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Record W2480093512 · doi:10.1113/jp272457

PET imaging of glucose movement into tissues <i>in vivo</i> sheds new light on an old problem

2016· letter· en· W2480093512 on OpenAlexaff
Chris I. Cheeseman

Bibliographic record

VenueThe Journal of Physiology · 2016
Typeletter
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGlucose transporterTransporterIn vivoMembraneGalactoseFructoseBiochemistryBiologyCell biologyChemistryEndocrinologyGeneInsulinGenetics

Abstract

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Since the first demonstrations that glucose movement across cell membranes is mediated by transport proteins enormous effort has been expended over the intervening 60 years to understand these processes at both the molecular and the tissue level (Widdas, 1951). While most of the major transporters responsible for these key metabolic processes have now been cloned, molecular techniques have not been able to provide a full understanding of how glucose enters the body and is subsequently distributed between tissues. Two types of transporter have been implicated in these processes; the first are members of the SLC2A protein family (GLUTs), which allow hexoses such as glucose, galactose and fructose to move across cell membranes down their concentration gradients (Mueckler & Thorens, 2013). The second belong to a separate gene family, SGLTs, which couple the movement of hexoses to the electrochemical gradient of sodium across cell membranes to enable the transport of glucose against a concentration gradient (Wright et al. 2011). When epithelial cells express these different transporters on opposite poles it is possible for the intestine or kidney to achieve a vectorial flux essential for the body to acquire carbohydrate from the diet and ensure glucose is not lost into the urine after glomerular filtration. However, while these functional models are supported by extensive indirect evidence using in vitro and in vivo techniques, there are some significant gaps in our understanding of the role of these transporters in a number of key tissues. For instance, the established model of intestinal and renal glucose handling is that SGLT1 and/or -2 provides uphill entry across the apical membrane with the subsequent exit across the basolateral pole down the concentration gradient mediated by GLUT2. However, in GLUT2 knock-out mice absorption of glucose from the diet appears to be normal, challenging this long accepted concept (Stumpel et al. 2001). Similarly, while GLUTs have long been considered to be the primary route by which glucose crosses the blood–brain barrier it has not been rigorously demonstrated in vivo. Finally, there have been indications that SGLTs might also play a role in the uptake of hexoses into cardiomyocytes. Molecular techniques are able to help with ascertaining in which tissues certain transporter proteins are found, but do not provide measures of their relative functional capacities. Also, locating proteins alone does not allow for determining physiological processes which modulate activity within the course of minutes or hours. Consequently, any approach which can follow the flux of hexoses between the blood and various tissues over relatively short time periods in vivo has enormous potential to advance our understanding of the role of these transporters. In this issue of The Journal of Physiology, Sala-Rabanal et al. (2016) report on a series of studies in live mice in which the distribution of hexose analogues specific for different transporters has been followed using PET imaging. They then determined with compartmental analysis which tissues employed SGLTs and/or GLUTs to handle these substrates. The authors were able to reach a number of conclusions. First, although SGLTs appear to be expressed in the blood–brain barrier, the primary route of entry for glucose into the brain is mediated by GLUT1 or -3, as this uptake was not affected in GLUT2−⁄− mice and the SGLT-specific analogue, 4-methyl-fluoro-deoxy-D-glucose, did not enter the brain. Second, they were able to confirm the model for glucose reabsorption across the proximal convoluted tubule in which uptake is mediated by SGLT1 and -2 and exit into the blood requires GLUT2. Finally, they also confirmed that GLUT2 mediates glucose fluxes into and out of hepatocytes in the liver and thus plays a major role in glucose homeostasis. However, there are still a number of significant unanswered questions with regard to glucose fluxes across and between tissues. There is strong evidence that in the intestine during the course of a single meal the carbohydrate capacity is up-regulated within minutes, matching the load so that there is no overspill from the small intestine into the colon. Part of this increase in capacity can be accounted for by rapid insertion of SGLT1 into the membrane, but there is also contested evidence that GLUT2 can also be inserted into the apical membrane to help with the nutrient load at the start of a meal (Kellett & Brot-Laroche, 2005; Röder et al. 2014). The signalling pathways for these responses appear to involve taste receptors and a neuroendocrine mechanism (Nguyen et al. 2012). Another puzzle regarding glucose absorption in the small intestine is the role of GLUT2 in mediating glucose efflux into the blood. Some studies have shown normal transport of glucose across the epithelium in GLUT2−⁄− mice (Stumpel et al. 2001) while more recent work indicate that it is significantly reduced in the absence of GLUT2 (Röder et al. 2014). This has raised the possibility that there might still be another route of exit for hexoses. If there is another transporter present that has previously been ignored, could other tissues also make use of the same system? New imaging techniques should help us to answer these important questions. None.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.275
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.259
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
Admission routes1
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