About: Paving the way for precision medicine v2.0 in intensive care by profiling necroinflammation in biofluids

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Paving the way for precision medicine v2.0 in intensive care by profiling necroinflammation in biofluids Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Paving the way for precision medicine v2.0 in intensive care by profiling necroinflammation in biofluids
Creator	Hoste, Eric Vanden Berghe, Tom
Source	PMC
abstract	Current clinical diagnosis is typically based on a combination of approaches including clinical examination of the patient, clinical experience, physiologic and/or genetic parameters, high-tech diagnostic medical imaging, and an extended list of laboratory values mostly determined in biofluids such as blood and urine. One could consider this as precision medicine v1.0. However, recent advances in technology and better understanding of molecular mechanisms underlying disease will allow us to better characterize patients in the future. These improvements will enable us to distinguish patients who have similar clinical presentations but different cellular and molecular responses. Treatments will be able to be chosen more “precisely”, resulting in more appropriate therapy, precision medicine v2.0. In this review, we will reflect on the potential added value of recent advances in technology and a better molecular understanding of necrosis and inflammation for improving diagnosis and treatment of critically ill patients. We give a brief overview on the mutual interplay between necrosis and inflammation, which are two crucial detrimental factors in organ and/or systemic dysfunction. One of the challenges for the future will thus be the cellular and molecular profiling of necroinflammation in biofluids. The huge amount of data generated by profiling biomolecules and single cells through, for example, different omic-approaches is needed for data mining methods to allow patient-clustering and identify novel biomarkers. The real-time monitoring of biomarkers will allow continuous (re)evaluation of treatment strategies using machine learning models. Ultimately, we may be able to offer precision therapies specifically designed to target the molecular set-up of an individual patient, as has begun to be done in cancer therapeutics.
has issue date	2018-09-10(xsd:dateTime)
bibo:doi	10.1038/s41418-018-0196-2
bibo:pmid	30201975
has license	cc-by
sha1sum (hex)	709308ced647f47567a363982c470a44b287cd17
schema:url	https://doi.org/10.1038/s41418-018-0196-2
resource representing a document's title	Paving the way for precision medicine v2.0 in intensive care by profiling necroinflammation in biofluids
has PubMed Central identifier	PMC6294775
has PubMed identifier	30201975
schema:publication	Cell Death Differ
resource representing a document's body	covid:709308ced647f47567a363982c470a44b287cd17#body_text
is schema:about of	named entity 'determined' named entity 'detrimental' named entity 'potential' named entity 'precision' named entity 'DYSFUNCTION' named entity 'POTENTIAL' named entity 'BUT' named entity 'APPROACHES' named entity 'ALLOW' named entity 'RESULTING IN' named entity 'VALUES' named entity 'DIAGNOSIS' named entity 'CLINICAL EXAMINATION' named entity 'GENETIC' named entity 'HUGE' named entity 'SYSTEMIC' named entity 'MONITORING' named entity 'THERAPIES' named entity 'PATIENTS' named entity 'data mining' named entity 'data' named entity 'patients' named entity 'strategies' named entity 'biomarkers' named entity 'One' named entity 'therapeutics' named entity 'based' named entity 'typically' named entity 'urine' named entity 'reflect' named entity 'list' named entity 'However' named entity 'cells' named entity 'molecular' named entity 'diagnosis' named entity 'future' named entity 'organ' named entity 'molecular mechanisms' named entity 'precision medicine' named entity 'urine' named entity 'necrosis' named entity 'precision medicine' named entity 'medical imaging' named entity 'technology' named entity 'medical care' named entity 'sepsis' named entity 'high volume' named entity 'MODS' named entity 'medical records' named entity 'Proximal tubular' named entity 'ischemia-reperfusion injury' named entity 'phagocytosis' named entity 'antigenicity' named entity 'pathogen' named entity 'Urine' named entity 'MODS' named entity 'next-generation sequencing' named entity 'histones' named entity 'global health' named entity 'necrosis' named entity 'glycome' named entity 'lung cancer' named entity 'CASP1' named entity 'iron' named entity 'LPS' named entity 'metabolome' named entity 'apoptosis' named entity 'sepsis' named entity 'Early diagnosis' named entity 'genetic characteristics' named entity 'transcriptome' named entity 'necrosis' named entity 'rodent models' named entity 'intensive care' named entity 'medical analysis' named entity 'pathogen recognition receptors' named entity 'necrosis' named entity 'Ang2' named entity 'critical care' named entity 'AKI'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software