huazhong Agricultural University HuBei HongShan laboratory

The dual challenges of global climate change and population growth have increased demand for higher crop yields per unit area. The innovative technology of smart agriculture aims to synergize breeding, cultivation, and production through the application of biological and informatics technologies. Historically, the “Green Revolution” introduced semidwarf varieties of certain key crops by utilizing mutations affecting gibberellin pathways, which significantly increased planting densities and yields.

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20 TO 30-DAY AND 30 TO 60-DAY OSCILLATIONS IN ASSIMILATED global DATASETS USING TRMM RAINFALL OBSERVATIONS

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Journal of Tropical Meteorology 2010年第3期16卷 210-220页

作者：陶丽杨松陆维松 Key laboratory of Meteorological Disaster of Ministry of Education I.M.systems Group at noaa/NESDIS Camp Springs

The influences of Tropical Rainfall Measuring Mission （TRMM） precipitation products on the structure and underlying physics of intraseasonal oscillation （ISO） are investigated with the U.S. National Aeronautics and Space Administration Goddard Earth Observing System model version 3 （GEOS-3） data assimilation system （DAS）. The strong ISO phase in the 1998 summer is apparently located in the Asian monsoon region and the east equatorial Pacific region. The eastward propagation is a dominant feature for the tropical ISO at 20 to 30-day oscillation while the northeastward propagation is the salient ISO at 30 to 60-day oscillation over the 10~N to 25~N belt region. It appears that the Kelvin wave structure is for the tropical 20 to 30-day oscillation. The tropical 30 to 60-day oscillation has the characteristics of the Kelvin-Rossby wave. The impact of satellite-derived precipitation （and its associated latent heating） on the ISO intensity is limited in the GEOS-3 assimilation system. However, its impact on the ISO spatial structures is obvious. Overall, the results demonstrate a better eastward propagation and a northward propagation of ISO with the TRMM precipitation simulation, indicating that latent heating is very important in exciting the equatorial ISO. Key words： 20 to 30-day oscillation; 30 to 60-day oscillation; GEOS data assimilation system; Kelvin wave; TRMM precipitation

关键词： infrared remote sensing retrieval atmospheric sounding profile MODIS AIRS

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Modeling study of a severe aerosol pollution event in December 2013over Shanghai China:An application of chemical data assimilation

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Particuology 2015年第3期13卷 41-51页

作者： Jian-Bin Wu Jianming Xu Mariusz Pagowski Fuhai Geng Songqiang Gu Guangqiang Zhou Ying Xie Zhongqi Yu Shanghai Meteorological Service noaa Earth System Research laboratory(ESRL)

This study focuses on the importance of initial conditions to air-quality predictions. We ran assimilation experiments using the WRF-Chem model and grid-point statistical interpolation （GSI）, for a 9-day severe particulate matter pollution event that occurred in Shanghai in December 2013. In this application, GSI used a three-dimensional variational approach to assimilate ground-based PM2.s observations into the chemical model, to obtain initial fields for the aerosol species. In our results, data assimilation significantly reduced the errors when compared to a simulation without assimilation, and improved forecasts of PM2.5 concentrations. Despite a drop in skill directly after the assimilation, a positive effect was present in forecasts for at least 12-2413, and there was a slight improvement in the 48-h forecasts. In addition to performing well in Shanghai, the verification statistics for this assimilation experiment are encouraging for most of the surface stations in China.

关键词： Data assimilationAerosol pollutionInitial conditionForecastingPM2.5

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Trends in Extremes of Surface Humidity, Temperature, and Summertime Heat Stress in China

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Advances in Atmospheric Sciences 2001年第5期18卷 742-751页

作者： Julian X.L. Wang and Dian J. Gaffen noaa/ Air Resources laboratory, Silver Spring, MD, 20910, USA noaa/ Air Resources laboratory Silver Spring USA

