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| 1 | 哮喘治疗的新进展显示文摘没有强有力的循证医学证据表明饮食方法或Buteyko技术对哮喘的临床管理有很大益处需要进一步研究确定当哮喘控制欠佳时患者应该怎么做小剂量吸入皮质激素可以和长效β2激动剂联合应用,以提供安全有效的哮喘控制静脉镁制剂和白三烯受体拮抗剂对急性哮喘可能具有一些作用,但仍需进一步评价将来哮喘治疗是否能得到炎症生物标志或患者基因型认识的帮助。 | Graeme P Currie Graham S Devereux Daniel K C Lee Jon G Ayres 刘艳(译) 代华平(校) | 2005 | 英国医学杂志中文版2005，8，4： | 3 |
| 2 | Effect of water activity and temperature on the germination and growth of Aspergillus tamarii isolated from “Maldive fish”显示文摘 | Shazla Mohamed Li Mo Steve Flint Jon Palmer Graham C. Fletcher | 2012 | International Journal of Food Microbiology2012，，2： | 1 |
| 3 | No Detection of CrylAc Protein in Soil After Multiple Years of Transgenic Bt Cotton ( Boll- gard) Use显示文摘 | GRAHAM H JAMES B JON A W | 2002 | Environmental Entomology2002，31，1： | 1 |
| 4 | Advanced Reproductive Age and Fertility显示文摘 | Kimberly Liu Allison Case Anthony P. Cheung Sony Sierra Saleh AlAsiri Belina Carranza-Mamane Allison Case Cathie Dwyer James Graham Jon Havelock Robert Hemmings Francis Lee Kimberly Liu Ward Murdock Vyta Senikas Tannys D.R. Vause Benjamin Chee-Man Wong | 2011 | International Journal of Gynecology and Obstetrics2011，，1： | 1 |
| 5 | Receiving hospital characteristics associated with survival after out-of-hospital cardiac arrest显示文摘 | Clifton W. Callaway Robert Schmicker Mitch Kampmeyer Judy Powell Tom D. Rea Mohamud R. Daya Thomas P. Aufderheide Daniel P. Davis Jon C. Rittenberger Ahamed H. Idris Graham Nichol | 2010 | Resuscitation2010，，5： | 1 |
| 6 | High throughput DNA sequence variant detection by conformation sensitive capillary electrophoresis and automated peak comparison显示文摘 | Helen Davies Ed Dicks Philip Stephens Charles Cox Jon Teague Chris Greenman Graham Bignell Sarah O’Meara Sarah Edkins Adrian Parker Claire Stevens Andrew Menzies Matt Blow Bill Bottomley Mark Dronsfield P. Andrew Futreal Michael R. Stratton Richard Wooste | 2005 | Genomics2005，，3： | 1 |
| 7 | Effect of water activity and temperature on the germination and growth of Aspergillus tamarii isolated from “Maldive fish”显示文摘 | Shazla Mohamed Li Mo Steve Flint Jon Palmer Graham C. Fletcher | 2012 | International Journal of Food Microbiology2012，，2： | 1 |
| 8 | No detection of CrylAc protein in soil after multiple years of transgenic Bt cotton (Bollgard) use显示文摘 | GRAHAM H JAMES B S JON A M | 2002 | Envrion Entomol2002，31，1： | 1 |
| 9 | HPLC analysis of plant DNA methylation: a study of critical methodological factors显示文摘 | Jason W. Johnston Keith Harding David H. Bremner Graham Souch Jon Green Paul T. Lynch Brian Grout Erica E. Benson | 2005 | Plant Physiology and Biochemistry2005，，9： | 1 |
| 10 | A Cohort Mortality Study of Cellulose Triacetate-Fiber Workers Exposed to Methylene Chloride显示文摘 | Graham W. Gibbs Jon Amsel Kevin Soden | 1996 | Journal of Occupational & Environmental Medicine1996，，7： | 1 |
| 11 | No detection of CrylAc protein in soil after multiple years of transgenic Bt cotton (Boll- gard) use显示文摘 | Graham H James B S Jon A W | 2002 | Environmental Entomology2002，31，1： | 1 |
| 12 | 13C discrimination during CO2 assimilation by the terrestrial biosphere显示文摘 | Jon Lloyd Graham D. Farquhar | 1994 | Oecologia (-)1994，，3： | 1 |
| 13 | Low-cost airlines in Europe: Reconciling liberalization and sustainability显示文摘 | Brian Graham Jon Shaw | 2008 | Geoforum2008，，： | 1 |
| 14 | Lithospherie, Cratonie, H, Nicholas T A, et and Geodynamie Setting of Ni-Cu-PGE Sulfide Deposits显示文摘 | Graham C B Jon A M al | 2010 | Eeonomie Geology2010，105，： | 1 |
| 15 | Management of Combined Pancreatoduodenal Injuries显示文摘 | DAVID V. FELICIANO TOMAS D. MARTIN PAMELA A. CRUSE JOSEPH M. GRAHAM JON M. BURCH KENNETH L. MATTOX CARMEL G. BITONDO GEORGE L. JORDAN | 1987 | Annals of Surgery1987，，6： | 1 |
| 16 | Effects of rising temperatures and CO2 on the physiology of tropical forest trees 显示文摘 | Jon L Graham D F | 2008 | Philosophical Trans- actions of the Royal Society of London ( Series B : Biological Sciences)2008，363，： | 1 |
| 17 | Revisiting classical SIR modelling in light of the COVID-19 pandemic显示文摘Background:Classical infectious disease models during epidemics have widespread usage,from predicting the probability of new infections to developing vaccination plans for informing policy decisions and public health responses.However,it is important to correctly classify reported data and understand how this impacts estimation of model parameters.The COVID-19 pandemic has provided an abundant amount of data that allow for thorough testing of disease modelling assumptions,as well as how we think about classical infectious disease modelling paradigms.Objective:We aim to assess the appropriateness of model parameter estimates and preiction results in classical infectious disease compartmental modelling frameworks given available data types(infected,active,quarantined,and recovered cases)for situations where just one data type is available to fit the model.Our main focus is on how model prediction results are dependent on data being assigned to the right model compartment.Methods:We first use simulated data to explore parameter reliability and prediction capability with three formulations of the classical Susceptible-Infected-Removed(SIR)modelling framework.We then explore two applications with reported data to assess which data and models are sufficient for reliable model parameter estimation and prediction accuracy:a classical influenza outbreak in a boarding school in England and COVID-19 data from the fall of 2020 in Missoula County,Montana,USA.Results:We demonstrated the magnitude of parameter estimation errors and subsequent prediction errors resulting from data misclassification to model compartments with simulated data.We showed that prediction accuracy in each formulation of the classical disease modelling framework was largely determined by correct data classification versus misclassification.Using a classical example of influenza epidemics in an England boarding school,we argue that the Susceptible-Infected-Quarantined-Recovered(SIQR)model is more appropriate than the commonly employed SIR model given the data collected(number of active cases).Similarly,we show in the COVID-19 disease model example that reported active cases could be used inappropriately in the SIR modelling framework if treated as infected.Conclusions:We demonstrate the role of misclassification of disease data and thus the importance of correctly classifying reported data to the proper compartment using both simulated and real data.For both a classical influenza data set and a COVID-19 case data set,we demonstrate the implications of using the“right”data in the“wrong”model.The importance of correctly classifying reported data will have downstream impacts on predictions of number of infections,as well as minimal vaccination requirements. | Leonid Kalachev Erin L.Landguth Jon Graham | 2023 | Infectious Disease Modelling2023，8，1： | 0 |
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