Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText.
Kick-your-searchterm to multiple Engines kick-your-query now !>
A dictionary by aggregated review articles of nephrology, medicine and the life sciences
Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

suck abstract from ncbi


10.1016/j.biopha.2020.110451

http://scihub22266oqcxt.onion/10.1016/j.biopha.2020.110451
suck pdf from google scholar
32603887!7309857!32603887
unlimited free pdf from europmc32603887    free
PDF from PMC    free
html from PMC    free

suck abstract from ncbi


Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534

Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
pmid32603887      Biomed+Pharmacother 2020 ; 129 (ä): 110451
Nephropedia Template TP

gab.com Text

Twit Text FOAVip

Twit Text #

English Wikipedia


  • When science goes viral: The research response during three months of the COVID-19 outbreak #MMPMID32603887
  • Nowakowska J; Sobocinska J; Lewicki M; Lemanska Z; Rzymski P
  • Biomed Pharmacother 2020[Sep]; 129 (ä): 110451 PMID32603887show ga
  • Here we present the results of a bibliometric survey of peer-reviewed and pre-print papers published in the English language on issues related to COVID-19 within the first three months since a cluster of a severe acute respiratory disease of unknown etiology was officially confirmed by the Chinese Center for Disease Control and Prevention on 31 December 2019. A systematic search using PubMed/Medline and Scopus databases and preprint servers was performed. The articles were classified according to their type, subject and country of origin. Up to 31 March 2020, a total of 2062 papers published in 578 peer-reviewed journals and 1425 preprints posted mostly on medRxiv (55.4 %), were identified. The mean number of published journal papers and preprints per day in the considered period was 27 and 12, respectively, and reached a maximum of 51 and 46 per day in March, respectively. The identified articles, journal papers and preprints, mostly covered the epidemiology of COVID-19 (35.7 %), clinical aspects of infection (21.0 %), preventative measures (12.8 %), treatment options (12.5 %), diagnostics (12.2 %), mathematical modeling of disease transmission and mitigation (9.6 %), and molecular biology and pathogenesis of SARS-CoV-2 (8.7 %). The majority of the journal papers were commentaries (38.5 %), reviews (33.6 %) and original research (21.3 %), while preprints predominantly presented original results (89.8 %). Chinese scientists contributed the highest share of original research and were responsible for 32.9 % journal papers and 43.9 % preprints published in the considered period. A high number of contributions was also seen from the United States, the United Kingdom, and Italy. The benefits and potential risks of such a massive publication output are discussed. The scientific response seen during the first 3 months of the COVID-19 outbreak is a demonstration of the capabilities of modern science to react rapidly to emerging global health threats by providing and discussing the essential information for understanding the etiological factor, its spread, preventative measures, and mitigation strategies.
  • |*Coronavirus Infections[MESH]
  • |*Pandemics[MESH]
  • |*Pneumonia, Viral[MESH]
  • |Bibliometrics[MESH]
  • |COVID-19[MESH]
  • |Databases, Factual/statistics & numerical data[MESH]
  • |Disease Outbreaks[MESH]
  • |Humans[MESH]
  • |Periodicals as Topic/*statistics & numerical data[MESH]


  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    Linkout box