In the past half century, the mean summertime temperature in China has increased, with nights warm- ing more than days. Using surface station observations, we show that the frequency of extreme heat-stress events in China, caused by extremely hot and humid days as well as by heatwaves lasting for a few days, has increased over the period from 1951 to 1994 When humidity is high, hot weather can cause heat stress in humans. The increased heatrstress trend may pose a public health problem

关键词： Trend detection Climate change Public health

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Scaling the Microphysics Equations and Analyzing the Variability of Hydrometeor Production Rates in a Controlled Parameter Space

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Advances in Atmospheric Sciences 2002年第4期19卷 619-650页

作者： Chungu Lu Paul Schultz and Gerald L Browning noaa Forecast systems laboratory Boulder Colorado USA Cooperative Institute for Research in the Atmosphere Colorado State University Fort Collins Colorado USA

A set of microphysics equations is scaled based on the convective length and velocity scales. Comparisons are made among the dynamical transport and various microphysical processes. From the scaling analysis, it becomes apparent which parameterized microphysical processes present off-scaled influences in the integration of the set of microphysics equations. The variabilities of the parameterized microphysical processes are also studied using the approach of a controlled parameter space. Given macroscopic dynamic and thermodynamic conditions in different regions of convective storms, it is possible to analyze and compare vertical profiles of these processes. Bulk diabatic heating profiles for a cumulus convective updraft and downdraft are also derived from this analysis. From the two different angles, the scale analysis and the controlled-parameter space approach can both provide an insight into and an understanding of microphysics parameterizations.

关键词： cloud microphysical parameterization scale analysis controlled parameter space numerical weather prediction

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Impact of Assimilating Radiances with the WRFDA ETKF/3DVAR Hybrid System on Prediction of Two Typhoons in 2012

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Journal of Meteorological Research 2015年第1期29卷 28-40页

作者：许冬梅黄向宇王洪利 Arthur P.MIZZI 闵锦忠 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science & Technology National Center for Atmospheric Research BoulderCO 80302USA global systems Division Earth System Research LaboratoryNOAABoulderCO 80302USA

The impacts of AMSU-A and IASI（Infrared Atmospheric Sounding Interferometer） radiances assimilation on the prediction of typhoons Vicente and Saola（2012） are studied by using the ensemble transform Kalman filter/three-dimensional variational（ETKF/3DVAR） Hybrid system for the Weather Research and Forecasting（WRF） model. The experiment without assimilating radiance data in 3DVAR is compared with two experiments using the 3DVAR and ETKF/3DVAR hybrid systems to assimilate AMSU-A radiance,respectively. The results show that AMSU-A radiance data have slight positive impacts on track forecasts of the 3DVAR system. When the ETKF/3DVAR hybrid system is employed, typhoon track forecast skills are greatly improved. For 36-h forecasts, the hybrid system has a lower root-mean-square error for wind and temperature at most levels, and specific humidity at low levels, compared to 3DVAR. It is also found that, on average, the use of the IASI radiance data along with AMSU-A radiance data in the hybrid system further increases the track, wind, and specific humidity forecast accuracy compared to the experiment without IASI radiance assimilation.

关键词： hybrid system ETKF ensemble spread radiance data typhoon tracks

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Value-added Impact of Geostationary Hyperspectral Infrared Sounders on Local Severe Storm Forecasts——via a Quick Regional OSSE

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Advances in Atmospheric Sciences 2018年第10期35卷 1217-1230页

作者： Zhenglong LI Jun LI Pei WANG Agnes LIM Jinlong LI Timothy J.SCHMIT Robert ATLAS Sid-Ahmed BOUKABARA Ross N.HOFFMAN Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-Madison Center for Satellite Applications and Research NOAA Atlantic Oceanographic and Meteorological laboratory OAR/NOAA Center for Satellite Applications and Research NOAA

Accurate atmospheric temperature and moisture information with high temporal/spatial resolutions are two of the key parameters needed in regional numerical weather prediction(NWP) models to reliably predict high-impact weather events such as local severe storms(LSSs). High spectral resolution or hyperspectral infrared(HIR) sounders from geostationary orbit(GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields—an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE(Observing System Simulation Experiment)framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO(low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference(RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated, and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems(such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km.

