The in vivo neuron-to-astrocyte lactate shuttle in human brain:evidence from modeling of measured lactate levels during visual stimulation

Silvia Mangia1, Ian A. Simpson2, Susan J. Vannucci3, and Anthony Carruthers4

1Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota,Minneapolis (MN), USA2Department of Neural and Behavioral Sciences, College of Medicine, Penn State University,Hershey (PA), USA3Department of Pediatrics/Newborn Medicine, Weill Cornell Medical College, New York, NY100654Department of Biochemistry and Molecular Pharmacology, University of Massachusetts MedicalSchool, Worcester (MA), USA

AbstractFunctional magnetic resonance spectroscopy (fMRS) allows the non-invasive measurement ofmetabolite concentrations in the human brain, including changes induced by variations inneurotransmission activity. However, the limited spatial and temporal resolution of fMRS does notallow specific measurements of metabolites in different cell types. Thus, the analysis of fMRSdata in the context of compartmentalized metabolism requires the formulation and application ofmathematical models. In the present study we utilized the mathematical model introduced bySimpson et al. (JCBFM 27: 1766-1791, 2007) to gain insights into compartmentalized metabolismin vivo from the fMRS data obtained in humans at ultra high magnetic field by Mangia et al.(JCBFM 27: 1055-1063, 2007). This model simulates brain glucose and lactate levels in atheoretical cortical slice. Using experimentally determined concentrations and catalytic activitiesfor the respective transporter proteins, we calculate inflow and export of glucose and lactate inendothelium, astrocytes and neurons. We then vary neuronal and astrocytic glucose and lactateutilization capacities until close correspondence is observed between in vivo and simulated glucoseand lactate levels. The results of the simulations indicate that, when literature values of glucosetransport capacity are utilized, the fMRS data are consistent with export of lactate by neurons andimport of lactate by astrocytes, a mechanism that can be referred to as a neuron-to-astrocyte lactateshuttle (NALS). A shuttle of lactate from astrocytes to neurons (ANLS) could be simulated, butthis required the astrocytic glucose transport capacity to be increased by 12-fold, and required thatneurons not respond to activation with increased glycolysis, two conditions that are not supportedby current literature.

Keywordsenergy metabolism; neuronal activation; glucose transport and utilization; lactate; human brain

Correspondence information: Silvia Mangia, Ph.D., Center for Magnetic Resonance Research, University of Minnesota, 2021 6thSt. S.E., Minneapolis, MN, 55455 (USA), e-mail: mangia@cmrr.umn.edu, tel: +1 612-626-7897, fax: +1 612-626-2004.

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Published in final edited form as:J Neurochem. 2009 May ; 109(Suppl 1): 55–62. doi:10.1111/j.1471-4159.2009.06003.x.

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IntroductionThe mammalian brain depends upon a continuous supply of circulating glucose to supportits energetic demands primarily by oxidative metabolism, both at rest and during activation.In recent years, the field of brain energy metabolism has been consumed with questionsregarding the precise fuel for neuronal metabolism during times of activation orneurotransmission, i.e. glucose or lactate, and the extent to which blood-borne glucose ismetabolized through glycolysis to lactate by astrocytes to fuel neuronal metabolism (Dieneland Cruz 2004, Pellerin et al. 2007). Astrocytes are known to play a pivotal role duringneurotransmission, as they are actively involved in neurotransmitter recycling, in theclearance of extracellular potassium ions, and in the propagation of Ca+ ‘waves’ (for review,refer to Hertz et al. 2007). The additional role of astrocytes as the source of energetic fuelfor neurons was originally proposed by Pellerin and Magistretti (1994) who suggested thatactivation of neurons with the release of the neurotransmitter glutamate stimulatedglycolysis in nearby astrocytes, and the lactate so produced was then released by astrocytesto fuel neuronal metabolism. This hypothesis was termed the astrocyte-neuron lactate shuttlehypothesis (ANLSH). The model does not exclude a direct neuronal glucose uptake,however it suggests that lactate produced by astrocytic glycolysis is the main metabolic fuelof (glutamatergic) neurons during neurotransmission.

