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1.
Estee Y Cramer; Evan L Ray; Velma K Lopez; Johannes Bracher; Andrea Brennen; Alvaro J Castro Rivadeneira; Aaron Gerding; Tilmann Gneiting; Katie H House; Yuxin Huang; Dasuni Jayawardena; Abdul H Kanji; Ayush Khandelwal; Khoa Le; Anja Muehlemann; Jarad Niemi; Apurv Shah; Ariane Stark; Yijin Wang; Nutcha Wattanachit; Martha W Zorn; Youyang Gu; Sansiddh Jain; Nayana Bannur; Ayush Deva; Mihir Kulkarni; Srujana Merugu; Alpan Raval; Siddhant Shingi; Avtansh Tiwari; Jerome White; Neil F Abernethy; Spencer Woody; Maytal Dahan; Spencer Fox; Kelly Gaither; Michael Lachmann; Lauren Ancel Meyers; James G Scott; Mauricio Tec; Ajitesh Srivastava; Glover E George; Jeffrey C Cegan; Ian D Dettwiller; William P England; Matthew W Farthing; Robert H Hunter; Brandon Lafferty; Igor Linkov; Michael L Mayo; Matthew D Parno; Michael A Rowland; Benjamin D Trump; Yanli Zhang-James; Samuel Chen; Stephen V Faraone; Jonathan Hess; Christopher P Morley; Asif Salekin; Dongliang Wang; Sabrina M Corsetti; Thomas M Baer; Marisa C Eisenberg; Karl Falb; Yitao Huang; Emily T Martin; Ella McCauley; Robert L Myers; Tom Schwarz; Daniel Sheldon; Graham Casey Gibson; Rose Yu; Liyao Gao; Yian Ma; Dongxia Wu; Xifeng Yan; Xiaoyong Jin; Yu-Xiang Wang; YangQuan Chen; Lihong Guo; Yanting Zhao; Quanquan Gu; Jinghui Chen; Lingxiao Wang; Pan Xu; Weitong Zhang; Difan Zou; Hannah Biegel; Joceline Lega; Steve McConnell; VP Nagraj; Stephanie L Guertin; Christopher Hulme-Lowe; Stephen D Turner; Yunfeng Shi; Xuegang Ban; Robert Walraven; Qi-Jun Hong; Stanley Kong; Axel van de Walle; James A Turtle; Michal Ben-Nun; Steven Riley; Pete Riley; Ugur Koyluoglu; David DesRoches; Pedro Forli; Bruce Hamory; Christina Kyriakides; Helen Leis; John Milliken; Michael Moloney; James Morgan; Ninad Nirgudkar; Gokce Ozcan; Noah Piwonka; Matt Ravi; Chris Schrader; Elizabeth Shakhnovich; Daniel Siegel; Ryan Spatz; Chris Stiefeling; Barrie Wilkinson; Alexander Wong; Sean Cavany; Guido Espana; Sean Moore; Rachel Oidtman; Alex Perkins; David Kraus; Andrea Kraus; Zhifeng Gao; Jiang Bian; Wei Cao; Juan Lavista Ferres; Chaozhuo Li; Tie-Yan Liu; Xing Xie; Shun Zhang; Shun Zheng; Alessandro Vespignani; Matteo Chinazzi; Jessica T Davis; Kunpeng Mu; Ana Pastore y Piontti; Xinyue Xiong; Andrew Zheng; Jackie Baek; Vivek Farias; Andreea Georgescu; Retsef Levi; Deeksha Sinha; Joshua Wilde; Georgia Perakis; Mohammed Amine Bennouna; David Nze-Ndong; Divya Singhvi; Ioannis Spantidakis; Leann Thayaparan; Asterios Tsiourvas; Arnab Sarker; Ali Jadbabaie; Devavrat Shah; Nicolas Della Penna; Leo A Celi; Saketh Sundar; Russ Wolfinger; Dave Osthus; Lauren Castro; Geoffrey Fairchild; Isaac Michaud; Dean Karlen; Matt Kinsey; Luke C. Mullany; Kaitlin Rainwater-Lovett; Lauren Shin; Katharine Tallaksen; Shelby Wilson; Elizabeth C Lee; Juan Dent; Kyra H Grantz; Alison L Hill; Joshua Kaminsky; Kathryn Kaminsky; Lindsay T Keegan; Stephen A Lauer; Joseph C Lemaitre; Justin Lessler; Hannah R Meredith; Javier Perez-Saez; Sam Shah; Claire P Smith; Shaun A Truelove; Josh Wills; Maximilian Marshall; Lauren Gardner; Kristen Nixon; John C. Burant; Lily Wang; Lei Gao; Zhiling Gu; Myungjin Kim; Xinyi Li; Guannan Wang; Yueying Wang; Shan Yu; Robert C Reiner; Ryan Barber; Emmanuela Gaikedu; Simon Hay; Steve Lim; Chris Murray; David Pigott; Heidi L Gurung; Prasith Baccam; Steven A Stage; Bradley T Suchoski; B. Aditya Prakash; Bijaya Adhikari; Jiaming Cui; Alexander Rodriguez; Anika Tabassum; Jiajia Xie; Pinar Keskinocak; John Asplund; Arden Baxter; Buse Eylul Oruc; Nicoleta Serban; Sercan O Arik; Mike Dusenberry; Arkady Epshteyn; Elli Kanal; Long T Le; Chun-Liang Li; Tomas Pfister; Dario Sava; Rajarishi Sinha; Thomas Tsai; Nate Yoder; Jinsung Yoon; Leyou Zhang; Sam Abbott; Nikos I Bosse; Sebastian Funk; Joel Hellewell; Sophie R Meakin; Katharine Sherratt; Mingyuan Zhou; Rahi Kalantari; Teresa K Yamana; Sen Pei; Jeffrey Shaman; Michael L Li; Dimitris Bertsimas; Omar Skali Lami; Saksham Soni; Hamza Tazi Bouardi; Turgay Ayer; Madeline Adee; Jagpreet Chhatwal; Ozden O Dalgic; Mary A Ladd; Benjamin P Linas; Peter Mueller; Jade Xiao; Yuanjia Wang; Qinxia Wang; Shanghong Xie; Donglin Zeng; Alden Green; Jacob Bien; Logan Brooks; Addison J Hu; Maria Jahja; Daniel McDonald; Balasubramanian Narasimhan; Collin Politsch; Samyak Rajanala; Aaron Rumack; Noah Simon; Ryan J Tibshirani; Rob Tibshirani; Valerie Ventura; Larry Wasserman; Eamon B O'Dea; John M Drake; Robert Pagano; Quoc T Tran; Lam Si Tung Ho; Huong Huynh; Jo W Walker; Rachel B Slayton; Michael A Johansson; Matthew Biggerstaff; Nicholas G Reich.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-21250974

