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Institution

Charles University in Prague

EducationPrague, Czechia
About: Charles University in Prague is a education organization based out in Prague, Czechia. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 32392 authors who have published 74435 publications receiving 1804208 citations.


Papers
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Journal ArticleDOI
TL;DR: Nonthermal plasma usage expanded to new biological areas of application like plasma microorganisms' in activation, ready-to-eat food preparation, biofilm degradation or in healthcare, where it seems to be important for the treatment of cancer cells and in the initiation of apoptosis, prion inactivation, prevention of nosocomial infections or in the therapy of infected wounds.

455 citations

Journal ArticleDOI
TL;DR: A rapid search in PubMed shows that using "flow cytometry immunology" as a search term yields more than 68 000 articles, the first of which is not about lymphocytes as mentioned in this paper.
Abstract: The marriage between immunology and cytometry is one of the most stable and productive in the recent history of science. A rapid search in PubMed shows that, as of July 2017, using “flow cytometry immunology” as a search term yields more than 68 000 articles, the first of which, interestingly, is not about lymphocytes. It might be stated that, after a short engagement, the exchange of the wedding rings between immunology and cytometry officially occurred when the idea to link fluorochromes to monoclonal antibodies came about. After this, recognizing different types of cells became relatively easy and feasible not only by using a simple fluorescence microscope, but also by a complex and sometimes esoteric instrument, the flow cytometer that is able to count hundreds of cells in a single second, and can provide repetitive results in a tireless manner. Given this, the possibility to analyse immune phenotypes in a variety of clinical conditions has changed the use of the flow cytometer, which was incidentally invented in the late 1960s to measure cellular DNA by using intercalating dyes, such as ethidium bromide. The epidemics of HIV/AIDS in the 1980s then gave a dramatic impulse to the technology of counting specific cells, since it became clear that the quantification of the number of peripheral blood CD4+ T cells was crucial to follow the course of the infection, and eventually for monitoring the therapy. As a consequence, the development of flow cytometers that had to be easy-to-use in all clinical laboratories helped to widely disseminate this technology. Nowadays, it is rare to find an immunological paper or read a conference abstract in which the authors did not use flow cytometry as the main tool to dissect the immune system and identify its fine and complex functions. Of note, recent developments have created the sophisticated technology of mass cytometry, which is able to simultaneously identify dozens of molecules at the single cell level and allows us to better understand the complexity and beauty of the immune system.

454 citations

Journal ArticleDOI
Albert M. Sirunyan, Armen Tumasyan, Wolfgang Adam1, Federico Ambrogi1  +2238 moreInstitutions (159)
TL;DR: In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented.
Abstract: Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The b jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV).

454 citations

Journal ArticleDOI
TL;DR: In patients with HeFH and inadequate LDL-C control at baseline despite maximally tolerated statin ± other LLT, alirocumab treatment resulted in significant LDL- C lowering and greater achievement of cholesterol-lowering target levels and was well tolerated.
Abstract: Aims To assess long-term (78 weeks) alirocumab treatment in patients with heterozygous familial hypercholesterolaemia (HeFH) and inadequate LDL-C control on maximally tolerated lipid-lowering therapy (LLT). Methods and results In two randomized, double-blind studies (ODYSSEY FH I, n = 486; FH II, n = 249), patients were randomized 2 : 1 to alirocumab 75 mg or placebo every 2 weeks (Q2W). Alirocumab dose was increased at Week 12 to 150 mg Q2W if Week 8 LDL-C was ≥1.8 mmol/L (70 mg/dL). Primary endpoint (both studies) was percentage change in calculated LDL-C from baseline to Week 24. Mean LDL-C levels decreased from 3.7 mmol/L (144.7 mg/dL) at baseline to 1.8 mmol/L (71.3 mg/dL; −57.9% vs. placebo) at Week 24 in patients randomized to alirocumab in FH I and from 3.5 mmol/L (134.6 mg/dL) to 1.8 mmol/L (67.7 mg/dL; −51.4% vs. placebo) in FH II ( P < 0.0001). These reductions were maintained through Week 78. LDL-C <1.8 mmol/L (regardless of cardiovascular risk) was achieved at Week 24 by 59.8 and 68.2% of alirocumab-treated patients in FH I and FH II, respectively. Adverse events resulted in discontinuation in 3.4% of alirocumab-treated patients in FH I (vs. 6.1% placebo) and 3.6% (vs. 1.2%) in FH II. Rate of injection site reactions in alirocumab-treated patients was 12.4% in FH I and 11.4% in FH II (vs. 11.0 and 7.4% with placebo). Conclusion In patients with HeFH and inadequate LDL-C control at baseline despite maximally tolerated statin ± other LLT, alirocumab treatment resulted in significant LDL-C lowering and greater achievement of LDL-C target levels and was well tolerated. Clinical trial registration Cinicaltrials.gov (identifiers: [NCT01623115][1]; [NCT01709500][2]). [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01623115&atom=%2Fehj%2Fearly%2F2015%2F08%2F27%2Feurheartj.ehv370.atom [2]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01709500&atom=%2Fehj%2Fearly%2F2015%2F08%2F27%2Feurheartj.ehv370.atom

454 citations

Book ChapterDOI
01 Jan 2010
TL;DR: In this article, the authors present formulas relevant for time series analysis: 31.1. Predictions in Time Series, 31.2. Decomposition of (economic) Time Series and 31.3. Estimation of Correlation and Spectral Characteristics.
Abstract: Chapter 31 contains formulas relevant for time series analysis: 31.1. Predictions in Time Series, 31.2. Decomposition of (Economic) Time Series, 31.3. Estimation of Correlation and Spectral Characteristics, 31.4. Linear Time Series, 31.5 Nonlinear and Financial Time Series, 31.6 Multivariate Time Series, 31.7. Kalman Filter.

453 citations


Authors

Showing all 32719 results

NameH-indexPapersCitations
Ronald C. Petersen1781091153067
P. Chang1702154151783
Vaclav Vrba141129895671
Milos Lokajicek139151198888
Christopher D. Manning138499147595
Yves Sirois137133495714
Rupert Leitner136120190597
Gerald M. Reaven13379980351
Roberto Sacchi132118689012
S. Errede132148198663
Mark Neubauer131125289004
Peter Kodys131126285267
Panos A Razis130128790704
Vit Vorobel13091979444
Jehad Mousa130122686564
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023203
2022554
20214,838
20204,793
20194,421
20183,991