Since the introduction of the ANLSH, a considerable amount of experimental and theoreticalwork has been put forth by different laboratories to validate or refute this workinghypothesis, although a consensus still has not been reached, as reviewed in several papers(Mangia et al. 2003, Pellerin et al. 2007, Chih and Roberts Jr 2003, Dienel and Cruz 2004,Simpson et al. 2007, Fillenz 2005, Mangia et al. 2008). Much of the original work that ledto the ANLSH derived from in vitro experiments, and establishing the metabolic role oflactate during neuronal activation in vivo is challenged by the difficulties in obtaining thenecessary experimental evidence. In this context, Magnetic Resonance Spectroscopy (MRS)is a powerful tool for non-invasive investigation of brain metabolism, due to its ability todetect temporal changes in metabolite concentrations during neuronal activation. Thereliable quantification of such changes during studies of functional MRS (fMRS) is still ademanding task (Mangia et al. 2008), and studies such as these have often producedinconsistent results (for review, see Mangia et al. 2006). However, ultra-high magnetic fieldsystems can help in obtaining robust and accurate time-courses of metabolite changes. Theconcentrations of 17 brain metabolites were recently measured with unprecedentedsensitivity and temporal resolution at 7 T in the human primary visual cortex duringparadigms of visual stimulation (Mangia et al. 2006, Mangia et al. 2007a, Mangia et al.2007b). Few metabolites were found to undergo changes in steady-state concentration inresponse to increased neuronal activity during prolonged visual stimulation (Mangia et al.2007a). In agreement with previous findings (Frahm et al. 1996), glucose concentration([Glc]) was found to undergo a gradual reduction during activation. In contrast to [Glc],lactate concentration ([Lac]) increased during the first minute of visual activation by ∼0.2μmol/g, reached a new-steady state, and returned to baseline at the end of the stimulus.

Despite the increased reliability of metabolite quantification attainable at ultra-high fields,the temporal and spatial resolution of fMRS does not provide direct evidence to prove ordisprove hypotheses involving metabolic compartmentalization among different cell types,because the measured signal is averaged from a relatively large volume of cortex.Specifically, fMRS cannot provide direct information about the amounts of lactate andglucose used by neurons and astrocytes during activation, and the interpretation of changesof lactate concentration in vivo is anything but straightforward. Therefore, the analysis oftissue [Lac] changes in the context of compartmentalized metabolism requires theformulation of mathematical models. Aubert and Costalat developed a mathematical model

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of neuroglial coupling that predicts the time-courses of observable variables (as the total[Lac]) under the assumptions of the ANLSH (Aubert and Costalat 2002, Aubert and Costalat2005, Aubert et al. 2005, Aubert et al. 2007). This approach was then utilized todemonstrate that the ANLSH is valid at least during the first period of prolongedstimulations (up to 30 s), and after the end of the stimulus (Aubert and Costalat 2005).Recently, another model has been suggested for brain metabolism, which includes thekinetic properties and distribution of glucose (GLUTs) and monocarboxylate (MCTs)transporter proteins in neurons, astrocytes, and endothelial cells (Simpson et al. 2007). Thismodel also takes into account that glucose transported across the blood brain barrier into thebasal lamina is free to diffuse into the interstitium. Based on the analysis of the extra-cellular [Lac] time-course measured in the rat brain during electrical stimulation (Hu andWilson 1997), Simpson et al. concluded that neurons, and not astrocytes, are the mainproducers and consumers of lactate during activation (Simpson et al. 2007). Neuronal ratherthan astrocytic glycolysis was previously suggested based on human data obtained withpositron emission tomography (Gjedde and Marrett 2001). In addition, several studies aimedat assessing glycolytic or oxidative activity in synaptosomes prepared from adult brainsupport the notion that neuronal glycolysis increases markedly during activation (Erecinskaet al. 1991, Kauppinen and Nicholls 1986, Kauppinen et al. 1989).

