Evidence map›Paper›PMID 33397035›Full record

ReviewEndocrinology and metabolism (Seoul, Korea)2020

In Vivo and In Vitro Quantification of Glucose Kinetics: From Bedside to Bench.

Il-Young Kim, Sanghee Park, Yeongmin Kim, Yewon Chang, Cheol Soo Choi, Sang-Hoon Suh, Robert R Wolfe

Abstract readReview
In one paragraph

Review in Endocrinology and metabolism (Seoul, Korea), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Il-Young KimDepartment of Molecular Medicine, College of Medicine, Gachon University, Incheon, Korea.
Sanghee ParkDepartment of Molecular Medicine, College of Medicine, Gachon University, Incheon, Korea.
Yeongmin KimDepartment of Health Sciences and Technology, Gachon Advanced Institute for Health Sciences & Technology (GAIHST), Gachon University, Incheon, Korea.
Yewon ChangDepartment of Health Sciences and Technology, Gachon Advanced Institute for Health Sciences & Technology (GAIHST), Gachon University, Incheon, Korea.
Cheol Soo ChoiDepartment of Molecular Medicine, College of Medicine, Gachon University, Incheon, Korea.
Sang-Hoon SuhDepartment of Physical Education, Yonsei University, Seoul, Korea.
Robert R WolfeDepartment of Geriatrics, the Center for Translational Research in Aging & Longevity, Donald W. Reynolds Institute on Aging, University of Arkansas for Medical Sciences, Little Rock, AR, USA.

Funding

Ministry of EducationMinistry of Sciences and ICTNational Research Foundation of Korea 2014M3A9D5A01073886National Research Foundation of Korea 2017R1D1A1B03032988National Research Foundation of Korea 2018R1D1A1B07051053National Research Foundation of Korea 2019H1D3A1A01071043National Research Foundation of Korea 2020R1I1A1A01074380
6 · The paper itself

Abstract

Like other substrates, plasma glucose is in a dynamic state of constant turnover (i.e., rates of glucose appearance [Ra glucose] into and disappearance [Rd glucose] from the plasma) while staying within a narrow range of normal concentrations, a physiological priority. Persistent imbalance of glucose turnover leads to elevations (i.e., hyperglycemia, Ra>Rd) or falls (i.e., hypoglycemia, Ra<Rd) in the pool size, leading to clinical conditions such as diabetes. Endogenous Ra glucose is divided into hepatic glucose production via glycogenolysis and gluconeogenesis (GNG) and renal GNG. On the other hand, Rd glucose, the summed rate of glucose uptake by tissues/organs, involves various intracellular metabolic pathways including glycolysis, the tricarboxylic acid (TCA) cycle, and oxidation at varying rates depending on the metabolic status. Despite the dynamic nature of glucose metabolism, metabolic studies typically rely on measurements of static, snapshot information such as the abundance of mRNAs and proteins and (in)activation of implicated signaling networks without determining actual flux rates. In this review, we will discuss the importance of obtaining kinetic information, basic principles of stable isotope tracer methodology, calculations of in vivo glucose kinetics, and assessments of metabolic flux in experimental models in vivo and in vitro.

Indexed as

GluconeogenesisAnimalsDiabetes MellitusGlucoseGlycogenolysisHumansHyperglycemiaHypoglycemiaInsulin ResistanceIsotopesKineticsLiverMetabolic Flux AnalysisGlucoseIsotopesDiabetes mellitusInsulin resistanceMetabolic fluxomicsStable isotope tracers

Identifiers

PMID33397035
PMCPMC7803595

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.