RESUMEN

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naive baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. Significance StatementThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.

2.
Artículo en Chino | WPRIM (Pacífico Occidental) | ID: wpr-433249

RESUMEN

AIM: To investigate the ethanolic and aqueous extracts from Sancao prescription (Spica prunellae, Oldenlandia diffuse (willd) Roxb, Herba agrimoniae) on the proliferation of human lung adenocarcinoma cell line (A549). METHODS: 95% ,60% and 30% ethanolic extract and aqueous extract were prepared from Sancao pre-scription. The MTT assay was used to determine the inhibitory action against the proliferation of A549. RESULTS: IC_(50) of 60% ethanolic extract over A549 was one of the lowest in extracts. Combination of 60% and 90% ethanolic extract showed the synergistic antitumour activity. CONCLUSION: Ethanolic extract of Sancao prescription has and effect on human hung adenocarcinoma(A549).

3.
Artículo en Chino | WPRIM (Pacífico Occidental) | ID: wpr-315374

RESUMEN

<p><b>OBJECTIVE</b>To research on the variation regularity of the five main flavonoids contents in Epimedium and processed Epimedium.</p><p><b>METHOD</b>The contents of Epimedin A, Epimedin B, Epimedin C, Icariin and Baohuoside I in Epimedium and processed Epimedium were determined, respectively.</p><p><b>RESULT</b>There were varieties in the contents of Epimedin A, Epimedin B, Epimedin C, Icariin and Baohuoside in Epimedium and processed Epimedium. There were different variety tendencies in different species and different batches.</p><p><b>CONCLUSION</b>The variety tendencies of the contents of five main flavonoids depend on the processing technology and the flavonoids proportion in Epimedium and processed Epimedium.</p>


Asunto(s)
Medicamentos Herbarios Chinos , Epimedium , Química , Flavonoides , Manipulación de Alimentos , Métodos
4.
China Pharmacy ; (12)2005.
Artículo en Chino | WPRIM (Pacífico Occidental) | ID: wpr-533823

RESUMEN

OBJECTIVE:To establish the method for the simultaneous determination of anticancer activity components of flavonoids from Hedyotis diffusa,i.e. quercetin,kaempferol. METHODS:HPLC was applied to determine the contents and performed on Alltima C18(250 mm?4.6 mm,5 ?m) column. Mobile phase consisted of methanol(A)-0.5% glacial acetic acid,(gradient elution). The detection wavelength was aet at 350 nm. RESULTS:The linear range of quercetin was 0.006 2~0.244 0 ?g(r=0.999 8)and that of kaempferol 0.007 8~0.310 6 ?g(r=0.999 9). The average recovery of quercetin was 101.84%(RSD=1.79%,n=6) and that of kaempferol 99.04%(RSD=2.90%,n=6). CONCLUSIONS:The method is simple,accurate and reproducible for the quality control of H. diffusa.

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