The purpose of the present study was to utilize the model of Simpson et al. (2007) toanalyze the experimental data obtained in humans with high field fMRS (Mangia et al.2007a). Specifically, two scenarios were considered: 1) our core model, where bothastrocytes and neurons increase glycolysis in response to increased neuronal activity, andneuronal glucose transport capacity is greater than that of the astrocytes, and 2) a variationon the model of Simpson et al. (2007) which mimics the ANLS condition, which requiredthat astrocytic glucose transport capacity increase12-fold and that neurons do not respond toactivation with increased glycolysis.

MethodsExperimental data

The human data utilized in these simulations have been previously published (Mangia et al.2007a). Briefly, the study group consisted of 12 healthy volunteers, age 19-26 years, andeach subject was studied twice during different visual stimulation paradigms; measurementswere performed on a 7T/90cm horizontal bore magnet (Mangia et al. 2007a). 1H NMRspectra were analyzed during rest and stimulation periods for each paradigm, and timecourses of 17 different metabolites were determined. Values for lactate and glucoseconcentrations during one of the functional paradigms were used in the simulationspresented in this study.

SoftwareSimulations were carried out by 4th order Runge Kutta Numerical Integration using thesoftware package Berkeley Madonna version 8.3.22. Details of the steady-state transportequations and differential equations used for modeling are fully accessible in Simpson et al.(2007), and can be downloaded from the website:http://glutxi.umassmed.edu/bbb/model.htm.

The modelBrain glucose and lactate uptake and utilization were simulated using the model of Simpsonet al. (2007). Using experimentally determined transporter concentrations and kineticparameters, the model calculates inflow and export of glucose and lactate in endothelium,astrocytes and neurons. The model varies the neuronal and astrocytic utilization of glucose

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and lactate until close correspondence is observed between in vivo and simulated glucoseand lactate levels (Simpson et al. 2007). For both transporter (GLUT and MCT) isoforms,kinetic behavior (e.g. catalytic turnover and substrate affinity), expression level, and cellularexpression are firmly based on experimentally determined values for neurons, astrocytes,endothelial cells, and erythrocytes. In addition, the model takes into account that smallmolecule self-diffusion within the basal lamina and interstitium allows for experimentallydetermined limits on diffusion such as tortuosity (Hrabetova and Nicholson 2004) and fordemonstrations of unrestricted diffusion between the basal lamina and interstitium(Brightman and Reese 1969). Metabolite flow between compartments is bidirectional and,when carrier (GLUT or MCT)-mediated transport is involved, the appropriate transportequations are employed (Simpson et al. 2007, Stein 1986). Electroneutral proton-lactate co-transport is unaffected by altered membrane potential but is influenced by altered extra- orintracellular pH (Stein 1986). Since the effects over physiologic pH ranges are very small(Broer et al. 1998, Simpson et al. 2007), we ignore the effects of pH changes and thereforeassume that net lactate transport proceeds in the direction of its concentration gradient. Thecompartmental sequence of glucose flow from blood to brain proceeds in the direction ofcapillary lumen to microvascular endothelial cell, to basal lamina, to astrocytic endfoot or tointerstitium and is illustrated in Fig 4 of Simpson et al. (2007). Astrocytic glucose isexported either to the interstitium or back to the basal lamina. Interstitial glucose may beimported by neurons and astrocytes or may diffuse back to the basal lamina. Intracellularglucose may be metabolized to pyruvate/lactate which is then oxidized to CO2 or is exportedto the interstitium whence it is imported by astrocytes or neurons, or diffuses to the basallamina and exits the brain to the blood.

