ub.xmlui.mirage2.page-structure.muninLogoub.xmlui.mirage2.page-structure.openResearchArchiveLogo
    • EnglishEnglish
    • norsknorsk
  • Velg spraakEnglish 
    • EnglishEnglish
    • norsknorsk
  • Administration/UB
View Item 
  •   Home
  • Fakultet for naturvitenskap og teknologi
  • Institutt for matematikk og statistikk
  • Artikler, rapporter og annet (matematikk og statistikk)
  • View Item
  •   Home
  • Fakultet for naturvitenskap og teknologi
  • Institutt for matematikk og statistikk
  • Artikler, rapporter og annet (matematikk og statistikk)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Spatiotemporal Analysis of COVID-19 Incidence Data

Permanent link
https://hdl.handle.net/10037/23563
DOI
https://doi.org/10.3390/v13030463
Thumbnail
View/Open
article.pdf (4.077Mb)
Published version (PDF)
Date
2021-03-11
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Spassiani, Ilaria; Sebastiani, Giovanni; Palu, Giorgio
Abstract
High-density lipoproteins (HDL) are a heterogenous group of plasma molecules with a large variety in composition. There is a wide specter in lipid content and the number of different proteins that has been associated with HDL is approaching 100. Given this heterogeneity and the fact that the total amount of HDL is inversely related to the risk of coronary heart disease (CHD), there has been increasing interest in the function of specific HDL subgroups and in what way measuring and quantifying these subgroups could be of clinical importance in determining individual CHD risk. If certain subgroups appear to be more protective than others, it may also in the future be possible to pharmacologically increase beneficial and decrease harmful subgroups in order to reduce CHD risk. In this review we give a short historical perspective, summarize some of the recent clinical findings regarding HDL subclassifications and discuss why such classification may or may not be of clinical relevance.
Publisher
MDPI
Citation
Spassiani, Sebastiani, Palu. Spatiotemporal Analysis of COVID-19 Incidence Data . Viruses. 2021;13(3):1-13
Metadata
Show full item record
Collections
  • Artikler, rapporter og annet (matematikk og statistikk) [354]
Copyright 2021 The Author(s)

Browse

Browse all of MuninCommunities & CollectionsAuthor listTitlesBy Issue DateBrowse this CollectionAuthor listTitlesBy Issue Date
Login

Statistics

View Usage Statistics
UiT

Munin is powered by DSpace

UiT The Arctic University of Norway
The University Library
uit.no/ub - munin@ub.uit.no

Accessibility statement (Norwegian only)