关键词： OSSE hyperspectral sounder high-impact weather

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Improving Multi-Model Ensemble Forecasts of Tropical Cyclone Intensity Using Bayesian Model Averaging

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Journal of Meteorological Research 2018年第5期32卷 794-803页

作者： Xiaojiang SONG Yuejian ZHU Jiayi PENG Hong GUAN Key laboratory of Research on Marine Hazards Forecasting National Marine Environmental Forecasting Center Environmental Modeling Center NOAA/NWS/NCEP I.M.systems Group Inc. and NOAA/NWS/NCEP/EMC System Research Group Inc. Colorado Springs CO 80901 and NOAA/NWS/NCEP/EMC

This paper proposes a method for multi-model ensemble forecasting based on Bayesian model averaging （BMA）, aiming to improve the accuracy of tropical cyclone （TC） intensity forecasts, especially forecasts of minimum surface pressure at the cyclone center （Pmin）＇ The multi-model ensemble comprises three operational forecast models： the global Forecast System （GFS） of NCEP, the Hurricane Weather Research and Forecasting （HWRF） models of NCEP, and the Integrated Forecasting System （IFS） of ECMWF. The mean of a predictive distribution is taken as the BMA forecast. In this investigation, bias correction of the minimum surface pressure was applied at each forecast lead time, and the distribution （or probability density function, PDF） of emin was used and transformed. Based on summer season forecasts for three years, we found that the intensity errors in TC forecast from the three models var-ied significantly. The HWRF had a much smaller intensity error for short lead-time forecasts. To demonstrate the proposed methodology, cross validation was implemented to ensure more efficient use of the sample data and more reliable testing. Comparative analysis shows that BMA for this three-model ensemble, after bias correction and distri-bution transformation, provided more accurate forecasts than did the best of the ensemble members （HWRF）, with a 5%-7% decrease in root-mean-square error on average. BMA also outperformed the multi-model ensemble, and it produced ＂predictive variance＂ that represented the forecast uncertainty of the member models. In a word, the BMA method used in the multi-model ensemble forecasting was successful in TC intensity forecasts, and it has the poten-tial to be applied to routine operational forecasting.

关键词： tropical cyclone Bayesian model average intensity bias correction forecast uncertainty ensemble forecast

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Partition of Forecast Error into Positional and Structural Components

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Advances in Atmospheric Sciences 2021年第6期38卷 1012-1019页

作者： Isidora JANKOV Scott GREGORY Sai RAVELA Zoltan TOTH Malaquías PEÑA global systems laboratory NOAA/OARBoulderCO 80305USA General Atomics Electromagnetic Systems GroupLongmontCO 80501USA Earth Signals and systems Group EarthAtmospheric and Planetary SciencesMassachusetts Institute of TechnologyCambridgeMA 02139USA Department of Civil and Environmental Engineering University of Connecticut StorrsCT 06269USA

Weather manifests in spatiotemporally coherent *** forecasts hence are affected by both positional and structural or amplitude *** has been long recognized by practicing forecasters(cf.,e.g.,Tropical Cyclone track and intensity errors).Despite the emergence in recent decades of various objective methods for the diagnosis of positional forecast errors,most routine verification or statistical post-processing methods implicitly assume that forecasts have no positional *** Forecast Error Decomposition(FED)method proposed in this study uses the Field Alignment technique which aligns a gridded forecast with its verifying analysis *** total error is then partitioned into three orthogonal components:(a)large scale positional,(b)large scale structural,and(c)small scale error *** use of FED is demonstrated over a month-long MSLP data *** expected,positional errors are often characterized by dipole patterns related to the displacement of features,while structural errors appear with single extrema,indicative of magnitude *** most important result of this study is that over the test period,more than 50%of the total mean sea level pressure forecast error variance is associated with large scale positional *** importance of positional error in forecasts of other variables and over different time periods remain to be explored.

关键词： forecast error orthogonal decomposition positional structural

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