As described previously (Simpson et al. 2007), the following experimental observations areinherent components of the model and are critical to the successful modeling of the availabledata: 1) The catalytic activity (kcat) of GLUT3 protein is 7-fold greater than that for GLUT1,thereby explaining why neuronal glucose transport capacity is much greater than that ofastrocytes (Maher et al. 1996); 2) Small molecules (≤ 40 kDa) are free to diffuse throughoutand between the interstitium and basal lamina (Brightman and Reese 1969); 3) To beconsistent with an oxygen to glucose index of 5.5 (an established number for the ratiobetween oxygen and glucose consumption rates in the human brain, Shulman et al. 2001),we assign 1/12 of the glucose entering both neurons and astrocytes to non-oxidativeprocesses; 4) The virtual brain slice has a volume of 68 fL; 5) Neuronal, astrocytic,interstitial, basal lamina, and endothelial compartments are 49.5%, 29%, 18%, 1.5%, and2% of total slice volume respectively (Hertz 2008). Our calculations do not account for theconcentrations of pyruvate, which are approximately 10% of the lactate levels and in steadystate with lactate (Siesjö 1978).

Rates of glucose and oxygen metabolism which are considered to test the predictability ofthe model are based on observed utilization rates in vivo, ∼0.3 μmol/g/min (Heiss et al.1984) and ∼1.6 μmol/g/min, respectively (Siesjö 1978). It should be noted that theglycolytic values observed in vitro are usually higher than those observed in vivo, whichlikely reflects the hypoxic nature of tissue culture.

While experimental values for the activity and distribution of glucose and lactatetransporters are accessible from an extensive number of studies on rat brain, the same doesnot apply for the human brain. However, the differences in metabolism between the rat andthe human brain are available from the current literature and were taken into account in thepresent work. Oxygen consumption by human brain (1.6 μmol/g/min) is approximately one-half of that of rat brain (McKenna et al. 2006); glucose utilization by human brain (0.23 -0.3 μmol/g/min) is 33% of that of rat brain (Clark and Sokoloff 1999); and glucose uptakeby human brain (0.4 μmol/g/min) is 27 - 40% of uptake by rat brain (Hasselbalch et al.

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1998). Based on these numbers, human glucose transport capacities in the current modelhave been adjusted to 40% of values used in simulations of the rat brain (Simpson et al.2007). There is no available information for the comparison of rates of lactate transportbetween human and rat brain; in the present work we assume that the transport of lactate inthe human brain is similar to that of rat brain. Human arterial serum glucose (5.5 mM) isslightly less than rat serum glucose (6 mM).

Glucose utilization and lactate oxidation are described by simple Michaelis-Menten kinetics,characterized by affinity constants Km (0.045 mM and 2 mM, respectively) and (maximum)capacities. Whereas the affinity constants are assumed a priori, the capacities are adjusted aposteriori until close correspondence between in vivo and simulated glucose and lactatelevels is obtained. The model does not include increases in cerebral blood flow occurringduring increased neuronal activity, since these should not significantly change either glucoseor lactate influx or efflux from the tissue (see Simpson et al. 2007 for discussion).

Results and DiscussionBefore simulating activation of the human visual cortex, the predictive value of the modelwas evaluated by examining how well the simulated serum [Glc] dependence of steady-statebrain glucose levels compares with the steady-state human brain glucose data of Gruetter etal (1998). According to the ratio-metric approach of Gruetter et al (1998) in whichMichaelis-Menten equations describe irreversible cerebral glucose utilization and reversibleglucose transport across the blood brain barrier, the maximum glucose transport to glucoseutilization ratio (Tmax:CMRglc) is 2.7. Our simulations mimic the experimental data ofGruetter et al (1998) (data not shown), suggesting that the model reproduces human brainglucose transport and utilization.

