Traditional approaches have so far considered aspects of tissues and biofluid markers independently.
2
Here we introduce an information theoretic framework for biomarker discovery, integrating biofluid and tissue information.
3
PTX3 protein concentration in the biofluid was unable to diagnose sepsis-induced ALI evidenced by its small AUROCC.
4
UCH-L1 CSF and serum data from 59 patients were used to determine biofluid correlations.
5
Further studies are being conducted to determine if exposure and kinetic metrics for biofluid-based biomarkers can predict clinical outcome.
6
Because urine is a noninvasive and readily available biofluid, the discovery of uEVs has opened a new field of biomarker research.
7
To that end, cord blood is a readily accessible biofluid whose proteomic makeup remains mostly unexplored when compared with that of adults.
8
This limitation is providing an impetus for the development of experimental methodologies and strategies to increase the possible number of detections within this biofluid.
9
While there has been much investment in wearable technologies to sense analytes, less effort has been directed to understanding the physiology of biofluid secretion.
10
A metabolomic approach for biomarker detection using urine as a biofluid is appropriate since the tumor is located in close proximity to the urinary space.
11
Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages.
12
This allows us to identify tissue information in peripheral biofluids.
13
The presence of miRNAs in extracellular biofluids is increasingly recognized.
14
Extracellular miRNAs are detectable in biofluids and represent a novel class of disease biomarker.
15
Several recent studies have shown their applicability as nonmechanical fluid viscosity sensors, particularly in biofluids containing proteins.
16
This suggests that types of nanocluster complexes are present in these biofluids as well as in milk.