Mangia Silvia, Simpson Ian A, Vannucci Susan J, Carruthers Anthony
Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA.
J Neurochem. 2009 May;109 Suppl 1(Suppl 1):55-62. doi: 10.1111/j.1471-4159.2009.06003.x.
Functional magnetic resonance spectroscopy (fMRS) allows the non-invasive measurement of metabolite concentrations in the human brain, including changes induced by variations in neurotransmission activity. However, the limited spatial and temporal resolution of fMRS does not allow specific measurements of metabolites in different cell types. Thus, the analysis of fMRS data in the context of compartmentalized metabolism requires the formulation and application of mathematical models. In the present study we utilized the mathematical model introduced by Simpson et al. (2007) to gain insights into compartmentalized metabolism in vivo from the fMRS data obtained in humans at ultra high magnetic field by Mangia et al. (2007a). This model simulates brain glucose and lactate levels in a theoretical cortical slice. Using experimentally determined concentrations and catalytic activities for the respective transporter proteins, we calculate inflow and export of glucose and lactate in endothelium, astrocytes, and neurons. We then vary neuronal and astrocytic glucose and lactate utilization capacities until close correspondence is observed between in vivo and simulated glucose and lactate levels. The results of the simulations indicate that, when literature values of glucose transport capacity are utilized, the fMRS data are consistent with export of lactate by neurons and import of lactate by astrocytes, a mechanism that can be referred to as a neuron-to-astrocyte lactate shuttle. A shuttle of lactate from astrocytes to neurons could be simulated, but this required the astrocytic glucose transport capacity to be increased by 12-fold, and required that neurons not respond to activation with increased glycolysis, two conditions that are not supported by current literature.
功能磁共振波谱(fMRS)能够对人脑内的代谢物浓度进行无创测量,包括神经传递活动变化所引起的浓度变化。然而,fMRS有限的空间和时间分辨率使得无法对不同细胞类型中的代谢物进行特异性测量。因此,在代谢区室化背景下分析fMRS数据需要构建并应用数学模型。在本研究中,我们利用了辛普森等人(2007年)提出的数学模型,以从曼吉亚等人(2007a年)在超高磁场下获得的人体fMRS数据中深入了解体内代谢区室化情况。该模型模拟了理论皮质切片中的脑葡萄糖和乳酸水平。利用实验测定的各转运蛋白的浓度和催化活性,我们计算了内皮细胞、星形胶质细胞和神经元中葡萄糖和乳酸的流入与流出。然后,我们改变神经元和星形胶质细胞对葡萄糖和乳酸的利用能力,直到观察到体内与模拟的葡萄糖和乳酸水平之间有密切对应关系。模拟结果表明,当采用葡萄糖转运能力的文献值时,fMRS数据与神经元输出乳酸和星形胶质细胞输入乳酸的情况一致,这一机制可称为神经元-星形胶质细胞乳酸穿梭。可以模拟乳酸从星形胶质细胞到神经元的穿梭,但这需要将星形胶质细胞的葡萄糖转运能力提高12倍,并且要求神经元在激活时不增加糖酵解反应,而目前的文献并不支持这两个条件。