The simulations show that, under basal conditions, the capacity of the simulated brain sliceto utilize glucose (sum of basal glycolytic capacities of neurons and astrocytes shown inTable 1) is 0.302 × 10-15 mmol/s for the core model, and 0.324 × 10-15 mmol/s for theANLS simulation. By considering that the volume of our simulated slice is 68 fL, and basal[Glc] = 1.4 mM, these numbers convert to CMRglc of 0.26 μmol/g/min and 0.28 μmol/g/min, respectively, which are in good agreement with the value of ∼0.3 μmol/g/min reportedfor the human brain (Siesjö 1978). The capacity of the simulated brain slice to oxidizelactate (sum of basal lactate oxidation capacities of neurons and astrocytes shown in table 1)is 1.79 × 10-15 mmol/s for the core model, and 1.94 × 10-15 mmol/s for the ANLSsimulation. At basal astrocytic and neuronal [Lac] ≈ 1 mM, these rates convert to lactateutilization rates of 0.52 μmol/g/min and 0.56 μmol/g/min, respectively, which translate to O2consumption rate of 1.60 μmol/g/min and 1.68 μmol/g/min. These numbers are in closeagreement with the value of ∼1.6 μmol/g/min reported for the human brain (Siesjö 1978).

Figure 1 illustrates the response of visual cortex glucose and lactate levels to stimulation.The lines drawn through the points represent the results of our simulations. In Figure 1A wesimulated these results by using the core model employed by Simpson et al (2007). The keyfeatures of this model include: 1) neuronal glucose transport is more rapid than astrocyticglucose transport; 2) both neurons and astrocytes respond to activation with enhancedglycolysis although the neuron produces the most robust response. The metabolic responseswhich were necessary in order to successfully model the experimental findings are shown inFigure 2A. The initial rapid increase in brain lactate levels contrasts with the gradualdecrease in brain glucose levels. The rapid phase was modeled by the introduction oftransiently increased neuronal and astrocytic glucose utilization and a commensuratetransient reduction in neuronal and astrocytic lactate utilization. Thereafter the slowtransients in brain glucose and lactate required a small but sustained increase in neuronal

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and astrocytic glycolytic flux plus commensurate gradual increases in neuronal andastrocytic oxidative flux. During post-activation recovery, glucose transport into the brain isnot sufficiently rapid to permit rapid recovery of brain glucose levels. Thus, reduced rates ofneuronal and astrocytic glycolysis are necessary to simulate post-activation glucoserecovery. Consequently, reduced neuronal and astrocytic lactate oxidation are required toprevent undershoot of lactate levels.

In Figure 1B, we simulated the experimental results by using a different set of assumptionsthat mimic the ANLS condition, as described previously by Simpson et al (2007). The keyfeatures of the model in this case include: 1) astrocytic glucose transport is increasedapproximately 12-fold to equal neuronal glucose transport; 2) only astrocytes respond toactivation with enhanced glycolysis. The metabolic responses which were necessary tosuccessfully model the experimental findings are shown in Figure 2B. Once again, the rapidearly lactate transient requires a transient increase in astrocytic glycolysis pluscommensurate transient reductions in astrocytic and neuronal lactate utilization. The ratherslow transients in brain glucose and lactate require a sustained elevation in astrocyticglycolytic flux and commensurate small increases in neuronal and astrocytic oxidative flux.Post activation, rapid recovery of lactate and glucose levels requires transiently reducedastrocytic glycolysis plus transiently reduced neuronal and astrocytic lactate oxidation.

