The gut microbiota is a complex ecosystem composed of many bacteria and their metabolites.It plays an irreplaceable role in human digestion,nutrient absorption,energy supply,fat metabolism,immune regulation,and many o...The gut microbiota is a complex ecosystem composed of many bacteria and their metabolites.It plays an irreplaceable role in human digestion,nutrient absorption,energy supply,fat metabolism,immune regulation,and many other aspects.Exploring the structure and function of the gut microbiota,as well as their key genes and metabolites,will enable the early diagnosis and auxiliary diagnosis of diseases,new treatment methods,better effects of drug treatments,and better guidance in the use of antibiotics.The identification of gut microbiota plays an important role in clinical diagnosis and treatment,as well as in drug research and development.Therefore,it is necessary to conduct a comprehensive review of this rapidly evolving topic.Traditional identification methods cannot comprehensively capture the diversity of gut microbiota.Currently,with the rapid development of molecular biology,the classification and identification methods for gut microbiota have evolved from the initial phenotypic and chemical identification to identification at the molecular level.This review integrates the main methods of gut microbiota identification and evaluates their application.We pay special attention to the research progress on molecular biological methods and focus on the application of high-throughput sequencing technology in the identification of gut microbiota.This revolutionary method for intestinal flora identification heralds a new chapter in our understanding of the microbial world.展开更多
To develop near-infrared （NIR） reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders ...To develop near-infrared （NIR） reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders of cefoperazone sodium/ sulbactam sodium were directly analyzed by non-destructive NIR reflectance spectroscopy using the spectrometer EQUINOX55. Two quantitative methods via integrating sphere （IS） and fiberoptic probe （FOP） models were explored from 6 batches of commercial samples and 42 batches of laboratory samples at a content ranging from 30% to 70% for cefoperazone and 60% to 20% for sulbactam. The root mean square errors of cross validation （RMSECV） and the root mean square errors of prediction （RMSEP） of IS were 1.79% and 2.85%, respectively, for cefoperazone sodium, and were 1.86% and 3.08%, respectively, for sulbactam sodium; and those of FOP were 2.93% and 2.92%, respectively, for cefoperazone sodium, and were 2.23% and 3.01%, respectively, for sulbactam sodium. Based on the ICH guidelines and Ref. 12, the quantitative models were then evaluated in terms of specificity, linearity, accuracy, precision, robustness and model transferability. The non-destructive quantitative NIR methods used in this study are applicable for rapid analysis of injectable powdered drugs from different manufacturers.展开更多
Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes.Remote sensing-based models,which integrate satellite data wit...Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes.Remote sensing-based models,which integrate satellite data with input from ground-based meteorological measurements and vegetation characteristics,improve spatially extended estimates of vegetation productivity with high accuracy.In this study,the authors simulated GPP in ASA areas by integrating moderate resolution imaging spectral radiometer (MODIS) data with eddy covariance and meteorological measurements at the flux tower sites using the Vegetation Photosynthesis Model (VPM),which is a remote sensing-based model for analyzing the spatial pattern of GPP in different land cover types.The field data were collected by coordinating observations at nine stations in 2008.The results indicate that in the region during the growing season GPP was highest in cropland sites,second highest in woodland sites,and lowest in grassland sites.VPM captured the temporal and spatial characteristics of GPP for different land covers in ASA areas.Further,Enhanced Vegetation Index (EVI) had a strong liner relationship with GPP in densely vegetated areas,while the Normalized Difference Vegetation Index (NDVI) had a strong liner relationship with GPP over less dense vegetation.This study demonstrates the potential of satellite-driven models for scaling-up GPP,which is a key component for studying the carbon cycle at regional and global scales.展开更多
文摘The gut microbiota is a complex ecosystem composed of many bacteria and their metabolites.It plays an irreplaceable role in human digestion,nutrient absorption,energy supply,fat metabolism,immune regulation,and many other aspects.Exploring the structure and function of the gut microbiota,as well as their key genes and metabolites,will enable the early diagnosis and auxiliary diagnosis of diseases,new treatment methods,better effects of drug treatments,and better guidance in the use of antibiotics.The identification of gut microbiota plays an important role in clinical diagnosis and treatment,as well as in drug research and development.Therefore,it is necessary to conduct a comprehensive review of this rapidly evolving topic.Traditional identification methods cannot comprehensively capture the diversity of gut microbiota.Currently,with the rapid development of molecular biology,the classification and identification methods for gut microbiota have evolved from the initial phenotypic and chemical identification to identification at the molecular level.This review integrates the main methods of gut microbiota identification and evaluates their application.We pay special attention to the research progress on molecular biological methods and focus on the application of high-throughput sequencing technology in the identification of gut microbiota.This revolutionary method for intestinal flora identification heralds a new chapter in our understanding of the microbial world.
基金National Key Technologies R&D Program Foundation of China (Grant No. 2006BAK04A11)
文摘To develop near-infrared （NIR） reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders of cefoperazone sodium/ sulbactam sodium were directly analyzed by non-destructive NIR reflectance spectroscopy using the spectrometer EQUINOX55. Two quantitative methods via integrating sphere （IS） and fiberoptic probe （FOP） models were explored from 6 batches of commercial samples and 42 batches of laboratory samples at a content ranging from 30% to 70% for cefoperazone and 60% to 20% for sulbactam. The root mean square errors of cross validation （RMSECV） and the root mean square errors of prediction （RMSEP） of IS were 1.79% and 2.85%, respectively, for cefoperazone sodium, and were 1.86% and 3.08%, respectively, for sulbactam sodium; and those of FOP were 2.93% and 2.92%, respectively, for cefoperazone sodium, and were 2.23% and 3.01%, respectively, for sulbactam sodium. Based on the ICH guidelines and Ref. 12, the quantitative models were then evaluated in terms of specificity, linearity, accuracy, precision, robustness and model transferability. The non-destructive quantitative NIR methods used in this study are applicable for rapid analysis of injectable powdered drugs from different manufacturers.
基金supported by the National Basic Research Program of China (Grant Nos. 2009CB723904 and 2006CB400500)
文摘Assessing large-scale patterns of gross primary production (GPP) in arid and semi-arid (ASA) areas is important for both scientific and practical purposes.Remote sensing-based models,which integrate satellite data with input from ground-based meteorological measurements and vegetation characteristics,improve spatially extended estimates of vegetation productivity with high accuracy.In this study,the authors simulated GPP in ASA areas by integrating moderate resolution imaging spectral radiometer (MODIS) data with eddy covariance and meteorological measurements at the flux tower sites using the Vegetation Photosynthesis Model (VPM),which is a remote sensing-based model for analyzing the spatial pattern of GPP in different land cover types.The field data were collected by coordinating observations at nine stations in 2008.The results indicate that in the region during the growing season GPP was highest in cropland sites,second highest in woodland sites,and lowest in grassland sites.VPM captured the temporal and spatial characteristics of GPP for different land covers in ASA areas.Further,Enhanced Vegetation Index (EVI) had a strong liner relationship with GPP in densely vegetated areas,while the Normalized Difference Vegetation Index (NDVI) had a strong liner relationship with GPP over less dense vegetation.This study demonstrates the potential of satellite-driven models for scaling-up GPP,which is a key component for studying the carbon cycle at regional and global scales.