Net lactate flows from neuron to interstitium and from interstitium to astrocyte are shown inFigure 3. With the core model of Simpson et al (2007), lactate flows from the neuron to theinterstitium and from the interstitium to the astrocyte under basal and stimulated conditions(Figure 3A). Thus the neuron is always a lactate exporter while the astrocyte is a net lactateimporter. More detailed analysis reveals that under basal conditions, simulated steady-stateneuronal, astrocytic, and interstitial lactate levels are 0.996, 0.925, and 0.967 mMrespectively. This means that rates of unidirectional lactate uptake and exit in neurons (6.56and 6.64 × 10-15 mmol/s, respectively) are almost balanced as are rates of unidirectionallactate uptake and exit in astrocytes (2.12 and 2.04 × 10-15 mmol/s, respectively) However,since [Lac]neuron > [Lac]interstitium > [Lac]astrocyte, the net flow of lactate, which approaches0.8 × 10-16 mmol/s), is from neuron to interstitium to astrocyte. Simulating the ANLScondition in which astrocytic glucose transport capacity is artificially increased 12-fold, andin which neurons do not respond to activation with increased glycolysis, the net flow oflactate proceeds from the astrocytes to interstitium and from interstitium to neuron, bothduring basal conditions and activation (Figure 3B). Simulated steady-state neuronal,astrocytic, and interstitial lactate levels in the basal, ANLS slice are 0.897, 1.096 and 0.978mM, respectively. This means that, as for the core model, rates of unidirectional lactateuptake and exit in neurons (6.25 and 6.02 × 10-15 mmol/s respectively) are almost balancedas are rates of unidirectional lactate uptake and exit in astrocytes (2.18 and 2.39 × 10-15

mmol/s respectively). However, since [Lac]astrocyte > [Lac]interstitium > [Lac]neuron, the netflow of lactate (which approaches 2.2 × 10-16 mmol/s) is from astrocyte to interstitium toneuron.

Overall, these results indicate that, when neuronal and astrocytic glucose transport capacitiesare based on values reported in literature (core model), the increase in [Lac] observed in thehuman visual cortex during prolonged visual stimuli is consistent with import of lactate byastrocytes and export of lactate by neurons, a mechanism that can be referred to as theneuron-to-astrocyte lactate shuttle (NALS). In order to force the astrocyte to become alactate exporter during stimulation (ANLS), the glucose transport capacity by astrocytesmust be arbitrarily increased by 12-fold, and neurons must not respond to activation withincreased glycolysis. Neither of these conditions is supported by current literature.

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A recent study of cerebellar metabolism in the anesthetized rat supported the notion thatastrocytic glutamate uptake (and therefore astrocytic glycolysis, as postulated by theANLSH) cannot be the sole mechanism responsible for the increase of extracellular lactatelevels during increased postsynaptic activity (Caesar et al. 2008). In fact, under normalneuronal activation, glucose consumption, oxygen consumption, and extracellular lactatelevels were found to increase. In addition, application of 6-Cyano-7-nitroquinoxaline-2,3-dione (CNQX), a drug that does not alter glutamate uptake into astrocytes but blocks theAMPA receptors, abolished all evoked increases in postsynaptic activity, blood flow,glucose consumption, oxygen consumption, as well as concomitant increases in lactate.

The present results are in agreement with previous conclusions obtained by simulatinganimal data (Simpson et al. 2007). In addition, consistent with the present findings, aneuronal, rather than astrocytic, release of lactate in the extracellular space was shown tooccur after the first 30 s of stimulation by the mathematical model implemented by Aubertand Costalat (2005) when the sodium neuronal influx was supposed to be 3-fold higher thanin astrocytes.

While these simulations indicate a net flow of lactate from neurons to astrocytes, they do notexclude a local shuttle of lactate from astrocytes to neurons. Lactate can indeed beefficiently oxidized by neurons, and can be utilized as a preferential fuel in specificconditions, including early brain development (Dombrowski et al. 1989, Thurston andHauhart 1989, Vannucci and Vannucci 2000). Several studies have shown that lactate has animportant role during the recovery of synaptic activity following hypoxia (Schurr et al.1997a, Schurr et al. 1997b) or traumatic brain injury (Chen et al. 2000), which lead toabnormal levels (up to 10 mM) of tissue lactate concentration [Lac].

We conclude that, based on the metabolic model introduced by Simpson et al. (2007), theevolution of [Lac] and [Glc] observed in humans by 1H MRS during prolonged visualstimulation (Mangia et al. 2007a) are consistent with a lactate shuttle from neurons toastrocytes (NALS). These results are in agreement with previous findings, however they donot rule out the possibility that lactate derived from astrocytic glycolysis can be utilized byneurons as a metabolic fuel in other metabolic conditions.

AcknowledgmentsSupporting grants and Institutes: NIH P41RR08079; P30 NS057091; the W. M. Keck Foundation and the MINDInstitute (S. Mangia); NIH DK 44888, DK 36081 (A. Carruthers); and DK075130 (I.A. Simpson), AHA 0575055N(S.J. Vannucci).

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31. McKenna, MC.; Gruetter, R.; Sonnewald, U.; Waagepetersen, HS.; Schousboe, A. Basicneurochemistry. Molecular, cellular and medical aspects. Lippincott-Raven; Philadelphia: 2006.Energy metabolism of the brain; p. 531-558.

32. Pellerin L, Bouzier-Sore AK, Aubert A, Serres S, Merle M, Costalat R, Magistretti PJ. Activity-dependent regulation of energy metabolism by astrocytes: an update. Glia. 2007; 55:1251–1262.[PubMed: 17659524]

33. Pellerin L, Magistretti PJ. Glutamate uptake into astrocytes stimulates aerobic glycolysis: amechanism coupling neuronal activity to glucose utilization. Proc Natl Acad Sci U S A. 1994;91:10625–10629. [PubMed: 7938003]

34. Schurr A, Payne RS, Miller JJ, Rigor BM. Brain lactate is an obligatory aerobic energy substratefor functional recovery after hypoxia: further in vitro validation. J Neurochem. 1997a; 69:423–426. [PubMed: 9202338]

35. Schurr A, Payne RS, Miller JJ, Rigor BM. Brain lactate, not glucose, fuels the recovery of synapticfunction from hypoxia upon reoxygenation: an in vitro study. Brain Res. 1997b; 744:105–111.[PubMed: 9030418]

36. Shulman R, Hyder F, Rothman D. Lactate efflux and the neuroenergetic basis of brain function.NMR Biomed. 2001; 14:389–396. [PubMed: 11746930]

37. Siesjö, B. Brain energy metabolism. John Wiley and Sons; New York: 1978.38. Simpson IA, Carruthers A, Vannucci SJ. Supply and demand in cerebral energy metabolism: the

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39. Stein, WD. Transport and diffusion across cell membranes. Academic Press; New York: 1986.40. Thurston JH, Hauhart RE. Effect of momentary stress on brain energy metabolism in weanling

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Figure 1. Simulations of changes in glucose and lactate concentrations from the human visualcortex during visual stimulationActivation is simulated at 1000 sec and ends at 1360 second (denoted by horizontal blackbar). The curves drawn through the experimental data represent the results from thesimulations, which were performed assuming: A) the core model of Simpson et al. (2007)or, B) a variation on the Simpson et al. (2007) model which mimics the ANLS modelwherein the astrocytic glucose transport capacity is increased 12-fold and neurons no longerrespond to activation with increased glycolysis.

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Figure 2. Adjustments in neuronal and astrocytic glycolytic capacities and lactate oxidationcapacities required to simulate the data of Figure 1Activation is simulated at 1000 sec and ends at 1360 second (denoted by horizontal blackbar). Glycolytic capacities and lactate oxidation capacities of astrocytes and neurons arerepresented by solid and dashed lines as described in the legend. These capacities wereapplied to: A) the core model of Simpson et al. (2007) or, B) the ANLS model described inFigure 1B.

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Figure 3. Contributions to interstitial lactate concentration before and after neuronalstimulationLactate flow is described either as export by the neuron to interstitium (solid lines) or asexport by the astrocyte to interstitium (dashed lined). Positive values indicate net export.Negative values indicate net import. Results are shown for: A the core model of Simpson etal. (2007) or, B) The simulated ANLS model employed in Figure 1B. Activation issimulated at 1000 sec and ends at 1360 second (denoted by horizontal black bar).

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Mangia et al. Page 13

Tabl

e 1

Sim

ulat

ion

Para

met

ers

Cor

e M

odel

par

amet

ers

AN

LS

Mod

el p

aram

eter

s

a Par

amet

erSe

rum

Endo

thel

ial c

ell

Astro

cyte

Neu

ron

Seru

mEn

doth

elia

l cel

lAs

trocy

teN

euro

n

[Glc

] mM

5.5

5.5

Km

Glc

mM

88

2.8

88

2.8

Vm

axG

lc3.

08 ×

10-1

5b 0

.06

× 10

-15

9.09

× 1

0-15

3.08

× 1

0-15

b 0.7

3 ×

10-1

59.

09 ×

10-1

5

c 0.8

0 ×

10-1

5c 9

.09

× 10

-15

Bas

al g

lyco

lytic

cap

acity

0.06

8 ×

10-1

50.

234

× 10

-15

0.25

0 ×

10-1

50.

077

× 10

-15

[Lac

] mM

1.0

1.0

Km

Lac m

M4.

08.

00.

74.

08.

00.

7

Vm

axLa

c0.

36 ×

10-1

5b 1

.21

× 10

-15

5.00

× 1

0-15

0.36

× 1

0-15

b 1.2

1 ×

10-1

55.

00 ×

10-1

5

c 15.

20 ×

10-1

5c 1

5.20

× 1

0-15

Bas

al la

ctat

e ox

idat

ion

capa

city

0.67

× 1

0-15

1.12

× 1

0-15

0.72

× 1

0-15

1.22

× 1

0-15

a Key

par

amet

ers u

sed

in th

e si

mul

atio

ns o

f Fig

ures

1, 2

and

3. T

he p

aram

eter

s are

: Ser

um g

luco

se a

nd la

ctat

e le

vels

in m

M; K

m(a

pp) f

or n

et im

port

of g

luco

se (K

mG

lc) o

r lac

tate

(Km

Lac)

in m

M;

Vm

ax(a

pp) f

or z

ero-

trans

net

upt

ake

of g

luco

se (V

max

Glc

) or l

acta

te (V

max

Lac)

in m

mol

/s p

er b

rain

slic

e, w

here

Vm

axG

lc a

re se

t to

40%

of t

he v

alue

s use

d fo

r sim

ulat

ions

of r

ats d

ata

(Sim

pson

et a

l.20

07),

see

text

; bas

al g

lyco

lytic

cap

acity

in m

mol

s of g

luco

se c

onsu

med

per

bra

in sl

ice

per s

ec; b

asal

lact

ate

oxid

atio

n ca

paci

ty in

mm

ols o

f lac

tate

oxi

dize

d pe

r bra

in sl

ice

per s

ec. T

he v

alue

s of m

etab

olic

capa

citie

s are

the

resu

lts o

f ite

rativ

e ad

just

men

ts u

ntil

clos

e co

rres

pond

ence

bet

wee

n in

viv

o an

d si

mul

ated

glu

cose

and

lact

ate

leve

ls is

obt

aine

d.

b Rep

rese

nts u

ptak

e fr

om th

e ba

sal l

amin

a in

to th

e as

trocy

tic e

ndfo

ot.

c Rep

rese

nts u

ptak

e fr

om th

e in

ters

titiu

m in

to th

e as

trocy

te. O

nly

capa

citie

s for

zer

o-tra

ns n

et u

ptak

e by

end

othe

lial c

ells

, ast

rocy

tes a

nd n

euro

ns a

re in

dica

ted

here

. The

bra

in sl

ice

com

pris

es a

cor

tical

sect

ion

of 2

× 2

× 1

7 μm

3 ab

uttin

g th

e ca

pilla

ry a

s des

crib

ed p

revi

ousl

y (S

imps

on e

t al.

2007

). N

ote

that

in th

e A

NLS

sim

ulat

ions

the

gluc

ose

trans

port

capa

city

is in

crea

sed

by 1

2 tim

es in

ast

rocy

tes

com

pare

d to

the

core

mod

el.

J Neurochem. Author manuscript; available in PMC 2009 May 8.